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   <news:title>ヒト-物体相互作用検出のための転移可能な相互作用性知識（Transferable Interactiveness Knowledge for Human-Object Interaction Detection）</news:title>
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   <news:title>不規則サンプリング時系列のデータ拡張手法 T-CGAN（T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling）</news:title>
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   <news:title>FALCON: 高速かつプライバシー保護されたCNN推論の実装（FALCON: A Fourier Transform Based Approach for Fast and Secure Convolutional Neural Network Predictions）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>Fristonの能動推論の幾何学（Geometry of Friston’s active inference）</news:title>
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   <news:title>Deep Unfolded Robust PCAによる超音波クラッタ除去の実務的意義（Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound）</news:title>
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   <news:title>自己組織化分類器とニッチ化された適応（Self Organizing Classifiers and Niched Fitness）</news:title>
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    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>分析的ネットワーク学習（Analytic Network Learning）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>正射影特徴変換による単眼3D物体検出（Orthographic Feature Transform for Monocular 3D Object Detection）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>Contingency Training：不要変数に強い学習を作る訓練法（Contingency Training）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>脳に学ぶスティグメルギー学習（Brain-Inspired Stigmergy Learning）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>位相情報のマルチスケール集約によるCNNベースDOA推定の計算コスト削減（MULTI-SCALE AGGREGATION OF PHASE INFORMATION FOR REDUCING COMPUTATIONAL COST OF CNN BASED DOA ESTIMATION）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-07T20:26:45Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>曲特徴を取り込む注意機構付きニューラル構造による音楽レコメンド（Attentive Neural Architecture Incorporating Song Features For Music Recommendation）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>公平な機械学習の最前線（State of the Art in Fair Machine Learning）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>CGNet: 軽量コンテキストガイドネットワークによるセマンティックセグメンテーション（CGNet: A Light-weight Context Guided Network for Semantic Segmentation）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>GAN生成画像の起源特定とフィンガープリント解析（Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>古い文献が示す洞察と現代物理学の接点（Coffee stains, cell receptors, and time crystals: Lessons from the old literature）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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   <news:title>ベクタースケッチ認識のための注意型ネットワーク（Sketch-R2CNN: An Attentive Network for Vector Sketch Recognition）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>形の概念を機械が自ら学ぶ方法（Unsupervised Learning of Shape Concepts – From Real-World Objects to Mental Simulation）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-07T19:33:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Hedge手法を巡る攻防：適応的意思決定と最悪ケースの解析（Playing with and against Hedge）</news:title>
   <news:publication_date>2026-07-07T19:33:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709240</loc>
  <lastmod>2026-07-07T18:41:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>De Sitterの地平線とホログラフィック流体（De Sitter Horizons &amp;amp; Holographic Liquids）</news:title>
   <news:publication_date>2026-07-07T18:41:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709238</loc>
  <lastmod>2026-07-07T18:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNを用いた可逆データ圧縮（DeepZip: Lossless Data Compression using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-07T18:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709236</loc>
  <lastmod>2026-07-07T18:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による脳外科スキル判定（Machine Learning Distinguishes Neurosurgical Skill Levels in a Virtual Reality Tumor Resection Task）</news:title>
   <news:publication_date>2026-07-07T18:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709234</loc>
  <lastmod>2026-07-07T18:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的学習による点群整合（Adversarial point set registration）</news:title>
   <news:publication_date>2026-07-07T18:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-07T18:40:28Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>深さと幅が局所最小値に与える影響（Effect of Depth and Width on Local Minima in Deep Learning）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>CNNが画像をどう見るか（How you see me）</news:title>
   <news:publication_date>2026-07-07T18:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-07T18:40:07Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>即時変化検出の学習：遡及畳み込みと静的サンプル合成 (Learning to Detect Instantaneous Changes with Retrospective Convolution and Static Sample Synthesis)</news:title>
   <news:publication_date>2026-07-07T18:40:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709226</loc>
  <lastmod>2026-07-07T17:48:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的フィードバックループによる生成画像の品質改善（Adversarial Feedback Loop）</news:title>
   <news:publication_date>2026-07-07T17:48:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709224</loc>
  <lastmod>2026-07-07T17:48:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DarwinML: グラフベースの進化的AutoML（DarwinML: A Graph-based Evolutionary Algorithm for Automated Machine Learning）</news:title>
   <news:publication_date>2026-07-07T17:48:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709222</loc>
  <lastmod>2026-07-07T17:48:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Auto-Set: ウェアラブルを用いた活動認識のための深層オートエンコーダセット（Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables）</news:title>
   <news:publication_date>2026-07-07T17:48:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709220</loc>
  <lastmod>2026-07-07T17:47:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルノイズ下で主要パターンを最大限学習する方法（Limited Gradient Descent: Learning With Noisy Labels）</news:title>
   <news:publication_date>2026-07-07T17:47:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709218</loc>
  <lastmod>2026-07-07T17:47:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーケンス基盤の人物属性認識とJoint CTC-Attentionモデル（Sequence-based Person Attribute Recognition with Joint CTC-Attention Model）</news:title>
   <news:publication_date>2026-07-07T17:47:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709216</loc>
  <lastmod>2026-07-07T17:47:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トラフィックを考慮したNFVスケーリングの閾値調整（Traffic-aware Threshold Adjustment for NFV Scaling using DRL）</news:title>
   <news:publication_date>2026-07-07T17:47:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709214</loc>
  <lastmod>2026-07-07T17:47:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在因子モデルの説明可能化と影響関数（Explaining Latent Factor Models for Recommendation with Influence Functions）</news:title>
   <news:publication_date>2026-07-07T17:47:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709212</loc>
  <lastmod>2026-07-07T16:55:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動フォント生成におけるマルチスケール埋め込みと生成的敵対学習の意義（Pyramid Embedded Generative Adversarial Network for Automated Font Generation）</news:title>
   <news:publication_date>2026-07-07T16:55:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709210</loc>
  <lastmod>2026-07-07T16:55:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト監督を付与したSeq2Seq音声変換の改善（IMPROVING SEQUENCE-TO-SEQUENCE VOICE CONVERSION BY ADDING TEXT-SUPERVISION）</news:title>
   <news:publication_date>2026-07-07T16:55:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709208</loc>
  <lastmod>2026-07-07T16:54:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔検出のための特徴融合とセグメンテーション監督による学習（Learning Better Features for Face Detection with Feature Fusion and Segmentation Supervision）</news:title>
   <news:publication_date>2026-07-07T16:54:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709206</loc>
  <lastmod>2026-07-07T16:54:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話生成の多様性を高める新しい目的関数（Another Diversity-Promoting Objective Function for Neural Dialogue Generation）</news:title>
   <news:publication_date>2026-07-07T16:54:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709204</loc>
  <lastmod>2026-07-07T16:54:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>先読み探索による連続制御の学習革新（Model Learning for Look-ahead Exploration in Continuous Control）</news:title>
   <news:publication_date>2026-07-07T16:54:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709202</loc>
  <lastmod>2026-07-07T16:54:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能なマルチプル・カーネル学習による統合的がんサブタイプの発見（An interpretable multiple kernel learning approach for the discovery of integrative cancer subtypes）</news:title>
   <news:publication_date>2026-07-07T16:54:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709200</loc>
  <lastmod>2026-07-07T16:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向敵対的オートエンコーダによるゼロショット学習（Bi-Adversarial Auto-Encoder for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-07-07T16:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709198</loc>
  <lastmod>2026-07-07T16:02:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Multiple-Instance Learning を無限のシェイプレットで拡張する手法（Multiple-Instance Learning by Boosting Infinitely Many Shapelet-based Classifiers）</news:title>
   <news:publication_date>2026-07-07T16:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709196</loc>
  <lastmod>2026-07-07T16:02:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ChainGAN: 逐次的編集で生成を安定化させるアプローチ（CHAINGAN: A SEQUENTIAL APPROACH TO GANS）</news:title>
   <news:publication_date>2026-07-07T16:02:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709194</loc>
  <lastmod>2026-07-07T16:01:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量リプシッツ・マージン学習による証明済み防御の実装可能性（Lightweight Lipschitz Margin Training for Certified Defense against Adversarial Examples）</news:title>
   <news:publication_date>2026-07-07T16:01:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709192</loc>
  <lastmod>2026-07-07T16:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩行者軌跡の表現学習――Actor–Critic Sequence-to-Sequence Autoencoderによる新展開（Representation Learning of Pedestrian Trajectories Using Actor-Critic Sequence-to-Sequence Autoencoder）</news:title>
   <news:publication_date>2026-07-07T16:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709190</loc>
  <lastmod>2026-07-07T16:01:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列ニューラルネットワークから学ぶ異種音声特徴の頑健学習（Learning Robust Heterogeneous Signal Features from Parallel Neural Network for Audio Sentiment Analysis）</news:title>
   <news:publication_date>2026-07-07T16:01:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709188</loc>
  <lastmod>2026-07-07T16:01:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遮蔽下で手と目を協調させる強化学習（Reinforcement Learning of Active Vision for Manipulating Objects under Occlusions）</news:title>
   <news:publication_date>2026-07-07T16:01:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709186</loc>
  <lastmod>2026-07-07T16:00:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Factorized DistillationによるHolistic Person Re-identificationの効率化（Factorized Distillation: Training Holistic Person Re-identiﬁcation Model by Distilling an Ensemble of Partial ReID Models）</news:title>
   <news:publication_date>2026-07-07T16:00:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709184</loc>
  <lastmod>2026-07-07T15:09:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外観変化下の視覚的自己位置推定：フィルタリング手法の可能性（Visual Localization Under Appearance Change: Filtering Approaches）</news:title>
   <news:publication_date>2026-07-07T15:09:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709182</loc>
  <lastmod>2026-07-07T15:09:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配整合型強正則化による深層学習の安定化（Gradient-Coherent Strong Regularization for Deep Neural Networks with Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-07-07T15:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709180</loc>
  <lastmod>2026-07-07T15:09:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模行列の対数行列式を並列で速く計算する方法（Parallel Matrix Condensation for Calculating Log-Determinant of Large Matrix）</news:title>
   <news:publication_date>2026-07-07T15:09:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709178</loc>
  <lastmod>2026-07-07T15:08:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量時系列データにおける教師なし異常検知と診断の深層ニューラルネットワーク（A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data）</news:title>
   <news:publication_date>2026-07-07T15:08:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709176</loc>
  <lastmod>2026-07-07T15:08:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多声音楽作曲のための結合リカレントモデル (Coupled Recurrent Models for Polyphonic Music Composition)</news:title>
   <news:publication_date>2026-07-07T15:08:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709174</loc>
  <lastmod>2026-07-07T15:08:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率粒子最適化サンプリングにおける分散削減（Variance Reduced Stochastic Particle-Optimization Sampling）</news:title>
   <news:publication_date>2026-07-07T15:08:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709172</loc>
  <lastmod>2026-07-07T15:07:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶を保存せずに継続学習する手法の要点解説（Learning without Memorizing）</news:title>
   <news:publication_date>2026-07-07T15:07:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709170</loc>
  <lastmod>2026-07-07T14:16:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテ上の抽出型要約のための無監督擬似ラベリング（Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records）</news:title>
   <news:publication_date>2026-07-07T14:16:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709168</loc>
  <lastmod>2026-07-07T14:16:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fenchel Lifted Networksによるニューラルネットワーク学習のラグランジュ緩和（Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training）</news:title>
   <news:publication_date>2026-07-07T14:16:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709166</loc>
  <lastmod>2026-07-07T14:15:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>携帯型単一導聯心電図からの同時12誘導心電図合成（Simultaneous 12-Lead Electrocardiogram Synthesis using a Single-Lead ECG Signal: Application to Handheld ECG Devices）</news:title>
   <news:publication_date>2026-07-07T14:15:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709164</loc>
  <lastmod>2026-07-07T14:15:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サロゲート機械学習モデルによる低スケーリングNEB計算法（Low-Scaling Algorithm for Nudged Elastic Band Calculations Using a Surrogate Machine Learning Model）</news:title>
   <news:publication_date>2026-07-07T14:15:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709162</loc>
  <lastmod>2026-07-07T14:14:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手のジェスチャーで舌を操るリアルタイム調音音声合成（SOUND-STREAM II: TOWARDS REAL-TIME GESTURE-CONTROLLED ARTICULATORY SOUND SYNTHESIS）</news:title>
   <news:publication_date>2026-07-07T14:14:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709160</loc>
  <lastmod>2026-07-07T14:14:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Role Action Embeddings: ネットワーク上の位置を捉える新しい表現（Role Action Embeddings: scalable representation of network positions）</news:title>
   <news:publication_date>2026-07-07T14:14:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709158</loc>
  <lastmod>2026-07-07T14:14:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Landerによる安定なドローン着陸制御（Neural Lander: Stable Drone Landing Control Using Learned Dynamics）</news:title>
   <news:publication_date>2026-07-07T14:14:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709156</loc>
  <lastmod>2026-07-07T13:23:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォントの組み合わせを学習する（Learning to Pair Fonts）</news:title>
   <news:publication_date>2026-07-07T13:23:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709154</loc>
  <lastmod>2026-07-07T13:22:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stackelberg GANによるGAN訓練の安定化（Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures）</news:title>
   <news:publication_date>2026-07-07T13:22:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709152</loc>
  <lastmod>2026-07-07T13:22:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Explain to Fix: DNN物体検出器の誤りを解釈して修正する枠組み（Explain to Fix: A Framework to Interpret and Correct DNN Object Detector Predictions）</news:title>
   <news:publication_date>2026-07-07T13:22:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709150</loc>
  <lastmod>2026-07-07T13:21:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続空間でのエンドツーエンド検索（End-to-End Retrieval in Continuous Space）</news:title>
   <news:publication_date>2026-07-07T13:21:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709148</loc>
  <lastmod>2026-07-07T13:21:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成3D肺結節画像生成とオートエンコーダ（Synthetic Lung Nodule 3D Image Generation Using Autoencoders）</news:title>
   <news:publication_date>2026-07-07T13:21:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709146</loc>
  <lastmod>2026-07-07T13:21:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルなロゴ認識とプロキシ学習（Scalable Logo Recognition using Proxies）</news:title>
   <news:publication_date>2026-07-07T13:21:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709144</loc>
  <lastmod>2026-07-07T13:20:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質の折りたたみと機械学習の基礎（Protein Folding and Machine Learning: Fundamentals）</news:title>
   <news:publication_date>2026-07-07T13:20:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709142</loc>
  <lastmod>2026-07-07T12:29:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的意味埋め込みに基づく汎化ゼロショット認識（Generalized Zero-Shot Recognition based on Visually Semantic Embedding）</news:title>
   <news:publication_date>2026-07-07T12:29:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709140</loc>
  <lastmod>2026-07-07T12:29:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検出器アレイを用いた自由空間光通信（Free-Space Optical Communications with Detector Arrays）</news:title>
   <news:publication_date>2026-07-07T12:29:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709138</loc>
  <lastmod>2026-07-07T12:29:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成顔はデータセットの偏りを解消するか（Can Synthetic Faces Undo the Damage of Dataset Bias To Face Recognition and Facial Landmark Detection?）</news:title>
   <news:publication_date>2026-07-07T12:29:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709136</loc>
  <lastmod>2026-07-07T12:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称結合とヘッブ則で学ぶ深層学習（Deep learning with asymmetric connections and Hebbian updates）</news:title>
   <news:publication_date>2026-07-07T12:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709134</loc>
  <lastmod>2026-07-07T12:28:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識の地図化が変える学術理解と応用（A Map of Knowledge）</news:title>
   <news:publication_date>2026-07-07T12:28:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709132</loc>
  <lastmod>2026-07-07T12:27:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライベート候補からの選択問題（Private Selection from Private Candidates）</news:title>
   <news:publication_date>2026-07-07T12:27:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709130</loc>
  <lastmod>2026-07-07T12:27:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Informed MCMCとベイズニューラルネットワークによる顔画像解析の実用化（Informed MCMC with Bayesian Neural Networks for Facial Image Analysis）</news:title>
   <news:publication_date>2026-07-07T12:27:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709128</loc>
  <lastmod>2026-07-07T11:35:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的合成における構造不整合の緩和（Mitigating Architectural Mismatch During the Evolutionary Synthesis of Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-07T11:35:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709126</loc>
  <lastmod>2026-07-07T11:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル変化検出と機械学習への応用（MODEL CHANGE DETECTION WITH APPLICATION TO MACHINE LEARNING）</news:title>
   <news:publication_date>2026-07-07T11:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709124</loc>
  <lastmod>2026-07-07T11:35:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Optimal Transport Classifierによる敵対的攻撃への防御（Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding）</news:title>
   <news:publication_date>2026-07-07T11:35:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709122</loc>
  <lastmod>2026-07-07T11:34:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LoTSS/HETDEXによる光学選択クエasarの低周波電波特性（LoTSS/HETDEX: Low-frequency radio properties of optically selected quasars）</news:title>
   <news:publication_date>2026-07-07T11:34:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709120</loc>
  <lastmod>2026-07-07T11:34:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絶縁相に残る整列した位相振動の理論（Theory of coherent phase modes in insulating Josephson junction chains）</news:title>
   <news:publication_date>2026-07-07T11:34:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709118</loc>
  <lastmod>2026-07-07T11:33:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定性を統合するアンサンブル特徴選択（Ensemble Feature Selection Integrating Stability）</news:title>
   <news:publication_date>2026-07-07T11:33:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709116</loc>
  <lastmod>2026-07-07T11:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による合成：低・高空間周波数の分離と再結合による画像回復（Learning to synthesize: splitting and recombining low and high spatial frequencies for image recovery）</news:title>
   <news:publication_date>2026-07-07T11:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709114</loc>
  <lastmod>2026-07-07T10:42:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DUNEのMeVニュートリノ観測可能性の開拓（Developing the MeV potential of DUNE: Detailed considerations of muon-induced spallation and other backgrounds）</news:title>
   <news:publication_date>2026-07-07T10:42:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709112</loc>
  <lastmod>2026-07-07T10:41:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語による指示で学ぶ方策（Guiding Policies with Language via Meta-Learning）</news:title>
   <news:publication_date>2026-07-07T10:41:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709110</loc>
  <lastmod>2026-07-07T10:41:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明と予測が人間の判断に与える影響（On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection）</news:title>
   <news:publication_date>2026-07-07T10:41:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709108</loc>
  <lastmod>2026-07-07T10:40:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬モデリングによるスケーラブルなエージェント整合性（Scalable agent alignment via reward modeling: a research direction）</news:title>
