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   <news:title>不連続な多語表現の識別を改善する新手法（Bridging the Gap: Attending to Discontinuity in Identification of Multiword Expressions）</news:title>
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   <news:title>屋内ロボット向け物体検出器のカスタマイズ (Customizing Object Detectors for Indoor Robots)</news:title>
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   <news:title>局所関数複雑性に基づく能動学習（Local Function Complexity for Active Learning via Mixture of Gaussian Processes）</news:title>
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   <news:title>電子イオン衝突器での半包摂深部非弾性散乱と分布・フラグメンテーション関数（Semi-inclusive Deep-Inelastic Scattering, Parton Distributions and Fragmentation Functions at a Future Electron-Ion Collider）</news:title>
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   <news:title>決定木の敵対的頑健化（Robust Decision Trees Against Adversarial Examples）</news:title>
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   <news:title>経験的リスク推定の集中性に対するWasserstein距離アプローチ (A Wasserstein distance approach for concentration of empirical risk estimates)</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>レベルセット学習による非線形次元削減（Learning nonlinear level sets for dimensionality reduction in function approximation）</news:title>
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   <news:title>vitrivrの概念検出とVBS2019での総括 (Deep Learning-based Concept Detection in vitrivr at the Video Browser Showdown 2019 – Final Notes)</news:title>
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   <news:title>Q学習のアンサンブル手法を社会選択理論で統一する（Unifying Ensemble Methods for Q-learning via Social Choice Theory）</news:title>
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   <news:title>勾配ベースのメタ学習に関する証明可能な保証 (Provable Guarantees for Gradient-Based Meta-Learning)</news:title>
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   <news:title>逐次混合モデルの準ベイズ性（Quasi-Bayes properties of a recursive procedure for mixtures）</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>動的目的を学習するポリシー（Learning Dynamic-Objective Policies from a Class of Optimal Trajectories）</news:title>
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   <news:title>ニューラルイメージングパイプラインとフォレンジクスの再考（Neural Imaging Pipelines - the Scourge or Hope of Forensics?）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>銀河衝突の観測とシミュレーションにおける識別（Identifying Galaxy Mergers in Observations and Simulations with Deep Learning）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>因子化マルコフ決定過程における</news:title>
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   <news:title>LPWAネットワークにおける再送を考慮したチャネル選択の学習（Upper-Confidence Bound for Channel Selection in LPWA Networks with Retransmissions）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>信頼できる学習内蔵型自律システムの設計（Architecting Dependable Learning-enabled Autonomous Systems: A Survey）</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>ツイートが実際に性差別的であるとき（When a Tweet is Actually Sexist）</news:title>
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   <news:title>関連性照合のための多解像度グラフアテンションネットワーク（Multiresolution Graph Attention Networks for Relevance Matching）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>多腕同時選択の全バンディット観測下での多腕同定の多項式時間アルゴリズム（Polynomial-time Algorithms for Multiple-arm Identification with Full-bandit Feedback）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-12T04:58:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>原子核における新しいクォークとグルーオン効果の露呈（Exposing Novel Quark and Gluon Effects in Nuclei）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-12T04:58:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>TrIK-SVMによる不定カーネルの新たな分解（TrIK-SVM : an alternative decomposition for kernel methods in Kre˘in spaces）</news:title>
   <news:publication_date>2026-08-12T04:58:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/722248</loc>
  <lastmod>2026-08-12T04:58:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>フォグ無線アクセスネットワークにおける強化学習による分散エッジキャッシング（Distributed Edge Caching via Reinforcement Learning in Fog Radio Access Networks）</news:title>
   <news:publication_date>2026-08-12T04:58:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>高解像度向け反復型MVSネットワーク（Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inference）</news:title>
   <news:publication_date>2026-08-12T04:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ELMによるLED MIMO受信機設計――非線形とクロスLED干渉を同時に扱う（EXTREME LEARNING MACHINE-BASED RECEIVER FOR MIMO LED COMMUNICATIONS）</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>DeepLO: Geometry-Aware Deep LiDAR Odometry（DeepLO: Geometry-Aware Deep LiDAR Odometry）</news:title>
   <news:publication_date>2026-08-12T04:56:34Z</news:publication_date>
   <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>自己対戦学習の高速化――KataGoによるGo学習効率の革新（Accelerating Self-Play Learning in Go）</news:title>
   <news:publication_date>2026-08-12T04:56:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-12T04:04:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習済み言語モデルからの転移学習の極めて単純なアプローチ（An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models）</news:title>
   <news:publication_date>2026-08-12T04:04:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722236</loc>
  <lastmod>2026-08-12T04:04:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性支援による部分検出と精錬による人物再識別の改善（Attributes-aided Part Detection and Refinement for Person Re-identification）</news:title>
   <news:publication_date>2026-08-12T04:04:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722234</loc>
  <lastmod>2026-08-12T04:03:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Active Subspacesによる高次元不確かさ伝播の可視化と削減（DEEP ACTIVE SUBSPACES - A SCALABLE METHOD FOR HIGH-DIMENSIONAL UNCERTAINTY PROPAGATION）</news:title>
   <news:publication_date>2026-08-12T04:03:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722232</loc>
  <lastmod>2026-08-12T04:03:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子構造学習（Atomistic Structure Learning）</news:title>
   <news:publication_date>2026-08-12T04:03:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722230</loc>
  <lastmod>2026-08-12T04:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物学的に妥当な深層学習—浅いネットワークでどこまで可能か？ (Biologically plausible deep learning – but how far can we go with shallow networks?)</news:title>
   <news:publication_date>2026-08-12T04:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722228</loc>
  <lastmod>2026-08-12T04:03:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>依存構文解析をラベリングで再定式化する意義（Viable Dependency Parsing as Sequence Labeling）</news:title>
   <news:publication_date>2026-08-12T04:03:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722226</loc>
  <lastmod>2026-08-12T04:02:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈に基づく文結合の大規模データセット（DISCOFUSE: A Large-Scale Dataset for Discourse-Based Sentence Fusion）</news:title>
   <news:publication_date>2026-08-12T04:02:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722224</loc>
  <lastmod>2026-08-12T03:11:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抵抗ノイズ測定が解き明かす1/f過剰雑音の正体（Learning to measure resistance noise demystifies the ubiquitous 1/f excess noise）</news:title>
   <news:publication_date>2026-08-12T03:11:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722222</loc>
  <lastmod>2026-08-12T03:01:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EL EmbeddingsによるEL++論理理論のベクトル化（EL Embeddings: Geometric construction of models for the Description Logic EL++）</news:title>
   <news:publication_date>2026-08-12T03:01:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722220</loc>
  <lastmod>2026-08-12T03:01:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>窒化物半導体Ca(Mg1−xZnx)2N2による可変発光とp型導電性（Tunable light-emission through the range 1.8–3.2 eV and p-type conductivity at room temperature for nitride semiconductors, Ca(Mg1−xZnx)2N2）</news:title>
   <news:publication_date>2026-08-12T03:01:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722218</loc>
  <lastmod>2026-08-12T03:00:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模公開オンラインコースとクラウドコンピューティング（Massive Open Online Courses and Cloud Computing）</news:title>
   <news:publication_date>2026-08-12T03:00:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722216</loc>
  <lastmod>2026-08-12T03:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習における小さなエピソード記憶の効用 (On Tiny Episodic Memories in Continual Learning)</news:title>
   <news:publication_date>2026-08-12T03:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722214</loc>
  <lastmod>2026-08-12T03:00:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的ガウシアンコピュラABC（Adaptive Gaussian Copula ABC）</news:title>
   <news:publication_date>2026-08-12T03:00:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722212</loc>
  <lastmod>2026-08-12T02:59:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス表現を誘導して少数例から学ぶ方法（Induction Networks for Few-Shot Text Classification）</news:title>
   <news:publication_date>2026-08-12T02:59:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722210</loc>
  <lastmod>2026-08-12T02:08:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込み事前分布を持つゲート付きコンテキストモデルによる深層画像圧縮（Gated Context Model with Embedded Priors for Deep Image Compression）</news:title>
   <news:publication_date>2026-08-12T02:08:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722208</loc>
  <lastmod>2026-08-12T02:07:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Generative Collaborative Networksによる単一画像超解像の新展開（Generative Collaborative Networks for Single Image Super-Resolution）</news:title>
   <news:publication_date>2026-08-12T02:07:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722206</loc>
  <lastmod>2026-08-12T02:07:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MBCliqueNetによるCNNの軽量化と実用化の意義（Modulated Binary Cliquenet）</news:title>
   <news:publication_date>2026-08-12T02:07:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722204</loc>
  <lastmod>2026-08-12T02:06:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固定分類器と正多面体による判別表現の安定化（Fix Your Features: Stationary and Maximally Discriminative Embeddings using Regular Polytope (Fixed Classifier) Networks）</news:title>
   <news:publication_date>2026-08-12T02:06:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722202</loc>
  <lastmod>2026-08-12T02:06:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所内在次元に基づくデータ分割（Data segmentation based on the local intrinsic dimension）</news:title>
   <news:publication_date>2026-08-12T02:06:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722200</loc>
  <lastmod>2026-08-12T02:06:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層量子ニューラルネットワークの効率的学習（Efficient Learning for Deep Quantum Neural Networks）</news:title>
   <news:publication_date>2026-08-12T02:06:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722198</loc>
  <lastmod>2026-08-12T02:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電波干渉計キャリブレーションの統計的性能（Statistical Performance of Radio Interferometric Calibration）</news:title>
   <news:publication_date>2026-08-12T02:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722196</loc>
  <lastmod>2026-08-12T01:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>収益最大化オークションで入札を学習する（Learning to bid in revenue-maximizing auctions）</news:title>
   <news:publication_date>2026-08-12T01:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722194</loc>
  <lastmod>2026-08-12T01:13:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延フィードバック下における適応ヘッジング（Adaptive Hedging under Delayed Feedback）</news:title>
   <news:publication_date>2026-08-12T01:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722192</loc>
  <lastmod>2026-08-12T01:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StyleRemix：ニューラル画像スタイル転送の解釈可能な表現（StyleRemix: An Interpretable Representation for Neural Image Style Transfer）</news:title>
   <news:publication_date>2026-08-12T01:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722190</loc>
  <lastmod>2026-08-12T01:12:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等化正規化によるニューラルネットワークの再パラメータ化（EQUI-NORMALIZATION OF NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-08-12T01:12:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722188</loc>
  <lastmod>2026-08-12T01:12:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FickleNetの要点と実務的意義（FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference）</news:title>
   <news:publication_date>2026-08-12T01:12:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722186</loc>
  <lastmod>2026-08-12T01:12:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像で安定動作するCNNの単一フレーム正則化（Single-frame Regularization for Temporally Stable CNNs）</news:title>
   <news:publication_date>2026-08-12T01:12:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722184</loc>
  <lastmod>2026-08-12T01:12:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文章から自動で問いを作る技術の革新（Learning to Generate Questions by Learning What not to Generate）</news:title>
