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   <news:title>幾何的に安定な特徴を自己教師ありで学ぶ方法（Self-supervised Learning of Geometrically Stable Features Through Probabilistic Introspection）</news:title>
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   <news:title>オンライン多ラベル分類：ラベル圧縮手法（Online Multi-Label Classification: A Label Compression Method）</news:title>
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   <news:title>匿名通信の容量（The Capacity of Anonymous Communications）</news:title>
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   <news:title>大量のマルチモーダル医療データから学習した臨床概念埋め込み（Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data）</news:title>
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   <news:title>RR Lyraeの近赤外（near-IR）光度曲線に基づく形状解析と金属量推定（A DATA-DRIVEN STUDY OF RR LYRAE NEAR-IR LIGHT CURVES）</news:title>
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   <news:title>赤外線で明らかにする銀河の原始記録（A NEAR-INFRARED RR LYRAE CENSUS ALONG THE SOUTHERN GALACTIC PLANE）</news:title>
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   <news:title>非独立同分布データにおけるガウス過程サブセットスキャニングによる異常パターン検出（Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>生の感覚入力から視覚対象と音声語を同時発見する研究（Jointly Discovering Visual Objects and Spoken Words from Raw Sensory Input）</news:title>
   <news:publication_date>2026-04-23T05:40:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:title>レイアウト誘導型動画表現によるエージェント・イン・プレイス行動認識（Layout-induced Video Representation for Recognizing Agent-in-Place Actions）</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>複数粒度で識別特徴を学習する手法（Learning Discriminative Features with Multiple Granularities for Person Re-Identification）</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>X-ARAPUCAによる液体アルゴン光検出の改良（The X-ARAPUCA: An improvement of the ARAPUCA device）</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>Iltis：論理学教育のための対話型Webシステム（Introduction to Iltis: An Interactive, Web-Based System for Teaching Logic）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-23T04:48:51Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>大規模手描きスケッチ検索を実現するDeep Hashingの実践（SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-23T04:48:36Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>細粒度動画魅力度予測（Fine-grained Video Attractiveness Prediction Using Multimodal Deep Learning on a Large Real-world Dataset）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>小規模データベースにおける手書き文字認識の強化（Boosting Handwriting Text Recognition in Small Databases with Transfer Learning）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>連続時間マルコフ連鎖の遷移率行列推定における不確かさの扱い（An Imprecise Probabilistic Estimator for the Transition Rate Matrix of a Continuous-Time Markov Chain）</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>生成的視覚的根拠（Generative Visual Rationales: GVR）によるモデル解釈の革新（Generative Visual Rationales）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-23T03:57:06Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>弱教師ありCNNセグメンテーションにおけるNormalized Cut損失（Normalized Cut Loss for Weakly-supervised CNN Segmentation）</news:title>
   <news:publication_date>2026-04-23T03:57:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-23T03:56:03Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Btrfly Net による脊椎椎体ラベリングの実用化可能性（Btrfly Net: Vertebrae Labelling with Energy-based Adversarial Learning of Local Spine Prior）</news:title>
   <news:publication_date>2026-04-23T03:56:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-23T03:55:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ハイブリッド・ブロック浮動小数点によるDNN訓練（Training DNNs with Hybrid Block Floating Point）</news:title>
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   <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>多段階・多目的ニューラルネットワークによる空撮画像の解釈と位置推定（A Multi-Stage Multi-Task Neural Network for Aerial Scene Interpretation and Geolocalization）</news:title>
   <news:publication_date>2026-04-23T03:55:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-23T03:55:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>イベントカメラと深層学習によるハンドル操作予測（Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Cars）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-23T03:03:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>効率的なCNN設計による手書き漢字認識の実務的意義（Building Efficient CNN Architecture for Offline Handwritten Chinese Character Recognition）</news:title>
   <news:publication_date>2026-04-23T03:03:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/682422</loc>
  <lastmod>2026-04-23T03:03:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NegPSpanによる負の逐次パターン抽出の効率化（NegPSpan: efficient extraction of negative sequential patterns with embedding constraints）</news:title>
   <news:publication_date>2026-04-23T03:03:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/682420</loc>
  <lastmod>2026-04-23T03:02:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在ダイナミクスモデルによる情報最大化探索（Information Maximizing Exploration with a Latent Dynamics Model）</news:title>
   <news:publication_date>2026-04-23T03:02:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/682418</loc>
  <lastmod>2026-04-23T03:02:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>判別的クロスビュー二値表現学習（Discriminative Cross-View Binary Representation Learning）</news:title>
   <news:publication_date>2026-04-23T03:02:34Z</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>自己教師あり敵対的ハッシングネットワークによるクロスモーダル検索（Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval）</news:title>
   <news:publication_date>2026-04-23T03:02:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-04-23T03:02:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>高次元PCAの問い合わせ下界：有限サンプル変形ウィグナー則からの示唆（Tight Query Complexity Lower Bounds for PCA via Finite Sample Deformed Wigner Law）</news:title>
   <news:publication_date>2026-04-23T03:02:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/682412</loc>
  <lastmod>2026-04-23T03:01:52Z</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>2026-04-23T03:01:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682410</loc>
  <lastmod>2026-04-23T02:10:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者の再入院予測 — 階層的スパース正則化による解釈可能なモデル（Hospital Readmission Prediction - Applying Hierarchical Sparsity Norms for Interpretable Models）</news:title>
   <news:publication_date>2026-04-23T02:10:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682408</loc>
  <lastmod>2026-04-23T02:03:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病院事例コスト予測モデルの評価とAzure Machine Learning Studioによる迅速評価ツールの示唆（Evaluating Hospital Case Cost Prediction Models Using Azure Machine Learning Studio）</news:title>
   <news:publication_date>2026-04-23T02:03:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682406</loc>
  <lastmod>2026-04-23T02:02:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セグメンテーションを意識した深層融合ネットワークによる圧縮センシングMRI（A Segmentation-aware Deep Fusion Network for Compressed Sensing MRI）</news:title>
   <news:publication_date>2026-04-23T02:02:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682404</loc>
  <lastmod>2026-04-23T02:02:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的収縮解析による反復ランダム作用素の解析（Probabilistic Contraction Analysis of Iterated Random Operators）</news:title>
   <news:publication_date>2026-04-23T02:02:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682402</loc>
  <lastmod>2026-04-23T02:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>配電系統停電持続時間のリアルタイム予測（Real-Time Prediction of the Duration of Distribution System Outages）</news:title>
   <news:publication_date>2026-04-23T02:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682400</loc>
  <lastmod>2026-04-23T02:00:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルに導かれる演繹探索によるリアルタイムプログラム合成（Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples）</news:title>
   <news:publication_date>2026-04-23T02:00:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682398</loc>
  <lastmod>2026-04-23T02:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速連続運動のための手指キーポイント検出（Towards Deep Learning based Hand Keypoints Detection for Rapid Sequential Movements from RGB Images）</news:title>
   <news:publication_date>2026-04-23T02:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682396</loc>
  <lastmod>2026-04-23T01:08:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Crystal Lossと品質重み付けによる顔認証の改善（Crystal Loss, Quality Pooling and Quality Attenuation）</news:title>
   <news:publication_date>2026-04-23T01:08:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682394</loc>
  <lastmod>2026-04-23T01:08:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツイッターにおける言語パターンと社会経済的要因の相関（Socioeconomic Dependencies of Linguistic Patterns in Twitter: A Multivariate Analysis）</news:title>
   <news:publication_date>2026-04-23T01:08:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682392</loc>
  <lastmod>2026-04-23T01:07:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子間力への直接・局所ディープニューラルネットワークの温度・サイズ移植性（Size and Temperature Transferability of Direct and Local Deep Neural Networks for Atomic Forces）</news:title>
   <news:publication_date>2026-04-23T01:07:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682390</loc>
  <lastmod>2026-04-23T01:06:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D人間姿勢推定のための教師なしジオメトリ認識表現（Unsupervised Geometry-Aware Representation for 3D Human Pose Estimation）</news:title>
   <news:publication_date>2026-04-23T01:06:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682388</loc>
  <lastmod>2026-04-23T01:06:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル広告における誤クリック検出と課金の滑らかな調整（Data-Driven Identification of Accidental Clicks on Mobile Ads with Applications to Advertiser Cost Discounting and Click-Through Rate Prediction）</news:title>
   <news:publication_date>2026-04-23T01:06:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682386</loc>
  <lastmod>2026-04-23T01:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽ジャンル分類の機械学習的アプローチ（Music Genre Classification using Machine Learning Techniques）</news:title>
   <news:publication_date>2026-04-23T01:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682384</loc>
  <lastmod>2026-04-23T01:05:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Renewal Monte Carloによる強化学習の革新（Renewal Monte Carlo: Renewal theory based reinforcement learning）</news:title>
   <news:publication_date>2026-04-23T01:05:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682382</loc>
  <lastmod>2026-04-23T00:14:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Compton厚い活動銀河核におけるIwasawa-Taniguchi効果の示唆（An Iwasawa-Taniguchi Effect for Compton-thick AGN）</news:title>
   <news:publication_date>2026-04-23T00:14:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682380</loc>
  <lastmod>2026-04-23T00:14:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典的検証による量子計算の検証（Classical Verification of Quantum Computations）</news:title>
   <news:publication_date>2026-04-23T00:14:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682378</loc>
  <lastmod>2026-04-23T00:13:48Z</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>2026-04-23T00:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682376</loc>
  <lastmod>2026-04-23T00:12:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いたRANS乱流モデルの新枠組み（Reynolds-Averaged Turbulence Modeling Using Type I and Type II Machine Learning Frameworks with Deep Learning）</news:title>
   <news:publication_date>2026-04-23T00:12:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682374</loc>
  <lastmod>2026-04-23T00:12:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DOCKによる常識知識の転移で実務に効く物体検出（Detecting Objects by transferring Common-sense Knowledge）</news:title>
   <news:publication_date>2026-04-23T00:12:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682372</loc>
  <lastmod>2026-04-23T00:12:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン環境での確率的勾配法によるPCA平均性能解析（Average performance analysis of the stochastic gradient method for online PCA）</news:title>
   <news:publication_date>2026-04-23T00:12:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682370</loc>
  <lastmod>2026-04-23T00:11:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化残差を考慮したVAEの学習（Training VAEs Under Structured Residuals）</news:title>
   <news:publication_date>2026-04-23T00:11:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682368</loc>
  <lastmod>2026-04-22T23:20:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチリンガルな自動タイトル生成でECの表示を変える（Multi-lingual neural title generation for e-Commerce browse pages）</news:title>
   <news:publication_date>2026-04-22T23:20:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682366</loc>
  <lastmod>2026-04-22T23:18:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フラクタル次元の簡易計算法（A simple and didactic method to calculate the fractal dimension - an interdisciplinary tool）</news:title>
   <news:publication_date>2026-04-22T23:18:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682364</loc>
  <lastmod>2026-04-22T23:18:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラグランジアン系の高精度追従を保証する学習ベースの頑健制御（Provably Robust Learning-Based Approach for High-Accuracy Tracking Control of Lagrangian Systems）</news:title>
   <news:publication_date>2026-04-22T23:18:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682362</loc>
  <lastmod>2026-04-22T23:18:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HERAにおけるチャームとビューティー（ボトム）生成断面積の結合とQCD解析（Combination and QCD analysis of charm and beauty production cross-section measurements in deep inelastic ep scattering at HERA）</news:title>
   <news:publication_date>2026-04-22T23:18:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682360</loc>
  <lastmod>2026-04-22T23:18:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布的線形化可能なデータ構造（Distributionally Linearizable Data Structures）</news:title>
   <news:publication_date>2026-04-22T23:18:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682358</loc>
  <lastmod>2026-04-22T23:17:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い光学トラップにおける分子のスタークシフト補償のための楕円偏光（Elliptical polarization for molecular Stark shift compensation in deep optical traps）</news:title>
   <news:publication_date>2026-04-22T23:17:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682356</loc>
  <lastmod>2026-04-22T23:17:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絡み合いを引き寄せることでパリティゲームを解く（Attracting Tangles to Solve Parity Games）</news:title>
   <news:publication_date>2026-04-22T23:17:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682354</loc>