   <news:publication_date>2026-07-07T10:40:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709106</loc>
  <lastmod>2026-07-07T10:40:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>日周縁（ペニュンブラル）マイクロジェットの観測に基づくモデル（OBSERVATIONALLY BASED MODELS OF PENUMBRAL MICROJETS）</news:title>
   <news:publication_date>2026-07-07T10:40:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709104</loc>
  <lastmod>2026-07-07T10:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現実的走行環境における深層強化学習と決定性有限状態機械による自動運転シミュレーション（Simulated Autonomous Driving in a Realistic Driving Environment using Deep Reinforcement Learning and a Deterministic Finite State Machine）</news:title>
   <news:publication_date>2026-07-07T10:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709102</loc>
  <lastmod>2026-07-07T10:40:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測に基づく意思決定と公正性のカタログ（Prediction-Based Decisions and Fairness: A Catalogue of Choices, Assumptions, and Definitions）</news:title>
   <news:publication_date>2026-07-07T10:40:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709100</loc>
  <lastmod>2026-07-07T09:48:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非部分加法性（Non-submodular）関数の最大化とマトロイド制約への拡張（Non-submodular Function Maximization subject to a Matroid Constraint, with Applications）</news:title>
   <news:publication_date>2026-07-07T09:48:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709098</loc>
  <lastmod>2026-07-07T09:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Prefetchファイルを使った振る舞い型マルウェア分類（Behavioral Malware Classification using Convolutional Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-07T09:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709096</loc>
  <lastmod>2026-07-07T09:47:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OrthoSeg：多モーダル正射画像のセマンティックセグメンテーション用深層畳み込みニューラルネットワーク（ORTHOSEG: A DEEP MULTIMODAL CONVOLUTIONAL NEURAL NETWORK ARCHITECTURE FOR SEMANTIC SEGMENTATION OF ORTHOIMAGERY）</news:title>
   <news:publication_date>2026-07-07T09:47:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709094</loc>
  <lastmod>2026-07-07T09:47:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>H35 HV-CMOS 単一化ピクセルセンサーの特性評価（Characterisation of AMS H35 HV-CMOS monolithic active pixel sensor prototypes for HEP applications）</news:title>
   <news:publication_date>2026-07-07T09:47:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709092</loc>
  <lastmod>2026-07-07T09:47:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標条件付き方策で学ぶ操作可能表現（Learning Actionable Representations with Goal-Conditioned Policies）</news:title>
   <news:publication_date>2026-07-07T09:47:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709090</loc>
  <lastmod>2026-07-07T09:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル信念伝搬デコーダによる量子誤り訂正（Neural Belief-Propagation Decoders for Quantum Error-Correcting Codes）</news:title>
   <news:publication_date>2026-07-07T09:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709088</loc>
  <lastmod>2026-07-07T09:46:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なランダムグラフの対応付け手法（Efficient random graph matching via degree profiles）</news:title>
   <news:publication_date>2026-07-07T09:46:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709086</loc>
  <lastmod>2026-07-07T08:55:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載CANのトークン化と翻訳（ACTT: Automotive CAN Tokenization and Translation）</news:title>
   <news:publication_date>2026-07-07T08:55:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709084</loc>
  <lastmod>2026-07-07T08:54:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波であぶり出すジェットの偏波――3C 84核領域の線偏波の空間分解（Spatially resolved origin of mm-wave linear polarization in the nuclear region of 3C 84）</news:title>
   <news:publication_date>2026-07-07T08:54:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709082</loc>
  <lastmod>2026-07-07T08:54:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次観測に基づくネットワーク平均信念の分散学習（Distributed Learning of Average Belief Over Networks Using Sequential Observations）</news:title>
   <news:publication_date>2026-07-07T08:54:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/709080</loc>
  <lastmod>2026-07-07T08:54:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの高速・高密度変形再構成を実現するDeep SfT（Deep Shape-from-Template: Wide-Baseline, Dense and Fast Registration and Deformable Reconstruction from a Single Image）</news:title>
   <news:publication_date>2026-07-07T08:54:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709078</loc>
  <lastmod>2026-07-07T08:54:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Visual Question Answeringに学ぶ「データバイアスの可視化」と経営応用（Explicit Bias Discovery in Visual Question Answering Models）</news:title>
   <news:publication_date>2026-07-07T08:54:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709076</loc>
  <lastmod>2026-07-07T08:53:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepIRによる画像リターゲティング（DeepIR: A Deep Semantics Driven Framework for Image Retargeting）</news:title>
   <news:publication_date>2026-07-07T08:53:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709074</loc>
  <lastmod>2026-07-07T08:53:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ETSチャレンジ：金融時系列シミュレーションのリアリズム評価手法（The ETS challenges: a machine learning approach to the evaluation of simulated financial time series for improving generation processes）</news:title>
   <news:publication_date>2026-07-07T08:53:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709072</loc>
  <lastmod>2026-07-07T08:02:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散探索によるベストアーム同定の進化（Decentralized Exploration in Multi-Armed Bandits - Extended version）</news:title>
   <news:publication_date>2026-07-07T08:02:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709070</loc>
  <lastmod>2026-07-07T08:01:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群の局所幾何構造をモデル化するGeo-CNN（Modeling Local Geometric Structure of 3D Point Clouds using Geo-CNN）</news:title>
   <news:publication_date>2026-07-07T08:01:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709068</loc>
  <lastmod>2026-07-07T08:01:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューリスティックを使った差分プライバシーの実装指針（How to Use Heuristics for Differential Privacy）</news:title>
   <news:publication_date>2026-07-07T08:01:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709066</loc>
  <lastmod>2026-07-07T08:00:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SEIGANによる合成的画像生成（SEIGAN: Towards Compositional Image Generation by Simultaneously Learning to Segment, Enhance, and Inpaint）</news:title>
   <news:publication_date>2026-07-07T08:00:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709064</loc>
  <lastmod>2026-07-07T08:00:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広視野地上観測における系外惑星トランジット検出と候補検証の機械学習手法（Machine-learning Approaches to Exoplanet Transit Detection and Candidate Validation in Wide-field Ground-based Surveys）</news:title>
   <news:publication_date>2026-07-07T08:00:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709062</loc>
  <lastmod>2026-07-07T08:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユニタリ群畳み込みによる効率的な深層ニューラルネットワークの構築（Building Efficient Deep Neural Networks with Unitary Group Convolutions）</news:title>
   <news:publication_date>2026-07-07T08:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709060</loc>
  <lastmod>2026-07-07T08:00:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スラムの個別検出と変化検知を実現する深層学習手法（Slum Segmentation and Change Detection : A Deep Learning Approach）</news:title>
   <news:publication_date>2026-07-07T08:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709058</loc>
  <lastmod>2026-07-07T07:08:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正確な追跡を追求するATOM（Accurate Tracking by Overlap Maximization）</news:title>
   <news:publication_date>2026-07-07T07:08:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709056</loc>
  <lastmod>2026-07-07T07:07:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性を超えて：ゼロショット学習のための敵対的消去埋め込みネットワーク（Beyond Attributes: Adversarial Erasing Embedding Network for Zero-shot Learning）</news:title>
   <news:publication_date>2026-07-07T07:07:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709054</loc>
  <lastmod>2026-07-07T07:06:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数のハウスホルダー反射子で近似固有値分解を実現する方法（Approximate Eigenvalue Decompositions of Linear Transformations with a Few Householder Reflectors）</news:title>
   <news:publication_date>2026-07-07T07:06:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709052</loc>
  <lastmod>2026-07-07T07:06:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外れ値に配慮した属性付きネットワーク埋め込み（Outlier Aware Network Embedding for Attributed Networks）</news:title>
   <news:publication_date>2026-07-07T07:06:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709050</loc>
  <lastmod>2026-07-07T07:06:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群のコンパクト表現を作る敵対的オートエンコーダ（Adversarial Autoencoders for Compact Representations of 3D Point Clouds）</news:title>
   <news:publication_date>2026-07-07T07:06:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709048</loc>
  <lastmod>2026-07-07T07:06:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆最近傍を用いた高効率な密度ベースクラスタリング（An efficient density-based clustering algorithm using reverse nearest neighbour）</news:title>
   <news:publication_date>2026-07-07T07:06:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709046</loc>
  <lastmod>2026-07-07T06:15:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己参照型深層学習（Self-Referenced Deep Learning）</news:title>
   <news:publication_date>2026-07-07T06:15:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709044</loc>
  <lastmod>2026-07-07T06:14:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話ボットにおけるチットチャット処理の信頼性・責任性・解釈可能性（A Trustworthy, Responsible and Interpretable System to Handle Chit Chat in Conversational Bots）</news:title>
   <news:publication_date>2026-07-07T06:14:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709042</loc>
  <lastmod>2026-07-07T06:14:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>測定に基づく適応プロトコルと量子強化学習（Measurement-Based Adaptation Protocol with Quantum Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-07T06:14:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709040</loc>
  <lastmod>2026-07-07T06:13:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルアーキテクチャ探索を組み込んだ深層能動学習（Deep Active Learning with a Neural Architecture Search）</news:title>
   <news:publication_date>2026-07-07T06:13:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709038</loc>
  <lastmod>2026-07-07T06:13:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一度見ただけで場所を想像して自己位置を推定する技術（Localisation via Deep Imagination: learn the features not the map）</news:title>
   <news:publication_date>2026-07-07T06:13:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709036</loc>
  <lastmod>2026-07-07T06:13:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習を用いた無線センサーネットワークの省エネ（Energy Efficiency in Reinforcement Learning for Wireless Sensor Networks）</news:title>
   <news:publication_date>2026-07-07T06:13:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709034</loc>
  <lastmod>2026-07-07T06:13:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の最適化をシンプルにする新手法（Deep Frank-Wolfe for Neural Network Optimization）</news:title>
   <news:publication_date>2026-07-07T06:13:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709032</loc>
  <lastmod>2026-07-07T05:21:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CA3Netによる歩行者再識別の文脈注意ネットワーク（CA3Net: Contextual-Attentional Attribute-Appearance Network for Person Re-Identification）</news:title>
   <news:publication_date>2026-07-07T05:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709030</loc>
  <lastmod>2026-07-07T05:13:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェブデータと補助カテゴリを組み合わせた細分類の学習（Fine-grained Classification using Heterogeneous Web Data and Auxiliary Categories）</news:title>
   <news:publication_date>2026-07-07T05:13:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709028</loc>
  <lastmod>2026-07-07T05:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル結合ソース・チャネル符号化（Neural Joint Source-Channel Coding）</news:title>
   <news:publication_date>2026-07-07T05:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709026</loc>
  <lastmod>2026-07-07T05:12:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三次元畳み込みニューラルネットワークの正則化ベース剪定（THREE-DIMENSIONAL CONVOLUTIONAL NEURAL NETWORK PRUNING WITH REGULARIZATION-BASED METHOD）</news:title>
   <news:publication_date>2026-07-07T05:12:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709024</loc>
  <lastmod>2026-07-07T05:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク完了型対話ポリシー学習の効率化—Switch‑DDQの提案（Switch-based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning）</news:title>
   <news:publication_date>2026-07-07T05:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709022</loc>
  <lastmod>2026-07-07T05:11:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習済みDenseNetエンコーダを用いた脳腫瘍セグメンテーション（A Pretrained DenseNet Encoder for Brain Tumor Segmentation）</news:title>
   <news:publication_date>2026-07-07T05:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709020</loc>
  <lastmod>2026-07-07T05:10:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現と注意を強化したメタ学習（Representation based and Attention augmented Meta learning）</news:title>
   <news:publication_date>2026-07-07T05:10:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709018</loc>
  <lastmod>2026-07-07T04:20:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MIMOチャネル情報のフィードバックに深層リカレントネットワークを用いる（MIMO Channel Information Feedback Using Deep Recurrent Network）</news:title>
   <news:publication_date>2026-07-07T04:20:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709016</loc>
  <lastmod>2026-07-07T04:20:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層事前分布を用いた変分ベイズ的ドロップアウト（Variational Bayesian Dropout with a Hierarchical Prior）</news:title>
   <news:publication_date>2026-07-07T04:20:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709014</loc>
  <lastmod>2026-07-07T04:19:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴選択をSR-DAGで解く：最良葉識別によるモンテカルロ探索の応用 (Feature selection as Monte-Carlo Search in Growing Single Rooted Directed Acyclic Graph by Best Leaf Identification)</news:title>
   <news:publication_date>2026-07-07T04:19:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709012</loc>
  <lastmod>2026-07-07T04:19:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習可能な高次表現による行動認識（Learnable Higher-order Representation for Action Recognition）</news:title>
   <news:publication_date>2026-07-07T04:19:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709010</loc>
  <lastmod>2026-07-07T04:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGデータに対するリザバー型ニューラルネットの教師なし学習による感情認識（Unsupervised Learning in Reservoir Computing for EEG-based Emotion Recognition）</news:title>
   <news:publication_date>2026-07-07T04:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709008</loc>
  <lastmod>2026-07-07T04:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実用的な深層強化学習による株式トレーディング手法の検討（Practical Deep Reinforcement Learning Approach for Stock Trading）</news:title>
   <news:publication_date>2026-07-07T04:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709006</loc>
  <lastmod>2026-07-07T04:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多分野にまたがる学習内容を用いた電磁気学教育の実践（Teaching electromagnetism through demonstration of a practical application involving learning content from multiple disciplines）</news:title>
   <news:publication_date>2026-07-07T04:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709004</loc>
  <lastmod>2026-07-07T03:27:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NSEENによるエンティティ正規化の革新（NSEEN: Neural Semantic Embedding for Entity Normalization）</news:title>
   <news:publication_date>2026-07-07T03:27:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709002</loc>
  <lastmod>2026-07-07T03:27:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dセファロメトリ自動注釈と3D畳み込みニューラルネットワーク（Automatic Three-Dimensional Cephalometric Annotation System Using Three-Dimensional Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-07T03:27:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709000</loc>
  <lastmod>2026-07-07T03:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルリングでRNNを圧縮し行動認識へ応用（Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition）</news:title>
   <news:publication_date>2026-07-07T03:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708998</loc>
  <lastmod>2026-07-07T03:26:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数フレーム・複数特徴の統合によるロバスト視覚追跡（Robust Visual Tracking using Multi-Frame Multi-Feature Joint Modeling）</news:title>
   <news:publication_date>2026-07-07T03:26:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708996</loc>
  <lastmod>2026-07-07T03:26:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者単位での加齢黄斑変性重症度自動判定を実現したDeepSeeNet（DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs）</news:title>
   <news:publication_date>2026-07-07T03:26:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708994</loc>
  <lastmod>2026-07-07T03:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多プロトコルに対応する自己適応型ネットワークによる多発性硬化症病変セグメンテーション（A SELF-ADAPTIVE NETWORK FOR MULTIPLE SCLEROSIS LESION SEGMENTATION FROM MULTI-CONTRAST MRI WITH VARIOUS IMAGING PROTOCOLS）</news:title>
   <news:publication_date>2026-07-07T03:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708992</loc>
  <lastmod>2026-07-07T03:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FotonNetによる3D深度と2D分類の統合的物体検出（FotonNet: A HW-Efﬁcient Object Detection System Using 3D-Depth Segmentation and 2D-DNN Classifier）</news:title>
   <news:publication_date>2026-07-07T03:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708990</loc>
  <lastmod>2026-07-07T02:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Memory In Memory：時空間ダイナミクスから高次非定常性を学習する予測ニューラルネットワーク（Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics）</news:title>
   <news:publication_date>2026-07-07T02:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708988</loc>
  <lastmod>2026-07-07T02:34:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>操作スキルを新環境に拡張する方法（Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models）</news:title>
   <news:publication_date>2026-07-07T02:34:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708986</loc>
  <lastmod>2026-07-07T02:33:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一貫した注意機構を持つSiameseネットワークによる人物再識別（Re-Identification with Consistent Attentive Siamese Networks）</news:title>
   <news:publication_date>2026-07-07T02:33:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708984</loc>
  <lastmod>2026-07-07T02:32:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における鍵となる注目領域の再強調（Global and Local Sensitivity Guided Key Salient Object Re-augmentation for Video Saliency Detection）</news:title>
   <news:publication_date>2026-07-07T02:32:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708982</loc>
  <lastmod>2026-07-07T02:32:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像と弾幕による感情解析の統合モデル（Visual-Textual Emotion Analysis with Deep Coupled Video and Danmu Neural Networks）</news:title>
   <news:publication_date>2026-07-07T02:32:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708980</loc>
  <lastmod>2026-07-07T02:32:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意の分離と一貫性による学習の鋭敏化（Sharpen Focus: Learning with Attention Separability and Consistency）</news:title>
   <news:publication_date>2026-07-07T02:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708978</loc>
  <lastmod>2026-07-07T02:32:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連結バンディットにおける最良腕同定（Best Arm Identification in Linked Bandits）</news:title>
   <news:publication_date>2026-07-07T02:32:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708976</loc>
  <lastmod>2026-07-07T01:40:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療教育におけるハプティクスの可能性（Haptics for Medical Training）</news:title>
   <news:publication_date>2026-07-07T01:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708974</loc>
  <lastmod>2026-07-07T01:40:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における人物再識別のためのマルチスケール3D畳み込みネットワーク（Multi-scale 3D Convolution Network for Video Based Person Re-Identification）</news:title>
   <news:publication_date>2026-07-07T01:40:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708972</loc>
  <lastmod>2026-07-07T01:40:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子特性予測における不確実性定量化とベイズニューラルネットワークの実用性（Uncertainty quantification of molecular property prediction using Bayesian neural network models）</news:title>
   <news:publication_date>2026-07-07T01:40:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708970</loc>
  <lastmod>2026-07-07T01:39:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VIEW—エンジニアリングのための仮想インタラクティブなウェブ学習環境（VIEW – A Virtual Interactive Web-based Learning Environment for Engineering）</news:title>
   <news:publication_date>2026-07-07T01:39:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708968</loc>
  <lastmod>2026-07-07T01:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Indoor GeoNetによる屋内深度・カメラ姿勢推定の弱教師ありハイブリッド学習（Indoor GeoNet: Weakly Supervised Hybrid Learning for Depth and Pose Estimation）</news:title>
   <news:publication_date>2026-07-07T01:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708966</loc>
  <lastmod>2026-07-07T01:39:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイジアン・サイクルGANによる安定化と多様化（Bayesian Cycle-Consistent Generative Adversarial Networks via Marginalizing Latent Sampling）</news:title>
   <news:publication_date>2026-07-07T01:39:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708964</loc>
  <lastmod>2026-07-07T01:38:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師付きで複数行動を検出するSTARネットワーク（Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection）</news:title>
   <news:publication_date>2026-07-07T01:38:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708961</loc>
  <lastmod>2026-07-07T00:47:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類層の特徴を用いた転移学習（TRANSFER LEARNING USING CLASSIFICATION LAYER FEATURES OF CNN）</news:title>
   <news:publication_date>2026-07-07T00:47:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708959</loc>
  <lastmod>2026-07-07T00:47:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル正規化による汎化可能な敵対的訓練（Generalizable Adversarial Training via Spectral Normalization）</news:title>