   <news:publication_date>2026-08-12T01:12:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722182</loc>
  <lastmod>2026-08-12T00:20:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付き内積による表現学習の普遍近似（Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities）</news:title>
   <news:publication_date>2026-08-12T00:20:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722180</loc>
  <lastmod>2026-08-12T00:20:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配フロー消滅による非線形固有関数の計算（Computing Nonlinear Eigenfunctions via Gradient Flow Extinction）</news:title>
   <news:publication_date>2026-08-12T00:20:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722178</loc>
  <lastmod>2026-08-12T00:20:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光ファイバーの非線形性緩和に向けた機械学習検出器の可能性（A Machine Learning-Based Detection Technique for Optical Fiber Nonlinearity Mitigation）</news:title>
   <news:publication_date>2026-08-12T00:20:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722176</loc>
  <lastmod>2026-08-12T00:19:46Z</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ℓp回帰に対する証明可能な近似法（Provable Approximations for Constrained ℓp Regression）</news:title>
   <news:publication_date>2026-08-12T00:19:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722174</loc>
  <lastmod>2026-08-12T00:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルビッグデータにおける信頼性と意味解析の展望（Social Credibility incorporating Semantic Analysis and Machine Learning）</news:title>
   <news:publication_date>2026-08-12T00:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722172</loc>
  <lastmod>2026-08-12T00:19:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーネットワークによる関数的画像表現（Hypernetwork functional image representation）</news:title>
   <news:publication_date>2026-08-12T00:19:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722170</loc>
  <lastmod>2026-08-12T00:19:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然画像のノイズ除去学習を地震データ補間に使えるか（Can learning from natural image denoising be used for seismic data interpolation?）</news:title>
   <news:publication_date>2026-08-12T00:19:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722168</loc>
  <lastmod>2026-08-11T23:26:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸ペナルティを用いるスパース線形回帰のCV高速化と安定性（Cross validation in sparse linear regression with piecewise continuous nonconvex penalties and its acceleration）</news:title>
   <news:publication_date>2026-08-11T23:26:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722166</loc>
  <lastmod>2026-08-11T23:26:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン制約付き広告キーワード生成（Domain-Constrained Advertising Keyword Generation）</news:title>
   <news:publication_date>2026-08-11T23:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/722164</loc>
  <lastmod>2026-08-11T23:26:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系譜検索のランキング統合（RANKING IN GENEALOGY: SEARCH RESULTS FUSION AT ANCESTRY）</news:title>
   <news:publication_date>2026-08-11T23:26:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722162</loc>
  <lastmod>2026-08-11T23:25:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布的頑健性に基づく多重カーネル学習の最適化手法（A Distributionally Robust Optimization Method for Adversarial Multiple Kernel Learning）</news:title>
   <news:publication_date>2026-08-11T23:25:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722160</loc>
  <lastmod>2026-08-11T23:25:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ損失認識に基づくチャネルプルーニング（MULTI-LOSS-AWARE CHANNEL PRUNING OF DEEP NETWORKS）</news:title>
   <news:publication_date>2026-08-11T23:25:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722158</loc>
  <lastmod>2026-08-11T23:25:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モチーフを利用した拡散ネットワークの時間的ダイナミクスモデル（Leveraging Motifs to Model the Temporal Dynamics of Diffusion Networks）</news:title>
   <news:publication_date>2026-08-11T23:25:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722156</loc>
  <lastmod>2026-08-11T23:25:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスター正則化量子化による深層ネットワーク圧縮（Cluster Regularized Quantization for Deep Networks Compression）</news:title>
   <news:publication_date>2026-08-11T23:25:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722154</loc>
  <lastmod>2026-08-11T22:33:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コメントの毒性分類における機械学習手法（A Machine Learning Approach to Comment Toxicity Classification）</news:title>
   <news:publication_date>2026-08-11T22:33:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722152</loc>
  <lastmod>2026-08-11T22:22:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット視覚におけるメトリック学習の重要性（The Importance of Metric Learning for Robotic Vision: Open Set Recognition and Active Learning）</news:title>
   <news:publication_date>2026-08-11T22:22:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722150</loc>
  <lastmod>2026-08-11T22:22:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN画像フォレンジクスの一般化に関する研究（On the Generalization of GAN Image Forensics）</news:title>
   <news:publication_date>2026-08-11T22:22:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722148</loc>
  <lastmod>2026-08-11T22:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>加齢性黄斑変性の進行予測に向けた深層学習アプローチ（A Deep-learning Approach for Prognosis of Age-Related Macular Degeneration Disease using SD-OCT Imaging Biomarkers）</news:title>
   <news:publication_date>2026-08-11T22:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722146</loc>
  <lastmod>2026-08-11T22:22:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予算制約下での因果構造探索を効率化する実験設計（ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery）</news:title>
   <news:publication_date>2026-08-11T22:22:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722144</loc>
  <lastmod>2026-08-11T22:21:34Z</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とガウス過程の深い結びつきが能動学習を加速する（Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning）</news:title>
   <news:publication_date>2026-08-11T22:21:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722142</loc>
  <lastmod>2026-08-11T22:21:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類に必要な語彙サイズの見積り手法（How Large a Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary Selection）</news:title>
   <news:publication_date>2026-08-11T22:21:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722140</loc>
  <lastmod>2026-08-11T21:30:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>治療効果下のサブグループ探索のための機械学習（Machine learning for subgroup discovery under treatment effect）</news:title>
   <news:publication_date>2026-08-11T21:30:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722138</loc>
  <lastmod>2026-08-11T21:30:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境におけるビザンチン耐性確率的勾配降下法（Distributed Byzantine Tolerant Stochastic Gradient Descent in the Era of Big Data）</news:title>
   <news:publication_date>2026-08-11T21:30:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722136</loc>
  <lastmod>2026-08-11T21:30:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分 disentangled 表現による自動エンコーディング正則化がもたらす頑健な画像分類（Disentangled Deep Autoencoding Regularization for Robust Image Classification）</news:title>
   <news:publication_date>2026-08-11T21:30:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722134</loc>
  <lastmod>2026-08-11T21:29:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知力学系の安全環境と制御器を決める新しいシミュレーション指標（A New Simulation Metric to Determine Safe Environments and Controllers for Systems with Unknown Dynamics）</news:title>
   <news:publication_date>2026-08-11T21:29:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722132</loc>
  <lastmod>2026-08-11T21:29:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TensorFlow Eagerが変えたプロトタイピングの常識（TensorFlow Eager: A multi-stage, Python-embedded DSL for machine learning）</news:title>
   <news:publication_date>2026-08-11T21:29:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722130</loc>
  <lastmod>2026-08-11T21:28:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルによるパケット分類の学習（Neural Packet Classification）</news:title>
   <news:publication_date>2026-08-11T21:28:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722128</loc>
  <lastmod>2026-08-11T21:28:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像特徴を時間と意味で豊かにする視覚エンコーディング（Spatio-Temporal Dynamics and Semantic Attribute Enriched Visual Encoding for Video Captioning）</news:title>
   <news:publication_date>2026-08-11T21:28:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722126</loc>
  <lastmod>2026-08-11T20:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FixyNNによるモバイル向け効率的画像認識ハードウェア（FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning）</news:title>
   <news:publication_date>2026-08-11T20:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722124</loc>
  <lastmod>2026-08-11T20:36:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>先端ナノ空洞による単一量子エミッタのチップ強化強結合（Tip-enhanced strong coupling spectroscopy, imaging, and control of a single quantum emitter）</news:title>
   <news:publication_date>2026-08-11T20:36:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722122</loc>
  <lastmod>2026-08-11T20:36:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ埋め込みを敵対的に整合する手法の要点と経営判断への示唆（Deep Adversarial Network Alignment）</news:title>
   <news:publication_date>2026-08-11T20:36:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722120</loc>
  <lastmod>2026-08-11T20:35:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型コンテンツ配信ネットワークにおける適応キャッシュのための深層強化学習 (Deep Reinforcement Learning for Adaptive Caching in Hierarchical Content Delivery Networks)</news:title>
   <news:publication_date>2026-08-11T20:35:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722118</loc>
  <lastmod>2026-08-11T20:35:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形式言語の表現：有限オートマタと再帰型ニューラルネットワークの比較（Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-08-11T20:35:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722116</loc>
  <lastmod>2026-08-11T20:35:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ANODE：無条件に正確なメモリ効率の良いニューラルODEの勾配（ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs）</news:title>
   <news:publication_date>2026-08-11T20:35:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722114</loc>
  <lastmod>2026-08-11T20:35:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッファード確率的変分推論によるVAEの訓練改善（Training Variational Autoencoders with Buffered Stochastic Variational Inference）</news:title>
   <news:publication_date>2026-08-11T20:35:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722112</loc>
  <lastmod>2026-08-11T19:42:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多原因因果推論における未観測交絡の限界と代替手段（On Multi-Cause Causal Inference with Unobserved Confounding: Counterexamples, Impossibility, and Alternatives）</news:title>
   <news:publication_date>2026-08-11T19:42:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722110</loc>
  <lastmod>2026-08-11T19:42:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序付き距離計量学習とMDSによる画像ランキング（Ordinal Distance Metric Learning with MDS）</news:title>
   <news:publication_date>2026-08-11T19:42:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722108</loc>
  <lastmod>2026-08-11T19:42:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データの価値を定量化する効率的手法（Towards Efficient Data Valuation Based on the Shapley Value）</news:title>
   <news:publication_date>2026-08-11T19:42:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722106</loc>
  <lastmod>2026-08-11T19:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層Q学習アルゴリズムのボトルネック診断（Diagnosing Bottlenecks in Deep Q-learning Algorithms）</news:title>
   <news:publication_date>2026-08-11T19:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722104</loc>
  <lastmod>2026-08-11T19:41:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ逆問題の「整定性」を緩やかに捉える新視点（On the well-posedness of Bayesian inverse problems）</news:title>
   <news:publication_date>2026-08-11T19:41:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722102</loc>
  <lastmod>2026-08-11T19:41:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的談話構造学習によるフェイクニュース検出の深化（Learning Hierarchical Discourse-level Structure for Fake News Detection）</news:title>
   <news:publication_date>2026-08-11T19:41:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722100</loc>
  <lastmod>2026-08-11T19:40:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群オブジェクトのゼロショット学習（Zero-shot Learning of 3D Point Cloud Objects）</news:title>
   <news:publication_date>2026-08-11T19:40:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722098</loc>
  <lastmod>2026-08-11T18:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lidarデータを圧縮して現場で使える地図と位置特定を両立する技術（TENSORMAP: LIDAR-BASED TOPOLOGICAL MAPPING AND LOCALIZATION VIA TENSOR DECOMPOSITIONS）</news:title>
   <news:publication_date>2026-08-11T18:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722096</loc>
  <lastmod>2026-08-11T18:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形力学系の線形埋め込みによる制御（Data-driven approximations of dynamical systems operators for control）</news:title>