  <lastmod>2026-04-22T22:26:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム自己適応システムの保証強化のための学習手法（A Learning Approach to Enhance Assurances for Real-Time Self-Adaptive Systems）</news:title>
   <news:publication_date>2026-04-22T22:26:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682352</loc>
  <lastmod>2026-04-22T22:26:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フーリエ特徴を用いた大規模Cox過程推論（Large-Scale Cox Process Inference using Variational Fourier Features）</news:title>
   <news:publication_date>2026-04-22T22:26:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682350</loc>
  <lastmod>2026-04-22T22:25:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定数ステップ確率的Douglas–Rachfordアルゴリズムと非可分正則化への応用（A CONSTANT STEP STOCHASTIC DOUGLAS-RACHFORD ALGORITHM WITH APPLICATION TO NON SEPARABLE REGULARIZATIONS）</news:title>
   <news:publication_date>2026-04-22T22:25:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682348</loc>
  <lastmod>2026-04-22T22:25:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>360度スタンス検出の実用化可能性（360° Stance Detection）</news:title>
   <news:publication_date>2026-04-22T22:25:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682346</loc>
  <lastmod>2026-04-22T22:25:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成ネットワークに学ぶデザイン創出（Design Inspiration from Generative Networks）</news:title>
   <news:publication_date>2026-04-22T22:25:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682344</loc>
  <lastmod>2026-04-22T22:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関のある離散データを敵対的学習で生成する手法（Correlated discrete data generation using adversarial training）</news:title>
   <news:publication_date>2026-04-22T22:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682342</loc>
  <lastmod>2026-04-22T21:33:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MFCCからの音声波形合成を実現するGAN活用法（Speech Waveform Synthesis from MFCC Sequences with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-22T21:33:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682340</loc>
  <lastmod>2026-04-22T21:33:40Z</lastmod>
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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: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: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:publication_date>2026-04-22T21:32:03Z</news:publication_date>
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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: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:publication_date>2026-04-22T20:39:01Z</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:publication_date>2026-04-22T20:38:05Z</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>
 <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>2026-04-22T20:37:39Z</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>
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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: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: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>
    <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>
  </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>
  <loc>https://aibr.jp/archives/682294</loc>
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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>2026-04-22T18:51:03Z</news:publication_date>
   <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:publication_date>2026-04-22T18:50:47Z</news:publication_date>
   <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>
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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>2026-04-22T17:59:24Z</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>
   </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>
   </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>
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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: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>
  </news:news>
 </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>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSignsによる深層学習モデルの権利保護（DeepSigns: A Generic Watermarking Framework for Protecting the Ownership of Deep Learning Models）</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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   <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>2026-04-22T16:13:15Z</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>
   </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:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterのハッシュタグを用いたイベント検出手法（An Event Detection Approach Based On Twitter Hashtags）</news:title>
   <news:publication_date>2026-04-22T16:11:41Z</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>
   </news:publication>
   <news:title>単一の視野検査から未来の視野を予測する深層学習（Forecasting Future Humphrey Visual Fields Using Deep Learning）</news:title>
   <news:publication_date>2026-04-22T16:11:06Z</news:publication_date>
   <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:publication_date>2026-04-22T15:20:08Z</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:title>まばらな時空間データのグラフベース深層モデルとリアルタイム予測（Graph-Based Deep Modeling and Real Time Forecasting of Sparse Spatio-Temporal Data）</news:title>
   <news:publication_date>2026-04-22T15:19:37Z</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:publication_date>2026-04-22T15:19:06Z</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>
   </news:publication>
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   <news:publication_date>2026-04-22T15:18:51Z</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>
   </news:publication>
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   <news:publication_date>2026-04-22T15:18:35Z</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>
   </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>
   <news:title>敵対的教師-生徒学習による教師なしドメイン適応（Adversarial Teacher-Student Learning for Unsupervised Domain Adaptation）</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:publication_date>2026-04-22T14:26:46Z</news:publication_date>
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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: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>
  </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>
   </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>
  </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:publication_date>2026-04-22T13:24:10Z</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>
   </news:publication>
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   <news:publication_date>2026-04-22T13:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-22T13:23:07Z</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>2026-04-22T13:23:07Z</news:publication_date>
   <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:publication_date>2026-04-22T13:22:30Z</news:publication_date>
   <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:publication_date>2026-04-22T13:22:13Z</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>
  </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:publication_date>2026-04-22T12:30:09Z</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>
   </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>
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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: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>
  <loc>https://aibr.jp/archives/682194</loc>
  <lastmod>2026-04-22T11:34:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報的不正取引の価値（THE VALUE OF INFORMATIONAL ARBITRAGE）</news:title>
   <news:publication_date>2026-04-22T11:34:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682192</loc>
  <lastmod>2026-04-22T11:34:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イオン結晶の赤外線スペクトルと統計力学との関連（Classical infrared spectra of ionic crystals and their relevance for statistical mechanics）</news:title>
   <news:publication_date>2026-04-22T11:34:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682190</loc>
  <lastmod>2026-04-22T11:33:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>mQAPVizによる大規模データ可視化の革新（mQAPViz: A divide-and-conquer multi-objective optimization algorithm to compute large data visualizations）</news:title>
   <news:publication_date>2026-04-22T11:33:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682188</loc>
  <lastmod>2026-04-22T11:33:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>加速MRIのための深層残差学習（Deep Residual Learning for Accelerated MRI using Magnitude and Phase Networks）</news:title>
   <news:publication_date>2026-04-22T11:33:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682186</loc>
  <lastmod>2026-04-22T11:33:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケールに強い物体検出で何が変わるか（SINet: A Scale-insensitive Convolutional Neural Network for Fast Vehicle Detection）</news:title>
   <news:publication_date>2026-04-22T11:33:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682184</loc>
  <lastmod>2026-04-22T11:32:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境を探索して学習する視覚的顕著性の獲得（Exploring to learn visual saliency: The RL-IAC approach）</news:title>
   <news:publication_date>2026-04-22T11:32:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682182</loc>
  <lastmod>2026-04-22T11:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた車両検出の実務的意義（A Vehicle Detection Approach using Deep Learning Methodologies）</news:title>
   <news:publication_date>2026-04-22T11:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682180</loc>
  <lastmod>2026-04-22T10:41:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SyncGANによるクロスモーダル生成の同期化（SyncGAN: Synchronize the Latent Space of Cross-modal Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-22T10:41:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682178</loc>
  <lastmod>2026-04-22T10:33:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール位置認識カーネル表現による物体検出（Multi-scale Location-aware Kernel Representation for Object Detection）</news:title>
   <news:publication_date>2026-04-22T10:33:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682176</loc>
  <lastmod>2026-04-22T10:32:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非並列データを用いた高品質な音声変換（HIGH-QUALITY NONPARALLEL VOICE CONVERSION BASED ON CYCLE-CONSISTENT ADVERSARIAL NETWORK）</news:title>
   <news:publication_date>2026-04-22T10:32:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682174</loc>
  <lastmod>2026-04-22T10:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学生の学習技能をファジィ関係方程式で評価する手法（A STUDY OF STUDENT LEARNING SKILLS USING FUZZY RELATION EQUATIONS）</news:title>
   <news:publication_date>2026-04-22T10:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682172</loc>
  <lastmod>2026-04-22T10:31:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KaldiのPLDA実装に関するメモ（A Note on Kaldi’s PLDA Implementation）</news:title>
   <news:publication_date>2026-04-22T10:31:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682170</loc>
  <lastmod>2026-04-22T10:31:09Z</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Gaussian ICAの再発見（Sparse Gaussian ICA）</news:title>
   <news:publication_date>2026-04-22T10:31:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682168</loc>
  <lastmod>2026-04-22T10:30:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画理解のためのエンドツーエンド運動表現学習（End-to-End Learning of Motion Representation for Video Understanding）</news:title>
   <news:publication_date>2026-04-22T10:30:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682166</loc>
  <lastmod>2026-04-22T09:39:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>好中球の生成的時空間モデリング（Generative Spatiotemporal Modeling Of Neutrophil Behavior）</news:title>
   <news:publication_date>2026-04-22T09:39:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682164</loc>
  <lastmod>2026-04-22T09:38:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データベース用エンドツーエンドニューラル自然言語インターフェース（DBPal: An End-to-end Neural Natural Language Interface for Databases）</news:title>
   <news:publication_date>2026-04-22T09:38:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682162</loc>
  <lastmod>2026-04-22T09:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2Dと3Dの橋渡しをする軽量3D融合ネットワーク（Bridging the Gap Between 2D and 3D Organ Segmentation with Volumetric Fusion Net）</news:title>
   <news:publication_date>2026-04-22T09:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682160</loc>
  <lastmod>2026-04-22T09:36:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を用いたアンサンブルによる深層距離学習の改良（Attention-based Ensemble for Deep Metric Learning）</news:title>
   <news:publication_date>2026-04-22T09:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682158</loc>
  <lastmod>2026-04-22T09:36:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習可能な辞書符号化層によるエンドツーエンド音声言語識別（A NOVEL LEARNABLE DICTIONARY ENCODING LAYER FOR END-TO-END LANGUAGE IDENTIFICATION）</news:title>
   <news:publication_date>2026-04-22T09:36:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682156</loc>
  <lastmod>2026-04-22T09:36:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>終端学習が言語識別を変える――話者属性の「発話単位表現」へ挑む（INSIGHTS INTO END-TO-END LEARNING SCHEME FOR LANGUAGE IDENTIFICATION）</news:title>
   <news:publication_date>2026-04-22T09:36:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682154</loc>
  <lastmod>2026-04-22T09:36:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インフラ施設の防護投資の最適化（Securing Infrastructure Facilities: When does proactive defense help?）</news:title>
   <news:publication_date>2026-04-22T09:36:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682152</loc>
  <lastmod>2026-04-22T08:42:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物検索のための検出と再識別を統合したエンドツーエンドネットワーク（End-to-End Detection and Re-identification Integrated Net for Person Search）</news:title>
   <news:publication_date>2026-04-22T08:42:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682150</loc>
  <lastmod>2026-04-22T08:42:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運動学的筋骨格環境に適応させた強化学習の実践（Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments）</news:title>
   <news:publication_date>2026-04-22T08:42:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682148</loc>
  <lastmod>2026-04-22T08:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リコールトレース：バックトラッキングモデルによる効率的強化学習（RECALL TRACES: BACKTRACKING MODELS FOR EFFICIENT REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-04-22T08:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682146</loc>