   <news:publication_date>2026-07-07T00:47:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708957</loc>
  <lastmod>2026-07-07T00:47:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きなノルムはより転移しやすい：Adaptive Feature Normによるドメイン適応の簡潔解説（Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-07-07T00:47:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708955</loc>
  <lastmod>2026-07-07T00:46:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書き筆跡検証のハイブリッド特徴学習（Hybrid Feature Learning for Handwriting Verification）</news:title>
   <news:publication_date>2026-07-07T00:46:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708953</loc>
  <lastmod>2026-07-07T00:46:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PyTorch-Kaldiによる音声認識の実用化基盤（THE PYTORCH-KALDI SPEECH RECOGNITION TOOLKIT）</news:title>
   <news:publication_date>2026-07-07T00:46:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708951</loc>
  <lastmod>2026-07-07T00:46:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーツ合成で「見えない形」を生み出すCompoNet（CompoNet: Learning to Generate the Unseen by Part Synthesis and Composition）</news:title>
   <news:publication_date>2026-07-07T00:46:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708949</loc>
  <lastmod>2026-07-07T00:46:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ダブリング次元における幾何学的アライメント（On Geometric Alignment in Low Doubling Dimension）</news:title>
   <news:publication_date>2026-07-07T00:46:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708947</loc>
  <lastmod>2026-07-06T23:55:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pixel-Anchor：画素ベースとアンカーベースを融合した単発テキスト検出器（Pixel-Anchor: A Single-Shot Oriented Scene Text Detector）</news:title>
   <news:publication_date>2026-07-06T23:55:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708945</loc>
  <lastmod>2026-07-06T23:54:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的深層ネットワークが切り拓く「分布を扱う」AIの新地平（Stochastic Deep Networks）</news:title>
   <news:publication_date>2026-07-06T23:54:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708943</loc>
  <lastmod>2026-07-06T23:53:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUに組み込まれたディープラーニングアクセラレータのモデリング（Modeling Deep Learning Accelerator Enabled GPUs）</news:title>
   <news:publication_date>2026-07-06T23:53:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708941</loc>
  <lastmod>2026-07-06T23:53:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイムスケジューリングと電力配分を実現する深層学習の実装（Realtime Scheduling and Power Allocation Using Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-06T23:53:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708939</loc>
  <lastmod>2026-07-06T23:53:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮テンソルのコア整合性が意味するもの（THE CORE CONSISTENCY OF A COMPRESSED TENSOR）</news:title>
   <news:publication_date>2026-07-06T23:53:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708937</loc>
  <lastmod>2026-07-06T23:53:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MALTS: 学習によるストレッチで改良するマッチング手法（MALTS: Matching After Learning to Stretch）</news:title>
   <news:publication_date>2026-07-06T23:53:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708935</loc>
  <lastmod>2026-07-06T23:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハーモニック・リコンポジションの条件付き自己回帰モデリング（Harmonic Recomposition using Conditional Autoregressive Modeling）</news:title>
   <news:publication_date>2026-07-06T23:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708933</loc>
  <lastmod>2026-07-06T23:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Taboo Trapによる敵対的サンプル検出の実装と意義（THE TABOO TRAP: BEHAVIOURAL DETECTION OF ADVERSARIAL SAMPLES）</news:title>
   <news:publication_date>2026-07-06T23:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708931</loc>
  <lastmod>2026-07-06T22:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル情報を深く結びつける設計の提案（Multimodal Densenet）</news:title>
   <news:publication_date>2026-07-06T22:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708929</loc>
  <lastmod>2026-07-06T22:53:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチユーザーVR360の遅延制御とQoE重視の深層学習支援マルチキャスト枠組み（Taming the latency in multi-user VR 360◦: A QoE-aware deep learning-aided multicast framework）</news:title>
   <news:publication_date>2026-07-06T22:53:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708927</loc>
  <lastmod>2026-07-06T22:53:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Siamese Networksとベイズ最適化による動画物体追跡の統合手法（Deep Siamese Networks with Bayesian non-Parametrics for Video Object Tracking）</news:title>
   <news:publication_date>2026-07-06T22:53:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708925</loc>
  <lastmod>2026-07-06T22:52:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>荷電流深非弾性散乱における準排他的重クォーク生成（Semi-Exclusive Heavy Quark Production in Charged-Current Deep Inelastic Scattering）</news:title>
   <news:publication_date>2026-07-06T22:52:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708923</loc>
  <lastmod>2026-07-06T22:51:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠距離歩行者検出を改善する深層生成とSSDの統合（Deep Learning based Pedestrian Detection at Distance in Smart Cities）</news:title>
   <news:publication_date>2026-07-06T22:51:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708921</loc>
  <lastmod>2026-07-06T22:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度画像を特権情報として用いるRGBベースの3D手指姿勢推定（RGB-based 3D Hand Pose Estimation via Privileged Learning with Depth Images）</news:title>
   <news:publication_date>2026-07-06T22:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708919</loc>
  <lastmod>2026-07-06T21:59:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>引用の役割と出典位置を同時に学習するニューラル手法（Neural Multi-Task Learning for Citation Function and Provenance）</news:title>
   <news:publication_date>2026-07-06T21:59:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708917</loc>
  <lastmod>2026-07-06T21:59:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>性別認識と年齢推定のための転移学習（Transfer Learning with Deep CNNs for Gender Recognition and Age Estimation）</news:title>
   <news:publication_date>2026-07-06T21:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708915</loc>
  <lastmod>2026-07-06T21:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル差分を探索価値に変える方策最適化（Policy Optimization with Model-based Explorations）</news:title>
   <news:publication_date>2026-07-06T21:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708913</loc>
  <lastmod>2026-07-06T21:58:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sparkエコシステム概観と実務への示唆（A Survey on Spark Ecosystem for Big Data Processing）</news:title>
   <news:publication_date>2026-07-06T21:58:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708911</loc>
  <lastmod>2026-07-06T21:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換領域に基づく多重線形動的システム（Transform-Based Multilinear Dynamical System for Tensor Time Series Analysis）</news:title>
   <news:publication_date>2026-07-06T21:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708909</loc>
  <lastmod>2026-07-06T21:58:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布差異最大化による画像プライバシー保護（Distribution Discrepancy Maximization for Image Privacy Preserving）</news:title>
   <news:publication_date>2026-07-06T21:58:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708907</loc>
  <lastmod>2026-07-06T21:58:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライブ映像で動く高精度顔認識の実装（Implementation of Robust Face Recognition System Using Live Video Feed Based on CNN）</news:title>
   <news:publication_date>2026-07-06T21:58:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708905</loc>
  <lastmod>2026-07-06T21:06:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能性のための正則化された敵対的生成例（Regularized adversarial examples for model interpretability）</news:title>
   <news:publication_date>2026-07-06T21:06:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708903</loc>
  <lastmod>2026-07-06T21:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>整形手術と変装による顔変化に対する照合手法（On Matching Faces with Alterations due to Plastic Surgery and Disguise）</news:title>
   <news:publication_date>2026-07-06T21:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708901</loc>
  <lastmod>2026-07-06T21:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種組み込み機器上でのDNN推論最適化：RLによるプリミティブ選択探索（Learning to infer: RL-based search for DNN primitive selection on Heterogeneous Embedded Systems）</news:title>
   <news:publication_date>2026-07-06T21:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708899</loc>
  <lastmod>2026-07-06T21:05:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>詳細GPUシミュレータによる機械学習ワークロード解析（Analyzing Machine Learning Workloads Using a Detailed GPU Simulator）</news:title>
   <news:publication_date>2026-07-06T21:05:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708897</loc>
  <lastmod>2026-07-06T21:05:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分ディリクレ枠組みによる異常検知（A Variational Dirichlet Framework for Out-of-Distribution Detection）</news:title>
   <news:publication_date>2026-07-06T21:05:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708895</loc>
  <lastmod>2026-07-06T21:04:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN-QP：勾配消失とLipschitz制約を同時に回避する新しいGAN枠組み (GAN-QP: A Novel GAN Framework without Gradient Vanishing and Lipschitz Constraint)</news:title>
   <news:publication_date>2026-07-06T21:04:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708893</loc>
  <lastmod>2026-07-06T21:04:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値混合モデルに関する情報理論的下界（Information Theoretic Bounds on Optimal Worst-case Error in Binary Mixture Identification）</news:title>
   <news:publication_date>2026-07-06T21:04:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708891</loc>
  <lastmod>2026-07-06T20:12:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化マップを用いた強化学習における知識の貯蔵と転移（Self-Organizing Maps for Storage and Transfer of Knowledge in Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-06T20:12:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708889</loc>
  <lastmod>2026-07-06T20:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像とGPSの検証を下から照合する手法（Image-to-GPS Verification Through A Bottom-Up Pattern Matching Network）</news:title>
   <news:publication_date>2026-07-06T20:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708887</loc>
  <lastmod>2026-07-06T20:12:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習モデルの理解を深める—適切な解像度で重要特徴を特定する手法（Understanding Learned Models by Identifying Important Features at the Right Resolution）</news:title>
   <news:publication_date>2026-07-06T20:12:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708885</loc>
  <lastmod>2026-07-06T20:11:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全な訓練データで学ぶ深層学習による画像修復（Deep Learning with Inaccurate Training Data for Image Restoration）</news:title>
   <news:publication_date>2026-07-06T20:11:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708883</loc>
  <lastmod>2026-07-06T20:11:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RePrによる畳み込みフィルタの改良訓練（RePr: Improved Training of Convolutional Filters）</news:title>
   <news:publication_date>2026-07-06T20:11:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708881</loc>
  <lastmod>2026-07-06T20:10:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CIFAR10で見る深層ニューラルネットワークと人間の視覚認識の比較（CIFAR10 to Compare Visual Recognition Performance between Deep Neural Networks and Humans）</news:title>
   <news:publication_date>2026-07-06T20:10:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708879</loc>
  <lastmod>2026-07-06T20:10:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主要作物の非生物的ストレス誘導遺伝子におけるシグナル配列の予測（Prediction of Signal Sequences in Abiotic Stress Inducible Genes from Main Crops by Association Rule Mining）</news:title>
   <news:publication_date>2026-07-06T20:10:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708877</loc>
  <lastmod>2026-07-06T19:19:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサー駆動の確率的グラフによる大規模電力系モデリング（Probabilistic Graphs for Sensor Data-driven Modelling of Power Systems at Scale）</news:title>
   <news:publication_date>2026-07-06T19:19:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708875</loc>
  <lastmod>2026-07-06T19:19:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepConsensus: 多層の特徴の合意で揺らぎに強い画像分類を実現する（DeepConsensus: using the consensus of features from multiple layers to attain robust image classification）</news:title>
   <news:publication_date>2026-07-06T19:19:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708873</loc>
  <lastmod>2026-07-06T19:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>より高品質なスタイル転送を実現するGLStyleNet（GLStyleNet: Higher Quality Style Transfer Combining Global and Local Pyramid Features）</news:title>
   <news:publication_date>2026-07-06T19:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708871</loc>
  <lastmod>2026-07-06T19:17:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロジェクト型実験授業での学びを探る—学生のリフレクションを用いた評価（Using reflections to explore student learning during the project component of an advanced laboratory course）</news:title>
   <news:publication_date>2026-07-06T19:17:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708869</loc>
  <lastmod>2026-07-06T19:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカルRGB-to-CAD対応関係を学習して物体姿勢を推定する手法（Learning Local RGB-to-CAD Correspondences for Object Pose Estimation）</news:title>
   <news:publication_date>2026-07-06T19:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708867</loc>
  <lastmod>2026-07-06T19:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理タスクにおける不確実性の定量化（Quantifying Uncertainties in Natural Language Processing Tasks）</news:title>
   <news:publication_date>2026-07-06T19:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708865</loc>
  <lastmod>2026-07-06T19:16:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ的交差性フェアネスの評価（Bayesian Modeling of Intersectional Fairness: The Variance of Bias）</news:title>
   <news:publication_date>2026-07-06T19:16:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708855</loc>
  <lastmod>2026-07-06T18:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Determinantal Point Processes（Deep Determinantal Point Processes）</news:title>
   <news:publication_date>2026-07-06T18:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708853</loc>
  <lastmod>2026-07-06T18:15:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PointConvによる3D点群向け深層畳み込みネットワーク（PointConv: Deep Convolutional Networks on 3D Point Clouds）</news:title>
   <news:publication_date>2026-07-06T18:15:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708851</loc>
  <lastmod>2026-07-06T18:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TTSにおける表現混合法（Representation Mixing for TTS Synthesis）</news:title>
   <news:publication_date>2026-07-06T18:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708849</loc>
  <lastmod>2026-07-06T18:14:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>匿名性の深掘り：Quora質問の大規模分析（Deep Dive into Anonymity: A Large Scale Analysis of Quora Questions）</news:title>
   <news:publication_date>2026-07-06T18:14:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708847</loc>
  <lastmod>2026-07-06T18:14:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴と抽象行動を学習して一般化計画を計算する（Learning Features and Abstract Actions for Computing Generalized Plans）</news:title>
   <news:publication_date>2026-07-06T18:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708845</loc>
  <lastmod>2026-07-06T18:14:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動ソースコード要約の改善（Improving Automatic Source Code Summarization via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-06T18:14:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708843</loc>
  <lastmod>2026-07-06T18:13:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワーク進化の加速（Accelerating the Evolution of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-06T18:13:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708841</loc>
  <lastmod>2026-07-06T17:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙ベクトルの非教師型後処理とコンセプタ反転（Unsupervised Post-processing of Word Vectors via Conceptor Negation）</news:title>
   <news:publication_date>2026-07-06T17:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708839</loc>
  <lastmod>2026-07-06T17:22:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形文表現における共通談話バイアスの補正（Correcting the Common Discourse Bias in Linear Representation of Sentences using Conceptors）</news:title>
   <news:publication_date>2026-07-06T17:22:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708837</loc>
  <lastmod>2026-07-06T17:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ共有によるマルチエージェント運転行動学習の設計（Parameter Sharing Reinforcement Learning Architecture for Multi Agent Driving Behaviors）</news:title>
   <news:publication_date>2026-07-06T17:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708835</loc>
  <lastmod>2026-07-06T17:20:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空散乱ネットワークによる電磁逆設計と断層撮影（Space-Time Scattering Network for Electromagnetic Inverse Design and Tomography）</news:title>
   <news:publication_date>2026-07-06T17:20:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708833</loc>
  <lastmod>2026-07-06T17:20:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多エージェント強化学習における言語規約の自発的出現（Emergence of linguistic conventions in multi-agent reinforcement learning）</news:title>
   <news:publication_date>2026-07-06T17:20:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708831</loc>
  <lastmod>2026-07-06T17:20:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層スパース符号化に基づく分類器は転移可能な敵対的例に頑健である（Classifiers Based on Deep Sparse Coding Architectures are Robust to Deep Learning Transferable Examples）</news:title>
   <news:publication_date>2026-07-06T17:20:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708829</loc>
  <lastmod>2026-07-06T17:19:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークのロバストネス評価の統計的アプローチ（A Statistical Approach to Assessing Neural Network Robustness）</news:title>
   <news:publication_date>2026-07-06T17:19:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708827</loc>
  <lastmod>2026-07-06T16:28:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ部分集合を用いた高速かつ貪欲なガウス過程のスパース化手法（A Fast and Greedy Subset-of-Data (SoD) Scheme for Sparsification in Gaussian processes）</news:title>
   <news:publication_date>2026-07-06T16:28:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708825</loc>
  <lastmod>2026-07-06T16:28:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的スパース擬似入力ガウス過程SARSA（Recursive Sparse Pseudo-input Gaussian Process SARSA）</news:title>
   <news:publication_date>2026-07-06T16:28:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708823</loc>
  <lastmod>2026-07-06T16:27:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エルゴード推論が開く並列化の扉（The Theory and Algorithm of Ergodic Inference）</news:title>
   <news:publication_date>2026-07-06T16:27:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708821</loc>
  <lastmod>2026-07-06T16:27:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布値データに対するBatch Self Organizing Mapと変数・成分の自動重み付け（Batch Self Organizing maps for distributional data with automatic weighting of variables and components）</news:title>
   <news:publication_date>2026-07-06T16:27:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708819</loc>
  <lastmod>2026-07-06T16:26:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚だけで触覚を推定する研究（Sequential Image-based Attention Network for Inferring Force Estimation without Haptic Sensor）</news:title>
   <news:publication_date>2026-07-06T16:26:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708817</loc>
  <lastmod>2026-07-06T16:26:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタッキング型深層解析ネットワークの実務的理解（Stacking-Based Deep Neural Network: Deep Analytic Network for Pattern Classification）</news:title>
   <news:publication_date>2026-07-06T16:26:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708815</loc>
  <lastmod>2026-07-06T16:26:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質量分析からの化学構造同定を部分構造で解く（Chemical Structure Elucidation from Mass Spectrometry by Matching Substructures）</news:title>
   <news:publication_date>2026-07-06T16:26:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708813</loc>
  <lastmod>2026-07-06T15:35:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的グラフにおけるリンク予測によるレコメンデーションの改良（Link Prediction in Dynamic Graphs for Recommendation）</news:title>
   <news:publication_date>2026-07-06T15:35:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708811</loc>
  <lastmod>2026-07-06T15:34:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を用いたWi‑Fiネットワークにおける歩行動作と方向の認識（Attention-based Walking Gait and Direction Recognition in Wi‑Fi Networks）</news:title>
   <news:publication_date>2026-07-06T15:34:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708809</loc>
  <lastmod>2026-07-06T15:34:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人の識別と体格指数（Person Identification and Body Mass Index: A Deep Learning-Based Study on Micro-Dopplers）</news:title>
   <news:publication_date>2026-07-06T15:34:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708807</loc>
  <lastmod>2026-07-06T15:33:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果的な3D CNNのための再帰畳み込み（Recurrent Convolutions for Causal 3D CNNs）</news:title>
   <news:publication_date>2026-07-06T15:33:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708805</loc>
  <lastmod>2026-07-06T15:33:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単調性分類の総覧（Monotonic classification: an overview on algorithms, performance measures and data sets）</news:title>
   <news:publication_date>2026-07-06T15:33:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708803</loc>
  <lastmod>2026-07-06T15:32:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限定的楽観が後悔を減らす——割引和ゲームにおける最小後悔のアルゴリズム（The Impatient May Use Limited Optimism to Minimize Regret）</news:title>
   <news:publication_date>2026-07-06T15:32:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708801</loc>
  <lastmod>2026-07-06T15:32:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キャッシュ占有チャネルによる堅牢なウェブサイト識別（Robust Website Fingerprinting Through the Cache Occupancy Channel）</news:title>
   <news:publication_date>2026-07-06T15:32:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708799</loc>
  <lastmod>2026-07-06T14:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高精度タンパク質二次構造Q8予測（High Quality Protein Q8 Secondary Structure Prediction）</news:title>
   <news:publication_date>2026-07-06T14:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708797</loc>