   <news:publication_date>2026-08-11T18:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722094</loc>
  <lastmod>2026-08-11T18:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ターゲット指向ハイパースペクトル分離と一般化Robust PCA（Target–Based Hyperspectral Demixing via Generalized Robust PCA）</news:title>
   <news:publication_date>2026-08-11T18:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722092</loc>
  <lastmod>2026-08-11T18:47:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入院患者の電子カルテからの継続的AKI予測（Continual Prediction from EHR Data for Inpatient Acute Kidney Injury）</news:title>
   <news:publication_date>2026-08-11T18:47:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722090</loc>
  <lastmod>2026-08-11T18:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書に基づく一般化されたロバストPCAによるハイパースペクトル分離（A Dictionary-Based Generalization of Robust PCA Part II: Applications to Hyperspectral Demixing）</news:title>
   <news:publication_date>2026-08-11T18:47:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722088</loc>
  <lastmod>2026-08-11T18:47:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回答しない判断を学習する仕組み（Learning When Not to Answer: A Ternary Reward Structure for Reinforcement Learning based Question Answering）</news:title>
   <news:publication_date>2026-08-11T18:47:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722086</loc>
  <lastmod>2026-08-11T18:46:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑ネットワークにおける疾病制御可能性の予測（Prediction of the disease controllability in a complex network using machine learning algorithms）</news:title>
   <news:publication_date>2026-08-11T18:46:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722084</loc>
  <lastmod>2026-08-11T17:54:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インプリシット・カーネル学習が切り拓く新しいカーネル設計（Implicit Kernel Learning）</news:title>
   <news:publication_date>2026-08-11T17:54:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722082</loc>
  <lastmod>2026-08-11T17:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重精度データから学ぶ複合ニューラルネットワーク（A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems）</news:title>
   <news:publication_date>2026-08-11T17:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722080</loc>
  <lastmod>2026-08-11T17:53:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転座標系の理解を深める映像教材の効果（Improving students’ understanding of rotating frames of reference using videos from different perspectives）</news:title>
   <news:publication_date>2026-08-11T17:53:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722078</loc>
  <lastmod>2026-08-11T17:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できる深層成績予測と不確実性推定（Reliable Deep Grade Prediction with Uncertainty Estimation）</news:title>
   <news:publication_date>2026-08-11T17:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722076</loc>
  <lastmod>2026-08-11T17:53:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RotatEによる知識グラフ埋め込みと実務的示唆（RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space）</news:title>
   <news:publication_date>2026-08-11T17:53:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722074</loc>
  <lastmod>2026-08-11T17:53:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全結合的低ランク・総変動正則化を用いたDeep MR Fingerprinting（Deep MR Fingerprinting with total-variation and low-rank subspace priors）</news:title>
   <news:publication_date>2026-08-11T17:53:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722072</loc>
  <lastmod>2026-08-11T17:52:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市の水・電力需要ネクサスの統合解析（Integrated analysis of the urban water-electricity demand nexus in the Midwestern United States）</news:title>
   <news:publication_date>2026-08-11T17:52:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722070</loc>
  <lastmod>2026-08-11T17:01:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>森林と都市での深層レーザーローカリゼーション（Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU）</news:title>
   <news:publication_date>2026-08-11T17:01:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722068</loc>
  <lastmod>2026-08-11T17:01:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化するグラフ畳み込みネットワーク（EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs）</news:title>
   <news:publication_date>2026-08-11T17:01:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722066</loc>
  <lastmod>2026-08-11T17:00:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Clever Hansを見抜く方法と機械が本当に学んでいることの評価（Unmasking Clever Hans Predictors and Assessing What Machines Really Learn）</news:title>
   <news:publication_date>2026-08-11T17:00:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722064</loc>
  <lastmod>2026-08-11T17:00:31Z</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おけるモデル不確実性の測定のための変分推論（Variational Inference to Measure Model Uncertainty in Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-11T17:00:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722062</loc>
  <lastmod>2026-08-11T17:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attentionは説明にならない（Attention is not Explanation）</news:title>
   <news:publication_date>2026-08-11T17:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722060</loc>
  <lastmod>2026-08-11T16:59:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かさを持つ線形システムの収束性（Convergence in uncertain linear systems）</news:title>
   <news:publication_date>2026-08-11T16:59:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722058</loc>
  <lastmod>2026-08-11T16:59:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な部分集合最適化を高速化するメモ化フレームワーク（A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems）</news:title>
   <news:publication_date>2026-08-11T16:59:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722056</loc>
  <lastmod>2026-08-11T16:08:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成による非線形近似（NONLINEAR APPROXIMATION VIA COMPOSITIONS）</news:title>
   <news:publication_date>2026-08-11T16:08:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722054</loc>
  <lastmod>2026-08-11T16:08:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>割引協調コストを伴う難しい部分モジュラ問題に対する近似アルゴリズム（Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs）</news:title>
   <news:publication_date>2026-08-11T16:08:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722052</loc>
  <lastmod>2026-08-11T16:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的予測を逐次学習で統合する手法（Online Learning with Continuous Ranked Probability Score）</news:title>
   <news:publication_date>2026-08-11T16:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722050</loc>
  <lastmod>2026-08-11T16:06:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次の十年における機械学習の役割（The Role of Machine Learning in the Next Decade of Cosmology）</news:title>
   <news:publication_date>2026-08-11T16:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722048</loc>
  <lastmod>2026-08-11T16:06:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常過渡現象の起源を探るHI観測の示唆（On the nature of the unusual transient AT 2018cow from Hi observations of its host galaxy）</news:title>
   <news:publication_date>2026-08-11T16:06:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722046</loc>
  <lastmod>2026-08-11T16:06:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頻出k-merの高速近似とメタゲノミクスへの応用（Fast Approximation of Frequent k-mers and Applications to Metagenomics）</news:title>
   <news:publication_date>2026-08-11T16:06:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722044</loc>
  <lastmod>2026-08-11T16:06:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模グラフの彩色をAlphaGoZeroで学ぶ（Coloring Big Graphs With AlphaGoZero）</news:title>
   <news:publication_date>2026-08-11T16:06:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722042</loc>
  <lastmod>2026-08-11T15:14:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテキスト化単語表現を用いたマルチタスク学習による拡張固有表現認識（Multi-Task Learning with Contextualized Word Representations for Extended Named Entity Recognition）</news:title>
   <news:publication_date>2026-08-11T15:14:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722040</loc>
  <lastmod>2026-08-11T15:14:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移でガス分率が高い主系列銀河の観測結果（High Gas Fraction in a CO-Selected Main-Sequence Galaxy at z &amp;gt; 3）</news:title>
   <news:publication_date>2026-08-11T15:14:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722038</loc>
  <lastmod>2026-08-11T15:14:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークに基づく病気遺伝子予測（Network-based methods for disease-gene prediction）</news:title>
   <news:publication_date>2026-08-11T15:14:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722036</loc>
  <lastmod>2026-08-11T15:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発話レベル集約による野外環境での話者認識（UTTERANCE-LEVEL AGGREGATION FOR SPEAKER RECOGNITION IN THE WILD）</news:title>
   <news:publication_date>2026-08-11T15:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722034</loc>
  <lastmod>2026-08-11T15:12:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>伝送系の故障を想定したオンライン適応学習による電圧安定性評価（Adaptive Online Learning with Momentum for Contingency-based Voltage Stability Assessment）</news:title>
   <news:publication_date>2026-08-11T15:12:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722032</loc>
  <lastmod>2026-08-11T15:12:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>摂動履歴による探索（Perturbed-History Exploration in Stochastic Multi-Armed Bandits）</news:title>
   <news:publication_date>2026-08-11T15:12:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722030</loc>
  <lastmod>2026-08-11T15:12:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度意見抽出のためのマルチモーダル映画レビューコーパス（A multimodal movie review corpus for fine-grained opinion mining）</news:title>
   <news:publication_date>2026-08-11T15:12:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722028</loc>
  <lastmod>2026-08-11T14:21:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反強磁性薄膜におけるドメイン壁移動の分散制御（Controllable dispersion of domain wall movement in antiferromagnetic thin films at finite temperatures）</news:title>
   <news:publication_date>2026-08-11T14:21:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722026</loc>
  <lastmod>2026-08-11T14:12:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンド行列演算子と自動微分時代のガウス・マルコフモデル（Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era）</news:title>
   <news:publication_date>2026-08-11T14:12:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722024</loc>
  <lastmod>2026-08-11T14:12:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直接的量子相関からの回復可能性（Recoverability from direct quantum correlations）</news:title>
   <news:publication_date>2026-08-11T14:12:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722022</loc>
  <lastmod>2026-08-11T14:11:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチドメイン特徴学習による視覚的場所認識の新展開（A Multi-Domain Feature Learning Method for Visual Place Recognition）</news:title>
   <news:publication_date>2026-08-11T14:11:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722020</loc>
  <lastmod>2026-08-11T14:11:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文法に基づく機械学習システムの指向的テスト（Grammar Based Directed Testing of Machine Learning Systems）</news:title>
   <news:publication_date>2026-08-11T14:11:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722018</loc>
  <lastmod>2026-08-11T14:10:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graph Neural Processes（Towards Bayesian Graph Neural Networks）</news:title>
   <news:publication_date>2026-08-11T14:10:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722016</loc>
  <lastmod>2026-08-11T14:10:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表データから臨床情報を取り出すためのフレームワーク（A framework for information extraction from tables in biomedical literature）</news:title>
   <news:publication_date>2026-08-11T14:10:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722014</loc>
  <lastmod>2026-08-11T13:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>STAR-Netによる動作認識と時空間活性化再投影（STAR-Net: Action Recognition using Spatio-Temporal Activation Reprojection）</news:title>
   <news:publication_date>2026-08-11T13:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722012</loc>
  <lastmod>2026-08-11T13:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>携帯型スパイロメトリにおける気流信号ベースの自動咳検出（Automatic cough detection based on airflow signals for portable spirometry system）</news:title>
   <news:publication_date>2026-08-11T13:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722010</loc>
  <lastmod>2026-08-11T13:17:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元離散分布に対する厳密な適合度検定の体系 (A Family of Exact Goodness-of-Fit Tests for High-Dimensional Discrete Distributions)</news:title>
   <news:publication_date>2026-08-11T13:17:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722008</loc>
  <lastmod>2026-08-11T13:17:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オプションの自律発見と終了条件の批評（The Termination Critic）</news:title>