  <lastmod>2026-04-22T08:41:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変数射影によるスパース主成分分析（Sparse Principal Component Analysis via Variable Projection）</news:title>
   <news:publication_date>2026-04-22T08:41:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682144</loc>
  <lastmod>2026-04-22T08:41:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的学習に基づく頑健なデータ融合（Social learning for resilient data fusion against data falsification attacks）</news:title>
   <news:publication_date>2026-04-22T08:41:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682142</loc>
  <lastmod>2026-04-22T08:41:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い指導情報を取り込む回帰の確率的枠組み（Probabilistic Formulations of Regression with Mixed Guidance）</news:title>
   <news:publication_date>2026-04-22T08:41:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682140</loc>
  <lastmod>2026-04-22T08:41:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし相関解析（Unsupervised Correlation Analysis）</news:title>
   <news:publication_date>2026-04-22T08:41:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682138</loc>
  <lastmod>2026-04-22T07:49:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高移動環境における車載ネットワークと機械学習の枠組み（Towards Intelligent Vehicular Networks: A Machine Learning Framework）</news:title>
   <news:publication_date>2026-04-22T07:49:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682136</loc>
  <lastmod>2026-04-22T07:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ構造化フィードバック下のオンライン学習と適応的敵対者への対策（Online learning with graph-structured feedback against adaptive adversaries）</news:title>
   <news:publication_date>2026-04-22T07:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682134</loc>
  <lastmod>2026-04-22T07:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代用教師ネットワークの考え方と示唆（Substitute Teacher Networks: Learning with Almost No Supervision）</news:title>
   <news:publication_date>2026-04-22T07:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682132</loc>
  <lastmod>2026-04-22T07:49:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全に教師なしで音素を認識する手法の要点（Completely Unsupervised Phoneme Recognition by Adversarially Learning Mapping Relationships from Audio Embeddings）</news:title>
   <news:publication_date>2026-04-22T07:49:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682130</loc>
  <lastmod>2026-04-22T07:48:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習データを狙う攻撃と防御――線形回帰に対する汚染（Poisoning）攻撃の体系的研究（Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning）</news:title>
   <news:publication_date>2026-04-22T07:48:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682128</loc>
  <lastmod>2026-04-22T07:48:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話型音声コンテンツ検索の共同学習と学習可能ユーザシミュレータ（Joint Learning of Interactive Spoken Content Retrieval and Trainable User Simulator）</news:title>
   <news:publication_date>2026-04-22T07:48:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682126</loc>
  <lastmod>2026-04-22T07:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Aggregated Momentumによる最適化の安定化（AGGREGATED MOMENTUM: STABILITY THROUGH PASSIVE DAMPING）</news:title>
   <news:publication_date>2026-04-22T07:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682124</loc>
  <lastmod>2026-04-22T06:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SGNSの再考：二乗正則化によるスキップグラム負例学習の改良（Revisiting Skip-Gram Negative Sampling Model With Rectification）</news:title>
   <news:publication_date>2026-04-22T06:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682122</loc>
  <lastmod>2026-04-22T06:57:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頑健な果実計数（Robust Fruit Counting: Combining Deep Learning, Tracking, and Structure from Motion）</news:title>
   <news:publication_date>2026-04-22T06:57:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682120</loc>
  <lastmod>2026-04-22T06:57:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>術後CTAにおける腹部大動脈血栓の完全自動検出と分割（Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using deep convolutional neural networks）</news:title>
   <news:publication_date>2026-04-22T06:57:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/682118</loc>
  <lastmod>2026-04-22T06:57:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EarthMapper: リモートセンシング画像の意味的セグメンテーションを手軽にするツールボックス（EarthMapper: A Tool Box for the Semantic Segmentation of Remote Sensing Imagery）</news:title>
   <news:publication_date>2026-04-22T06:57:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/682116</loc>
  <lastmod>2026-04-22T06:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の注意型マルチラベル学習（Attentional Multilabel Learning over Graphs: A Message Passing Approach）</news:title>
   <news:publication_date>2026-04-22T06:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682114</loc>
  <lastmod>2026-04-22T06:56:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短発話のスピーカ認証を改善するi-vector変換（I-vector Transformation Using Conditional Generative Adversarial Networks for Short Utterance Speaker Verification）</news:title>
   <news:publication_date>2026-04-22T06:56:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682112</loc>
  <lastmod>2026-04-22T06:56:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>商品タイトル品質評価に対する深層＋浅層アンサンブル（CIKM AnalytiCup 2017 – Lazada Product Title Quality Challenge: An Ensemble of Deep and Shallow Learning to predict the Quality of Product Titles）</news:title>
   <news:publication_date>2026-04-22T06:56:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682110</loc>
  <lastmod>2026-04-22T06:05:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リモートセンシングにおける圧縮アーティファクト除去のOne‑Two‑Oneネットワーク（One‑Two‑One Networks for Compression Artifacts Reduction in Remote Sensing）</news:title>
   <news:publication_date>2026-04-22T06:05:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682108</loc>
  <lastmod>2026-04-22T06:04:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SampleAheadによる合成データ学習の実践（SampleAhead: Online Classifier-Sampler Communication for Learning from Synthesized Data）</news:title>
   <news:publication_date>2026-04-22T06:04:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682106</loc>
  <lastmod>2026-04-22T06:04:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スムーズな入力準備が拓く量子機械学習の現場応用（Smooth input preparation for quantum and quantum-inspired machine learning）</news:title>
   <news:publication_date>2026-04-22T06:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682104</loc>
  <lastmod>2026-04-22T06:02:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ対応の転送による人物再識別（Graph Correspondence Transfer for Person Re-identification）</news:title>
   <news:publication_date>2026-04-22T06:02:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682102</loc>
  <lastmod>2026-04-22T06:02:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造転送機械の理論と応用 (The Structure Transfer Machine Theory and Applications)</news:title>
   <news:publication_date>2026-04-22T06:02:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682100</loc>
  <lastmod>2026-04-22T06:02:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲーム行動における個人差のモデル化（Modeling Individual Differences in Game Behavior using HMM）</news:title>
   <news:publication_date>2026-04-22T06:02:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682098</loc>
  <lastmod>2026-04-22T06:01:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Transformerモデルの学習ノウハウ（Training Tips for the Transformer Model）</news:title>
   <news:publication_date>2026-04-22T06:01:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682096</loc>
  <lastmod>2026-04-22T05:10:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メカニズム型ネットワークモデルの柔軟なモデル選択（Flexible model selection for mechanistic network models）</news:title>
   <news:publication_date>2026-04-22T05:10:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682094</loc>
  <lastmod>2026-04-22T05:09:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VRにおける多感覚手がかりが市民科学者のパターン認識を鍛えるか（Can Multisensory Cues in VR Help Train Pattern Recognition to Citizen Scientists?）</news:title>
   <news:publication_date>2026-04-22T05:09:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682092</loc>
  <lastmod>2026-04-22T05:09:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歴史文書に含まれる手書き注記の検出と評価（Recognizing Challenging Handwritten Annotations with Fully Convolutional Networks）</news:title>
   <news:publication_date>2026-04-22T05:09:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682090</loc>
  <lastmod>2026-04-22T05:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純化された0ビット一貫重み付きサンプリングの工学（Engineering a Simplified 0-Bit Consistent Weighted Sampling）</news:title>
   <news:publication_date>2026-04-22T05:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682088</loc>
  <lastmod>2026-04-22T05:07:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ある種の関数最適化問題に関するいくつかの結果（Some results on a class of functional optimization problems）</news:title>
   <news:publication_date>2026-04-22T05:07:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682086</loc>
  <lastmod>2026-04-22T05:07:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模マルチタスク学習による汎用文分散表現学習（LEARNING GENERAL PURPOSE DISTRIBUTED SENTENCE REPRESENTATIONS VIA LARGE SCALE MULTI-TASK LEARNING）</news:title>
   <news:publication_date>2026-04-22T05:07:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682084</loc>
  <lastmod>2026-04-22T05:06:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Generative Modelsによる歯科補綴設計の自動化（Learning Beyond Human Expertise with Generative Models for Dental Restorations）</news:title>
   <news:publication_date>2026-04-22T05:06:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682082</loc>
  <lastmod>2026-04-22T04:15:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚に基づくロボットタスク計画（Visual Robot Task Planning）</news:title>
   <news:publication_date>2026-04-22T04:15:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682080</loc>
  <lastmod>2026-04-22T04:14:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分クラス選択による転移学習の最適化（Class Subset Selection for Transfer Learning using Submodularity）</news:title>
   <news:publication_date>2026-04-22T04:14:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682078</loc>
  <lastmod>2026-04-22T04:14:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論で理解するオートエンコーダ（Understanding Autoencoders with Information Theoretic Concepts）</news:title>
   <news:publication_date>2026-04-22T04:14:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682076</loc>
  <lastmod>2026-04-22T04:13:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的転移畳み込みニューラルネットワーク（Hierarchical Transfer Convolutional Neural Networks for Image Classification）</news:title>
   <news:publication_date>2026-04-22T04:13:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682074</loc>
  <lastmod>2026-04-22T04:13:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きエンドツーエンド音声変換（Conditional End-to-End Audio Transforms）</news:title>
   <news:publication_date>2026-04-22T04:13:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682072</loc>
  <lastmod>2026-04-22T04:12:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム多指ハンドの把持計画：フィンガースプリッティング法 (Real-Time Grasp Planning for Multi-Fingered Hands by Finger Splitting)</news:title>
   <news:publication_date>2026-04-22T04:12:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682070</loc>
  <lastmod>2026-04-22T04:12:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再電離期における紫外金属線の分光制約（Spectroscopic Constraints on UV Metal Line Emission at z ≃6−9: The Nature of Lyα Emitting Galaxies in the Reionization-Era）</news:title>
   <news:publication_date>2026-04-22T04:12:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682068</loc>
  <lastmod>2026-04-22T03:20:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド音声処理の実用プラットフォームの要点（ESPnet: End-to-End Speech Processing Toolkit）</news:title>
   <news:publication_date>2026-04-22T03:20:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682066</loc>
  <lastmod>2026-04-22T03:20:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化されたヒッグス臨界性（Self-Organized Higgs Criticality）</news:title>
   <news:publication_date>2026-04-22T03:20:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682064</loc>
  <lastmod>2026-04-22T03:19:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRベースの電気特性トモグラフィに深層学習を開く（Opening a new window on MR-based Electrical Properties Tomography with deep learning）</news:title>
   <news:publication_date>2026-04-22T03:19:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682062</loc>
  <lastmod>2026-04-22T03:19:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ブロックモデルの固有値が示すもの（THE EIGENVALUES OF STOCHASTIC BLOCKMODEL GRAPHS）</news:title>
   <news:publication_date>2026-04-22T03:19:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682060</loc>
  <lastmod>2026-04-22T03:18:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔匿名化によるプライバシー保護付き行動検出の学習（Learning to Anonymize Faces for Privacy Preserving Action Detection）</news:title>
   <news:publication_date>2026-04-22T03:18:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682058</loc>
  <lastmod>2026-04-22T03:18:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>上向きANITA事象とCPT対称宇宙（Upgoing ANITA events as evidence of the CPT symmetric universe）</news:title>
   <news:publication_date>2026-04-22T03:18:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682056</loc>
  <lastmod>2026-04-22T03:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全データにおけるマルチモーダル疾患分類の幾何行列補完（Multi-modal Disease Classification in Incomplete Datasets Using Geometric Matrix Completion）</news:title>
   <news:publication_date>2026-04-22T03:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682054</loc>
  <lastmod>2026-04-22T02:26:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言葉でCNNを導く――対話による視覚モデルの性能改善（Guide Me: Interacting with Deep Networks）</news:title>
   <news:publication_date>2026-04-22T02:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682052</loc>
  <lastmod>2026-04-22T02:26:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルネットワークを用いた量子機械学習の展望（Towards Quantum Machine Learning with Tensor Networks）</news:title>
   <news:publication_date>2026-04-22T02:26:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682050</loc>
  <lastmod>2026-04-22T02:26:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群データに対するパラメータ化畳み込みフィルタ（SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters）</news:title>