  <lastmod>2026-07-06T14:40:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質可溶性予測に向けたDNNと条件付きWGANの統合（Deep learning framework DNN with conditional WGAN for protein solubility prediction）</news:title>
   <news:publication_date>2026-07-06T14:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708795</loc>
  <lastmod>2026-07-06T14:40:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電力系統データストリームから学ぶフェーザ探偵法（Learning from power system data stream: phasor-detective approach）</news:title>
   <news:publication_date>2026-07-06T14:40:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708793</loc>
  <lastmod>2026-07-06T14:39:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信号・雑音統計を要さない高SNR一貫性圧縮センシング（High SNR Consistent Compressive Sensing Without Signal and Noise Statistics）</news:title>
   <news:publication_date>2026-07-06T14:39:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708791</loc>
  <lastmod>2026-07-06T14:39:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間関節関係の明示的学習による姿勢追跡（Explicit Spatiotemporal Joint Relation Learning for Tracking Human Pose）</news:title>
   <news:publication_date>2026-07-06T14:39:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708789</loc>
  <lastmod>2026-07-06T14:39:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層を活かす深層分類器の知識統合（Integrating Domain Knowledge: Using Hierarchies to Improve Deep Classifiers）</news:title>
   <news:publication_date>2026-07-06T14:39:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708787</loc>
  <lastmod>2026-07-06T14:38:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Batch DropBlock による人物再識別の改良（Batch DropBlock Network for Person Re-identification and Beyond）</news:title>
   <news:publication_date>2026-07-06T14:38:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708785</loc>
  <lastmod>2026-07-06T13:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚類似性と語義類似性の関係を再考する（Not just a matter of semantics: the relationship between visual and semantic similarity）</news:title>
   <news:publication_date>2026-07-06T13:47:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708783</loc>
  <lastmod>2026-07-06T13:47:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TFT型NORフラッシュを用いたSTDPによる複数出力ニューロンの教師なしオンライン学習（Unsupervised Online Learning With Multiple Postsynaptic Neurons Based on Spike-Timing-Dependent Plasticity Using a TFT-Type NOR Flash Memory Array）</news:title>
   <news:publication_date>2026-07-06T13:47:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708781</loc>
  <lastmod>2026-07-06T13:46:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張LiDARシミュレータによる自動運転データ拡張（Augmented LiDAR Simulator for Autonomous Driving）</news:title>
   <news:publication_date>2026-07-06T13:46:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708779</loc>
  <lastmod>2026-07-06T13:45:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーシステンスランドスケープの非パラメトリック混合モデルと重要点抽出（Finite Mixture Model of Nonparametric Density Estimation using Sampling Importance Resampling for Persistence Landscape）</news:title>
   <news:publication_date>2026-07-06T13:45:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708777</loc>
  <lastmod>2026-07-06T13:45:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線ネットワークの混合整数資源割当問題に対する転移学習（Transfer Learning for Mixed-Integer Resource Allocation Problems in Wireless Networks）</news:title>
   <news:publication_date>2026-07-06T13:45:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708775</loc>
  <lastmod>2026-07-06T13:45:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNNの堅牢性検証を加速する「弱点発見ブースティング」手法（Boosting the Robustness Verification of DNN by Identifying the Achilles’s Heel）</news:title>
   <news:publication_date>2026-07-06T13:45:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708773</loc>
  <lastmod>2026-07-06T13:45:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホログラフィーに明視野コントラストをもたらすクロスモダリティ深層学習（Cross-modality deep learning brings bright-field microscopy contrast to holography）</news:title>
   <news:publication_date>2026-07-06T13:45:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708771</loc>
  <lastmod>2026-07-06T12:53:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RelationNet2による深層比較列で進化する少数ショット学習（RelationNet2: Deep Comparison Columns for Few-Shot Learning）</news:title>
   <news:publication_date>2026-07-06T12:53:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708769</loc>
  <lastmod>2026-07-06T12:53:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乱流スカラー混合の深層学習によるモデル発見（Deep Learning of Turbulent Scalar Mixing）</news:title>
   <news:publication_date>2026-07-06T12:53:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708767</loc>
  <lastmod>2026-07-06T12:52:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ネットワークのヘッセ行列スペクトル全体像（The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size）</news:title>
   <news:publication_date>2026-07-06T12:52:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708765</loc>
  <lastmod>2026-07-06T12:52:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチオミクス統合による相乗効果薬剤組合せ予測（Synergistic Drug Combination Prediction by Integrating Multi-omics Data in Deep Learning Models）</news:title>
   <news:publication_date>2026-07-06T12:52:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708763</loc>
  <lastmod>2026-07-06T12:52:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係型LSTMによる動画行動認識（Relational Long Short-Term Memory for Video Action Recognition）</news:title>
   <news:publication_date>2026-07-06T12:52:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708761</loc>
  <lastmod>2026-07-06T12:52:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン適応型トランスファー学習と専門家モデル（Domain Adaptive Transfer Learning with Specialist Models）</news:title>
   <news:publication_date>2026-07-06T12:52:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708759</loc>
  <lastmod>2026-07-06T12:51:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称性を制約に組み込む機械学習（Symmetry constrained machine learning）</news:title>
   <news:publication_date>2026-07-06T12:51:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708757</loc>
  <lastmod>2026-07-06T12:00:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンティティ同義語集合の効率的発見（Mining Entity Synonyms with Efficient Neural Set Generation）</news:title>
   <news:publication_date>2026-07-06T12:00:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708755</loc>
  <lastmod>2026-07-06T12:00:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程で加速するFeldman–Cousins法（Gaussian Process Accelerated Feldman-Cousins Approach for Physical Parameter Inference）</news:title>
   <news:publication_date>2026-07-06T12:00:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708753</loc>
  <lastmod>2026-07-06T11:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事実抽出と検証を統合するニューラル意味マッチングネットワーク（Combining Fact Extraction and Verification with Neural Semantic Matching Networks）</news:title>
   <news:publication_date>2026-07-06T11:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708751</loc>
  <lastmod>2026-07-06T11:59:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTによる環境・健康モニタリングの信頼管理スキーム（A Trust Management Scheme for IoT-Enabled Environmental Health/Accessibility Monitoring Services）</news:title>
   <news:publication_date>2026-07-06T11:59:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708749</loc>
  <lastmod>2026-07-06T11:59:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リカレントニューラルネットワークの生涯学習への挑戦（Towards Training Recurrent Neural Networks for Lifelong Learning）</news:title>
   <news:publication_date>2026-07-06T11:59:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708747</loc>
  <lastmod>2026-07-06T11:59:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GD-1 ストリームの前駆天体探索（Searching for the GD-1 Stream Progenitor in Gaia DR2 with Direct N-body Simulations）</news:title>
   <news:publication_date>2026-07-06T11:59:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708745</loc>
  <lastmod>2026-07-06T11:58:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モノセロスR2の密集コア調査（Early science with the Large Millimetre Telescope: An LMT/AzTEC 1.1 mm Survey of Dense Cores in the Monoceros R2 Giant Molecular Cloud）</news:title>
   <news:publication_date>2026-07-06T11:58:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708743</loc>
  <lastmod>2026-07-06T11:07:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み空間の病理を避ける投影ベイズニューラルネットワーク（Projected Bayesian Neural Networks: Avoiding weight-space pathologies by learning latent representations of neural network weights）</news:title>
   <news:publication_date>2026-07-06T11:07:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708741</loc>
  <lastmod>2026-07-06T11:07:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>座位から立ち上がる動作のロバスト制御（Robust Control of the Sit-to-Stand Movement for a Powered Lower Limb Orthosis）</news:title>
   <news:publication_date>2026-07-06T11:07:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708739</loc>
  <lastmod>2026-07-06T11:06:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習の未解決課題を整理する（The Barbados 2018 List of Open Issues in Continual Learning）</news:title>
   <news:publication_date>2026-07-06T11:06:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708737</loc>
  <lastmod>2026-07-06T11:06:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基板部品検出のためのデータ効率的グラフ埋め込み学習（Data-Efficient Graph Embedding Learning for PCB Component Detection）</news:title>
   <news:publication_date>2026-07-06T11:06:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708735</loc>
  <lastmod>2026-07-06T11:06:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超新星インポスターの後期観測（Deep Late-Time Observations of the Supernova Impostors SN 1954J and SN 1961V）</news:title>
   <news:publication_date>2026-07-06T11:06:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708733</loc>
  <lastmod>2026-07-06T11:06:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>傾斜した光学超格子におけるボース粒子の共鳴的二サイトトンネリングダイナミクス（Resonant two-site tunnelling dynamics of bosons in a tilted optical superlattice）</news:title>
   <news:publication_date>2026-07-06T11:06:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708731</loc>
  <lastmod>2026-07-06T11:05:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像分類のスーパーコンピュータ規模での学習（Image Classification at Supercomputer Scale）</news:title>
   <news:publication_date>2026-07-06T11:05:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708729</loc>
  <lastmod>2026-07-06T10:14:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間的グラウンディンググラフによる言語理解と蓄積された視覚言語文脈（Temporal Grounding Graphs for Language Understanding with Accrued Visual-Linguistic Context）</news:title>
   <news:publication_date>2026-07-06T10:14:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708727</loc>
  <lastmod>2026-07-06T10:14:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DARCCC：カプセル再構成による敵対的入力の検出（DARCCC: Detecting Adversaries by Reconstruction from Class Conditional Capsules）</news:title>
   <news:publication_date>2026-07-06T10:14:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708725</loc>
  <lastmod>2026-07-06T10:13:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPipeによる大規模モデルの効率的な分散学習（GPipe: Easy Scaling with Micro-Batch Pipeline Parallelism）</news:title>
   <news:publication_date>2026-07-06T10:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708723</loc>
  <lastmod>2026-07-06T10:13:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光回折断層撮像におけるコヒーレントノイズ低減の深層学習アプローチ（Deep Learning Approach to Coherent Noise Reduction in Optical Diffraction Tomography）</news:title>
   <news:publication_date>2026-07-06T10:13:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708721</loc>
  <lastmod>2026-07-06T10:13:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Grasp2Vec：自律的把持から学ぶ物体表現（Grasp2Vec: Learning Object Representations from Self-Supervised Grasping）</news:title>
   <news:publication_date>2026-07-06T10:13:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708719</loc>
  <lastmod>2026-07-06T10:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モード変動に強いLSTM：見えない変動に耐える時系列特徴の符号化（Mode Variational LSTM Robust to Unseen Modes of Variation: Application to Facial Expression Recognition）</news:title>
   <news:publication_date>2026-07-06T10:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708717</loc>
  <lastmod>2026-07-06T10:12:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習型ビデオ圧縮の衝撃（Learned Video Compression）</news:title>
   <news:publication_date>2026-07-06T10:12:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708715</loc>
  <lastmod>2026-07-06T09:22:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超グラフ確率的ブロックモデルにおける完全復元（EXACT RECOVERY IN THE HYPERGRAPH STOCHASTIC BLOCK MODEL: A SPECTRAL ALGORITHM）</news:title>
   <news:publication_date>2026-07-06T09:22:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708713</loc>
  <lastmod>2026-07-06T09:21:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフデータの事前学習でGNNを強化する（Pre-training Graph Neural Networks with Kernels）</news:title>
   <news:publication_date>2026-07-06T09:21:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708711</loc>
  <lastmod>2026-07-06T09:21:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコヴィッツポートフォリオ選択におけるベイズ学習（Bayesian learning for the Markowitz portfolio selection problem）</news:title>
   <news:publication_date>2026-07-06T09:21:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708709</loc>
  <lastmod>2026-07-06T09:20:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転不変で汎用的な低次元3D点群記述子の実現（The Perfect Match: 3D Point Cloud Matching with Smoothed Densities）</news:title>
   <news:publication_date>2026-07-06T09:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708707</loc>
  <lastmod>2026-07-06T09:20:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特権情報を用いる回帰と分類のための一般化メタ損失関数 (A Generalized Meta-loss function for regression and classification using privileged information)</news:title>
   <news:publication_date>2026-07-06T09:20:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708705</loc>
  <lastmod>2026-07-06T09:20:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゴール駆動ナビゲーションにおける探索の複雑性（On the Complexity of Exploration in Goal-Driven Navigation）</news:title>
   <news:publication_date>2026-07-06T09:20:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708703</loc>
  <lastmod>2026-07-06T09:20:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次元削減が回帰木ベースの荷重予測に与える影響（A case study : Influence of dimension reduction on regression trees-based algorithms - Predicting aeronautics loads of a derivative aircraft）</news:title>
   <news:publication_date>2026-07-06T09:20:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708701</loc>
  <lastmod>2026-07-06T08:29:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差畳み込みニューラルネットワークの再検討（Residual Convolutional Neural Network Revisited with Active Weighted Mapping）</news:title>
   <news:publication_date>2026-07-06T08:29:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708699</loc>
  <lastmod>2026-07-06T08:28:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTカメラ向けコスト意識細粒度認識（Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations）</news:title>
   <news:publication_date>2026-07-06T08:28:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708697</loc>
  <lastmod>2026-07-06T08:28:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像補完による異常検知の実務的解説（Anomaly Detection using Deep Learning based Image Completion）</news:title>
   <news:publication_date>2026-07-06T08:28:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708695</loc>
  <lastmod>2026-07-06T08:27:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U-net内で時間・周波数軸に再帰性を組み込む音声強調手法（USING RECURRENCES IN TIME AND FREQUENCY WITHIN U-NET ARCHITECTURE FOR SPEECH ENHANCEMENT）</news:title>
   <news:publication_date>2026-07-06T08:27:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708693</loc>
  <lastmod>2026-07-06T08:27:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サリエンシー監視による痛み強度回帰の直感的かつ有効な手法（Saliency Supervision: An intuitive and effective approach for pain intensity regression）</news:title>
   <news:publication_date>2026-07-06T08:27:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708691</loc>
  <lastmod>2026-07-06T08:27:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PaccMannによる抗がん剤感受性予測（PaccMann: Prediction of anticancer compound sensitivity with multi-modal attention-based neural networks）</news:title>
   <news:publication_date>2026-07-06T08:27:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708689</loc>
  <lastmod>2026-07-06T08:27:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転制御における不確実性定量の評価（Evaluating Uncertainty Quantification in End-to-End Autonomous Driving Control）</news:title>
   <news:publication_date>2026-07-06T08:27:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708687</loc>
  <lastmod>2026-07-06T07:36:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DropFilterによるCNNの正則化手法の提案（DropFilter: A Novel Regularization Method for Learning Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-06T07:36:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708685</loc>
  <lastmod>2026-07-06T07:36:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AoI最適化のための強化学習ベーススケジューリング（Reinforcement Learning Based Scheduling Algorithm for Optimizing Age of Information in URLLC）</news:title>
   <news:publication_date>2026-07-06T07:36:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708683</loc>
  <lastmod>2026-07-06T07:35:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換領域更新と指数的適応閾値を用いた疎な逆共分散推定（A Novel Approach to Sparse Inverse Covariance Estimation Using Transform Domain Updates and Exponentially Adaptive Thresholding）</news:title>
   <news:publication_date>2026-07-06T07:35:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708681</loc>
  <lastmod>2026-07-06T07:34:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キーワード検出のための確率的適応ニューラルアーキテクチャ探索（Stochastic Adaptive Neural Architecture Search for Keyword Spotting）</news:title>
   <news:publication_date>2026-07-06T07:34:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708679</loc>
  <lastmod>2026-07-06T07:34:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>概ね最適な契約を学習する（Learning Approximately Optimal Contracts）</news:title>
   <news:publication_date>2026-07-06T07:34:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708677</loc>
  <lastmod>2026-07-06T07:34:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械的判断と人間への影響（MACHINE DECISIONS AND HUMAN CONSEQUENCES）</news:title>
   <news:publication_date>2026-07-06T07:34:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708675</loc>
  <lastmod>2026-07-06T07:33:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エントロピー正則化最適輸送を用いた生成モデル（Entropy-regularized Optimal Transport Generative Models）</news:title>
   <news:publication_date>2026-07-06T07:33:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708673</loc>
  <lastmod>2026-07-06T06:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>領域内位置検証とネットワーク配置の機械学習アプローチ（Location-Verification and Network Planning via Machine Learning Approaches）</news:title>
   <news:publication_date>2026-07-06T06:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708671</loc>
  <lastmod>2026-07-06T06:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチチャネル音声強調におけるVAEとNMFの半教師ありアプローチ（SEMI-SUPERVISED MULTICHANNEL SPEECH ENHANCEMENT WITH VARIATIONAL AUTOENCODERS AND NON-NEGATIVE MATRIX FACTORIZATION）</news:title>
   <news:publication_date>2026-07-06T06:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708669</loc>
  <lastmod>2026-07-06T06:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>模倣学習のアルゴリズム的展望（An Algorithmic Perspective on Imitation Learning）</news:title>
   <news:publication_date>2026-07-06T06:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708667</loc>
  <lastmod>2026-07-06T06:41:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブタスクゲーティングによる非侵襲型消費電力分解（Subtask Gated Networks for Non-Intrusive Load Monitoring）</news:title>
   <news:publication_date>2026-07-06T06:41:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708665</loc>
  <lastmod>2026-07-06T06:40:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粗から細へのタスク転移によるアスペクトレベル感情分類の改善（Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification）</news:title>
   <news:publication_date>2026-07-06T06:40:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708663</loc>
  <lastmod>2026-07-06T06:40:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成によるモデル-Xノックオフの実装と有効性（Deep Knockoffs）</news:title>
   <news:publication_date>2026-07-06T06:40:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708661</loc>
  <lastmod>2026-07-06T06:39:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マゼラン雲における共生星探索の手法と初期発見（A deep survey for symbiotic stars in the Magellanic Clouds - 1. Methodology and first discoveries in the SMC）</news:title>
   <news:publication_date>2026-07-06T06:39:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708659</loc>
  <lastmod>2026-07-06T05:48:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発音方式検出を用いたビームサーチ復号化（BEAM SEARCH DECODING USING MANNER OF ARTICULATION DETECTION）</news:title>
   <news:publication_date>2026-07-06T05:48:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708657</loc>
  <lastmod>2026-07-06T05:48:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTストリーミングデータにおける異常パターン検出と転倒検知（Detecting Irregular Patterns in IoT Streaming Data for Fall Detection）</news:title>
   <news:publication_date>2026-07-06T05:48:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708655</loc>
  <lastmod>2026-07-06T05:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習型インデックス構造による索引圧縮の可能性 (The Potential of Learned Index Structures for Index Compression)</news:title>
   <news:publication_date>2026-07-06T05:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708653</loc>
  <lastmod>2026-07-06T05:47:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同質性に基づく伝播モデルによる真偽ニュースの解析（Homogeneity-Based Transmissive Process To Model True and False News in Social Networks）</news:title>
   <news:publication_date>2026-07-06T05:47:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708651</loc>
  <lastmod>2026-07-06T05:47:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ACLNETによる効率的なエンドツーエンド音声分類（ACLNET: EFFICIENT END-TO-END AUDIO CLASSIFICATION CNN）</news:title>
   <news:publication_date>2026-07-06T05:47:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708649</loc>
  <lastmod>2026-07-06T05:47:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>土の上のAI――圃場内綿花収量予測の空間時系列マルチタスク学習（Spatial-temporal Multi-Task Learning for Within-field Cotton Yield Prediction）</news:title>