   <news:publication_date>2026-08-11T13:17:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722006</loc>
  <lastmod>2026-08-11T13:17:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果影響図で読み解くエージェントのインセンティブ（Understanding Agent Incentives using Causal Influence Diagrams: Part I: Single Decision Settings）</news:title>
   <news:publication_date>2026-08-11T13:17:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722004</loc>
  <lastmod>2026-08-11T13:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全分散型ベイズ最適化と確率的方策（Fully Distributed Bayesian Optimization with Stochastic Policies）</news:title>
   <news:publication_date>2026-08-11T13:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722002</loc>
  <lastmod>2026-08-11T13:16:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的強化学習における局所方策での計画保証（Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies）</news:title>
   <news:publication_date>2026-08-11T13:16:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722000</loc>
  <lastmod>2026-08-11T12:24:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序モデルにおける意図的バックドアの設計（DESIGN OF INTENTIONAL BACKDOORS IN SEQUENTIAL MODELS）</news:title>
   <news:publication_date>2026-08-11T12:24:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721998</loc>
  <lastmod>2026-08-11T12:24:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事象予測に基づく行動プリミティブの自律的同定と目標指向呼び出し（AUTONOMOUS IDENTIFICATION AND GOAL-DIRECTED INVOCATION OF EVENT-PREDICTIVE BEHAVIORAL PRIMITIVES）</news:title>
   <news:publication_date>2026-08-11T12:24:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721996</loc>
  <lastmod>2026-08-11T12:23:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データだけで物体検出を学ばせる（An Annotation Saved is an Annotation Earned: Using Fully Synthetic Training for Object Instance Detection）</news:title>
   <news:publication_date>2026-08-11T12:23:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721994</loc>
  <lastmod>2026-08-11T12:22:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味関係に基づく物体追跡（Semantic Relational Object Tracking）</news:title>
   <news:publication_date>2026-08-11T12:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721992</loc>
  <lastmod>2026-08-11T12:22:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>摂動理論に基づく特徴選択（A Feature Selection Based on Perturbation Theory）</news:title>
   <news:publication_date>2026-08-11T12:22:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721990</loc>
  <lastmod>2026-08-11T12:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頂点畳み込みネットワークによるグラフ分類の学習（Learning Vertex Convolutional Networks for Graph Classification）</news:title>
   <news:publication_date>2026-08-11T12:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721988</loc>
  <lastmod>2026-08-11T12:22:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造情報を用いた特徴選択のためのフューズドラッソ（Fused Lasso for Feature Selection using Structural Information）</news:title>
   <news:publication_date>2026-08-11T12:22:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721986</loc>
  <lastmod>2026-08-11T11:30:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画行動認識における時間情報と特徴融合の革新（Information Fused Temporal Transformation Network）</news:title>
   <news:publication_date>2026-08-11T11:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721984</loc>
  <lastmod>2026-08-11T11:30:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>透明性を導くアンサンブル畳み込みニューラルネットの臨床適用可能性（Transparency guided ensemble convolutional neural networks for stratification of pseudoprogression and true progression of glioblastoma multiform）</news:title>
   <news:publication_date>2026-08-11T11:30:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721982</loc>
  <lastmod>2026-08-11T11:29:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプリングバイアス下における二群間効果推定（Effect Inference from Two-Group Data with Sampling Bias）</news:title>
   <news:publication_date>2026-08-11T11:29:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721980</loc>
  <lastmod>2026-08-11T11:29:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Region Deformer Networksを用いた単眼無監督深度推定（Region Deformer Networks for Unsupervised Depth Estimation from Unconstrained Monocular Videos）</news:title>
   <news:publication_date>2026-08-11T11:29:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721978</loc>
  <lastmod>2026-08-11T11:28:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トップ粒子識別の機械学習の全景（The Machine Learning Landscape of Top Taggers）</news:title>
   <news:publication_date>2026-08-11T11:28:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721976</loc>
  <lastmod>2026-08-11T11:28:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な敵対的データに効率的に対応するオンラインカーネル学習（EFFICIENT ONLINE LEARNING WITH KERNELS FOR ADVERSARIAL LARGE SCALE PROBLEMS）</news:title>
   <news:publication_date>2026-08-11T11:28:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721974</loc>
  <lastmod>2026-08-11T11:28:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HexaGANによる実世界分類問題への統合的対処（HexaGAN: Generative Adversarial Nets for Real World Classification）</news:title>
   <news:publication_date>2026-08-11T11:28:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721972</loc>
  <lastmod>2026-08-11T10:36:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D顔形状の分離表現学習（Disentangled Representation Learning for 3D Face Shape）</news:title>
   <news:publication_date>2026-08-11T10:36:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721970</loc>
  <lastmod>2026-08-11T10:36:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海草（シーグラス）検出とマッピングのための撮像と分類技術（Imaging and Classification Techniques for Seagrass Mapping and Monitoring: A Comprehensive Survey）</news:title>
   <news:publication_date>2026-08-11T10:36:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721968</loc>
  <lastmod>2026-08-11T10:35:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮定・拡張・学習：ランダムラベルとデータ拡張による教師なし少数ショットメタ学習（Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation）</news:title>
   <news:publication_date>2026-08-11T10:35:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721966</loc>
  <lastmod>2026-08-11T10:35:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽光発電の翌日時間別出力予測（Day-Ahead Hourly Forecasting of Power Generation from Photovoltaic Plants）</news:title>
   <news:publication_date>2026-08-11T10:35:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721964</loc>
  <lastmod>2026-08-11T10:34:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈ベクトルは単語ベクトルの半分の次元での反射である（Context Vectors are Reflections of Word Vectors in Half the Dimensions）</news:title>
   <news:publication_date>2026-08-11T10:34:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721962</loc>
  <lastmod>2026-08-11T10:34:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D人間姿勢推定の弱教師あり再投影ネットワーク（RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation）</news:title>
   <news:publication_date>2026-08-11T10:34:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721960</loc>
  <lastmod>2026-08-11T10:34:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボリック伝播による深層ニューラルネットワーク検証の高精度化と高速化（Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification）</news:title>
   <news:publication_date>2026-08-11T10:34:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721958</loc>
  <lastmod>2026-08-11T09:42:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FliPerClassによるTESSデータの自動分類の実用性（FliPerClass: In search of solar-like pulsators among TESS targets）</news:title>
   <news:publication_date>2026-08-11T09:42:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721956</loc>
  <lastmod>2026-08-11T09:42:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデータで学ぶ：条件付きPGGANによる脳転移検出のデータ拡張（Learning More with Less: Conditional PGGAN-based Data Augmentation for Brain Metastases Detection Using Highly-Rough Annotation on MR Images）</news:title>
   <news:publication_date>2026-08-11T09:42:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721954</loc>
  <lastmod>2026-08-11T09:41:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群におけるインスタンスと意味の相互分割（Associatively Segmenting Instances and Semantics in Point Clouds）</news:title>
   <news:publication_date>2026-08-11T09:41:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721952</loc>
  <lastmod>2026-08-11T09:41:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超音波センサの現実的環境シミュレーション（Realistic Ultrasonic Environment Simulation Using Conditional Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-11T09:41:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721950</loc>
  <lastmod>2026-08-11T09:41:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>LaSOによる多ラベル少数例学習のためのラベル集合操作ネットワーク（LaSO: Label-Set Operations networks for multi-label few-shot learning）</news:title>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>生成的視覚対話システムの学習手法（Generative Visual Dialogue System via Weighted Likelihood Estimation）</news:title>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>再帰畳み込みによる圧縮とコスト可変化（Recurrent Convolution for Compact and Cost-Adjustable Neural Networks）</news:title>
   <news:publication_date>2026-08-11T07:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>BMSTとテールバイティング畳み込み符号の統計学習支援復号（Statistical Learning Aided Decoding of BMST of Tail-Biting Convolutional Code）</news:title>
   <news:publication_date>2026-08-11T07:55:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>テキスト表現学習のためのセマンティック・ヒルベルト空間（Semantic Hilbert Space for Text Representation Learning）</news:title>
   <news:publication_date>2026-08-11T07:54:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-11T06:02:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文体（スタイロメトリ）を文法で捉える合成的アプローチ（Syntactic Recurrent Neural Network for Authorship Attribution）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>分散学習と最適化における線形収束の維持（On Maintaining Linear Convergence of Distributed Learning and Optimization under Limited Communication）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:language>ja</news:language>
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 <url>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <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:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ポリグロット文脈表現が切り拓く越境学習の実利（Polyglot Contextual Representations Improve Crosslingual Transfer）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-11T03:13:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-11T03:12:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-11T03:12:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-11T03:12:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>消光と銀河コンフォーミティの一般的手法 (A general approach to quenching and galactic conformity)</news:title>
   <news:publication_date>2026-08-10T23:37:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721799</loc>
  <lastmod>2026-08-10T23:37:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FEELVOSによる高速エンドツーエンド埋め込み学習で変わる動画物体セグメンテーション（FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation）</news:title>
   <news:publication_date>2026-08-10T23:37:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721797</loc>
  <lastmod>2026-08-10T23:36:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件不変なマルチビュー場所認識の実務的インパクト（Condition-Invariant Multi-View Place Recognition）</news:title>
   <news:publication_date>2026-08-10T23:36:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721795</loc>
  <lastmod>2026-08-10T23:36:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>流入境界に基づくNavier–Stokes数値波槽：平坦底と傾斜底上の波伝播に関する検証と妥当性検証（An inflow-boundary-based Navier-Stokes wave tank: verification and validation for waves propagating over flat and inclined bottoms）</news:title>
   <news:publication_date>2026-08-10T23:36:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721793</loc>
  <lastmod>2026-08-10T23:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GQA：実世界の視覚的推論のための新データセット（GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering）</news:title>
   <news:publication_date>2026-08-10T23:36:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721791</loc>
  <lastmod>2026-08-10T23:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体の深層特徴のみを用いた画像記述（Using Deep Features of Only Objects to Describe Images）</news:title>
   <news:publication_date>2026-08-10T23:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721789</loc>
  <lastmod>2026-08-10T23:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成ノイズによる機械翻訳の堅牢化（Improving Robustness of Machine Translation with Synthetic Noise）</news:title>
   <news:publication_date>2026-08-10T23:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721784</loc>
  <lastmod>2026-08-10T22:44:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頭蓋内高血圧の早期予測を目指す多階層波形解析（Forecasting intracranial hypertension using multi-scale waveform metrics）</news:title>
   <news:publication_date>2026-08-10T22:44:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721782</loc>