   <news:publication_date>2026-04-22T02:26:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682048</loc>
  <lastmod>2026-04-22T02:25:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野外物体の3D姿勢推定と3Dモデル取得（3D Pose Estimation and 3D Model Retrieval for Objects in the Wild）</news:title>
   <news:publication_date>2026-04-22T02:25:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682046</loc>
  <lastmod>2026-04-22T02:24:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル音声表現の再利用による聴覚感情認識（Reusing Neural Speech Representations for Auditory Emotion Recognition）</news:title>
   <news:publication_date>2026-04-22T02:24:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682044</loc>
  <lastmod>2026-04-22T02:24:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QMIX: 中央集権的学習で分散実行を可能にした価値関数分解（QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-22T02:24:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682042</loc>
  <lastmod>2026-04-22T02:24:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン教師あり学習と特徴選択の新しい枠組み（A Novel Framework for Online Supervised Learning with Feature Selection）</news:title>
   <news:publication_date>2026-04-22T02:24:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682040</loc>
  <lastmod>2026-04-22T01:32:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測器ベースの適応最適出力包含制御（Observer-based Adaptive Optimal Output Containment Control problem of Linear Heterogeneous Multi-agent Systems with Relative Output Measurements）</news:title>
   <news:publication_date>2026-04-22T01:32:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682038</loc>
  <lastmod>2026-04-22T01:23:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二乗型フーリエ関数解析における最小最大推定（Minimax Estimation of Quadratic Fourier Functionals）</news:title>
   <news:publication_date>2026-04-22T01:23:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682036</loc>
  <lastmod>2026-04-22T01:23:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模化するロゴ検出のための自動学習手法（Scalable Deep Learning Logo Detection）</news:title>
   <news:publication_date>2026-04-22T01:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682034</loc>
  <lastmod>2026-04-22T01:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット把持検出のための大規模合成データセットの意義（Jacquard: A Large Scale Dataset for Robotic Grasp Detection）</news:title>
   <news:publication_date>2026-04-22T01:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682032</loc>
  <lastmod>2026-04-22T01:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分割ポテンシャル箱におけるPT対称と反対称の非線形状態（PT-symmetric and antisymmetric nonlinear states in a split potential box）</news:title>
   <news:publication_date>2026-04-22T01:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682030</loc>
  <lastmod>2026-04-22T01:22:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>K-NNとDNNにおけるラベルノイズの耐性（Label Noise in K-NN and DNN）</news:title>
   <news:publication_date>2026-04-22T01:22:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682028</loc>
  <lastmod>2026-04-22T01:22:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小サンプル学習のためのCNNフィルタの構造と強さの学習（Learning Structure and Strength of CNN Filters for Small Sample Size Training）</news:title>
   <news:publication_date>2026-04-22T01:22:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682026</loc>
  <lastmod>2026-04-22T00:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスモーダル深層変分手位姿推定（Cross-modal Deep Variational Hand Pose Estimation）</news:title>
   <news:publication_date>2026-04-22T00:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682024</loc>
  <lastmod>2026-04-22T00:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コントラスト志向の深層ニューラルネットワークによる顕在物体検出（Contrast-Oriented Deep Neural Networks for Salient Object Detection）</news:title>
   <news:publication_date>2026-04-22T00:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682022</loc>
  <lastmod>2026-04-22T00:30:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非局所相似性とモデル導関数領域適応スパース正則化を用いたフルウェーブフォーム反転（Full waveform inversion with nonlocal similarity and model-derivative domain adaptive sparsity-promoting regularization）</news:title>
   <news:publication_date>2026-04-22T00:30:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682020</loc>
  <lastmod>2026-04-22T00:29:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によって分類器を生成する手法（Learning to generate classifiers）</news:title>
   <news:publication_date>2026-04-22T00:29:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682018</loc>
  <lastmod>2026-04-22T00:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列グリッドプーリングによるデータ拡張（Parallel Grid Pooling for Data Augmentation）</news:title>
   <news:publication_date>2026-04-22T00:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682016</loc>
  <lastmod>2026-04-22T00:29:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D顔形状における特徴の分離による同時再構成と認識（Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition）</news:title>
   <news:publication_date>2026-04-22T00:29:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682014</loc>
  <lastmod>2026-04-22T00:28:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械的文章理解のためのニューロモデル訓練（The Training of Neuromodels for Machine Comprehension of Text）</news:title>
   <news:publication_date>2026-04-22T00:28:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682012</loc>
  <lastmod>2026-04-21T23:37:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベントログから学習者行動パターンを発見する（Discovering Student Behavior Patterns from Event Logs: Preliminary Results on A Novel Probabilistic Latent Variable Model）</news:title>
   <news:publication_date>2026-04-21T23:37:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682010</loc>
  <lastmod>2026-04-21T23:37:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分岐するプログラムを微分可能にするDDRフレームワーク（DDRprog: A CLEVR Differentiable Dynamic Reasoning Programmer）</news:title>
   <news:publication_date>2026-04-21T23:37:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682008</loc>
  <lastmod>2026-04-21T23:36:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズラベル下での共同最適化フレームワーク（Joint Optimization Framework for Learning with Noisy Labels）</news:title>
   <news:publication_date>2026-04-21T23:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682006</loc>
  <lastmod>2026-04-21T23:36:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的な現実環境での迅速適応を学ぶ（LEARNING TO ADAPT IN DYNAMIC, REAL-WORLD ENVIRONMENTS THROUGH META-REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-04-21T23:36:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682004</loc>
  <lastmod>2026-04-21T23:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点特化型ディープネットワークによる人物再識別（Learning View-Specific Deep Networks for Person Re-Identification）</news:title>
   <news:publication_date>2026-04-21T23:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682002</loc>
  <lastmod>2026-04-21T23:35:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多階層類似度による効率的な人物再識別（Efficient and Deep Person Re-Identification using Multi-Level Similarity）</news:title>
   <news:publication_date>2026-04-21T23:35:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/682000</loc>
  <lastmod>2026-04-21T23:35:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キャッシュ対応型動的ビットレート配分と深い自己転移強化学習（Cache-Enabled Dynamic Rate Allocation via Deep Self-Transfer Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-21T23:35:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681998</loc>
  <lastmod>2026-04-21T22:44:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移的バイアス除去埋め込みによるゼロショット学習の改良（Transductive Unbiased Embedding for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-04-21T22:44:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681996</loc>
  <lastmod>2026-04-21T22:43:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインショッピングアシスタントにおける深いカスケード型マルチタスク学習（Deep Cascade Multi-task Learning for Slot Filling in Online Shopping Assistant）</news:title>
   <news:publication_date>2026-04-21T22:43:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681994</loc>
  <lastmod>2026-04-21T22:43:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体検出を目指したタスク駆動型超解像（Task-Driven Super Resolution: Object Detection in Low-resolution Images）</news:title>
   <news:publication_date>2026-04-21T22:43:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681992</loc>
  <lastmod>2026-04-21T22:42:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマンロボット協調のためのPOMDPモデル学習（POMDP Model Learning for Human Robot Collaboration）</news:title>
   <news:publication_date>2026-04-21T22:42:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681990</loc>
  <lastmod>2026-04-21T22:42:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ストレージ問題のシミュレーション手法（Simulation Methods for Stochastic Storage Problems: A Statistical Learning Perspective）</news:title>
   <news:publication_date>2026-04-21T22:42:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681988</loc>
  <lastmod>2026-04-21T22:42:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膵臓のCT/MRI画像におけるセグメンテーション手法の統合的改良（Pancreas Segmentation in CT and MRI Images via Domain Specific Network Designing and Recurrent Neural Contextual Learning）</news:title>
   <news:publication_date>2026-04-21T22:42:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681986</loc>
  <lastmod>2026-04-21T22:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルフリー自動蛍光を用いた深層学習による仮想組織染色（Deep learning-based virtual histology staining using auto-fluorescence of label-free tissue）</news:title>
   <news:publication_date>2026-04-21T22:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681984</loc>
  <lastmod>2026-04-21T21:50:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>依存構文コンテキストを用いた頑健なクロスリンガル上位語検出（Robust Cross-lingual Hypernymy Detection using Dependency Context）</news:title>
   <news:publication_date>2026-04-21T21:50:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681982</loc>
  <lastmod>2026-04-21T21:50:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測と特徴が同時に分散された大規模学習の確率的手法（Stochastic Large-scale Machine Learning Algorithms with Distributed Features and Observations）</news:title>
   <news:publication_date>2026-04-21T21:50:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681980</loc>
  <lastmod>2026-04-21T21:49:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>商品属性抽出における深層再帰ニューラルネットワーク（Deep Recurrent Neural Networks for Product Attribute Extraction in eCommerce）</news:title>
   <news:publication_date>2026-04-21T21:49:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681978</loc>
  <lastmod>2026-04-21T21:49:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプリングと時間の不可分性が分子記録と化石記録の統合に与える影響（THE INSEPARABILITY OF SAMPLING AND TIME AND ITS INFLUENCE ON ATTEMPTS TO UNIFY THE MOLECULAR AND FOSSIL RECORDS）</news:title>
   <news:publication_date>2026-04-21T21:49:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681976</loc>
  <lastmod>2026-04-21T21:48:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像誘導下動作学習における速さと正確さのトレードオフ（Getting nowhere fast: trade-off between speed and precision in training to execute image-guided hand-tool movements）</news:title>
   <news:publication_date>2026-04-21T21:48:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681974</loc>
  <lastmod>2026-04-21T21:48:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典データを量子系で学習する意義（Learning quantum models from quantum or classical data）</news:title>
   <news:publication_date>2026-04-21T21:48:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681972</loc>
  <lastmod>2026-04-21T21:48:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経路知識を組み込むことで解釈性と汎化性を高める機械学習手法（PIMKL: Pathway Induced Multiple Kernel Learning）</news:title>
   <news:publication_date>2026-04-21T21:48:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681970</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>人間動作データセットの自作生成（DIY Human Action Data Set Generation）</news:title>
   <news:publication_date>2026-04-21T20:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681968</loc>
  <lastmod>2026-04-21T20:57:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間データを用いた統計・機械学習モデルの性能評価とハイパーパラメータ調整（Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data）</news:title>
   <news:publication_date>2026-04-21T20:57:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681966</loc>
  <lastmod>2026-04-21T20:57:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的信号除去のための効率的な一次アルゴリズム（Efficient First-Order Algorithms for Adaptive Signal Denoising）</news:title>
   <news:publication_date>2026-04-21T20:57:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681964</loc>
  <lastmod>2026-04-21T20:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核内のエキゾチックなグルーオン状態の探索（Search for Exotic Gluonic States in the Nucleus）</news:title>
   <news:publication_date>2026-04-21T20:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681962</loc>
  <lastmod>2026-04-21T20:56:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファインチューニング不要の転移学習改善（Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images）</news:title>
   <news:publication_date>2026-04-21T20:56:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681960</loc>
  <lastmod>2026-04-21T20:55:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2Dレーザレンジデータのみを用いたパレット検出・局所化・追跡（Pallet Detection, Localisation and Tracking using 2D Range Data）</news:title>
   <news:publication_date>2026-04-21T20:55:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681958</loc>
  <lastmod>2026-04-21T20:55:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像概念を用いたテキストグラウンディングの解釈可能でグローバル最適な予測（Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts）</news:title>
   <news:publication_date>2026-04-21T20:55:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681956</loc>
  <lastmod>2026-04-21T20:04:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MemGEN: 記憶に基づく生成モデルの寓話（MemGEN: Memory is All You Need）</news:title>
   <news:publication_date>2026-04-21T20:04:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681954</loc>
  <lastmod>2026-04-21T20:03:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MaskRNNによるインスタンスレベル動画物体セグメンテーション（MaskRNN: Instance Level Video Object Segmentation）</news:title>
   <news:publication_date>2026-04-21T20:03:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681952</loc>
  <lastmod>2026-04-21T20:03:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしテキストグラウンディング（Unsupervised Textual Grounding: Linking Words to Image Concepts）</news:title>