   <news:publication_date>2026-07-06T05:47:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708647</loc>
  <lastmod>2026-07-06T05:47:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Composite Binary Decomposition Networks（Composite Binary Decomposition Networks）</news:title>
   <news:publication_date>2026-07-06T05:47:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708645</loc>
  <lastmod>2026-07-06T04:56:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の非古典的相関の同時学習の実験（Experimental Simultaneous Learning of Multiple Non-Classical Correlations）</news:title>
   <news:publication_date>2026-07-06T04:56:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/708643</loc>
  <lastmod>2026-07-06T04:55:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテンツ認識型の個別化レート適応（Content-Aware Personalised Rate Adaptation for Adaptive Streaming via Deep Video Analysis）</news:title>
   <news:publication_date>2026-07-06T04:55:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708641</loc>
  <lastmod>2026-07-06T04:55:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークを使った量子状態推定の効率化（Neural network state estimation for full quantum state tomography）</news:title>
   <news:publication_date>2026-07-06T04:55:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708639</loc>
  <lastmod>2026-07-06T04:55:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤特定ガウス過程モデルの平均二乗予測誤差（Mean Square Prediction Error of Misspecified Gaussian Process Models）</news:title>
   <news:publication_date>2026-07-06T04:55:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708637</loc>
  <lastmod>2026-07-06T04:54:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声で操作するECウェブアプリケーション（A Voice Controlled E-Commerce Web Application）</news:title>
   <news:publication_date>2026-07-06T04:54:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708635</loc>
  <lastmod>2026-07-06T04:54:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載向けモジュール型軽量ネットワークによる道路上物体検出（Detecting The Objects on The Road Using Modular Lightweight Network）</news:title>
   <news:publication_date>2026-07-06T04:54:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708633</loc>
  <lastmod>2026-07-06T04:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル生成が切り拓く現代音楽の可能性（Generating Black Metal and Math Rock: Beyond Bach, Beethoven, and Beatles）</news:title>
   <news:publication_date>2026-07-06T04:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708631</loc>
  <lastmod>2026-07-06T04:03:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SampleRNNによるアルバム自動生成（Generating Albums with SampleRNN to Imitate Metal, Rock, and Punk Bands）</news:title>
   <news:publication_date>2026-07-06T04:03:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708629</loc>
  <lastmod>2026-07-06T04:03:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lagrangian系の追従制御におけるGaussian Processによるモデル適応と利得調整（Stable Gaussian Process based Tracking Control of Lagrangian Systems）</news:title>
   <news:publication_date>2026-07-06T04:03:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708627</loc>
  <lastmod>2026-07-06T04:03:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>より安全なスマートコントラクトへ：セキュリティ脅威検出のための系列学習アプローチ (Towards Safer Smart Contracts: A Sequence Learning Approach to Detecting Security Threats)</news:title>
   <news:publication_date>2026-07-06T04:03:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708625</loc>
  <lastmod>2026-07-06T04:02:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>概念指向ディープラーニング：生成的概念表現（Concept-Oriented Deep Learning: Generative Concept Representations）</news:title>
   <news:publication_date>2026-07-06T04:02:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708623</loc>
  <lastmod>2026-07-06T04:02:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制御におけるスパース表現の有用性（The Utility of Sparse Representations for Control in Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-06T04:02:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708621</loc>
  <lastmod>2026-07-06T04:02:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックス攻撃におけるハイパーパラメータの扱い（A NOTE ON HYPERPARAMETERS IN BLACK-BOX ADVERSARIAL EXAMPLES）</news:title>
   <news:publication_date>2026-07-06T04:02:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708619</loc>
  <lastmod>2026-07-06T04:01:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈依存の上側信頼境界による指向的探索（Context-Dependent Upper-Confidence Bounds for Directed Exploration）</news:title>
   <news:publication_date>2026-07-06T04:01:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708617</loc>
  <lastmod>2026-07-06T03:10:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情を表現するオープンドメイン対話応答生成（Generating Responses Expressing Emotion in an Open–domain Dialogue System）</news:title>
   <news:publication_date>2026-07-06T03:10:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708615</loc>
  <lastmod>2026-07-06T03:10:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多忠度ガウス過程で光ナノ構造を効率最適化する（Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes）</news:title>
   <news:publication_date>2026-07-06T03:10:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708613</loc>
  <lastmod>2026-07-06T03:09:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル的視点で見る敵対的に堅牢な特徴（A Spectral View of Adversarially Robust Features）</news:title>
   <news:publication_date>2026-07-06T03:09:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708611</loc>
  <lastmod>2026-07-06T03:09:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無制約サブモジュラ最大化と低適応複雑度（Unconstrained Submodular Maximization with Constant Adaptive Complexity）</news:title>
   <news:publication_date>2026-07-06T03:09:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708609</loc>
  <lastmod>2026-07-06T03:09:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無限時域ガウス過程（Infinite-Horizon Gaussian Processes）</news:title>
   <news:publication_date>2026-07-06T03:09:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708607</loc>
  <lastmod>2026-07-06T03:09:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分野横断的な重複質問検出の一般性と知識転移可能性（On Generality and Knowledge Transferability in Cross-Domain Duplicate Question Detection for Heterogeneous Community Question Answering）</news:title>
   <news:publication_date>2026-07-06T03:09:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708605</loc>
  <lastmod>2026-07-06T03:09:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合外観ネットワークによる人物追跡と追跡誤差の評価（CAN: Composite Appearance Network for Person Tracking and How to Model Errors in a Tracking System）</news:title>
   <news:publication_date>2026-07-06T03:09:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708603</loc>
  <lastmod>2026-07-06T02:17:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速学習を可能にする安定テンソルニューラルネットワーク（Stable Tensor Neural Networks for Rapid Deep Learning）</news:title>
   <news:publication_date>2026-07-06T02:17:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708601</loc>
  <lastmod>2026-07-06T02:17:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分空間クラスタリングをサブクラスタで拡張する（Subspace Clustering through Sub-Clusters）</news:title>
   <news:publication_date>2026-07-06T02:17:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708599</loc>
  <lastmod>2026-07-06T02:17:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seq2Seqな模倣ゲームとシグナリングの視点（Seq2Seq Mimic Games: A Signaling Perspective）</news:title>
   <news:publication_date>2026-07-06T02:17:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708597</loc>
  <lastmod>2026-07-06T02:16:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MUSE‑Wideサーベイの概要と第一次データリリース（The MUSE‑Wide Survey: Survey Description and First Data Release）</news:title>
   <news:publication_date>2026-07-06T02:16:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708595</loc>
  <lastmod>2026-07-06T02:16:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSST Deep-Drilling Fieldsにおける活動銀河核（AGN）観測要件（Active Galaxy Science in the LSST Deep-Drilling Fields: Footprints, Cadence Requirements, and Total-Depth Requirements）</news:title>
   <news:publication_date>2026-07-06T02:16:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708593</loc>
  <lastmod>2026-07-06T02:15:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダークウェブ掲示板のネットワーク分析による企業サイバー攻撃予測（Predicting enterprise cyber incidents using social network analysis on the darkweb hacker forums）</news:title>
   <news:publication_date>2026-07-06T02:15:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708591</loc>
  <lastmod>2026-07-06T02:15:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二つのブラックホール探索ツール（The binary black hole explorer: on-the-fly visualizations of precessing binary black holes）</news:title>
   <news:publication_date>2026-07-06T02:15:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708589</loc>
  <lastmod>2026-07-06T01:24:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙構造形成を予測する学習モデル（Learning to Predict the Cosmological Structure Formation）</news:title>
   <news:publication_date>2026-07-06T01:24:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708587</loc>
  <lastmod>2026-07-06T01:23:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習におけるMACモデルの改良と応用（On transfer learning using a MAC model variant）</news:title>
   <news:publication_date>2026-07-06T01:23:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708585</loc>
  <lastmod>2026-07-06T01:23:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズの多いデータで「学べるクラス」を見極める手法（Exploiting Class Learnability in Noisy Data）</news:title>
   <news:publication_date>2026-07-06T01:23:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708583</loc>
  <lastmod>2026-07-06T01:23:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QCDの臨界点探索における新しい発想と動的記述の前進（The QCD critical point hunt: emergent new ideas and new dynamics）</news:title>
   <news:publication_date>2026-07-06T01:23:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708581</loc>
  <lastmod>2026-07-06T01:22:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルネットワークによる近似最適化とスピンガラスのドロップレット発見（Approximate optimization, sampling and spin-glass droplets discovery with tensor networks）</news:title>
   <news:publication_date>2026-07-06T01:22:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708579</loc>
  <lastmod>2026-07-06T01:22:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人の好みとデモから学ぶ報酬学習（Reward learning from human preferences and demonstrations in Atari）</news:title>
   <news:publication_date>2026-07-06T01:22:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708577</loc>
  <lastmod>2026-07-06T01:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>治療効果の分布を滑らかに推定する手法（Kernel Smoothing of the Treatment Effect CDF）</news:title>
   <news:publication_date>2026-07-06T01:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708575</loc>
  <lastmod>2026-07-06T00:31:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバスト強化学習におけるベイズ的あいまい集合の最適化（Tight Bayesian Ambiguity Sets for Robust MDPs）</news:title>
   <news:publication_date>2026-07-06T00:31:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708573</loc>
  <lastmod>2026-07-06T00:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の潜在表現における交絡因子補正（Adjusting for Confounding in Unsupervised Latent Representations of Images）</news:title>
   <news:publication_date>2026-07-06T00:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708571</loc>
  <lastmod>2026-07-06T00:30:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前立腺がんのGleason評価を改善する深層学習の実装と検証（Development and Validation of a Deep Learning Algorithm for Improving Gleason Scoring of Prostate Cancer）</news:title>
   <news:publication_date>2026-07-06T00:30:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/708569</loc>
  <lastmod>2026-07-06T00:30:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Calabi-Yau三重項の数と三角分割の推定（Estimating Calabi-Yau Hypersurface and Triangulation Counts with Equation Learners）</news:title>
   <news:publication_date>2026-07-06T00:30:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708567</loc>
  <lastmod>2026-07-06T00:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的攻撃の数学的解析 (Mathematical Analysis of Adversarial Attacks)</news:title>
   <news:publication_date>2026-07-06T00:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708565</loc>
  <lastmod>2026-07-06T00:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細胞分類ニューラルネットワークの深層特徴空間の探究 (Exploring the Deep Feature Space of a Cell Classification Neural Network)</news:title>
   <news:publication_date>2026-07-06T00:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708563</loc>
  <lastmod>2026-07-06T00:29:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接場放射による熱伝達デバイス（A near-field radiative heat transfer device）</news:title>
   <news:publication_date>2026-07-06T00:29:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708561</loc>
  <lastmod>2026-07-05T23:38:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバルクラスターに潜むブラックホールを機械学習で探す手法（Finding Black Holes with Black Boxes – Using Machine Learning to Identify Globular Clusters with Black Hole Subsystems）</news:title>
   <news:publication_date>2026-07-05T23:38:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708559</loc>
  <lastmod>2026-07-05T23:38:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多セルLSTMに基づくニューラル言語モデル（Multi-cell LSTM Based Neural Language Model）</news:title>
   <news:publication_date>2026-07-05T23:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708557</loc>
  <lastmod>2026-07-05T23:38:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クレジット審査に向けた説明可能な深層学習の試み（Towards Explainable Deep Learning for Credit Lending）</news:title>
   <news:publication_date>2026-07-05T23:38:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708555</loc>
  <lastmod>2026-07-05T23:37:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ESO 428-G014の深チャンドラ観測：核領域の硬連続光とFe Kα線の形態（Deep Chandra Observations of ESO 428-G014: IV. The Morphology of the Nuclear Region in the Hard Continuum and Fe Kα Line）</news:title>
   <news:publication_date>2026-07-05T23:37:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708553</loc>
  <lastmod>2026-07-05T23:37:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサーの情報鮮度（Age of Information）を減らす方法（Minimizing the Age of Information from Sensors with Common Observations）</news:title>
   <news:publication_date>2026-07-05T23:37:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708551</loc>
  <lastmod>2026-07-05T23:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を考慮した医療ケアプロトコル（Contextual Care Protocol using Neural Networks and Decision Trees）</news:title>
   <news:publication_date>2026-07-05T23:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708549</loc>
  <lastmod>2026-07-05T23:36:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アドバーサリアル・レジリエンス学習—大規模複雑システムの脆弱性分析に向けて（Adversarial Resilience Learning — Towards Systemic Vulnerability Analysis for Large and Complex Systems）</news:title>
   <news:publication_date>2026-07-05T23:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708547</loc>
  <lastmod>2026-07-05T22:45:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス・ベイズ誤差率の上界学習（Learning to Bound the Multi-class Bayes Error）</news:title>
   <news:publication_date>2026-07-05T22:45:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708545</loc>
  <lastmod>2026-07-05T22:45:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル予測的信念表現（NEURAL PREDICTIVE BELIEF REPRESENTATIONS）</news:title>
   <news:publication_date>2026-07-05T22:45:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708543</loc>
  <lastmod>2026-07-05T22:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗号学的擬似乱数から生じる敵対的事例（Adversarial Examples from Cryptographic Pseudo-Random Generators）</news:title>
   <news:publication_date>2026-07-05T22:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708541</loc>
  <lastmod>2026-07-05T22:44:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理信号の深層分類による車両識別の実用可能性（Physical Signal Classification Via Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-05T22:44:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708539</loc>
  <lastmod>2026-07-05T22:44:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンプレートマッチングによる手書き中国語文字認識（Deep Template Matching for Offline Handwritten Chinese Character Recognition）</news:title>
   <news:publication_date>2026-07-05T22:44:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708537</loc>
  <lastmod>2026-07-05T22:44:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル帯域幅選択のトレース基準（The Trace Criterion for Kernel Bandwidth Selection for Support Vector Data Description）</news:title>
   <news:publication_date>2026-07-05T22:44:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708535</loc>
  <lastmod>2026-07-05T22:43:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期確率的合成最適化における分散削減（Asynchronous Stochastic Composition Optimization with Variance Reduction）</news:title>
   <news:publication_date>2026-07-05T22:43:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708533</loc>
  <lastmod>2026-07-05T21:52:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声から巣箱の状態を識別する研究（AUDIO-BASED IDENTIFICATION OF BEEHIVE STATES）</news:title>
   <news:publication_date>2026-07-05T21:52:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708531</loc>
  <lastmod>2026-07-05T21:52:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地点ごとの履歴を統合して予測精度を高める手法の要点（Spatio-temporal Stacked LSTM for Temperature Prediction）</news:title>
   <news:publication_date>2026-07-05T21:52:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708529</loc>
  <lastmod>2026-07-05T21:51:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間時系列ホーキンス過程によるネットワーク再構築（MULTIVARIATE SPATIOTEMPORAL HAWKES PROCESSES AND NETWORK RECONSTRUCTION）</news:title>
   <news:publication_date>2026-07-05T21:51:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708527</loc>
  <lastmod>2026-07-05T21:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人化時系列セグメンテーションによる携帯電話行動分析（Individualized Time-Series Segmentation for Mining Mobile Phone User Behavior）</news:title>
   <news:publication_date>2026-07-05T21:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708525</loc>
  <lastmod>2026-07-05T21:51:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CycleGANの一対一写像を最適輸送で導く（Guiding the One-to-one Mapping in CycleGAN via Optimal Transport）</news:title>
   <news:publication_date>2026-07-05T21:51:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708523</loc>
  <lastmod>2026-07-05T21:51:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト上で構造化クエリに直接応答する方法（Answering Structured Queries Directly over Text）</news:title>
   <news:publication_date>2026-07-05T21:51:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708521</loc>
  <lastmod>2026-07-05T21:51:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択的特徴結合機構（Selective Feature Connection Mechanism: Concatenating Multi-layer CNN Features with a Feature Selector）</news:title>
   <news:publication_date>2026-07-05T21:51:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708519</loc>
  <lastmod>2026-07-05T20:59:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反実仮想で学ぶ方策探索（WOULDA, COULDA, SHOULDA: COUNTERFACTUALLY-GUIDED POLICY SEARCH）</news:title>
   <news:publication_date>2026-07-05T20:59:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708517</loc>
  <lastmod>2026-07-05T20:59:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による3次元電子密度の効率的予測（Efficient prediction of 3D electron densities using machine learning）</news:title>
   <news:publication_date>2026-07-05T20:59:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708515</loc>
  <lastmod>2026-07-05T20:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の「切り取り（クリッピング）」を復元する深層ネットワーク（IMAGE DECLIPPING WITH DEEP NETWORKS）</news:title>
   <news:publication_date>2026-07-05T20:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708513</loc>
  <lastmod>2026-07-05T20:58:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポリマーナノコンポジットの界面表現を再考する（Rethinking Interphase Representations for Modeling Viscoelastic Properties for Polymer Nanocomposites）</news:title>
   <news:publication_date>2026-07-05T20:58:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708511</loc>
  <lastmod>2026-07-05T20:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音と映像を同時に使う「会話強化」の学び方（ON TRAINING TARGETS AND OBJECTIVE FUNCTIONS FOR DEEP-LEARNING-BASED AUDIO-VISUAL SPEECH ENHANCEMENT）</news:title>
   <news:publication_date>2026-07-05T20:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708509</loc>
  <lastmod>2026-07-05T20:58:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師ありスペクトルグラフ表現の実用性（SGR: Self-Supervised Spectral Graph Representation Learning）</news:title>
   <news:publication_date>2026-07-05T20:58:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708507</loc>
  <lastmod>2026-07-05T20:57:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雑音下における話し方の反射がAV音声強調に与える影響（EFFECTS OF LOMBARD REFLEX ON THE PERFORMANCE OF DEEP-LEARNING-BASED AUDIO-VISUAL SPEECH ENHANCEMENT SYSTEMS）</news:title>
   <news:publication_date>2026-07-05T20:57:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708505</loc>
  <lastmod>2026-07-05T20:06:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高分子の物性予測にGCNNを使う意義（Graph Convolutional Neural Networks for Polymers Property Prediction）</news:title>
   <news:publication_date>2026-07-05T20:06:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708503</loc>
  <lastmod>2026-07-05T20:06:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次意思決定における報酬推定分散の消去（Reward-estimation variance elimination in sequential decision processes）</news:title>
   <news:publication_date>2026-07-05T20:06:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708501</loc>
  <lastmod>2026-07-05T20:05:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルに基づく近似クエリ処理（Model-based Approximate Query Processing）</news:title>
   <news:publication_date>2026-07-05T20:05:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708499</loc>
  <lastmod>2026-07-05T20:04:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>眼科手術画像における顔照合と偽造検出（Face Verification and Forgery Detection for Ophthalmic Surgery Images）</news:title>
   <news:publication_date>2026-07-05T20:04:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708497</loc>
  <lastmod>2026-07-05T20:04:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期風速予測におけるカーネルスペクトル隠れマルコフモデル（Short-Term Wind-Speed Forecasting Using Kernel Spectral Hidden Markov Models）</news:title>
   <news:publication_date>2026-07-05T20:04:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708495</loc>