  <lastmod>2026-08-10T22:44:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈依存型単語埋め込みの言語間整合とゼロショット構文解析への応用（Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing）</news:title>
   <news:publication_date>2026-08-10T22:44:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721780</loc>
  <lastmod>2026-08-10T22:43:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚質問応答のためのマルチモーダル関係推論（MUREL: Multimodal Relational Reasoning for Visual Question Answering）</news:title>
   <news:publication_date>2026-08-10T22:43:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721778</loc>
  <lastmod>2026-08-10T22:43:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似k近傍探索における適応的推定の考え方（Adaptive Estimation for Approximate k-Nearest-Neighbor Computations）</news:title>
   <news:publication_date>2026-08-10T22:43:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721776</loc>
  <lastmod>2026-08-10T22:42:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付き損失関数と異種信号のための行列デノイジング（Matrix denoising for weighted loss functions and heterogeneous signals）</news:title>
   <news:publication_date>2026-08-10T22:42:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721774</loc>
  <lastmod>2026-08-10T22:42:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸特異値しきい値によるロジスティック主成分分析（Logistic principal component analysis via non-convex singular value thresholding）</news:title>
   <news:publication_date>2026-08-10T22:42:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721772</loc>
  <lastmod>2026-08-10T22:42:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MedMentions：UMLSで注釈された大規模バイオ医療コーパスの公開（MedMentions: A Large Biomedical Corpus Annotated with UMLS Concepts）</news:title>
   <news:publication_date>2026-08-10T22:42:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721770</loc>
  <lastmod>2026-08-10T21:51:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長距離屋内ナビゲーションを実現するPRM-RL（Long-Range Indoor Navigation with PRM-RL）</news:title>
   <news:publication_date>2026-08-10T21:51:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721768</loc>
  <lastmod>2026-08-10T21:50:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>S-TRIGGER：自己トリガー型生成リプレイによる継続的状態表現学習（S-TRIGGER: Continual State Representation Learning via Self-Triggered Generative Replay）</news:title>
   <news:publication_date>2026-08-10T21:50:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721766</loc>
  <lastmod>2026-08-10T21:50:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>加法的パラメータ分解による順序に頑健な継続学習（Scalable and Order‑Robust Continual Learning with Additive Parameter Decomposition）</news:title>
   <news:publication_date>2026-08-10T21:50:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721764</loc>
  <lastmod>2026-08-10T21:49:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的サンプリングと新規特徴選択によるてんかん発作検出の実用性（Epileptic seizure classification using statistical sampling and a novel feature selection algorithm）</news:title>
   <news:publication_date>2026-08-10T21:49:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721762</loc>
  <lastmod>2026-08-10T21:49:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超低消費エネルギーのCTFベースシナプスと寄生リーク抑制（Ultra-low Energy charge trap flash based synapse enabled by parasitic leakage mitigation）</news:title>
   <news:publication_date>2026-08-10T21:49:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721760</loc>
  <lastmod>2026-08-10T21:49:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子スケールの現場をつなぐデータ駆動型材料モデル（Data-driven Material Models for Atomistic Simulation）</news:title>
   <news:publication_date>2026-08-10T21:49:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721758</loc>
  <lastmod>2026-08-10T21:48:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子変調によるマルチマーの伝播制御（Manipulating multimer propagation using lattice modulation）</news:title>
   <news:publication_date>2026-08-10T21:48:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721756</loc>
  <lastmod>2026-08-10T20:57:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共同研究データをネットワーク層に変換して分析を強化する手法（Transforming Collaboration Data into Network Layers for Enhanced Analytics）</news:title>
   <news:publication_date>2026-08-10T20:57:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721754</loc>
  <lastmod>2026-08-10T20:49:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的クローン性がもたらす見える影と隠れた影響（The discernible and hidden effects of clonality on the genotypic and genetic states of populations）</news:title>
   <news:publication_date>2026-08-10T20:49:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721752</loc>
  <lastmod>2026-08-10T20:49:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習された変換によるワンショット医療画像セグメンテーションのデータ拡張（Data augmentation using learned transformations for one-shot medical image segmentation）</news:title>
   <news:publication_date>2026-08-10T20:49:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721750</loc>
  <lastmod>2026-08-10T20:48:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文と意味を分離して協調学習する手法（Cooperative Learning of Disjoint Syntax and Semantics）</news:title>
   <news:publication_date>2026-08-10T20:48:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721748</loc>
  <lastmod>2026-08-10T20:47:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトファジーモデル構築のための分散ルール導出アルゴリズムCFM-BD（CFM-BD: a distributed rule induction algorithm for building Compact Fuzzy Models in Big Data classification problems）</news:title>
   <news:publication_date>2026-08-10T20:47:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721746</loc>
  <lastmod>2026-08-10T20:47:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師付き・弱教師付き階層テキスト分類のための効率的パス予測 (Efficient Path Prediction for Semi-Supervised and Weakly Supervised Hierarchical Text Classification)</news:title>
   <news:publication_date>2026-08-10T20:47:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721744</loc>
  <lastmod>2026-08-10T20:47:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>履歴を重視する視覚対話学習（Making History Matter: History-Advantage Sequence Training for Visual Dialog）</news:title>
   <news:publication_date>2026-08-10T20:47:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721742</loc>
  <lastmod>2026-08-10T19:54:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きパーソナライズ行列因子分解によるマルチラベルネットワーク分類（Multi-Label Network Classification via Weighted Personalized Factorizations）</news:title>
   <news:publication_date>2026-08-10T19:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721740</loc>
  <lastmod>2026-08-10T19:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wasserstein-Wassersteinオートエンコーダ（Wasserstein-Wasserstein Auto-Encoders）</news:title>
   <news:publication_date>2026-08-10T19:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721738</loc>
  <lastmod>2026-08-10T19:53:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーソナライズされた仮想教育アシスタント（A Virtual Teaching Assistant for Personalized Learning）</news:title>
   <news:publication_date>2026-08-10T19:53:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721736</loc>
  <lastmod>2026-08-10T19:53:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密な軌跡と欠損軌跡を同時に扱う都市全域交通量推定（Joint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference）</news:title>
   <news:publication_date>2026-08-10T19:53:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721734</loc>
  <lastmod>2026-08-10T19:52:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数依存ビームの影響下でEoR信号を分離する畳み込みデノイジングオートエンコーダ（Separating the EoR signal with a convolutional denoising autoencoder: a deep-learning-based method）</news:title>
   <news:publication_date>2026-08-10T19:52:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721732</loc>
  <lastmod>2026-08-10T19:52:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的文脈条件付けを用いた関係抽出（Relation Extraction using Explicit Context Conditioning）</news:title>
   <news:publication_date>2026-08-10T19:52:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721730</loc>
  <lastmod>2026-08-10T19:52:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人の目に見えない敵対的攻撃の隠し方（Adversarial attacks hidden in plain sight）</news:title>
   <news:publication_date>2026-08-10T19:52:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721728</loc>
  <lastmod>2026-08-10T19:01:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で明かす量子カオスの姿（Revealing quantum chaos with machine learning）</news:title>
   <news:publication_date>2026-08-10T19:01:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721726</loc>
  <lastmod>2026-08-10T18:52:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MBPEP：高品質な不確かさ予測を実現する深層アンサンブル剪定アルゴリズム (The MBPEP: a deep ensemble pruning algorithm providing high quality uncertainty prediction)</news:title>
   <news:publication_date>2026-08-10T18:52:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721724</loc>
  <lastmod>2026-08-10T18:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ない内部センサで高精度な触覚を実現する（Robust Affordable 3D Haptic Sensation via Learning Deformation Patterns）</news:title>
   <news:publication_date>2026-08-10T18:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721722</loc>
  <lastmod>2026-08-10T18:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モジュール化によるニューラルネットワークの複雑性管理（Modularity as a Means for Complexity Management in Neural Networks Learning）</news:title>
   <news:publication_date>2026-08-10T18:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721720</loc>
  <lastmod>2026-08-10T18:51:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度表現学習による人物姿勢推定の刷新（Deep High-Resolution Representation Learning for Human Pose Estimation）</news:title>
   <news:publication_date>2026-08-10T18:51:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721718</loc>
  <lastmod>2026-08-10T18:51:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大尤度とGANの調和による多モーダル条件付き生成（HARMONIZING MAXIMUM LIKELIHOOD WITH GANS FOR MULTIMODAL CONDITIONAL GENERATION）</news:title>
   <news:publication_date>2026-08-10T18:51:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721716</loc>
  <lastmod>2026-08-10T18:51:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Contrastive Learningの理論的枠組みが示した本質（A Theoretical Analysis of Contrastive Unsupervised Representation Learning）</news:title>
   <news:publication_date>2026-08-10T18:51:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721714</loc>
  <lastmod>2026-08-10T17:58:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みネットワークに対するバッチ仮想敵対的訓練（Batch Virtual Adversarial Training for Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-10T17:58:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721712</loc>
  <lastmod>2026-08-10T17:58:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実生活下における鏡像系の皮質活動（Cortical Mirror-System Activation During Real-Life Game Playing: An Intracranial Electroencephalography (EEG) Study）</news:title>
   <news:publication_date>2026-08-10T17:58:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721710</loc>
  <lastmod>2026-08-10T17:57:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>応答の多様性を高める周波数対応交差エントロピー損失（Improving Neural Response Diversity with Frequency-Aware Cross-Entropy Loss）</news:title>
   <news:publication_date>2026-08-10T17:57:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721708</loc>
  <lastmod>2026-08-10T17:57:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙の塵に覆われた星形成銀河の統計的性質—Herschelデータの多波長de-blend解析 (A multi-wavelength de-blended Herschel view of the statistical properties of dusty star-forming galaxies across cosmic time)</news:title>
   <news:publication_date>2026-08-10T17:57:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721706</loc>
  <lastmod>2026-08-10T17:56:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数領域を同時に学習する短答自動採点（Joint Multi-Domain Learning for Automatic Short Answer Grading）</news:title>
   <news:publication_date>2026-08-10T17:56:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721704</loc>
  <lastmod>2026-08-10T17:56:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転におけるコーナーケース検出の実装と評価（Towards Corner Case Detection for Autonomous Driving）</news:title>
   <news:publication_date>2026-08-10T17:56:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721702</loc>
  <lastmod>2026-08-10T17:56:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GFCN：並列フローに基づく新しいグラフ畳み込みネットワーク（GFCN: A New Graph Convolutional Network Based on Parallel Flows）</news:title>
   <news:publication_date>2026-08-10T17:56:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721700</loc>
  <lastmod>2026-08-10T17:05:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像解析におけるクラウドソーシングの概観（A Survey of Crowdsourcing in Medical Image Analysis）</news:title>
   <news:publication_date>2026-08-10T17:05:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721698</loc>
  <lastmod>2026-08-10T17:04:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインクラスタリングバンディットの改良アルゴリズム（Improved Algorithm on Online Clustering of Bandits）</news:title>