   <news:publication_date>2026-04-21T20:03:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681950</loc>
  <lastmod>2026-04-21T20:02:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配ハミルトンモンテカルロの分散低減によるベイズ推論の改善（Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference）</news:title>
   <news:publication_date>2026-04-21T20:02:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681948</loc>
  <lastmod>2026-04-21T20:02:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ニューラルネットワークの訓練における『不毛地帯（Barren Plateaus）』問題（Barren plateaus in quantum neural network training landscapes）</news:title>
   <news:publication_date>2026-04-21T20:02:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681946</loc>
  <lastmod>2026-04-21T20:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文を数値ベクトルに変える技術の実務的意義（Universal Sentence Encoder）</news:title>
   <news:publication_date>2026-04-21T20:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681944</loc>
  <lastmod>2026-04-21T20:01:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた画像フォレンジクスの安全性検討（Security Consideration For Deep Learning-Based Image Forensics）</news:title>
   <news:publication_date>2026-04-21T20:01:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681942</loc>
  <lastmod>2026-04-21T19:10:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河と大規模構造の分類に向けた機械学習的アプローチ（A Machine Learning Approach to Galaxy-LSS Classification I: Imprints on Halo Merger Trees）</news:title>
   <news:publication_date>2026-04-21T19:10:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681940</loc>
  <lastmod>2026-04-21T19:09:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組込み機器における詳細なエネルギー・性能プロファイリング手法（Fine-Grained Energy and Performance Profiling framework for Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-21T19:09:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681938</loc>
  <lastmod>2026-04-21T19:08:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPAREによる運動学記述学習（Learning Kinematic Descriptions using SPARE）</news:title>
   <news:publication_date>2026-04-21T19:08:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681936</loc>
  <lastmod>2026-04-21T19:07:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>色のない緑の再帰的ネットワークは階層的に夢を見る（Colorless green recurrent networks dream hierarchically）</news:title>
   <news:publication_date>2026-04-21T19:07:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681934</loc>
  <lastmod>2026-04-21T19:07:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠隔クラウド実験ラボが変える制御教育の現場（Decentralized Control Systems Laboratory Using Human Centered Robotic Actuators）</news:title>
   <news:publication_date>2026-04-21T19:07:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681932</loc>
  <lastmod>2026-04-21T19:06:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算困難性と統計的可能性のギャップの予測（NOTES ON COMPUTATIONAL-TO-STATISTICAL GAPS: PREDICTIONS USING STATISTICAL PHYSICS）</news:title>
   <news:publication_date>2026-04-21T19:06:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681930</loc>
  <lastmod>2026-04-21T19:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特権情報（LUPI）とSVM+が早期創薬にもたらすもの（Application of SVM+ in Early Drug Discovery）</news:title>
   <news:publication_date>2026-04-21T19:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681928</loc>
  <lastmod>2026-04-21T18:15:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的なずれを注釈なしで検出する方法（Identifying Semantic Divergences in Parallel Text without Annotations）</news:title>
   <news:publication_date>2026-04-21T18:15:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681926</loc>
  <lastmod>2026-04-21T18:07:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列分類を画像化して解く新発想：Bag of Recurrence Patterns（Bag of Recurrence Patterns Representation for Time-Series Classification）</news:title>
   <news:publication_date>2026-04-21T18:07:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681924</loc>
  <lastmod>2026-04-21T18:05:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習による信号制御の要点解説（Deep Reinforcement Learning for Traffic Light Control in Vehicular Networks）</news:title>
   <news:publication_date>2026-04-21T18:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681922</loc>
  <lastmod>2026-04-21T18:03:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頻出アイテム集合採掘におけるユビキタスアイテムの除去（Frequent Item-set Mining without Ubiquitous Items）</news:title>
   <news:publication_date>2026-04-21T18:03:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681920</loc>
  <lastmod>2026-04-21T18:02:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mining on Manifolds: Metric Learning without Labels（Mining on Manifolds: Metric Learning without Labels）</news:title>
   <news:publication_date>2026-04-21T18:02:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681918</loc>
  <lastmod>2026-04-21T18:02:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3次元で整合性のある両心室心筋セグメンテーションによるメッシュ生成（3D Consistent Biventricular Myocardial Segmentation Using Deep Learning for Mesh Generation）</news:title>
   <news:publication_date>2026-04-21T18:02:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681916</loc>
  <lastmod>2026-04-21T18:01:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔のなりすまし検出における二値監督と補助的監督の比較（Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision）</news:title>
   <news:publication_date>2026-04-21T18:01:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681914</loc>
  <lastmod>2026-04-21T17:10:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COBRAS: 高速反復型ペアワイズ制約アクティブクラスタリング（COBRAS: Fast, Iterative, Active Clustering with Pairwise Constraints）</news:title>
   <news:publication_date>2026-04-21T17:10:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681912</loc>
  <lastmod>2026-04-21T17:10:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CobWebによるトモグラフィー画像自動解析の実装と応用（CobWeb ― a toolbox for automatic tomographic image analysis based on machine learning techniques: application and examples）</news:title>
   <news:publication_date>2026-04-21T17:10:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681910</loc>
  <lastmod>2026-04-21T17:09:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化注意付き畳み込みニューラル場による単眼深度推定（Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-04-21T17:09:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681908</loc>
  <lastmod>2026-04-21T17:08:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタアンサンブルに基づくハイパーパラメータ探索（On Hyperparameter Search in Cluster Ensembles）</news:title>
   <news:publication_date>2026-04-21T17:08:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-21T17:08:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースのマルチホップ経路探索でLPWANの省エネを実現する（Towards Energy Efficient LPWANs through Learning-based Multi-hop Routing）</news:title>
   <news:publication_date>2026-04-21T17:08:43Z</news:publication_date>
   <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:publication_date>2026-04-21T17:08:29Z</news:publication_date>
   <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>
   <news:title>コピュラ変分ベイズ推論の情報幾何学的視点（Copula Variational Bayes inference via information geometry）</news:title>
   <news:publication_date>2026-04-21T17:07:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681900</loc>
  <lastmod>2026-04-21T16:15:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジヒドロール角予測にGANを適用する研究（Dihedral angle prediction using generative adversarial networks）</news:title>
   <news:publication_date>2026-04-21T16:15:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681898</loc>
  <lastmod>2026-04-21T16:15:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Winograd畳み込みの誤差解析と精度改善（ERROR ANALYSIS AND IMPROVING THE ACCURACY OF WINOGRAD CONVOLUTION FOR DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-04-21T16:15:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681896</loc>
  <lastmod>2026-04-21T16:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クローン防御による深層学習の安全性強化（Protection against Cloning for Deep Learning）</news:title>
   <news:publication_date>2026-04-21T16:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681894</loc>
  <lastmod>2026-04-21T16:14:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意力付き統計プーリングによる深層話者埋め込み（Attentive Statistics Pooling for Deep Speaker Embedding）</news:title>
   <news:publication_date>2026-04-21T16:14:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681892</loc>
  <lastmod>2026-04-21T16:13:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子イオン衝突型加速器における二ジェット光生成で核のパートン分布関数を測る可能性（Nuclear parton density functions from dijet photoproduction at the EIC）</news:title>
   <news:publication_date>2026-04-21T16:13:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681890</loc>
  <lastmod>2026-04-21T16:13:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロトンドリップラインを越えた探査：アルゴンと塩素同位体鎖の新知見（Deep excursion beyond the proton dripline. I. Argon and chlorine isotope chains）</news:title>
   <news:publication_date>2026-04-21T16:13:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681888</loc>
  <lastmod>2026-04-21T16:13:22Z</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の最良腕同定（Best arm identification in multi-armed bandits with delayed feedback）</news:title>
   <news:publication_date>2026-04-21T16:13:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681886</loc>
  <lastmod>2026-04-21T15:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>B-DCGANによるFPGA実装の評価（B-DCGAN: Evaluation of Binarized DCGAN for FPGA）</news:title>
   <news:publication_date>2026-04-21T15:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681884</loc>
  <lastmod>2026-04-21T15:22:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による自由形状変形を用いた3D物体再構築（Learning Free-Form Deformations for 3D Object Reconstruction）</news:title>
   <news:publication_date>2026-04-21T15:22:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681882</loc>
  <lastmod>2026-04-21T15:21:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語モデリングのためのLPベースハイパーパラメータ最適化（An LP-based hyperparameter optimization model for language modeling）</news:title>
   <news:publication_date>2026-04-21T15:21:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681880</loc>
  <lastmod>2026-04-21T15:20:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブモジュラ・ラプラシアン系の多項式時間アルゴリズム（Polynomial-Time Algorithms for Submodular Laplacian Systems）</news:title>
   <news:publication_date>2026-04-21T15:20:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681878</loc>
  <lastmod>2026-04-21T15:20:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な人物再識別のための敵対的バイナリ符号化（Adversarial Binary Coding for Efficient Person Re-identification）</news:title>
   <news:publication_date>2026-04-21T15:20:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681876</loc>
  <lastmod>2026-04-21T15:20:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビーム深層アトラクタネットワークによるカクテルパーティ問題の打破（Cracking the Cocktail Party Problem by Multi-Beam Deep Attractor Network）</news:title>
   <news:publication_date>2026-04-21T15:20:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681874</loc>
  <lastmod>2026-04-21T15:19:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小規模音声キーワード検出における注意機構終端モデル（Attention-based End-to-End Models for Small-Footprint Keyword Spotting）</news:title>
   <news:publication_date>2026-04-21T15:19:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681872</loc>
  <lastmod>2026-04-21T14:28:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列積演算子を用いた系列から系列への学習（Matrix Product Operators for Sequence to Sequence Learning）</news:title>
   <news:publication_date>2026-04-21T14:28:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681870</loc>
  <lastmod>2026-04-21T14:28:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による教師なし顕著領域検出：複数ノイズラベリング視点（Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective）</news:title>
   <news:publication_date>2026-04-21T14:28:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681868</loc>
  <lastmod>2026-04-21T14:28:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマート交通における汎用データ源の応用調査（Transport-domain applications of widely used data sources in the smart transportation: A survey）</news:title>
   <news:publication_date>2026-04-21T14:28:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681866</loc>
  <lastmod>2026-04-21T14:26:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地表テクスチャの深層マニホールド (Deep Texture Manifold for Ground Terrain Recognition)</news:title>
   <news:publication_date>2026-04-21T14:26:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681864</loc>
  <lastmod>2026-04-21T14:26:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ステガノグラフィに対するCNNベース検出器の弱点を突く手法（Weakening the Detecting Capability of CNN-Based Steganalysis）</news:title>
   <news:publication_date>2026-04-21T14:26:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681862</loc>
  <lastmod>2026-04-21T14:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>C1,1関数クラス回帰の構造的リスク最小化（Structural Risk Minimization for C1,1(R^d) Regression）</news:title>
   <news:publication_date>2026-04-21T14:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681860</loc>
  <lastmod>2026-04-21T14:26:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付きサポートベクトル分位回帰による風力の確率予測（Constrained Support Vector Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power）</news:title>
   <news:publication_date>2026-04-21T14:26:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681858</loc>
  <lastmod>2026-04-21T13:34:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体の周囲を見て見えない部分を推定するトップビュー表現（Learning to Look around Objects for Top-View Representations of Outdoor Scenes）</news:title>
   <news:publication_date>2026-04-21T13:34:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681856</loc>
  <lastmod>2026-04-21T13:34:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>静止画像における表情認識の特徴選択と分類器設計（Manifold-Based Feature Selection for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-04-21T13:34:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681854</loc>
  <lastmod>2026-04-21T13:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットビジョンにおける深層学習手法の総説 (A Survey on Deep Learning Methods for Robot Vision)</news:title>
   <news:publication_date>2026-04-21T13:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681852</loc>
  <lastmod>2026-04-21T13:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1日屋外フォトメトリックステレオ（Single Day Outdoor Photometric Stereo）</news:title>
   <news:publication_date>2026-04-21T13:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681850</loc>