  <lastmod>2026-07-05T20:04:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深いドメイン適応の理論的理解（On Deep Domain Adaptation: Some Theoretical Understandings）</news:title>
   <news:publication_date>2026-07-05T20:04:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708493</loc>
  <lastmod>2026-07-05T20:04:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結晶グラフと材料記述子から熱電特性を予測する（Predicting thermoelectric properties from crystal graphs and material descriptors – first application for functional materials）</news:title>
   <news:publication_date>2026-07-05T20:04:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708491</loc>
  <lastmod>2026-07-05T19:12:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩容を「集合」とみなす新視点が開く人物識別の実用性向上（GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition）</news:title>
   <news:publication_date>2026-07-05T19:12:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708489</loc>
  <lastmod>2026-07-05T19:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>介入支援強化学習による安全で実用的なナビゲーション方策最適化（Intervention Aided Reinforcement Learning for Safe and Practical Policy Optimization in Navigation）</news:title>
   <news:publication_date>2026-07-05T19:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708487</loc>
  <lastmod>2026-07-05T19:11:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EHR駆動フェノタイプ抽出アルゴリズムの設計パターン特性解析 (Characterizing Design Patterns of EHR-Driven Phenotype Extraction Algorithms)</news:title>
   <news:publication_date>2026-07-05T19:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708485</loc>
  <lastmod>2026-07-05T19:11:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tiyuntsong：自己対戦型強化学習とGANでABRを再設計する（TIYUNTSONG: A SELF-PLAY REINFORCEMENT LEARNING APPROACH FOR ABR VIDEO STREAMING）</news:title>
   <news:publication_date>2026-07-05T19:11:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708483</loc>
  <lastmod>2026-07-05T19:11:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサー不要の深度予測（Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos）</news:title>
   <news:publication_date>2026-07-05T19:11:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708481</loc>
  <lastmod>2026-07-05T19:11:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>金融ニュースを活用した株価動向予測（Leveraging Financial News for Stock Trend Prediction with Attention-Based Recurrent Neural Network）</news:title>
   <news:publication_date>2026-07-05T19:11:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708479</loc>
  <lastmod>2026-07-05T19:10:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療質問応答のための文埋め込み活用（Exploiting Sentence Embedding for Medical Question Answering）</news:title>
   <news:publication_date>2026-07-05T19:10:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708477</loc>
  <lastmod>2026-07-05T18:19:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直交ポリシー勾配と自動運転への応用（Orthogonal Policy Gradient and Autonomous Driving Application）</news:title>
   <news:publication_date>2026-07-05T18:19:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708475</loc>
  <lastmod>2026-07-05T18:19:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エフェクトハンドラによる可換なプログラム変換の実装（Effect Handling for Composable Program Transformations in Edward2）</news:title>
   <news:publication_date>2026-07-05T18:19:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708473</loc>
  <lastmod>2026-07-05T18:19:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークによる電力系統のリアルタイム状態推定と予測（Real-time Power System State Estimation and Forecasting via Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-05T18:19:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708471</loc>
  <lastmod>2026-07-05T18:18:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BESIII実験での機械学習の応用（Application of machine learning techniques at BESIII experiment）</news:title>
   <news:publication_date>2026-07-05T18:18:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708469</loc>
  <lastmod>2026-07-05T18:17:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘテロジニアスソース上での大規模探索的検索の展望（Towards Large-Scale Exploratory Search over Heterogeneous Sources）</news:title>
   <news:publication_date>2026-07-05T18:17:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708467</loc>
  <lastmod>2026-07-05T18:17:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリ拡張型ニューラルネットワークによる概念学習の強化学習アプローチ（Concept Learning through Deep Reinforcement Learning with Memory-Augmented Neural Networks）</news:title>
   <news:publication_date>2026-07-05T18:17:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708465</loc>
  <lastmod>2026-07-05T18:17:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組合せ最適化に機械学習を組み合わせる方法論的概観（Machine Learning for Combinatorial Optimization: a Methodological Tour d’Horizon）</news:title>
   <news:publication_date>2026-07-05T18:17:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708463</loc>
  <lastmod>2026-07-05T17:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>繰り返し公共財ゲームにおける協力の強制と共謀耐性（Cooperation Enforcement and Collusion Resistance in Repeated Public Goods Games）</news:title>
   <news:publication_date>2026-07-05T17:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708461</loc>
  <lastmod>2026-07-05T17:24:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェーブレット領域における深層学習（Deep Learning in the Wavelet Domain）</news:title>
   <news:publication_date>2026-07-05T17:24:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708459</loc>
  <lastmod>2026-07-05T17:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過去の入札から学ぶ戦略的参加方法（Learning from Past Bids to Participate Strategically in Day-Ahead Electricity Markets）</news:title>
   <news:publication_date>2026-07-05T17:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708457</loc>
  <lastmod>2026-07-05T17:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延情報を伴う予測モデリング（Predictive Modeling with Delayed Information: a Case Study in E-commerce Transaction Fraud Control）</news:title>
   <news:publication_date>2026-07-05T17:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708455</loc>
  <lastmod>2026-07-05T17:22:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量時系列類似度評価と早期低血圧エピソード検出（Multivariate Time-series Similarity Assessment via Unsupervised Representation Learning and Stratified Locality Sensitive Hashing）</news:title>
   <news:publication_date>2026-07-05T17:22:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708453</loc>
  <lastmod>2026-07-05T17:22:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークのためのニュートン法（Newton Methods for Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-05T17:22:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708451</loc>
  <lastmod>2026-07-05T17:22:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークによる変調認識とISI・敵対的事例への示唆（Deep Neural Networks based Modrec: Some Results with Inter-Symbol Interference and Adversarial Examples）</news:title>
   <news:publication_date>2026-07-05T17:22:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708449</loc>
  <lastmod>2026-07-05T16:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指紋ポア検出を小さなFCNで改善する（Improving Fingerprint Pore Detection with a Small FCN）</news:title>
   <news:publication_date>2026-07-05T16:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708447</loc>
  <lastmod>2026-07-05T16:30:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対照的潜在変数モデルによる教師なし学習の転換（Unsupervised Learning with Contrastive Latent Variable Models）</news:title>
   <news:publication_date>2026-07-05T16:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708445</loc>
  <lastmod>2026-07-05T16:30:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き逐次パターンマイニングと多値決定図 (Constraint-based Sequential Pattern Mining with Decision Diagrams)</news:title>
   <news:publication_date>2026-07-05T16:30:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708443</loc>
  <lastmod>2026-07-05T16:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活動時系列の敵対的・教師なし表現学習（Adversarial Unsupervised Representation Learning for Activity Time-Series）</news:title>
   <news:publication_date>2026-07-05T16:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708441</loc>
  <lastmod>2026-07-05T16:29:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク解析の最小最大率：グラフォン推定・コミュニティ検出・仮説検定（Minimax Rates in Network Analysis: Graphon Estimation, Community Detection and Hypothesis Testing）</news:title>
   <news:publication_date>2026-07-05T16:29:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708439</loc>
  <lastmod>2026-07-05T16:29:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有解釈な深層学習による太陽光素子の構造–物性探索（Interpretable deep learning for guided structure-property explorations in photovoltaics）</news:title>
   <news:publication_date>2026-07-05T16:29:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708437</loc>
  <lastmod>2026-07-05T16:29:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な個別治療ルールの学習（Learning Optimal Personalized Treatment Rules Using Robust Regression Informed K-NN）</news:title>
   <news:publication_date>2026-07-05T16:29:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708435</loc>
  <lastmod>2026-07-05T15:37:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間らしい学習を目指す機械学習の限界と示唆（Human-like machine learning: limitations and suggestions）</news:title>
   <news:publication_date>2026-07-05T15:37:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708433</loc>
  <lastmod>2026-07-05T15:37:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレベルConvLSTMによる左心室心筋の自動セグメンテーション（A MULTI-LEVEL CONVOLUTIONAL LSTM MODEL FOR THE SEGMENTATION OF LEFT VENTRICLE MYOCARDIUM IN INFARCTED PORCINE CINE MR IMAGES）</news:title>
   <news:publication_date>2026-07-05T15:37:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708431</loc>
  <lastmod>2026-07-05T15:37:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の分子表現を用いた化学物性予測の混合DNN（CheMixNet: Mixed DNN Architectures for Predicting Chemical Properties using Multiple Molecular Representations）</news:title>
   <news:publication_date>2026-07-05T15:37:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708429</loc>
  <lastmod>2026-07-05T15:36:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型ニューラルネットワークの検証とルール抽出（Verification of Recurrent Neural Networks Through Rule Extraction）</news:title>
   <news:publication_date>2026-07-05T15:36:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708427</loc>
  <lastmod>2026-07-05T15:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的マルチタスクによる意味埋め込み学習 (A Hierarchical Multi-task Approach for Learning Embeddings from Semantic Tasks)</news:title>
   <news:publication_date>2026-07-05T15:36:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708425</loc>
  <lastmod>2026-07-05T15:36:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像セグメンテーションにおける自己アンサンブリングを用いた教師なしドメイン適応（Unsupervised domain adaptation for medical imaging segmentation with self-ensembling）</news:title>
   <news:publication_date>2026-07-05T15:36:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708423</loc>
  <lastmod>2026-07-05T15:35:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然環境を取り入れた強化学習ベンチマーク（Natural Environment Benchmarks for Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-05T15:35:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708421</loc>
  <lastmod>2026-07-05T14:44:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択的データ開示による探索誘導（Incentivizing Exploration with Selective Data Disclosure）</news:title>
   <news:publication_date>2026-07-05T14:44:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708419</loc>
  <lastmod>2026-07-05T14:44:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深宇宙X線で確証されたCompton厚AGNの再評価 — NGC 1358のNuSTARとXMM-Newton共同観測 (COMPTON-THICK AGN IN THE NuSTAR ERA II: A DEEP NuSTAR AND XMM-Newton VIEW OF THE CANDIDATE COMPTON THICK AGN IN NGC 1358)</news:title>
   <news:publication_date>2026-07-05T14:44:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708417</loc>
  <lastmod>2026-07-05T14:44:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成フローの性能推定に関するLSTMと転移学習の応用（Performance Estimation of Synthesis Flows cross Technologies using LSTMs and Transfer Learning）</news:title>
   <news:publication_date>2026-07-05T14:44:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708415</loc>
  <lastmod>2026-07-05T14:43:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ランダムフォレスト：ノイズの多いデータ向け機械学習アルゴリズム（Probabilistic Random Forest: A machine learning algorithm for noisy datasets）</news:title>
   <news:publication_date>2026-07-05T14:43:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708413</loc>
  <lastmod>2026-07-05T14:43:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トラック候補の捕捉と延長：1つのRNNによる同時判定と探索（Catch and Prolong: recurrent neural network for seeking track-candidates）</news:title>
   <news:publication_date>2026-07-05T14:43:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708411</loc>
  <lastmod>2026-07-05T14:43:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミツバチ巣箱音認識における機械学習の可能性（To be or not to bee: investigating machine learning approaches for beehive sound recognition）</news:title>
   <news:publication_date>2026-07-05T14:43:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708409</loc>
  <lastmod>2026-07-05T14:42:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘテロティック軌道空間における深層学習の応用（Deep learning in the heterotic orbifold landscape）</news:title>
   <news:publication_date>2026-07-05T14:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708407</loc>
  <lastmod>2026-07-05T13:51:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星形成銀河の回転曲線の形状が示すもの（The Shapes of the Rotation Curves of Star-forming Galaxies Over the Last ≈10 Gyr）</news:title>
   <news:publication_date>2026-07-05T13:51:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708405</loc>
  <lastmod>2026-07-05T13:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的プログラム結合器によるモデリングと推論の合成（Composing Modeling and Inference Operations with Probabilistic Program Combinators）</news:title>
   <news:publication_date>2026-07-05T13:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708403</loc>
  <lastmod>2026-07-05T13:51:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンプルなヒューマン・オブジェクト相互作用検出（No-Frills Human-Object Interaction Detection: Factorization, Layout Encodings, and Training Techniques）</news:title>
   <news:publication_date>2026-07-05T13:51:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708401</loc>
  <lastmod>2026-07-05T13:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模対話型レコメンデーションにおける木構造ポリシー勾配（Large-scale Interactive Recommendation with Tree-structured Policy Gradient）</news:title>
   <news:publication_date>2026-07-05T13:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708399</loc>
  <lastmod>2026-07-05T13:50:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文とトークンを同時に学習するラベリング（Jointly Learning to Label Sentences and Tokens）</news:title>
   <news:publication_date>2026-07-05T13:50:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708397</loc>
  <lastmod>2026-07-05T13:50:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形・非ガウスフィルタリングによる動的システムの状態推定（Deep Nonlinear Non-Gaussian Filtering for Dynamical Systems）</news:title>
   <news:publication_date>2026-07-05T13:50:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708395</loc>
  <lastmod>2026-07-05T13:50:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーン特化型車両検出と姿勢推定のためのドメインランダマイゼーション（Domain Randomization for Scene-Specific Car Detection and Pose Estimation）</news:title>
   <news:publication_date>2026-07-05T13:50:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708393</loc>
  <lastmod>2026-07-05T12:58:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graph Neural Network評価の落とし穴（Pitfalls of Graph Neural Network Evaluation）</news:title>
   <news:publication_date>2026-07-05T12:58:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708391</loc>
  <lastmod>2026-07-05T12:58:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き文生成のためのメトロポリス・ヘイスティングス法（Constrained Sentence Generation by Metropolis-Hastings Sampling）</news:title>
   <news:publication_date>2026-07-05T12:58:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708389</loc>
  <lastmod>2026-07-05T12:58:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュークリア・パートン分布をニューラルネットワークで推定（Nuclear Parton Distributions from Neural Networks）</news:title>
   <news:publication_date>2026-07-05T12:58:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708387</loc>
  <lastmod>2026-07-05T12:58:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Drop-Activation：非活性化を使った過学習抑制と調和的正則化（Drop-Activation: Implicit Parameter Reduction and Harmonious Regularization）</news:title>
   <news:publication_date>2026-07-05T12:58:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708385</loc>
  <lastmod>2026-07-05T12:57:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースのラインスペクトル超解像フレームワーク（A LEARNING-BASED FRAMEWORK FOR LINE-SPECTRA SUPER-RESOLUTION）</news:title>
   <news:publication_date>2026-07-05T12:57:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708383</loc>
  <lastmod>2026-07-05T12:57:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強凸制約下における投影不要最適化の再検討（Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets）</news:title>
   <news:publication_date>2026-07-05T12:57:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708381</loc>
  <lastmod>2026-07-05T12:57:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチフィジックス系の時間発展を予測するseq2seqモデル（Predicting the time-evolution of multi-physics systems with sequence-to-sequence models）</news:title>
   <news:publication_date>2026-07-05T12:57:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708379</loc>
  <lastmod>2026-07-05T12:06:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歪みに強い画像分類（DISTORTION ROBUST IMAGE CLASSIFICATION USING DEEP CONVOLUTIONAL NEURAL NETWORK WITH DISCRETE COSINE TRANSFORM）</news:title>
   <news:publication_date>2026-07-05T12:06:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708377</loc>
  <lastmod>2026-07-05T12:06:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前立腺GANによる拡散画像合成でデータバイアスを緩和（ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-05T12:06:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708375</loc>
  <lastmod>2026-07-05T12:06:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文法に基づく構造的CNNデコーダによるコード生成（A Grammar-Based Structural CNN Decoder for Code Generation）</news:title>
   <news:publication_date>2026-07-05T12:06:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708373</loc>
  <lastmod>2026-07-05T12:05:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動物の形状と動きを動画から復元する手法（Creatures great and SMAL: Recovering the shape and motion of animals from video）</news:title>
   <news:publication_date>2026-07-05T12:05:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708371</loc>
  <lastmod>2026-07-05T12:05:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学生のマインドセット介入効果の異質性をMLで明らかにする（Machine Learning Analysis of Heterogeneity in the Effect of Student Mindset Interventions）</news:title>
   <news:publication_date>2026-07-05T12:05:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708369</loc>
  <lastmod>2026-07-05T12:05:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LoANsによる弱教師あり物体検出の要点解説（LoANs: Weakly Supervised Object Detection with Localizer Assessor Networks）</news:title>
   <news:publication_date>2026-07-05T12:05:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708367</loc>
  <lastmod>2026-07-05T12:05:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度ユーザープロファイリングによるモバイルクラウドセンシングのタスク個人化マッチング（Fine-Grained User Profiling for Personalized Task Matching in Mobile Crowdsensing）</news:title>
   <news:publication_date>2026-07-05T12:05:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708365</loc>
  <lastmod>2026-07-05T11:13:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽プラージュにおける磁束と輝度コントラストの関係（Intensity contrast of solar plage as a function of magnetic flux at high spatial resolution）</news:title>
   <news:publication_date>2026-07-05T11:13:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708363</loc>
  <lastmod>2026-07-05T11:12:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自由文から医療記録のクラスタを見つける（FROM FREE TEXT TO CLUSTERS OF CONTENT IN HEALTH RECORDS）</news:title>
   <news:publication_date>2026-07-05T11:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708361</loc>
  <lastmod>2026-07-05T11:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で作る古典密度汎関数（A classical density functional from machine learning and a convolutional neural network）</news:title>
   <news:publication_date>2026-07-05T11:12:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708359</loc>
  <lastmod>2026-07-05T11:12:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似性が冗長性ベースのプログラム修復で果たす重要な役割（The Remarkable Role of Similarity in Redundancy-based Program Repair）</news:title>
   <news:publication_date>2026-07-05T11:12:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708357</loc>
  <lastmod>2026-07-05T11:11:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CT画像におけるラジオミクスで外傷性脳損傷を予測する（A Radiomics Approach to Traumatic Brain Injury Prediction in CT Scans）</news:title>
   <news:publication_date>2026-07-05T11:11:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708355</loc>
  <lastmod>2026-07-05T11:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ほぼゼロリソース環境でのASR不要キーワード検出を可能にする特徴探索（Feature exploration for almost zero-resource ASR-free keyword spotting）</news:title>
   <news:publication_date>2026-07-05T11:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708353</loc>
  <lastmod>2026-07-05T11:11:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水素充填ホログラフィック光ファイバーによる深紫外・真空紫外のしきい値なしラマン周波数変換（Thresholdless deep and vacuum ultraviolet Raman frequency conversion in H2-filled photonic crystal fiber）</news:title>
   <news:publication_date>2026-07-05T11:11:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708351</loc>
  <lastmod>2026-07-05T10:20:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短文会話における多様な応答生成（Generating Multiple Diverse Responses for Short-Text Conversation）</news:title>
   <news:publication_date>2026-07-05T10:20:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708349</loc>
  <lastmod>2026-07-05T10:19:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>旋律フレーズ分割と深層ニューラルネットワーク（Melodic Phrase Segmentation By Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-05T10:19:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708347</loc>
  <lastmod>2026-07-05T10:19:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大量タスクに対応する効率的でスケーラブルなマルチタスク回帰（Efficient and Scalable Multi-task Regression on Massive Number of Tasks）</news:title>