   <news:publication_date>2026-08-10T17:04:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721696</loc>
  <lastmod>2026-08-10T17:04:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かな穴への迅速なペグ挿入（Quickly Inserting Pegs into Uncertain Holes using Multi-view Images and Deep Network Trained on Synthetic Data）</news:title>
   <news:publication_date>2026-08-10T17:04:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721694</loc>
  <lastmod>2026-08-10T17:04:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長読みに基づくウイルスゲノム進化の未来的方法（Futuristic methods in virus genome evolution using the Third-Generation DNA sequencing and artificial neural networks）</news:title>
   <news:publication_date>2026-08-10T17:04:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721692</loc>
  <lastmod>2026-08-10T17:04:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチグリッド偏微分方程式（PDE）ソルバーの最適化を学習する（Learning to Optimize Multigrid PDE Solvers）</news:title>
   <news:publication_date>2026-08-10T17:04:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721690</loc>
  <lastmod>2026-08-10T17:03:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Bayesian Multi-Target Learningによる推薦最適化の実務的理解（Deep Bayesian Multi-Target Learning for Recommender Systems）</news:title>
   <news:publication_date>2026-08-10T17:03:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721688</loc>
  <lastmod>2026-08-10T17:03:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DDFlow: ラベルなしデータから学ぶ光学フローの蒸留学習（DDFlow: Learning Optical Flow with Unlabeled Data Distillation）</news:title>
   <news:publication_date>2026-08-10T17:03:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721686</loc>
  <lastmod>2026-08-10T16:12:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフの集合を“点”で扱う時代へ（Unsupervised Network Embedding for Graph Visualization, Clustering and Classification）</news:title>
   <news:publication_date>2026-08-10T16:12:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721684</loc>
  <lastmod>2026-08-10T16:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を備えたグラフ畳み込みLSTMによるスケルトン動作認識（An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition）</news:title>
   <news:publication_date>2026-08-10T16:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721682</loc>
  <lastmod>2026-08-10T16:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリップされたバイナリのニューラル逆解析（Neural Reverse Engineering of Stripped Binaries using Augmented Control Flow Graphs）</news:title>
   <news:publication_date>2026-08-10T16:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721680</loc>
  <lastmod>2026-08-10T16:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル誤差を超えて: 自己教師ありエゴモーション推定における幾何学的マッチングの導入 (Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation)</news:title>
   <news:publication_date>2026-08-10T16:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721678</loc>
  <lastmod>2026-08-10T16:10:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク生成モデルによる動画表現と再構成（Generative Models for Low-Rank Video Representation and Reconstruction）</news:title>
   <news:publication_date>2026-08-10T16:10:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721676</loc>
  <lastmod>2026-08-10T16:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可視化、判別性、解釈可能なSaak特徴の応用（Visualization, Discriminability and Applications of Interpretable Saak Features）</news:title>
   <news:publication_date>2026-08-10T16:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721674</loc>
  <lastmod>2026-08-10T16:09:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Marathon Environments：商用ゲームエンジン上での連続制御ベンチマーク（Marathon Environments: Multi-Agent Continuous Control Benchmarks in a Modern Video Game Engine）</news:title>
   <news:publication_date>2026-08-10T16:09:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721672</loc>
  <lastmod>2026-08-10T15:18:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGA上のグラフ処理の分類と課題（Graph Processing on FPGAs: Taxonomy, Survey, Challenges）</news:title>
   <news:publication_date>2026-08-10T15:18:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721670</loc>
  <lastmod>2026-08-10T15:09:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィールド対応ニューラル因子分解機によるクリック率予測（Field-aware Neural Factorization Machine for Click-Through Rate Prediction）</news:title>
   <news:publication_date>2026-08-10T15:09:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721668</loc>
  <lastmod>2026-08-10T15:09:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DRAMの電源立ち上げ特性を機器認証に使う新手法（DRAMNet: Authentication based on Physical Unique Features of DRAM Using Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-10T15:09:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721666</loc>
  <lastmod>2026-08-10T15:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系列データの転移学習：単語の共起を学んで移す（TRANSFER LEARNING FOR SEQUENCES VIA LEARNING TO COLLOCATE）</news:title>
   <news:publication_date>2026-08-10T15:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721664</loc>
  <lastmod>2026-08-10T15:08:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極端温度下で動作する自己整流BFOメモリスタの学習・記憶機能（Synaptic Learning and Memory Functions Achieved in Self-rectifying BFO Memristor under Extreme Environmental Temperature）</news:title>
   <news:publication_date>2026-08-10T15:08:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721662</loc>
  <lastmod>2026-08-10T15:07:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レンズレスな秘匿映像で行動認識を可能にする技術（Privacy-Preserving Action Recognition using Coded Aperture Videos）</news:title>
   <news:publication_date>2026-08-10T15:07:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721660</loc>
  <lastmod>2026-08-10T15:07:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識ベースを活用するLSTMによる機械読解の向上（Leveraging Knowledge Bases in LSTMs for Improving Machine Reading）</news:title>
   <news:publication_date>2026-08-10T15:07:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721658</loc>
  <lastmod>2026-08-10T14:15:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩行者検出における意味的自己注意による精度向上（SSA-CNN: Semantic Self-Attention CNN for Pedestrian Detection）</news:title>
   <news:publication_date>2026-08-10T14:15:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721656</loc>
  <lastmod>2026-08-10T14:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャネル敵対的学習によるクロスチャネル話者認識の改善（Channel Adversarial Training for Cross-Channel Text-Independent Speaker Recognition）</news:title>
   <news:publication_date>2026-08-10T14:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721654</loc>
  <lastmod>2026-08-10T14:15:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-10T14:15:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721652</loc>
  <lastmod>2026-08-10T14:14:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルゴンにおける39Arと37Arの宇宙生成（Cosmogenic production of 39Ar and 37Ar in argon）</news:title>
   <news:publication_date>2026-08-10T14:14:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721650</loc>
  <lastmod>2026-08-10T14:13:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wasserstein GANがPCAを実現する可能性（Wasserstein GAN Can Perform PCA）</news:title>
   <news:publication_date>2026-08-10T14:13:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721648</loc>
  <lastmod>2026-08-10T14:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転意図予測の実用的アプローチ（A Driving Intention Prediction Method Based on Hidden Markov Model for Autonomous Driving）</news:title>
   <news:publication_date>2026-08-10T14:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721646</loc>
  <lastmod>2026-08-10T14:13:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アフリカ森林ゾウの受動音響モニタリングにおける自動検出と圧縮（Automatic Detection and Compression for Passive Acoustic Monitoring of the African Forest Elephant）</news:title>
   <news:publication_date>2026-08-10T14:13:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721644</loc>
  <lastmod>2026-08-10T13:21:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測下における自律型コンピュータネットワーク防御のための敵対的強化学習（Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence）</news:title>
   <news:publication_date>2026-08-10T13:21:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721642</loc>
  <lastmod>2026-08-10T13:21:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル演算による高価なベイズ計算の高速化（Vector operations for accelerating expensive Bayesian computations – a tutorial guide）</news:title>
   <news:publication_date>2026-08-10T13:21:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721640</loc>
  <lastmod>2026-08-10T13:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動ロボットによる堅牢で適応的なドア操作（Robust and Adaptive Door Operation with a Mobile Robot）</news:title>
   <news:publication_date>2026-08-10T13:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721638</loc>
  <lastmod>2026-08-10T13:20:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最急適応モーメント推定（Rapidly Adapting Moment Estimation）</news:title>
   <news:publication_date>2026-08-10T13:20:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721636</loc>
  <lastmod>2026-08-10T13:20:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単調単一インデックスモデルの非線形一般化（Nonlinear generalization of the monotone single index model）</news:title>
   <news:publication_date>2026-08-10T13:20:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721634</loc>
  <lastmod>2026-08-10T13:19:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一前向きステップによる射影分割：ココーシビティの活用（Single-Forward-Step Projective Splitting: Exploiting Cocoercivity）</news:title>
   <news:publication_date>2026-08-10T13:19:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721632</loc>
  <lastmod>2026-08-10T13:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的推定器は深層ニューラルネットの情報圧縮を示す（Adaptive Estimators Show Information Compression in Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-10T13:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721630</loc>
  <lastmod>2026-08-10T12:26:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>役割と充填子の結合学習（Learning to Perform Role-Filler Binding with Schematic Knowledge）</news:title>
   <news:publication_date>2026-08-10T12:26:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721628</loc>
  <lastmod>2026-08-10T12:24:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エアリービームを用いた蛍光イメージングの深部透過（Deep penetration fluorescence imaging through dense yeast cells suspensions using Airy beams）</news:title>
   <news:publication_date>2026-08-10T12:24:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721626</loc>
  <lastmod>2026-08-10T12:24:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きなマージンを持つ半空間の差分プライバシー学習アルゴリズム（Efficient Private Algorithms for Learning Large-Margin Halfspaces）</news:title>
   <news:publication_date>2026-08-10T12:24:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721624</loc>
  <lastmod>2026-08-10T12:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無制約オンライン学習のための人工的制約とリプシッツヒント（Artificial Constraints and Lipschitz Hints for Unconstrained Online Learning）</news:title>
   <news:publication_date>2026-08-10T12:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721622</loc>
  <lastmod>2026-08-10T12:22:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元制約付き連合モデル選択と分布シフト下の多目的ベイズ最適化 (High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions)</news:title>
   <news:publication_date>2026-08-10T12:22:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721620</loc>
  <lastmod>2026-08-10T12:22:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AgentBuddy: 顧客対応支援のための文脈型バンディット（AgentBuddy: A Contextual Bandit based Decision Support System for Customer Support Agents）</news:title>
   <news:publication_date>2026-08-10T12:22:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721618</loc>
  <lastmod>2026-08-10T12:21:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数のオンライン学習アルゴリズムを安全に組み合わせる方法（Combining Online Learning Guarantees）</news:title>
   <news:publication_date>2026-08-10T12:21:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721616</loc>
  <lastmod>2026-08-10T11:29:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U-NetPlusによる手術器具セグメンテーションの改良（U-NetPlus: A Modified Encoder-Decoder U-Net Architecture for Semantic and Instance Segmentation of Surgical Instrument）</news:title>
   <news:publication_date>2026-08-10T11:29:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721614</loc>
  <lastmod>2026-08-10T11:28:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部位を超えた深層学習によるがん検出の移植性（Transferability of Deep Learning Algorithms for Malignancy Detection in Confocal Laser Endomicroscopy Images from Different Anatomical Locations of the Upper Gastrointestinal Tract）</news:title>
   <news:publication_date>2026-08-10T11:28:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721612</loc>
  <lastmod>2026-08-10T11:28:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>慢性疼痛における防護的行動の深層学習による検出（Chronic-Pain Protective Behavior Detection with Deep Learning）</news:title>
   <news:publication_date>2026-08-10T11:28:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721610</loc>