  <lastmod>2026-04-21T13:33:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期オンライン動画表現のためのメモリワープ（Memory Warps for Learning Long-Term Online Video Representations）</news:title>
   <news:publication_date>2026-04-21T13:33:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681848</loc>
  <lastmod>2026-04-21T13:33:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数カメラでの多人数追跡と再識別の特徴学習（Features for Multi-Target Multi-Camera Tracking and Re-Identification）</news:title>
   <news:publication_date>2026-04-21T13:33:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681846</loc>
  <lastmod>2026-04-21T13:33:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適量子制御のガラス的相（Glassy Phase of Optimal Quantum Control）</news:title>
   <news:publication_date>2026-04-21T13:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681844</loc>
  <lastmod>2026-04-21T12:41:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半ランダム敵対者に対する非凸行列補完（Non-Convex Matrix Completion Against a Semi-Random Adversary）</news:title>
   <news:publication_date>2026-04-21T12:41:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681842</loc>
  <lastmod>2026-04-21T12:41:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生態系モニタリングにおける物体検出の実用化（Deep Learning Object Detection Methods for Ecological Camera Trap Data）</news:title>
   <news:publication_date>2026-04-21T12:41:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681840</loc>
  <lastmod>2026-04-21T12:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基底関数変換による敵対的画像への防御（Defending against Adversarial Images using Basis Functions Transformations）</news:title>
   <news:publication_date>2026-04-21T12:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681838</loc>
  <lastmod>2026-04-21T12:40:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化重み行列に基づくハードウェアアクセラレータ（Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs）</news:title>
   <news:publication_date>2026-04-21T12:40:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-21T12:40:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一細胞セグメンテーションを簡潔にする深距離推定器と深層細胞検出器（Learn to segment single cells with deep distance estimator and deep cell detector）</news:title>
   <news:publication_date>2026-04-21T12:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681834</loc>
  <lastmod>2026-04-21T12:40:19Z</lastmod>
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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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   <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:genres>Blog</news:genres>
  </news:news>
 </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:publication_date>2026-04-21T11:48:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </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>2026-04-21T11:47:53Z</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>
   </news:publication>
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   <news:publication_date>2026-04-21T11:47:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681820</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>TrackingNetによる「実世界」トラッキングの基盤再構築（TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild）</news:title>
   <news:publication_date>2026-04-21T11:47:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681818</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>学習ソフトにおける感情状態の持続時間の分析（Analysis of permanence time in emotional states: A case study using educational software）</news:title>
   <news:publication_date>2026-04-21T11:47:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681816</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>局所接続通信網を用いた電力網電圧制御のための分散均衡学習 (Distributed Equilibrium-Learning for Power Network Voltage Control With a Locally Connected Communication Network)</news:title>
   <news:publication_date>2026-04-21T10:56:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681814</loc>
  <lastmod>2026-04-21T10:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォルナックス銀河団の半径内に分布する矮小銀河群（NGFS Dwarf Galaxies Inside Half of Fornax’s Virial Radius）</news:title>
   <news:publication_date>2026-04-21T10:55:45Z</news:publication_date>
   <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>
   <news:title>超新星爆発と宇宙線の起源（Supernova explosions of massive stars and cosmic rays）</news:title>
   <news:publication_date>2026-04-21T10:55:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681810</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>広告クリック率予測のための深層監督セマンティックモデル（Deeply Supervised Semantic Model for Click-Through Rate Prediction in Sponsored Search）</news:title>
   <news:publication_date>2026-04-21T10:54:44Z</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>
   </news:publication>
   <news:title>誘導表現間のインタートゥイナーと等変ニューラルネットワークへの応用（Intertwiners between Induced Representations with Applications to the Theory of Equivariant Neural Networks）</news:title>
   <news:publication_date>2026-04-21T10:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681806</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>敵対的ネットワーク圧縮（Adversarial Network Compression）</news:title>
   <news:publication_date>2026-04-21T10:54:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/681804</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>疑似周辺尤度を使った教師ありGaussian process潜在変数モデルのベイズ推論（Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models）</news:title>
   <news:publication_date>2026-04-21T10:53:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/681802</loc>
  <lastmod>2026-04-21T10:02:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡な医療画像セグメンテーションにおける非対称類似度損失とパッチベースDenseNet（Asymmetric similarity loss functions and deep densely connected networks for highly imbalanced medical image segmentation）</news:title>
   <news:publication_date>2026-04-21T10:02:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681800</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>部分観測された属性付きグラフにおける構造化回帰の半教師あり学習（Semi-supervised learning for structured regression on partially observed attributed graphs）</news:title>
   <news:publication_date>2026-04-21T10:02:28Z</news:publication_date>
   <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:publication_date>2026-04-21T10:02:05Z</news:publication_date>
   <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:publication_date>2026-04-21T10:00:26Z</news:publication_date>
   <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>
   </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>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681788</loc>
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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>
  <loc>https://aibr.jp/archives/681786</loc>
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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>2026-04-21T08:58:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681784</loc>
  <lastmod>2026-04-21T08:57:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IACTデータ解析へのDeep Learning適用（Application of Deep Learning methods to analysis of Imaging Atmospheric Cherenkov Telescopes data）</news:title>
   <news:publication_date>2026-04-21T08:57:58Z</news:publication_date>
   <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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  <lastmod>2026-04-21T08:56:31Z</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>2026-04-21T08:56:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-21T08:56:21Z</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>2026-04-21T08:56:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681776</loc>
  <lastmod>2026-04-21T08:56:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の不合理な有効性（The Unreasonable Effectiveness of Deep Learning）</news:title>
   <news:publication_date>2026-04-21T08:56:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-21T08:04:30Z</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>2026-04-21T08:04:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681772</loc>
  <lastmod>2026-04-21T08:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>家庭内遠隔マイクでの会話音声認識を問う CHiME-5（The fifth ‘CHiME’ Speech Separation and Recognition Challenge）</news:title>
   <news:publication_date>2026-04-21T08:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681770</loc>
  <lastmod>2026-04-21T08:04:06Z</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>2026-04-21T08:04:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681768</loc>
  <lastmod>2026-04-21T08:02:44Z</lastmod>
  <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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  <lastmod>2026-04-21T08:02:33Z</lastmod>
  <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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  <lastmod>2026-04-21T08:02:17Z</lastmod>
  <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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  <lastmod>2026-04-21T08:02:07Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離表現による画像生成と翻訳 (Image Generation and Translation with Disentangled Representations)</news:title>
   <news:publication_date>2026-04-21T08:02:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681760</loc>
  <lastmod>2026-04-21T07:09:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔属性の複数同時転送を可能にするELEGANT（ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes）</news:title>
   <news:publication_date>2026-04-21T07:09:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681758</loc>
  <lastmod>2026-04-21T07:08:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解析的分散伝播によるニューラルネットワークの正規化（Normalization of Neural Networks using Analytic Variance Propagation）</news:title>
   <news:publication_date>2026-04-21T07:08:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681756</loc>
  <lastmod>2026-04-21T07:08:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二要因を同時に扱うJoint PLDAの実践的意義（Joint PLDA for Simultaneous Modeling of Two Factors）</news:title>
   <news:publication_date>2026-04-21T07:08:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681754</loc>
  <lastmod>2026-04-21T07:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D-SIMDプロセッサをFPGAで実装して省メモリ・高速化を図る手法（FPGA Implementations of 3D-SIMD Processor Architecture for Deep Neural Networks Using Relative Indexed Compressed Sparse Filter Encoding Format and Stacked Filters Stationary Flow）</news:title>
   <news:publication_date>2026-04-21T07:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681752</loc>
  <lastmod>2026-04-21T07:07:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速ビジュアルトラッキングのための文脈認識深部特徴圧縮（Context-aware Deep Feature Compression for High-speed Visual Tracking）</news:title>
   <news:publication_date>2026-04-21T07:07:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681750</loc>
  <lastmod>2026-04-21T07:07:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的システムの分類：モデルベースとサポートベクターマシン（Classification for Dynamical Systems: Model-based Approach and Support Vector Machines）</news:title>
   <news:publication_date>2026-04-21T07:07:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681748</loc>
  <lastmod>2026-04-21T07:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストの信用性評価のためのニューラルネットワークアーキテクチャ（Neural Network Architecture for Credibility Assessment of Textual Claims）</news:title>
   <news:publication_date>2026-04-21T07:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681746</loc>
  <lastmod>2026-04-21T06:15:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列の高次元データから因果効果を推定する手法の拡張（Estimating causal effects of time-dependent exposures on a binary endpoint in a high-dimensional setting）</news:title>
   <news:publication_date>2026-04-21T06:15:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681744</loc>
  <lastmod>2026-04-21T06:14:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程の訓練を量子アルゴリズムで高速化する（Quantum algorithms for training Gaussian Processes）</news:title>
   <news:publication_date>2026-04-21T06:14:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681742</loc>
  <lastmod>2026-04-21T06:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械的スピーチチェーンとワンショット話者適応（Machine Speech Chain with One-shot Speaker Adaptation）</news:title>
   <news:publication_date>2026-04-21T06:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681740</loc>
  <lastmod>2026-04-21T06:13:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサー駆動システムの信頼性を設計するフレーミングモデル（Making Sense of the World: Framing Models for Trustworthy Sensor-Driven Systems）</news:title>
   <news:publication_date>2026-04-21T06:13:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681738</loc>
  <lastmod>2026-04-21T06:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画のブレを「リアルに」消す技術の要点（Adversarial Spatio-Temporal Learning for Video Deblurring）</news:title>
   <news:publication_date>2026-04-21T06:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681736</loc>
  <lastmod>2026-04-21T06:12:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Learningが「心を読む力」に何を教えるか（What deep learning can tell us about higher cognitive functions like mindreading?）</news:title>
   <news:publication_date>2026-04-21T06:12:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681734</loc>
  <lastmod>2026-04-21T06:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中における超分子ポリマーの原子スケール高速シミュレーション（Accelerated Atomistic Simulations of a Supramolecular Polymer in Water）</news:title>
   <news:publication_date>2026-04-21T06:12:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681732</loc>
  <lastmod>2026-04-21T05:20:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像レベルラベルから学ぶ画素間意味親和性（Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation）</news:title>
   <news:publication_date>2026-04-21T05:20:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681730</loc>
  <lastmod>2026-04-21T05:10:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graphiteによるグラフの反復生成モデリング（Graphite: Iterative Generative Modeling of Graphs）</news:title>
   <news:publication_date>2026-04-21T05:10:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681728</loc>
  <lastmod>2026-04-21T05:10:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クッキーを越えてユーザーをつなぐ学習手法（Siamese Cookie Embedding Networks for Cross-Device User Matching）</news:title>
   <news:publication_date>2026-04-21T05:10:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681726</loc>