   <news:publication_date>2026-07-05T10:19:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708345</loc>
  <lastmod>2026-07-05T10:18:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知のポスト損傷分布を伴う構造物損傷検知と局所化（Structural Damage Detection and Localization with Unknown Post-Damage Feature Distribution Using Sequential Change-Point Detection Method）</news:title>
   <news:publication_date>2026-07-05T10:18:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708343</loc>
  <lastmod>2026-07-05T10:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TetrisによるCNN演算の再設計（Tetris: Re-architecting Convolutional Neural Network Computation for Machine Learning Accelerators）</news:title>
   <news:publication_date>2026-07-05T10:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708341</loc>
  <lastmod>2026-07-05T10:18:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MT-CGCNNによる物質特性予測の多目的学習（MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction）</news:title>
   <news:publication_date>2026-07-05T10:18:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708339</loc>
  <lastmod>2026-07-05T10:18:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>談話文の一貫性をモデル化する機構（Modeling Coherence for Discourse Neural Machine Translation）</news:title>
   <news:publication_date>2026-07-05T10:18:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708337</loc>
  <lastmod>2026-07-05T09:27:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーティション同定の標本複雑度と多腕バンディットの純粋探索（Sample complexity of partition identification using multi-armed bandits）</news:title>
   <news:publication_date>2026-07-05T09:27:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708335</loc>
  <lastmod>2026-07-05T09:26:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>床平面図から視覚障害者向けに説明を生成するSUGAMAN（SUGAMAN: Describing Floor Plans for Visually Impaired by Annotation Learning and Proximity based Grammar）</news:title>
   <news:publication_date>2026-07-05T09:26:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708333</loc>
  <lastmod>2026-07-05T09:26:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーム上のサブモジュラ最適化と不均一な劣化（Submodular Optimization Over Streams with Inhomogeneous Decays）</news:title>
   <news:publication_date>2026-07-05T09:26:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708331</loc>
  <lastmod>2026-07-05T09:25:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリ効率の高い量子回路シミュレーション（Memory-Efficient Quantum Circuit Simulation by Using Lossy Data Compression）</news:title>
   <news:publication_date>2026-07-05T09:25:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708329</loc>
  <lastmod>2026-07-05T09:25:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市配電網におけるµPMUを用いた迅速な線路停電検出（Fast Distribution Grid Line Outage Identification with µPMU）</news:title>
   <news:publication_date>2026-07-05T09:25:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708327</loc>
  <lastmod>2026-07-05T09:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>準局所演算子によるトポロジカル相の検出（Detection of topological phases by quasi-local operators）</news:title>
   <news:publication_date>2026-07-05T09:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708325</loc>
  <lastmod>2026-07-05T09:25:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称非負行列因子分解を高速化する「非対称化」の発想（Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization）</news:title>
   <news:publication_date>2026-07-05T09:25:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708323</loc>
  <lastmod>2026-07-05T08:33:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Alibabaクラスタにおける共置ワークロードの異常解析（Anomaly Analysis for Co-located Datacenter Workloads in the Alibaba Cluster）</news:title>
   <news:publication_date>2026-07-05T08:33:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708321</loc>
  <lastmod>2026-07-05T08:33:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタイルとコンテンツを分離するGANの設計（Style and Content Disentanglement in Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-05T08:33:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708319</loc>
  <lastmod>2026-07-05T08:33:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズに強い遠隔教師あり関係抽出の改良（Improving Distantly Supervised Relation Extraction with Neural Noise Converter and Conditional Optimal Selector）</news:title>
   <news:publication_date>2026-07-05T08:33:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708317</loc>
  <lastmod>2026-07-05T08:32:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因子化された部分観測POMDPにおけるベイズ強化学習（Bayesian Reinforcement Learning in Factored POMDPs）</news:title>
   <news:publication_date>2026-07-05T08:32:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708315</loc>
  <lastmod>2026-07-05T08:31:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語自身が圧縮コードであるという発見（Extractive Summary as Discrete Latent Variables）</news:title>
   <news:publication_date>2026-07-05T08:31:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708313</loc>
  <lastmod>2026-07-05T08:31:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク埋め込みに分離性を導入する手法（SepNE: Bringing Separability to Network Embedding）</news:title>
   <news:publication_date>2026-07-05T08:31:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708311</loc>
  <lastmod>2026-07-05T08:31:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TrolleyModによる自動運転の倫理判断データ収集プラットフォーム（TrolleyMod v1.0: An Open-Source Simulation and Data-Collection Platform for Ethical Decision Making in Autonomous Vehicles）</news:title>
   <news:publication_date>2026-07-05T08:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708309</loc>
  <lastmod>2026-07-05T07:40:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化された顔の痛み検出のレビュー（Automated Pain Detection from Facial Expressions using FACS）</news:title>
   <news:publication_date>2026-07-05T07:40:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708307</loc>
  <lastmod>2026-07-05T07:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的学習を用いたネットワークの可制御性・多重化・転移学習（Controllability, Multiplexing, and Transfer Learning in Networks using Evolutionary Learning）</news:title>
   <news:publication_date>2026-07-05T07:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708305</loc>
  <lastmod>2026-07-05T07:29:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディアデータによるオピオイド再発予測（Predicting Opioid Relapse Using Social Media Data）</news:title>
   <news:publication_date>2026-07-05T07:29:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708303</loc>
  <lastmod>2026-07-05T07:29:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短文の多言語マッチングと深層学習（Cross-lingual Short-text Matching with Deep Learning）</news:title>
   <news:publication_date>2026-07-05T07:29:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708301</loc>
  <lastmod>2026-07-05T07:28:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル・ウェーブテーブル：演奏可能なウェーブテーブル合成器（Neural Wavetable: a playable wavetable synthesizer using neural networks）</news:title>
   <news:publication_date>2026-07-05T07:28:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708299</loc>
  <lastmod>2026-07-05T07:28:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波の地域参照スペクトルパワー動態（Region-Referenced Spectral Power Dynamics of EEG Signals）</news:title>
   <news:publication_date>2026-07-05T07:28:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708297</loc>
  <lastmod>2026-07-05T07:28:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SVDDに基づく多変量工程能力ベクトルの提案（PCSVDD: SVDD-based Process Capability Vector）</news:title>
   <news:publication_date>2026-07-05T07:28:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708295</loc>
  <lastmod>2026-07-05T06:37:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型の支配方程式近似に向けた深層ニューラルネットワークの構成（DATA DRIVEN GOVERNING EQUATIONS APPROXIMATION USING DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-07-05T06:37:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708293</loc>
  <lastmod>2026-07-05T06:37:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似度に基づく対話型次元圧縮（Interactive dimensionality reduction using similarity projections）</news:title>
   <news:publication_date>2026-07-05T06:37:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708291</loc>
  <lastmod>2026-07-05T06:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半双対エントロピック正則化付き最適輸送（Semi-Dual Regularized Optimal Transport）</news:title>
   <news:publication_date>2026-07-05T06:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708289</loc>
  <lastmod>2026-07-05T06:36:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択（セレクション）が入ったデータに対するベイジアンネットワークの制約の解明（TOWARDS CHARACTERISING BAYESIAN NETWORK MODELS UNDER SELECTION）</news:title>
   <news:publication_date>2026-07-05T06:36:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708287</loc>
  <lastmod>2026-07-05T06:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Q学習によるニューラルネット騙し（Deep Q learning for fooling neural networks）</news:title>
   <news:publication_date>2026-07-05T06:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708285</loc>
  <lastmod>2026-07-05T06:35:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LoTSSによる低光度ラジオAGNの全体像の提示（The LoTSS view of radio AGN in the local Universe）</news:title>
   <news:publication_date>2026-07-05T06:35:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708283</loc>
  <lastmod>2026-07-05T06:35:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN評価のドメイン非依存指標（A Domain Agnostic Measure for Monitoring and Evaluating GANs）</news:title>
   <news:publication_date>2026-07-05T06:35:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708281</loc>
  <lastmod>2026-07-05T05:43:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QUBOによる組合せ最適化の再定義（Quadratic Unconstrained Binary Optimization）</news:title>
   <news:publication_date>2026-07-05T05:43:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708279</loc>
  <lastmod>2026-07-05T05:42:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工ニューラルネットワークによる次元削減と重み係数空間での重力波推定（Reduced-order modeling with artificial neurons for gravitational-wave inference）</news:title>
   <news:publication_date>2026-07-05T05:42:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708277</loc>
  <lastmod>2026-07-05T05:42:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共同正則化によるドメイン適応の新手法（Co-regularized Alignment for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-07-05T05:42:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708275</loc>
  <lastmod>2026-07-05T05:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体中心ポリシーによる自律運転（Deep Object-Centric Policies for Autonomous Driving）</news:title>
   <news:publication_date>2026-07-05T05:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708273</loc>
  <lastmod>2026-07-05T05:41:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話理解と状態追跡を同時学習で効率化するアプローチ（Multi-task learning for Joint Language Understanding and Dialogue State Tracking）</news:title>
   <news:publication_date>2026-07-05T05:41:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708271</loc>
  <lastmod>2026-07-05T05:41:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な人体姿勢推定の効率化戦略（Fast Human Pose Estimation）</news:title>
   <news:publication_date>2026-07-05T05:41:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708269</loc>
  <lastmod>2026-07-05T05:40:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ML-Netによる医療テキストのマルチラベル分類（ML-Net: multi-label classification of biomedical texts with deep neural networks）</news:title>
   <news:publication_date>2026-07-05T05:40:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708267</loc>
  <lastmod>2026-07-05T04:49:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテの埋め込みによる臨床情報検索の強化（Embedding Electronic Health Records for Clinical Information Retrieval）</news:title>
   <news:publication_date>2026-07-05T04:49:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708265</loc>
  <lastmod>2026-07-05T04:49:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リプシッツ関数近似の整理（Sorting Out Lipschitz Function Approximation）</news:title>
   <news:publication_date>2026-07-05T04:49:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708263</loc>
  <lastmod>2026-07-05T04:49:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群を彫刻へと変える発想：Amalgamated DeepDreamによる3D造形の生成（Hallucinating Point Cloud into 3D Sculptural Object）</news:title>
   <news:publication_date>2026-07-05T04:49:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708261</loc>
  <lastmod>2026-07-05T04:48:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形態情報を活用した光学赤方偏移推定（Morpho-Photometric Redshifts）</news:title>
   <news:publication_date>2026-07-05T04:48:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708259</loc>
  <lastmod>2026-07-05T04:47:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>携帯通信データから所得を推定する手法の比較（Comparison of Feature Extraction Methods and Predictors for Income Inference）</news:title>
   <news:publication_date>2026-07-05T04:47:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708257</loc>
  <lastmod>2026-07-05T04:47:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声対話エージェントにおける教師なし転移学習（Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent Agents）</news:title>
   <news:publication_date>2026-07-05T04:47:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708255</loc>
  <lastmod>2026-07-05T04:46:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常検知型ネットワーク侵入検知のベンチマーク再考（Benchmarking datasets for Anomaly-based Network Intrusion Detection: KDD CUP 99 alternatives）</news:title>
   <news:publication_date>2026-07-05T04:46:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708253</loc>
  <lastmod>2026-07-05T03:54:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル評価・モデル選択・アルゴリズム選択に関する実務指南（Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning）</news:title>
   <news:publication_date>2026-07-05T03:54:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708251</loc>
  <lastmod>2026-07-05T03:54:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>360度動画からの深度とカメラ動作の自己教師あり学習（Self-Supervised Learning of Depth and Camera Motion from 360◦Videos）</news:title>
   <news:publication_date>2026-07-05T03:54:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708249</loc>
  <lastmod>2026-07-05T03:54:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク量子化のためのルックアップテーブル逐次学習（Iteratively Training Look-Up Tables for Network Quantization）</news:title>
   <news:publication_date>2026-07-05T03:54:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708247</loc>
  <lastmod>2026-07-05T03:53:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高性能計算システムにおけるオートエンコーダを用いた異常検知（Anomaly Detection using Autoencoders in High Performance Computing Systems）</news:title>
   <news:publication_date>2026-07-05T03:53:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708245</loc>
  <lastmod>2026-07-05T03:53:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SAFEによる関数埋め込みとバイナリ類似性（SAFE: Self-Attentive Function Embeddings for Binary Similarity）</news:title>
   <news:publication_date>2026-07-05T03:53:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708243</loc>
  <lastmod>2026-07-05T03:53:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数注釈で医療テキストの固有表現抽出を強化する手法（Few-shot Learning for Named Entity Recognition in Medical Text）</news:title>
   <news:publication_date>2026-07-05T03:53:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708241</loc>
  <lastmod>2026-07-05T03:52:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>年次報告書のテキスト深層学習による破綻予測（Predicting Distresses using Deep Learning of Text Segments in Annual Reports）</news:title>
   <news:publication_date>2026-07-05T03:52:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708239</loc>
  <lastmod>2026-07-05T03:02:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dirichlet分布に対する共役事前分布（A conjugate prior for the Dirichlet distribution）</news:title>
   <news:publication_date>2026-07-05T03:02:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708237</loc>
  <lastmod>2026-07-05T03:01:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイドチャネルによる深層学習の逆解析の安全性（How Secure are Deep Learning Algorithms from Side-Channel based Reverse Engineering?）</news:title>
   <news:publication_date>2026-07-05T03:01:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708235</loc>
  <lastmod>2026-07-05T03:01:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>背景差分における深層ニューラルネットワークの体系的レビュー（Deep Neural Network Concepts for Background Subtraction: A Systematic Review and Comparative Evaluation）</news:title>
   <news:publication_date>2026-07-05T03:01:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708233</loc>
  <lastmod>2026-07-05T03:00:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的注意機構と方策勾配最適化による画像キャプション生成（Image Captioning via a Hierarchical Attention Mechanism and Policy Gradient Optimization）</news:title>
   <news:publication_date>2026-07-05T03:00:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708231</loc>
  <lastmod>2026-07-05T03:00:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海面における小型目標検出のFAR制御型SVM検出器（SVM-Based Sea-Surface Small Target Detection: A False-Alarm-Rate-Controllable Approach）</news:title>
   <news:publication_date>2026-07-05T03:00:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708229</loc>
  <lastmod>2026-07-05T03:00:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル注意機構による音声—映像統合の革新（MODALITY ATTENTION FOR END-TO-END AUDIO-VISUAL SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-07-05T03:00:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708227</loc>
  <lastmod>2026-07-05T03:00:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツーストリーム畳み込みネットワークによる自己運転学習の短期時間情報活用（Two-Stream Convolutional Networks for End-to-end Learning of Self-driving Cars）</news:title>
   <news:publication_date>2026-07-05T03:00:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708225</loc>
  <lastmod>2026-07-05T02:09:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モジュール化ネットワーク：ニューラル計算の分解学習（Modular Networks: Learning to Decompose Neural Computation）</news:title>
   <news:publication_date>2026-07-05T02:09:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708223</loc>
  <lastmod>2026-07-05T02:08:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン注意機構を用いた音声認識の実時間化（AN ONLINE ATTENTION-BASED MODEL FOR SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-07-05T02:08:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708221</loc>
  <lastmod>2026-07-05T02:08:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット音声指示の意味解釈を多層LSTMで行う研究（A Multi-layer LSTM-based Approach for Robot Command Interaction Modeling）</news:title>
   <news:publication_date>2026-07-05T02:08:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708219</loc>
  <lastmod>2026-07-05T02:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チームメイトの動的共同方策のモデリング（Modelling the Dynamic Joint Policy of Teammates with Attention Multi-agent DDPG）</news:title>
   <news:publication_date>2026-07-05T02:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708217</loc>
  <lastmod>2026-07-05T02:07:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的学習の理論解析（Theoretical Analysis of Adversarial Learning: A Minimax Approach）</news:title>
   <news:publication_date>2026-07-05T02:07:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708215</loc>
  <lastmod>2026-07-05T02:07:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一次元強相互作用量子気体における対称性と相関（Symmetries and Correlations in Strongly Interacting One-dimensional Quantum Gases）</news:title>
   <news:publication_date>2026-07-05T02:07:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708213</loc>
  <lastmod>2026-07-05T02:07:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模分散SGDによる超高速ImageNet学習（Massively Distributed SGD: ImageNet/ResNet-50 Training in a Flash）</news:title>
   <news:publication_date>2026-07-05T02:07:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708211</loc>
  <lastmod>2026-07-05T01:16:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単隠れ層ニューラルネットワークの誤差境界の鋭さ（On Sharpness of Error Bounds for Single Hidden Layer Feedforward Neural Networks）</news:title>
   <news:publication_date>2026-07-05T01:16:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708209</loc>
  <lastmod>2026-07-05T01:15:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習フレームワークとプラットフォームに関する実証的比較研究（An Orchestrated Empirical Study on Deep Learning Frameworks and Platforms）</news:title>
   <news:publication_date>2026-07-05T01:15:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708207</loc>
  <lastmod>2026-07-05T01:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空画像からの太陽光発電変動補償を学習する手法（Learning to Compensate Photovoltaic Power Fluctuations from Images of the Sky by Imitating an Optimal Policy）</news:title>
   <news:publication_date>2026-07-05T01:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708205</loc>
  <lastmod>2026-07-05T01:14:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人の走行パターン認識に対する Faster R-CNN の応用（Application of Faster R-CNN Model on Human Running Pattern Recognitions）</news:title>
   <news:publication_date>2026-07-05T01:14:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708203</loc>
  <lastmod>2026-07-05T01:14:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四方向畳み込み特徴による車両再識別（Vehicle Re-identification Using Quadruple Directional Deep Learning Features）</news:title>
   <news:publication_date>2026-07-05T01:14:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708201</loc>
  <lastmod>2026-07-05T01:14:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>旅行コスト予測のための再帰型マルチグラフニューラルネットワーク（Recurrent Multi-Graph Neural Networks for Travel Cost Prediction）</news:title>
   <news:publication_date>2026-07-05T01:14:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708199</loc>
  <lastmod>2026-07-05T01:13:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Garbage In, Reward Out：ブートストラップ探索によるバンディット問題の再構築（Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits）</news:title>
   <news:publication_date>2026-07-05T01:13:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708197</loc>
  <lastmod>2026-07-05T00:22:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチフレームを用いた顔の対偽造における時間的・深度情報の活用（Exploiting temporal and depth information for multi-frame face anti-spoofing）</news:title>
   <news:publication_date>2026-07-05T00:22:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708195</loc>
  <lastmod>2026-07-05T00:13:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英語・ヒンディー語混合ツイートにおけるヘイトスピーチ検出（Hate Speech Detection from Code-mixed Hindi-English Tweets Using Deep Learning Models）</news:title>
   <news:publication_date>2026-07-05T00:13:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708193</loc>