  <lastmod>2026-08-10T11:28:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習に基づくモデル予測制御（An Online Learning Approach to Model Predictive Control）</news:title>
   <news:publication_date>2026-08-10T11:28:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721608</loc>
  <lastmod>2026-08-10T11:27:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同期双方向推論が変える系列生成の常識（Synchronous Bidirectional Inference for Neural Sequence Generation）</news:title>
   <news:publication_date>2026-08-10T11:27:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721606</loc>
  <lastmod>2026-08-10T11:27:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載CANログからのセンサ信号抽出による運転者再識別（Extracting vehicle sensor signals from CAN logs for driver re-identification）</news:title>
   <news:publication_date>2026-08-10T11:27:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721604</loc>
  <lastmod>2026-08-10T11:27:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似度に基づく自然勾配法の一般化（A Formalization of The Natural Gradient Method for General Similarity Measures）</news:title>
   <news:publication_date>2026-08-10T11:27:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721602</loc>
  <lastmod>2026-08-10T10:35:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動配送仕分けのための視覚ベースピッキングシステム（Vision Based Picking System for Automatic Express Package Dispatching）</news:title>
   <news:publication_date>2026-08-10T10:35:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721600</loc>
  <lastmod>2026-08-10T10:35:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠心加速度でGANの学習を安定化する（Training GANs with Centripetal Acceleration）</news:title>
   <news:publication_date>2026-08-10T10:35:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721598</loc>
  <lastmod>2026-08-10T10:34:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルレスな能動コンプライアンス：リカレントニューラルネットワークによる連続体ロボット制御（Model-less Active Compliance for Continuum Robots using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-08-10T10:34:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721596</loc>
  <lastmod>2026-08-10T10:34:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャネル不確実性下における離散デノイジングの反復チャネル推定（Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty）</news:title>
   <news:publication_date>2026-08-10T10:34:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721594</loc>
  <lastmod>2026-08-10T10:34:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>健康経済評価における非遵守と欠測データ（Non-compliance and missing data in health economic evaluation）</news:title>
   <news:publication_date>2026-08-10T10:34:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721592</loc>
  <lastmod>2026-08-10T10:33:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置情報データ公開における機械学習ベース匿名化の実務的意義（Privacy Preserving Location Data Publishing: A Machine Learning Approach）</news:title>
   <news:publication_date>2026-08-10T10:33:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721590</loc>
  <lastmod>2026-08-10T10:33:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高冗長クラウド注釈の真実推定法（Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations）</news:title>
   <news:publication_date>2026-08-10T10:33:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721588</loc>
  <lastmod>2026-08-10T09:41:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動きブレ補正を高速化するBi-Skipと自己ペース学習（Bi-Skip: A Motion Deblurring Network Using Self-paced Learning）</news:title>
   <news:publication_date>2026-08-10T09:41:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721586</loc>
  <lastmod>2026-08-10T09:41:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-10T09:41:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721584</loc>
  <lastmod>2026-08-10T09:41:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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 <url>
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 </url>
 <url>
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 <url>
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 <url>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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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: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:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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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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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TESS惑星候補の迅速分類（Rapid Classification of TESS Planet Candidates with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-10T00:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721438</loc>
  <lastmod>2026-08-10T00:26:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助知識整合による敵対的モデル反転の実行手法（Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment）</news:title>
   <news:publication_date>2026-08-10T00:26:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721436</loc>
  <lastmod>2026-08-10T00:25:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パルス渦電流の終端から終端の分類と回帰へのCNN（Towards end-to-end pulsed eddy current classification and regression with CNN）</news:title>
   <news:publication_date>2026-08-10T00:25:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721434</loc>
  <lastmod>2026-08-09T23:35:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2Dレーザで走行位置を推定するLSTMベースのリアルタイム走行推定（An LSTM Network for Real-Time Odometry Estimation）</news:title>
   <news:publication_date>2026-08-09T23:35:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721432</loc>
  <lastmod>2026-08-09T23:34:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロトコル非依存のグラフベース異常検知によるボット検出（Anomaly- and Graph-Based Bot Detection）</news:title>
   <news:publication_date>2026-08-09T23:34:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721430</loc>
  <lastmod>2026-08-09T23:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冷媒漏れのオンライントラブル診断を変えるスケーリング則（Fault Diagnosis Method Based on Scaling Law for On-line Refrigerant Leak Detection）</news:title>
   <news:publication_date>2026-08-09T23:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721428</loc>
  <lastmod>2026-08-09T23:33:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数運転モードを持つ産業システムの故障検知に向けたソフトセンサ半教師あり手法（Semi-supervised Approach to Soft Sensor Modeling for Fault Detection in Industrial Systems with Multiple Operation Modes）</news:title>
   <news:publication_date>2026-08-09T23:33:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721426</loc>
  <lastmod>2026-08-09T23:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク内集約による分散学習の高速化（Scaling Distributed Machine Learning with In-Network Aggregation）</news:title>
   <news:publication_date>2026-08-09T23:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721424</loc>
  <lastmod>2026-08-09T23:33:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低コントラスト・高形状多様性MRデータからの3D上腕骨・肩甲骨抽出の有効手法（Effective 3D Humerus and Scapula Extraction using Low-contrast and High-shape-variability MR Data）</news:title>
   <news:publication_date>2026-08-09T23:33:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721422</loc>
  <lastmod>2026-08-09T23:32:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AReSとMaRS—SDE推定の敵対的・MMD最小化回帰（AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs）</news:title>
   <news:publication_date>2026-08-09T23:32:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721420</loc>
  <lastmod>2026-08-09T22:40:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速多言語LSTMベースのオンライン手書き認識（Fast Multi-language LSTM-based Online Handwriting Recognition）</news:title>
   <news:publication_date>2026-08-09T22:40:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721418</loc>
  <lastmod>2026-08-09T22:40:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元でのモデルベースクラスタリングと適応射影（Model-based clustering in very high dimensions via adaptive projections）</news:title>
   <news:publication_date>2026-08-09T22:40:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721416</loc>
  <lastmod>2026-08-09T22:40:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データストリーム分類におけるアンサンブルの多様性（Diversity of Ensembles for Data Stream Classification）</news:title>
   <news:publication_date>2026-08-09T22:40:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721414</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>詳細な探索空間分類による集合問題の列挙困難変種の高速化 (Fine-grained Search Space Classification for Hard Enumeration Variants of Subset Problems)</news:title>
   <news:publication_date>2026-08-09T22:39:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721412</loc>
  <lastmod>2026-08-09T22:38:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸分布の効率的サンプリング手法の改善（Nonconvex sampling with the Metropolis-adjusted Langevin algorithm）</news:title>
   <news:publication_date>2026-08-09T22:38:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721410</loc>
  <lastmod>2026-08-09T22:38:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン異常検知がHPC運用を変える（Online Anomaly Detection in HPC Systems）</news:title>
   <news:publication_date>2026-08-09T22:38:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721408</loc>
  <lastmod>2026-08-09T22:38:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイバーフィジカル生産システムにおける認知アーキテクチャの評価（Evaluation of Cognitive Architectures for Cyber-Physical Production Systems）</news:title>
   <news:publication_date>2026-08-09T22:38:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721406</loc>
  <lastmod>2026-08-09T21:47:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインメタラーニングの教科書的解説（Online Meta-Learning）</news:title>
   <news:publication_date>2026-08-09T21:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721404</loc>
  <lastmod>2026-08-09T21:47:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズのあるリンク重みを扱うロバストなグラフ埋め込み（Robust Graph Embedding with Noisy Link Weights）</news:title>
   <news:publication_date>2026-08-09T21:47:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721402</loc>
  <lastmod>2026-08-09T21:46:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分非対称を用いたトランスベシティ分布の抽出（Transversity distributions from difference asymmetries in semi-inclusive DIS）</news:title>
   <news:publication_date>2026-08-09T21:46:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721400</loc>
  <lastmod>2026-08-09T21:46:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓病学における深層学習（Deep Learning in Cardiology）</news:title>
   <news:publication_date>2026-08-09T21:46:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721398</loc>
  <lastmod>2026-08-09T21:46:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>整列名義集合上の高速計算（Fast Computations on Ordered Nominal Sets）</news:title>
   <news:publication_date>2026-08-09T21:46:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721396</loc>
  <lastmod>2026-08-09T21:46:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ゲート制御に深層強化学習を使う意義（Deep Reinforcement Learning for Quantum Gate Control）</news:title>
   <news:publication_date>2026-08-09T21:46:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721394</loc>
  <lastmod>2026-08-09T21:45:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレーン・カプセルネットワークの実務的理解（The Multi-Lane Capsule Network）</news:title>
   <news:publication_date>2026-08-09T21:45:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721392</loc>
  <lastmod>2026-08-09T20:54:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ学習を用いたグラフニューラルネットワークへの敵対的攻撃（ADVERSARIAL ATTACKS ON GRAPH NEURAL NETWORKS VIA META LEARNING）</news:title>
   <news:publication_date>2026-08-09T20:54:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721390</loc>
  <lastmod>2026-08-09T20:53:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模皮質モデルの活動状態と並列シミュレーション性能のスケーリング（Scaling of a Large-Scale Simulation of Synchronous Slow-Wave and Asynchronous Awake-Like Activity of a Cortical Model With Long-Range Interconnections）</news:title>
   <news:publication_date>2026-08-09T20:53:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721388</loc>
  <lastmod>2026-08-09T20:52:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークによる二値マルコフ確率場の確率的推論（Probabilistic Inference of Binary Markov Random Fields in Spiking Neural Networks through Mean-field Approximation）</news:title>
   <news:publication_date>2026-08-09T20:52:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721386</loc>
  <lastmod>2026-08-09T20:52:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PhysNetによる分子エネルギーと力の高精度予測（PHYSNET: A NEURAL NETWORK FOR PREDICTING ENERGIES, FORCES, DIPOLE MOMENTS AND PARTIAL CHARGES）</news:title>
   <news:publication_date>2026-08-09T20:52:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721384</loc>
  <lastmod>2026-08-09T20:52:18Z</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・コンディショナーによる指数的条件分布学習（Learning about an exponential amount of conditional distributions）</news:title>
   <news:publication_date>2026-08-09T20:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721382</loc>