  <lastmod>2026-04-21T05:09:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JPEGとJPEG2000圧縮が敵対的例（Adversarial Examples）攻撃に与える影響（The Effects of JPEG and JPEG2000 Compression on Attacks using Adversarial Examples）</news:title>
   <news:publication_date>2026-04-21T05:09:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681724</loc>
  <lastmod>2026-04-21T05:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BIVASによる階層的変数選択のスケーリング（BIVAS: A scalable Bayesian method for bi-level variable selection with applications）</news:title>
   <news:publication_date>2026-04-21T05:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681722</loc>
  <lastmod>2026-04-21T05:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>眼球運動シミュレーションと検出器生成による面倒なパラメータ調整の削減（Eye movement simulation and detector creation to reduce laborious parameter adjustments）</news:title>
   <news:publication_date>2026-04-21T05:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681720</loc>
  <lastmod>2026-04-21T05:08:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HAM10000：皮膚病変の自動診断研究を前進させた大規模皮膚画像データセット（HAM10000: A Large Collection of Multi-Source Dermatoscopic Images）</news:title>
   <news:publication_date>2026-04-21T05:08:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681718</loc>
  <lastmod>2026-04-21T04:16:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半バンディット（Semi-Bandit）フィードバックによる資源配分アルゴリズムの改良（A Better Resource Allocation Algorithm with Semi-Bandit Feedback）</news:title>
   <news:publication_date>2026-04-21T04:16:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681716</loc>
  <lastmod>2026-04-21T04:16:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3DMV：3Dマルチビュー統合による3次元意味シーン分割（3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation）</news:title>
   <news:publication_date>2026-04-21T04:16:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681714</loc>
  <lastmod>2026-04-21T04:16:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>唇の動きを音声から生成する研究の要点（Lip Movements Generation at a Glance）</news:title>
   <news:publication_date>2026-04-21T04:16:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681712</loc>
  <lastmod>2026-04-21T04:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲームアバターのシナジーと対立を埋め込みでモデル化する手法（Modeling Game Avatar Synergy and Opposition through Embedding）</news:title>
   <news:publication_date>2026-04-21T04:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681710</loc>
  <lastmod>2026-04-21T04:14:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的手法で教師なし学習を制御する（Supervising Unsupervised Learning with Evolutionary Algorithm in Deep Neural Network）</news:title>
   <news:publication_date>2026-04-21T04:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681708</loc>
  <lastmod>2026-04-21T04:14:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期運転意図予測に基づく自動運転判断の精度向上（Predictions of short-term driving intention using recurrent neural network on sequential data）</news:title>
   <news:publication_date>2026-04-21T04:14:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681706</loc>
  <lastmod>2026-04-21T04:13:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Actor–Criticによる抽象的要約のための訓練枠組み（Actor-Critic based Training Framework for Abstractive Summarization）</news:title>
   <news:publication_date>2026-04-21T04:13:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681704</loc>
  <lastmod>2026-04-21T03:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非把持操作に対する強化学習：シミュレーションから実機への移行（Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system）</news:title>
   <news:publication_date>2026-04-21T03:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681702</loc>
  <lastmod>2026-04-21T03:21:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピックモデリングに基づくマルチモーダルうつ検出（Topic Modeling Based Multi-modal Depression Detection）</news:title>
   <news:publication_date>2026-04-21T03:21:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681700</loc>
  <lastmod>2026-04-21T03:21:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み向け超小型畳み込みネットワークMicronNet（MicronNet: A Highly Compact Deep Convolutional Neural Network Architecture for Real-time Embedded Traffic Sign Classification）</news:title>
   <news:publication_date>2026-04-21T03:21:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681698</loc>
  <lastmod>2026-04-21T03:21:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長文要約に挑む「Deep Communicating Agents」(Deep Communicating Agents for Abstractive Summarization)</news:title>
   <news:publication_date>2026-04-21T03:21:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681696</loc>
  <lastmod>2026-04-21T03:21:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元における平滑化オンライン凸最適化とOnline Balanced Descent（Smoothed Online Convex Optimization in High Dimensions via Online Balanced Descent）</news:title>
   <news:publication_date>2026-04-21T03:21:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681694</loc>
  <lastmod>2026-04-21T03:21:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ClickBAIT-v2によるリアルタイム物体検出の現場学習（ClickBAIT-v2: Training an Object Detector in Real-Time）</news:title>
   <news:publication_date>2026-04-21T03:21:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681692</loc>
  <lastmod>2026-04-21T03:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的画像修復の進化（Structural inpainting）</news:title>
   <news:publication_date>2026-04-21T03:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681690</loc>
  <lastmod>2026-04-21T02:29:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習ワークフローの反復と実務（How Developers Iterate on Machine Learning Workflows）</news:title>
   <news:publication_date>2026-04-21T02:29:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/681688</loc>
  <lastmod>2026-04-21T02:20:55Z</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>2026-04-21T02:20:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-21T02:20:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結晶化画像の分類における深層畳み込みニューラルネットワークの適用（Classification of crystallization outcomes using deep convolutional neural networks）</news:title>
   <news:publication_date>2026-04-21T02:20:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-21T02:19:54Z</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>2026-04-21T02:19:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681682</loc>
  <lastmod>2026-04-21T02:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形時系列部分空間表現による行動認識（Non-Linear Temporal Subspace Representations for Activity Recognition）</news:title>
   <news:publication_date>2026-04-21T02:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681680</loc>
  <lastmod>2026-04-21T02:19:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共通ソースグラフを持つデータセットのカノニカル相関分析（Canonical Correlation Analysis of Datasets with a Common Source Graph）</news:title>
   <news:publication_date>2026-04-21T02:19:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681678</loc>
  <lastmod>2026-04-21T02:19:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再考：EEGベースの非侵襲的脳インタフェースの設計（Re-thinking EEG-based non-invasive brain interfaces: modeling and analysis）</news:title>
   <news:publication_date>2026-04-21T02:19:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681676</loc>
  <lastmod>2026-04-21T01:27:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子構造計算のための量子機械学習（Quantum Machine Learning for Electronic Structure Calculations）</news:title>
   <news:publication_date>2026-04-21T01:27:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681674</loc>
  <lastmod>2026-04-21T01:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトルから銀河の物理量を推定する機械学習手法の進化（GAME: GAlaxy Machine learning for Emission lines）</news:title>
   <news:publication_date>2026-04-21T01:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681672</loc>
  <lastmod>2026-04-21T01:18:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルリッジ回帰におけるクラスタリングと階層行列形式の研究（A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression）</news:title>
   <news:publication_date>2026-04-21T01:18:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681670</loc>
  <lastmod>2026-04-21T01:17:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー保護された予測（Privacy-preserving Prediction）</news:title>
   <news:publication_date>2026-04-21T01:17:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681668</loc>
  <lastmod>2026-04-21T01:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CANDELSにおける多波長バルジ・ディスク分解カタログ（A catalog of polychromatic bulge-disk decompositions of ~17.600 galaxies in CANDELS）</news:title>
   <news:publication_date>2026-04-21T01:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681666</loc>
  <lastmod>2026-04-21T01:16:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疾患軌跡を読むための深層学習アプローチ（Disease-Atlas: Navigating Disease Trajectories using Deep Learning）</news:title>
   <news:publication_date>2026-04-21T01:16:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681664</loc>
  <lastmod>2026-04-21T01:15:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い優先度衝突のゼロオーバーヘッドな曖昧性除去（Towards Zero-Overhead Disambiguation of Deep Priority Conflicts）</news:title>
   <news:publication_date>2026-04-21T01:15:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681654</loc>
  <lastmod>2026-04-21T00:23:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人間の相互作用予測（Predicting interactions between individuals with structural and dynamical information）</news:title>
   <news:publication_date>2026-04-21T00:23:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681652</loc>
  <lastmod>2026-04-21T00:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HDM-Netによる単眼非剛体3D再構成の新展開（HDM-Net: Monocular Non-Rigid 3D Reconstruction with Learned Deformation Model）</news:title>
   <news:publication_date>2026-04-21T00:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681650</loc>
  <lastmod>2026-04-21T00:15:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一分子ナノポア検出のための畳み込みニューラルネットワークQuipuNet（QuipuNet: convolutional neural network for single-molecule nanopore sensing）</news:title>
   <news:publication_date>2026-04-21T00:15:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681648</loc>
  <lastmod>2026-04-21T00:15:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル行列近似のための分散適応サンプリング（Distributed Adaptive Sampling for Kernel Matrix Approximation）</news:title>
   <news:publication_date>2026-04-21T00:15:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681646</loc>
  <lastmod>2026-04-21T00:15:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stein Pointsによる代表点列による事後近似の効率化（Stein Points）</news:title>
   <news:publication_date>2026-04-21T00:15:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681644</loc>
  <lastmod>2026-04-21T00:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周囲カメラとルートプランナーを用いた運転モデルのエンドツーエンド学習 (End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners)</news:title>
   <news:publication_date>2026-04-21T00:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681642</loc>
  <lastmod>2026-04-21T00:13:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次拡張による畳み込みニューラルネットワークの学習効率化（Incremental Training of Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-21T00:13:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681640</loc>
  <lastmod>2026-04-20T23:21:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全なエンドツーエンド模倣学習によるモデル予測制御（Safe end-to-end imitation learning for model predictive control）</news:title>
   <news:publication_date>2026-04-20T23:21:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681638</loc>
  <lastmod>2026-04-20T23:21:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による分岐（Learning to Branch）</news:title>
   <news:publication_date>2026-04-20T23:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681636</loc>
  <lastmod>2026-04-20T23:21:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者適応の実証評価（Empirical Evaluation of Speaker Adaptation on DNN based Acoustic Model）</news:title>
   <news:publication_date>2026-04-20T23:21:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681634</loc>
  <lastmod>2026-04-20T23:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>あなたはメタデータ：ソーシャルメディア利用者の識別と難読化（You Are Your Metadata: Identification and Obfuscation of Social Media Users using Metadata Information）</news:title>
   <news:publication_date>2026-04-20T23:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681632</loc>
  <lastmod>2026-04-20T23:20:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク境界を前提としない継続学習の実装（Task Agnostic Continual Learning Using Online Variational Bayes）</news:title>
   <news:publication_date>2026-04-20T23:20:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681630</loc>
  <lastmod>2026-04-20T23:19:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声の残響除去におけるGANの活用（Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition）</news:title>
   <news:publication_date>2026-04-20T23:19:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681628</loc>
  <lastmod>2026-04-20T23:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベンガル語の実数読み上げ音声コーパスの構築（Comprehending Real Numbers: Development of Bengali Real Number Speech Corpus）</news:title>
   <news:publication_date>2026-04-20T23:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681626</loc>
  <lastmod>2026-04-20T22:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー保護型機械学習の脅威と解決策（Privacy Preserving Machine Learning: Threats and Solutions）</news:title>
   <news:publication_date>2026-04-20T22:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681624</loc>
  <lastmod>2026-04-20T22:27:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>世界モデルの構築と活用（World Models）</news:title>
   <news:publication_date>2026-04-20T22:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681622</loc>
  <lastmod>2026-04-20T22:26:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期的形状変化分布の学習：微分同相写像の多様体上の階層モデル（Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms）</news:title>
   <news:publication_date>2026-04-20T22:26:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681620</loc>
  <lastmod>2026-04-20T22:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepScores：小さな物体の検出・分類のための大規模楽譜データセット（DeepScores – A Dataset for Segmentation, Detection and Classification of Tiny Objects）</news:title>
   <news:publication_date>2026-04-20T22:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681618</loc>
  <lastmod>2026-04-20T22:26:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張演算子による点群畳み込み（Point Convolutional Neural Networks by Extension Operators）</news:title>
   <news:publication_date>2026-04-20T22:26:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681616</loc>