  <lastmod>2026-07-05T00:13:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コミュニティ探索問題の系統的研究（Community Exploration: From Offline Optimization to Online Learning）</news:title>
   <news:publication_date>2026-07-05T00:13:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708191</loc>
  <lastmod>2026-07-05T00:12:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>停留点集合写像の感度解析（Sensitivity Analysis of a Stationary Point Set Map under Total Perturbations. Part 1: Lipschitzian Stability）</news:title>
   <news:publication_date>2026-07-05T00:12:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708189</loc>
  <lastmod>2026-07-05T00:12:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復符号化された空間変調検出の低計算量解法（A Variational Inference based Detection Method for Repetition Coded Generalized Spatial Modulation）</news:title>
   <news:publication_date>2026-07-05T00:12:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708187</loc>
  <lastmod>2026-07-05T00:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的依存をモデル化するMulti-Channel RNN（Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-05T00:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708185</loc>
  <lastmod>2026-07-05T00:11:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アフリカ言語へのニューラル機械翻訳の取り組み（Towards Neural Machine Translation for African Languages）</news:title>
   <news:publication_date>2026-07-05T00:11:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708183</loc>
  <lastmod>2026-07-04T23:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルに「質問させる」ことで可視化する学習機構（Interpreting Models by Allowing to Ask）</news:title>
   <news:publication_date>2026-07-04T23:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708181</loc>
  <lastmod>2026-07-04T23:20:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNN-Transducerを用いた中国語音声認識の探究（Exploring RNN-Transducer for Chinese Speech Recognition）</news:title>
   <news:publication_date>2026-07-04T23:20:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708179</loc>
  <lastmod>2026-07-04T23:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳画像モダリティ融合によるアルツハイマー分類（Neuroimaging Modality Fusion in Alzheimer’s Classification Using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-04T23:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708177</loc>
  <lastmod>2026-07-04T23:19:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値多次元データから学ぶ確率的テンソル分解の最適性（Learning from Binary Multiway Data: Probabilistic Tensor Decomposition and its Statistical Optimality）</news:title>
   <news:publication_date>2026-07-04T23:19:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708175</loc>
  <lastmod>2026-07-04T23:19:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>振分け可能な変分フィルタリングの一般的方法（A General Method for Amortizing Variational Filtering）</news:title>
   <news:publication_date>2026-07-04T23:19:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708173</loc>
  <lastmod>2026-07-04T23:19:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライベートなモデル圧縮と知識蒸留の実装戦略（Private Model Compression via Knowledge Distillation）</news:title>
   <news:publication_date>2026-07-04T23:19:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708171</loc>
  <lastmod>2026-07-04T23:19:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸オンライン学習における局所的後悔（A Local Regret in Nonconvex Online Learning）</news:title>
   <news:publication_date>2026-07-04T23:19:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708169</loc>
  <lastmod>2026-07-04T22:27:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAVネットワークにおける分散協調スペクトラム共有と多エージェント強化学習（Distributed Cooperative Spectrum Sharing in UAV Networks Using Multi-Agent Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-04T22:27:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708167</loc>
  <lastmod>2026-07-04T22:27:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴量重要度に基づく動的スケーリングによるK近傍法の精度向上（Dynamic Feature Scaling for K-Nearest Neighbor Algorithm）</news:title>
   <news:publication_date>2026-07-04T22:27:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708165</loc>
  <lastmod>2026-07-04T22:27:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>nスタック・スチュワートプラットフォームの逆運動学と感度最小化（Inverse Kinematics and Sensitivity Minimization of an n-Stack Stewart Platform）</news:title>
   <news:publication_date>2026-07-04T22:27:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708163</loc>
  <lastmod>2026-07-04T22:27:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適解の近傍にあるすべてのベイジアンネットワーク構造を探索する方法（Finding All Bayesian Network Structures within a Factor of Optimal）</news:title>
   <news:publication_date>2026-07-04T22:27:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708161</loc>
  <lastmod>2026-07-04T22:26:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所特徴パターンの活用による教師なしドメイン適応（Exploiting Local Feature Patterns for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-07-04T22:26:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708159</loc>
  <lastmod>2026-07-04T22:26:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LookinGood: リアルタイムニューラル再レンダリングによるパフォーマンスキャプチャの高画質化（LookinGood: Enhancing Performance Capture with Real-time Neural Re-Rendering）</news:title>
   <news:publication_date>2026-07-04T22:26:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708157</loc>
  <lastmod>2026-07-04T22:26:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>惑星状星雲Lin49とTc1の赤外線スペクトル同定（Astronomical Infrared Spectrum of Planetary Nebula Lin49 and Tc1 Identified by Ionized Polycyclic-Pure-Carbon C23 and C60）</news:title>
   <news:publication_date>2026-07-04T22:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708155</loc>
  <lastmod>2026-07-04T21:34:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔表情合成によるデータ拡張法（Deep Neural Network Augmentation: Generating Faces for Affect Analysis）</news:title>
   <news:publication_date>2026-07-04T21:34:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708153</loc>
  <lastmod>2026-07-04T21:34:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイアボールの発生と消滅におけるヒステリシスのメカニズム（On the hysteresis in fireball formation and extinction）</news:title>
   <news:publication_date>2026-07-04T21:34:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708151</loc>
  <lastmod>2026-07-04T21:34:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間的点過程を強化学習で学習する（Learning Temporal Point Processes via Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-04T21:34:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708149</loc>
  <lastmod>2026-07-04T21:33:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>災害時のボランティア調整を自律化する手法（Coordinating Disaster Emergency Response with Heuristic Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-04T21:33:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708147</loc>
  <lastmod>2026-07-04T21:33:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乗算を不要にする一般化三値接続（Generalized Ternary Connect: End-to-End Learning and Compression of Multiplication-Free Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-04T21:33:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708145</loc>
  <lastmod>2026-07-04T21:33:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知語の分散表現の誘導（Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces）</news:title>
   <news:publication_date>2026-07-04T21:33:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708143</loc>
  <lastmod>2026-07-04T21:32:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚を遮ったベースラインが示したもの — Blindfold Baselines for Embodied QA (Blindfold Baselines for Embodied QA)</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/708141</loc>
  <lastmod>2026-07-04T20:41:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在的差別（ラテント差別）を取り除く実務的な手法（Eliminating Latent Discrimination: Train Then Mask）</news:title>
   <news:publication_date>2026-07-04T20:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708139</loc>
  <lastmod>2026-07-04T20:41:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適ドーピング近傍のクーパー酸化物に対するSU(2)ゲージ理論の提案（Gauge theory for the cuprates near optimal doping）</news:title>
   <news:publication_date>2026-07-04T20:41:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708137</loc>
  <lastmod>2026-07-04T20:40:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PennyLaneによる量子-古典ハイブリッド自動微分（PennyLane: Automatic differentiation of hybrid quantum-classical computations）</news:title>
   <news:publication_date>2026-07-04T20:40:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708135</loc>
  <lastmod>2026-07-04T20:39:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過学習しない過剰パラメータ化ニューラルネットワークの学習と一般化（Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers）</news:title>
   <news:publication_date>2026-07-04T20:39:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708133</loc>
  <lastmod>2026-07-04T20:39:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HTRUサーベイにおけるGPU加速再処理による23個のパルサー発見（The High Time Resolution Universe survey XIV: Discovery of 23 pulsars through GPU-accelerated reprocessing）</news:title>
   <news:publication_date>2026-07-04T20:39:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708131</loc>
  <lastmod>2026-07-04T20:39:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳腫瘍患者の生存予測における深層学習と古典的回帰の比較（Deep Learning versus Classical Regression for Brain Tumor Patient Survival Prediction）</news:title>
   <news:publication_date>2026-07-04T20:39:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708129</loc>
  <lastmod>2026-07-04T20:39:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシーを用いたモデル集約で性能を高める（Boosting Model Performance through Differentially Private Model Aggregation）</news:title>
   <news:publication_date>2026-07-04T20:39:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708127</loc>
  <lastmod>2026-07-04T19:47:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像のためのディープラーニングに対するシステム的アプローチの全体像（Focusing on the Big Picture: Insights into a Systems Approach to Deep Learning for Satellite Imagery）</news:title>
   <news:publication_date>2026-07-04T19:47:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708125</loc>
  <lastmod>2026-07-04T19:47:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言葉の選び方はいつ影響するか（When do Words Matter? Understanding the Impact of Lexical Choice on Audience Perception using Individual Treatment Effect Estimation）</news:title>
   <news:publication_date>2026-07-04T19:47:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708123</loc>
  <lastmod>2026-07-04T19:47:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非侵襲的な皮膚特徴に基づく室内熱的快適性の可視化と推定（Non-invasive thermal comfort perception based on subtleness magnification and deep learning for energy efficiency）</news:title>
   <news:publication_date>2026-07-04T19:47:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708121</loc>
  <lastmod>2026-07-04T19:46:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散乱光による星の偏光とデブリ円盤の比較（Polarization of stars with debris disks: comparing observations with models）</news:title>
   <news:publication_date>2026-07-04T19:46:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708119</loc>
  <lastmod>2026-07-04T19:46:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Generative Dual Adversarial Networkによる一般化ゼロショット学習の統合的枠組み（Generative Dual Adversarial Network for Generalized Zero-shot Learning）</news:title>
   <news:publication_date>2026-07-04T19:46:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708117</loc>
  <lastmod>2026-07-04T19:45:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込みシステム向け物体検出における転移学習の枠組み（A Framework of Transfer Learning in Object Detection for Embedded Systems）</news:title>
   <news:publication_date>2026-07-04T19:45:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708115</loc>
  <lastmod>2026-07-04T19:45:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚予測に基づく自己教師ありイベント分節化の枠組み（A Perceptual Prediction Framework for Self Supervised Event Segmentation）</news:title>
   <news:publication_date>2026-07-04T19:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708113</loc>
  <lastmod>2026-07-04T18:54:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在ゲームに基づく非短視的センサネットワーク計画（Potential Game-Based Non-Myopic Sensor Network Planning for Multi-Target Tracking）</news:title>
   <news:publication_date>2026-07-04T18:54:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708111</loc>
  <lastmod>2026-07-04T18:54:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床診断と治療助言における分類学習の実務（On the practice of classification learning for clinical diagnosis and therapy advice in oncology）</news:title>
   <news:publication_date>2026-07-04T18:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708109</loc>
  <lastmod>2026-07-04T18:54:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子着想に基づく低ランク線形方程式の亜線形古典アルゴリズム（Quantum-inspired sublinear classical algorithms for solving low-rank linear systems）</news:title>
   <news:publication_date>2026-07-04T18:54:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708107</loc>
  <lastmod>2026-07-04T18:53:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PositiveとUnlabeledデータから学ぶ方法（Learning From Positive and Unlabeled Data: A Survey）</news:title>
   <news:publication_date>2026-07-04T18:53:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708105</loc>
  <lastmod>2026-07-04T18:52:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>気候データに対する畳み込みニューラルネットワークの適用例：クラスター化された気象パターンの再識別（A test case for application of convolutional neural networks to spatio-temporal climate data: Re-identifying clustered weather patterns）</news:title>
   <news:publication_date>2026-07-04T18:52:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708103</loc>
  <lastmod>2026-07-04T18:52:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模光学ニューラルネットワークと光電乗算（Large-Scale Optical Neural Networks based on Photoelectric Multiplication）</news:title>
   <news:publication_date>2026-07-04T18:52:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708101</loc>
  <lastmod>2026-07-04T18:52:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意（Attention）機構の入門概観（An Introductory Survey on Attention Mechanisms in NLP Problems）</news:title>
   <news:publication_date>2026-07-04T18:52:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708099</loc>
  <lastmod>2026-07-04T18:01:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超音波画像における腎臓自動セグメンテーションの新展開（Fully Automatic Kidney Segmentation in Ultrasound Images via Boundary Distance Regression and Pixelwise Classification）</news:title>
   <news:publication_date>2026-07-04T18:01:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708097</loc>
  <lastmod>2026-07-04T18:00:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離表現を用いた抽象推論課題の一般化改善（Improving Generalization for Abstract Reasoning Tasks Using Disentangled Feature Representations）</news:title>
   <news:publication_date>2026-07-04T18:00:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708095</loc>
  <lastmod>2026-07-04T18:00:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UMBCにおけるSFSサマーリサーチ ― 実務型学習がサイバーセキュリティ教育を変えた（The SFS Summer Research Study at UMBC: Project-Based Learning Inspires Cybersecurity Students）</news:title>
   <news:publication_date>2026-07-04T18:00:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708093</loc>
  <lastmod>2026-07-04T18:00:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文はELMoでの意味理解を助けるか（Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL?）</news:title>
   <news:publication_date>2026-07-04T18:00:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708091</loc>
  <lastmod>2026-07-04T18:00:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ拡張ポリシーの探索を連続化して性能を高める方法（LEARNING DATA AUGMENTATION POLICIES USING AUGMENTED RANDOM SEARCH）</news:title>
   <news:publication_date>2026-07-04T18:00:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708089</loc>
  <lastmod>2026-07-04T17:59:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデル分類器におけるマルコフ性の役割（Markov Property in Generative Classifiers）</news:title>
   <news:publication_date>2026-07-04T17:59:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708087</loc>
  <lastmod>2026-07-04T17:59:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光輸送の潜在空間を深層学習する（Deep-learning the Latent Space of Light Transport）</news:title>
   <news:publication_date>2026-07-04T17:59:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708085</loc>
  <lastmod>2026-07-04T17:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損データの表現学習による患者アウトカム予測の革新（Learning Representations of Missing Data for Predicting Patient Outcomes）</news:title>
   <news:publication_date>2026-07-04T17:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708083</loc>
  <lastmod>2026-07-04T17:07:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウシアン・オートエンコーダの分布整合手法（Gaussian AutoEncoder）</news:title>
   <news:publication_date>2026-07-04T17:07:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708081</loc>
  <lastmod>2026-07-04T17:07:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用マージナライザによる償却化推論と生成モデルの埋め込み（Universal Marginalizer for Amortised Inference and Embedding of Generative Models）</news:title>
   <news:publication_date>2026-07-04T17:07:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708079</loc>
  <lastmod>2026-07-04T17:06:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層CNNに基づく発話埋め込みの音響モデル適応への解析（ANALYZING DEEP CNN-BASED UTTERANCE EMBEDDINGS FOR ACOUSTIC MODEL ADAPTATION）</news:title>
   <news:publication_date>2026-07-04T17:06:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708077</loc>
  <lastmod>2026-07-04T17:06:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MarkovとHuffmanによる自動ステガノグラフィテキスト生成（Automatically Generate Steganographic Text Based on Markov Model and Huffman Coding）</news:title>
   <news:publication_date>2026-07-04T17:06:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708075</loc>
  <lastmod>2026-07-04T17:06:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル依存性を敵対的に学習する新枠組み（ADVERSARIAL LEARNING OF LABEL DEPENDENCY: A NOVEL FRAMEWORK FOR MULTI-CLASS CLASSIFICATION）</news:title>
   <news:publication_date>2026-07-04T17:06:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708073</loc>
  <lastmod>2026-07-04T17:05:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフィカルモデルの分配関数を解く新手法—Gaugeと多項式の接続（Gauges, Loops, and Polynomials for Partition Functions of Graphical Models）</news:title>
   <news:publication_date>2026-07-04T17:05:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708071</loc>
  <lastmod>2026-07-04T16:14:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布頑健な半教師あり学習と人中心センシング（Distributionally Robust Semi-Supervised Learning for People-Centric Sensing）</news:title>
   <news:publication_date>2026-07-04T16:14:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/708069</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レーダーのマイクロドップラー信号に対する敵対的デノイズ法（Towards Adversarial Denoising of Radar Micro-Doppler Signatures）</news:title>
   <news:publication_date>2026-07-04T16:07:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/708067</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープアンサンブルによるフェイクニュース検出と分類（A Deep Ensemble Framework for Fake News Detection and Classification）</news:title>
   <news:publication_date>2026-07-04T16:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/708065</loc>
  <lastmod>2026-07-04T16:06:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>独立事前分布によるセグメンテーションマスク学習（Learning Segmentation Masks with the Independence Prior）</news:title>
   <news:publication_date>2026-07-04T16:06:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/708063</loc>
  <lastmod>2026-07-04T16:05:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌詞生成における構造と語彙の統合（Combining Learned Lyrical Structures and Vocabulary for Improved Lyric Generation）</news:title>
   <news:publication_date>2026-07-04T16:05:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/708061</loc>
  <lastmod>2026-07-04T16:05:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RelDenCluによる非線形特徴関係の発見（RelDenClu: A Relative Density based Biclustering Method for identifying non-linear feature relations）</news:title>
   <news:publication_date>2026-07-04T16:05:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708059</loc>
  <lastmod>2026-07-04T16:05:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動ポリソムノグラフィ解析によるREM睡眠行動障害の検出（Detection of REM Sleep Behaviour Disorder by Automated Polysomnography Analysis）</news:title>
   <news:publication_date>2026-07-04T16:05:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708057</loc>
  <lastmod>2026-07-04T15:13:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変数選択を伴う最適化のためのグローバル感度解析（Global sensitivity analysis for optimization with variable selection）</news:title>
   <news:publication_date>2026-07-04T15:13:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708055</loc>
  <lastmod>2026-07-04T15:13:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽の中間周期性に関する研究（On Midrange Periodicities in Solar Radio Flux and Sunspot Areas）</news:title>
   <news:publication_date>2026-07-04T15:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708053</loc>
  <lastmod>2026-07-04T15:12:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャネル情報不要でIoTの集約を速める方法（Blind Over-the-Air Computation and Data Fusion via Provable Wirtinger Flow）</news:title>
   <news:publication_date>2026-07-04T15:12:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708051</loc>
  <lastmod>2026-07-04T15:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きMinHashアルゴリズムの総覧（A Review for Weighted MinHash Algorithms）</news:title>
   <news:publication_date>2026-07-04T15:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708049</loc>
  <lastmod>2026-07-04T15:12:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力波の伝播速度は重力の定数で決まる（Gravitational waves at their own gravitational speed）</news:title>
   <news:publication_date>2026-07-04T15:12:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708047</loc>
  <lastmod>2026-07-04T15:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習セグメンテーション網の追加構造対応（Extending Pretrained Segmentation Networks with Additional Anatomical Structures）</news:title>
   <news:publication_date>2026-07-04T15:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708045</loc>
  <lastmod>2026-07-04T15:11:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生理信号からの感情認識を日常環境で実現する道（Angry or Climbing Stairs? Towards Physiological Emotion Recognition in the Wild）</news:title>
   <news:publication_date>2026-07-04T15:11:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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