  <lastmod>2026-08-09T20:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的テンソル表現とカプセルネットワークによるグラフ分類（Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations）</news:title>
   <news:publication_date>2026-08-09T20:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721380</loc>
  <lastmod>2026-08-09T20:51:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>autoAxによる近似回路ライブラリを用いた自動設計空間探索と回路構築（autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components）</news:title>
   <news:publication_date>2026-08-09T20:51:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721378</loc>
  <lastmod>2026-08-09T20:00:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMによる極性符号のSCフリップ復号学習（Learning to Flip Successive Cancellation Decoding of Polar Codes with LSTM Networks）</news:title>
   <news:publication_date>2026-08-09T20:00:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721376</loc>
  <lastmod>2026-08-09T19:59:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド自己符号化器通信系に対する物理的敵対的攻撃（Physical Adversarial Attacks Against End-to-End Autoencoder Communication Systems）</news:title>
   <news:publication_date>2026-08-09T19:59:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721374</loc>
  <lastmod>2026-08-09T19:59:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何的輸送問題の前処理（Preconditioning for the Geometric Transportation Problem）</news:title>
   <news:publication_date>2026-08-09T19:59:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721372</loc>
  <lastmod>2026-08-09T19:58:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ℓ1最小化における唯一の鋭い局所最小点（Unique Sharp Local Minimum in ℓ1-minimization Complete Dictionary Learning）</news:title>
   <news:publication_date>2026-08-09T19:58:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721370</loc>
  <lastmod>2026-08-09T19:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語監督から学ぶセマンティックパーサの学習（Learning to Learn Semantic Parsers from Natural Language Supervision）</news:title>
   <news:publication_date>2026-08-09T19:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721368</loc>
  <lastmod>2026-08-09T19:57:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超臨界流体における普遍性・スケーリング・崩壊（Universality, scaling and collapse in supercritical fluids）</news:title>
   <news:publication_date>2026-08-09T19:57:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721366</loc>
  <lastmod>2026-08-09T19:57:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>揮発性ディープユーテクトリック溶媒からの結晶化（Crystallisation From Volatile Deep Eutectic Solvents）</news:title>
   <news:publication_date>2026-08-09T19:57:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721364</loc>
  <lastmod>2026-08-09T19:06:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非自己回帰翻訳と補助正則化の実用的意義（Non-Autoregressive Machine Translation with Auxiliary Regularization）</news:title>
   <news:publication_date>2026-08-09T19:06:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721362</loc>
  <lastmod>2026-08-09T19:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模版・質問者の心の中にいる回答者による視覚対話質問生成（LARGE-SCALE ANSWERER IN QUESTIONER’S MIND FOR VISUAL DIALOG QUESTION GENERATION）</news:title>
   <news:publication_date>2026-08-09T19:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721360</loc>
  <lastmod>2026-08-09T19:05:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データの因子分離を可能にするFAVAE（FAVAE: Sequence Disentanglement using Information Bottleneck Principle）</news:title>
   <news:publication_date>2026-08-09T19:05:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721358</loc>
  <lastmod>2026-08-09T19:04:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力データ分布に対する敵対的頑健性の感度（On the Sensitivity of Adversarial Robustness to Input Data Distributions）</news:title>
   <news:publication_date>2026-08-09T19:04:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721356</loc>
  <lastmod>2026-08-09T19:04:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ネットワークのリンク予測を変えるE-LSTM-D（E-LSTM-D: A Deep Learning Framework for Dynamic Network Link Prediction）</news:title>
   <news:publication_date>2026-08-09T19:04:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721354</loc>
  <lastmod>2026-08-09T19:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間データに対する深層階層モデルと深層ニューラルモデルの比較（Comparison of Deep Neural Networks and Deep Hierarchical Models for Spatio-Temporal Data）</news:title>
   <news:publication_date>2026-08-09T19:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721352</loc>
  <lastmod>2026-08-09T19:03:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械ネットワークにおける学習された多安定性（Learned multi-stability in mechanical networks）</news:title>
   <news:publication_date>2026-08-09T19:03:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721350</loc>
  <lastmod>2026-08-09T18:12:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書に基づくRobust PCAの一般化とハイパースペクトル画像におけるターゲット局所化（A Dictionary-Based Generalization of Robust PCA with Applications to Target Localization in Hyperspectral Imaging）</news:title>
   <news:publication_date>2026-08-09T18:12:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721348</loc>
  <lastmod>2026-08-09T18:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NIGENS 一般音イベントデータベースの意義（NIGENS general sound events database）</news:title>
   <news:publication_date>2026-08-09T18:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721346</loc>
  <lastmod>2026-08-09T18:03:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的距離尺度学習の効率化と縮約（Reduced-Rank Local Distance Metric Learning for k-NN Classification）</news:title>
   <news:publication_date>2026-08-09T18:03:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721344</loc>
  <lastmod>2026-08-09T18:01:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復一階法による非凸ミンマックス問題の解法（Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods）</news:title>
   <news:publication_date>2026-08-09T18:01:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721342</loc>
  <lastmod>2026-08-09T18:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ再最適化で性能問題を克服する方法（How I Learned to Stop Worrying and Love Re-optimization）</news:title>
   <news:publication_date>2026-08-09T18:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721340</loc>
  <lastmod>2026-08-09T18:01:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一方非凸ミンマックス問題に対するハイブリッドブロック逐次近似（Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications）</news:title>
   <news:publication_date>2026-08-09T18:01:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721338</loc>
  <lastmod>2026-08-09T18:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lingvo: シーケンス・ツー・シーケンス研究のためのモジュラー・フレームワーク（Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling）</news:title>
   <news:publication_date>2026-08-09T18:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721336</loc>
  <lastmod>2026-08-09T17:09:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインサンプルからオフライン母集団の規模を推定する方法（Using an online sample to estimate the size of an offline population）</news:title>
   <news:publication_date>2026-08-09T17:09:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721334</loc>
  <lastmod>2026-08-09T17:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データベース修復による因果的公平性の実現（CAPUCHIN: Causal Database Repair for Algorithmic Fairness）</news:title>
   <news:publication_date>2026-08-09T17:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721332</loc>
  <lastmod>2026-08-09T17:08:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ最適早期停止ポリシーによるブラックボックス最適化の高速化（Bayes Optimal Early Stopping Policies for Black-Box Optimization）</news:title>
   <news:publication_date>2026-08-09T17:08:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721330</loc>
  <lastmod>2026-08-09T17:06:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>即時対応者配置のためのオンライン意思決定パイプライン（An Online Decision-Theoretic Pipeline for Responder Dispatch）</news:title>
   <news:publication_date>2026-08-09T17:06:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721328</loc>
  <lastmod>2026-08-09T17:06:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超伝導宇宙ひもと初期宇宙の21cm信号による制約（Constraints on Superconducting Cosmic Strings from the Global 21-cm Signal before Reionization）</news:title>
   <news:publication_date>2026-08-09T17:06:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721326</loc>
  <lastmod>2026-08-09T17:06:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>An IDEA: Ingestionによるデータ強化フレームワーク（An IDEA: An Ingestion Framework for Data Enrichment in AsterixDB）</news:title>
   <news:publication_date>2026-08-09T17:06:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721324</loc>
  <lastmod>2026-08-09T17:06:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クォークとグルーオンのエンドツーエンド分類（End-to-End Jet Classification of Quarks and Gluons with the CMS Open Data）</news:title>
   <news:publication_date>2026-08-09T17:06:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721322</loc>
  <lastmod>2026-08-09T16:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩行者検出における予測的不均衡（Predictive Inequity in Object Detection）</news:title>
   <news:publication_date>2026-08-09T16:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721320</loc>
  <lastmod>2026-08-09T16:14:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込み解析オペレータ学習と訓練データ依存性（Convolutional Analysis Operator Learning: Dependence on Training Data）</news:title>
   <news:publication_date>2026-08-09T16:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721318</loc>
  <lastmod>2026-08-09T16:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的例の知覚歪みの定量化（Quantifying Perceptual Distortion of Adversarial Examples）</news:title>
   <news:publication_date>2026-08-09T16:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721316</loc>
  <lastmod>2026-08-09T16:12:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースRFI検出を最適化する深層学習（Optimizing Sparse RFI Prediction using Deep Learning）</news:title>
   <news:publication_date>2026-08-09T16:12:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721314</loc>
  <lastmod>2026-08-09T16:12:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を備えた同時刻ヘルス指標（UQ-CHI: An Uncertainty Quantification-Based Contemporaneous Health Index for Degenerative Disease Monitoring）</news:title>
   <news:publication_date>2026-08-09T16:12:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721312</loc>
  <lastmod>2026-08-09T16:12:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在表現を橋渡ししてモダリティを越える（Latent Translation: Crossing Modalities by Bridging Generative Models）</news:title>
   <news:publication_date>2026-08-09T16:12:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721310</loc>
  <lastmod>2026-08-09T16:12:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部CT画像と臨床情報の共同学習による肺がん検出（Lung Cancer Detection using Co-learning from Chest CT Images and Clinical Demographics）</news:title>
   <news:publication_date>2026-08-09T16:12:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721308</loc>
  <lastmod>2026-08-09T15:19:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模バッチSGDに構造化共分散ノイズを加える手法（Large-Batch Stochastic Gradient Descent with Structured Covariance Noise）</news:title>
   <news:publication_date>2026-08-09T15:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721306</loc>
  <lastmod>2026-08-09T15:19:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動物個体再識別のための類似度学習ネットワーク（Similarity Learning Networks for Animal Individual Re-Identification – Beyond the Capabilities of a Human Observer）</news:title>
   <news:publication_date>2026-08-09T15:19:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721304</loc>
  <lastmod>2026-08-09T15:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモデル忘却の克服（Overcoming Multi-model Forgetting）</news:title>
   <news:publication_date>2026-08-09T15:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721302</loc>
  <lastmod>2026-08-09T15:18:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン対数凸分布からのサンプリング（Online Sampling from Log-Concave Distributions）</news:title>
   <news:publication_date>2026-08-09T15:18:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721300</loc>
  <lastmod>2026-08-09T15:18:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚に基づくサブワード音声単位の発見に向けて（TOWARDS VISUALLY GROUNDED SUB-WORD SPEECH UNIT DISCOVERY）</news:title>
   <news:publication_date>2026-08-09T15:18:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721298</loc>
  <lastmod>2026-08-09T15:18:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス認識型トラッカーと動的モデル更新によるオンライン多対象追跡（Online Multi-Object Tracking with Instance-Aware Tracker and Dynamic Model Refreshment）</news:title>
   <news:publication_date>2026-08-09T15:18:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721296</loc>
  <lastmod>2026-08-09T15:18:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ステルス攻撃の学習データ要件（Learning Requirements for Stealth Attacks）</news:title>
   <news:publication_date>2026-08-09T15:18:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>