  <lastmod>2026-04-20T22:25:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CHiME-4を使った雑音下音声認識の単一ベースライン構築（Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline）</news:title>
   <news:publication_date>2026-04-20T22:25:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681614</loc>
  <lastmod>2026-04-20T22:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるDNAハイブリダイゼーション解析（Analyzing DNA Hybridization via machine learning）</news:title>
   <news:publication_date>2026-04-20T22:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681612</loc>
  <lastmod>2026-04-20T21:33:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な多領域ディープニューラルネットワークの表現（Efficient parametrization of multi-domain deep neural networks）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681610</loc>
  <lastmod>2026-04-20T21:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepJDOTによる深層結合分布の最適輸送で実現する教師なしドメイン適応（DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-04-20T21:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681608</loc>
  <lastmod>2026-04-20T21:33:20Z</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>2026-04-20T21:33:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681606</loc>
  <lastmod>2026-04-20T21:31:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的PETのキネティック圧縮センシング（Kinetic Compressive Sensing）</news:title>
   <news:publication_date>2026-04-20T21:31:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681604</loc>
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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>2026-04-20T21:31:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681602</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>6自由度オブジェクトトラッキングの評価フレームワーク (A Framework for Evaluating 6-DOF Object Trackers)</news:title>
   <news:publication_date>2026-04-20T21:31:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681600</loc>
  <lastmod>2026-04-20T21:31:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性メモリによる高速パラメトリック学習（Fast Parametric Learning with Activation Memorization）</news:title>
   <news:publication_date>2026-04-20T21:31:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681598</loc>
  <lastmod>2026-04-20T20:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの深度学習と焦点距離の埋め込み（Learning Depth from Single Images with Deep Neural Network Embedding Focal Length）</news:title>
   <news:publication_date>2026-04-20T20:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T20:38:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Return of the features — 効率的な特徴選択と解釈性の高いフォトメトリック赤方偏移推定（Efficient feature selection and interpretation for photometric redshifts）</news:title>
   <news:publication_date>2026-04-20T20:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681594</loc>
  <lastmod>2026-04-20T20:37:59Z</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>2026-04-20T20:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681592</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>BLSTMマスクを使った単一チャネル音声強調の学生–教師学習（Student-Teacher Learning for BLSTM Mask-based Speech Enhancement）</news:title>
   <news:publication_date>2026-04-20T20:36:56Z</news:publication_date>
   <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:publication_date>2026-04-20T20:36:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T20:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元空間における交差検証の効率化（Cross-validation in high-dimensional spaces: a lifeline for least-squares models and multi-class LDA）</news:title>
   <news:publication_date>2026-04-20T20:36:29Z</news:publication_date>
   <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:publication_date>2026-04-20T20:36:04Z</news:publication_date>
   <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:publication_date>2026-04-20T19:44:17Z</news:publication_date>
   <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>
   <news:title>押しと掴みの協調を自己監督で学ぶ（Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-20T19:44:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681580</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>深い非弾性散乱におけるジェット生成のN3LO補正（N3LO Corrections to Jet Production in Deep Inelastic Scattering using the Projection-to-Born Method）</news:title>
   <news:publication_date>2026-04-20T19:43:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T19:43:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力波検出器における雑音トランジェントの画像ベース深層学習による分類（Image-based deep learning for classification of noise transients in gravitational wave detectors）</news:title>
   <news:publication_date>2026-04-20T19:43:08Z</news:publication_date>
   <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>
   <news:title>文脈を考慮した特徴列のための二重注意マッチングネットワーク (Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification)</news:title>
   <news:publication_date>2026-04-20T19:42:55Z</news:publication_date>
   <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>
   <news:title>複素数値Restricted Boltzmann Machineによる複素スペクトルからの直接音声パラメータ化（Complex-Valued Restricted Boltzmann Machine for Direct Speech Parameterization from Complex Spectra）</news:title>
   <news:publication_date>2026-04-20T19:42:47Z</news:publication_date>
   <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:publication_date>2026-04-20T19:42:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681570</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>Diagonalwise RefactorizationによるDepthwise Convolutionの高速学習（Diagonalwise Refactorization: An Efficient Training Method for Depthwise Convolutions）</news:title>
   <news:publication_date>2026-04-20T18:51:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681568</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>匿名化されたマルチエージェント環境におけるエントロピー基準の独立学習（Entropy Based Independent Learning in Anonymous Multi-Agent Settings）</news:title>
   <news:publication_date>2026-04-20T18:50:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T18:50:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手作り特徴と深層姿勢ベース領域特徴の融合による人物再識別（Person re-identification with fusion of hand-crafted and deep pose-based body region features）</news:title>
   <news:publication_date>2026-04-20T18:50:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T18:50:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分可能プログラミングの解剖（Demystifying Differentiable Programming: Shift/Reset the Penultimate Backpropagator）</news:title>
   <news:publication_date>2026-04-20T18:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681562</loc>
  <lastmod>2026-04-20T18:49:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数判別器を用いたCycleGANによる非並列音声ドメイン適応（A Multi-Discriminator CycleGAN for Unsupervised Non-Parallel Speech Domain Adaptation）</news:title>
   <news:publication_date>2026-04-20T18:49:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T18:49:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mittens：既存語彙表現を領域特化させる手法（Mittens: An Extension of GloVe for Learning Domain-Specialized Representations）</news:title>
   <news:publication_date>2026-04-20T18:49:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T18:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール構造認識ネットワークによる姿勢推定（Multi-Scale Structure-Aware Network for Human Pose Estimation）</news:title>
   <news:publication_date>2026-04-20T18:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T17:58:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標から逆算して学ぶ強化学習（Forward-Backward Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-20T17:58:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T17:58:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLE誘導尤度によるマルコフ確率場の近似 (MLE-induced Likelihood for Markov Random Fields)</news:title>
   <news:publication_date>2026-04-20T17:58:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681552</loc>
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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>2026-04-20T17:57:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-20T17:57:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitter API制限を回避するウェブスクレイピング手法（A Web Scraping Methodology for Bypassing Twitter API Restrictions）</news:title>
   <news:publication_date>2026-04-20T17:57:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-20T17:56:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画ベース人物再識別のための多様性正則化時空間注意（Diversity Regularized Spatiotemporal Attention for Video-based Person Re-identification）</news:title>
   <news:publication_date>2026-04-20T17:56:57Z</news:publication_date>
   <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:title>DRACO：冗長勾配によるビザンチン耐性分散学習（Byzantine-resilient Distributed Training via Redundant Gradients）</news:title>
   <news:publication_date>2026-04-20T17:56:08Z</news:publication_date>
   <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>
   </news:publication>
   <news:title>UCT木探索によるエンパワーメント計算の高速化（Accelerating Empowerment Computation with UCT Tree Search）</news:title>
   <news:publication_date>2026-04-20T17:03:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/681536</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>てんかん発作検出の深層学習アプローチ（Epileptic Seizure Detection: A Deep Learning Approach）</news:title>
   <news:publication_date>2026-04-20T17:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/681534</loc>
  <lastmod>2026-04-20T17:02:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性を作用素として扱う：未知の属性-物体組合せの分解 (Attributes as Operators: Factorizing Unseen Attribute-Object Compositions)</news:title>
   <news:publication_date>2026-04-20T17:02:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/681532</loc>
  <lastmod>2026-04-20T17:01:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>家庭内暴力の再犯予測における決定木アプローチ（A Decision Tree Approach to Predicting Recidivism in Domestic Violence）</news:title>
   <news:publication_date>2026-04-20T17:01:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681530</loc>
  <lastmod>2026-04-20T17:01:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Webから学ぶセマンティックセグメンテーション（WebSeg: Learning Semantic Segmentation from Web Searches）</news:title>
   <news:publication_date>2026-04-20T17:01:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681528</loc>
  <lastmod>2026-04-20T16:09:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンクド・オープンデータにおける基礎的区別の実証的分析（Empirical Analysis of Foundational Distinctions in Linked Open Data）</news:title>
   <news:publication_date>2026-04-20T16:09:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681526</loc>
  <lastmod>2026-04-20T16:09:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるメタ安定多形の振動特性予測（Vibrational properties of metastable polymorph structures by machine learning）</news:title>
   <news:publication_date>2026-04-20T16:09:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681524</loc>
  <lastmod>2026-04-20T16:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ない注釈データで地表画像をピクセル単位で識別する方法（Low-Shot Learning for the Semantic Segmentation of Remote Sensing Imagery）</news:title>
   <news:publication_date>2026-04-20T16:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681522</loc>
  <lastmod>2026-04-20T16:08:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雪上の女性も写すキャプション生成の偏りを正す研究（Women also Snowboard: Overcoming Bias in Captioning Models）</news:title>
   <news:publication_date>2026-04-20T16:08:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681520</loc>
  <lastmod>2026-04-20T16:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークのハイパーパラメータに対する規律あるアプローチ（A Disciplined Approach to Neural Network Hyper-Parameters: Part 1 – Learning Rate, Batch Size, Momentum, and Weight Decay）</news:title>
   <news:publication_date>2026-04-20T16:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681518</loc>
  <lastmod>2026-04-20T16:07:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声強調における模倣損失の導入（SPECTRAL FEATURE MAPPING WITH MIMIC LOSS FOR ROBUST SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-04-20T16:07:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681516</loc>
  <lastmod>2026-04-20T16:07:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルデータ解析のための深層学習（Deep learning as a tool for neural data analysis: speech classification and cross-frequency coupling in human sensorimotor cortex）</news:title>
   <news:publication_date>2026-04-20T16:07:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681514</loc>
  <lastmod>2026-04-20T15:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別的プーリングによる動画表現学習 (Video Representation Learning Using Discriminative Pooling)</news:title>
   <news:publication_date>2026-04-20T15:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681512</loc>
  <lastmod>2026-04-20T15:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的環境でゴール指向の自律性を示すチャットボット（On Chatbots Exhibiting Goal-Directed Autonomy in Dynamic Environments）</news:title>
   <news:publication_date>2026-04-20T15:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681510</loc>
  <lastmod>2026-04-20T15:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然勾配とテイラー近似を結ぶ共通枠組み（A Common Framework for Natural Gradient and Taylor based Optimisation using Manifold Theory）</news:title>
   <news:publication_date>2026-04-20T15:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681508</loc>
  <lastmod>2026-04-20T15:06:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移可能な属性・識別共同深層学習による教師なし人物再識別（Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification）</news:title>
   <news:publication_date>2026-04-20T15:06:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681506</loc>
  <lastmod>2026-04-20T15:06:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膨張黒鉛に埋め込まれたタンタル標的のスケール試作と陽子ビーム衝撃下の評価（Scaled prototype of a tantalum target embedded in expanded graphite for antiproton production）</news:title>
   <news:publication_date>2026-04-20T15:06:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681504</loc>
  <lastmod>2026-04-20T15:05:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習アーキテクチャにおける量子もつれの表現力（Quantum Entanglement in Deep Learning Architectures）</news:title>
   <news:publication_date>2026-04-20T15:05:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/681502</loc>
  <lastmod>2026-04-20T15:04:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短時間実行で不良設定を素早く打ち切るための方策学習（Algorithm Configuration: Learning policies for the quick termination of poor performers）</news:title>
   <news:publication_date>2026-04-20T15:04:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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