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   <news:title>患者依存性を排した特徴学習のための敵対的訓練（Adversarial Training for Patient-Independent Feature Learning with IVOCT Data for Plaque Classification）</news:title>
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   <news:title>合成非類似度測度とフィンガープリント測位への応用（CDM: Compound dissimilarity measure and an application to fingerprinting-based positioning）</news:title>
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   <news:title>軽量ピラミッドネットワークによる単一画像の雨除去（Lightweight Pyramid Networks for Image Deraining）</news:title>
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   <news:title>文脈的拡張によるテキストデータ増強（Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations）</news:title>
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    <news:language>ja</news:language>
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   <news:title>多関係ネットワークの構造表現学習（A Structural Representation Learning for Multi-relational Networks）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>DNSグラフマイニングにおけるアジリティバイアスの検証（Investigating the Agility Bias in DNS Graph Mining）</news:title>
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    <news:language>ja</news:language>
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   <news:title>単眼カメラとコンパクトセマンティックマップによる車両自己位置推定（Monocular Vehicle Self-localization method based on Compact Semantic Map）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>FollowNet：自然言語指示に従うロボット航行（FollowNet: Robot Navigation by Following Natural Language Directions with Deep Reinforcement Learning）</news:title>
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   <news:title>候補抽出と解答選択の共同学習による読解強化（Joint Training of Candidate Extraction and Answer Selection for Reading Comprehension）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>仮想エッジコンピューティングにおける最適化された計算オフロード性能（Optimized Computation Offloading Performance in Virtual Edge Computing Systems via Deep Reinforcement Learning）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>市場の自己学習とインビジブルハンド推論（Market Self-Learning of Signals, Impact and Optimal Trading: Invisible Hand Inference with Free Energy）</news:title>
   <news:publication_date>2026-05-05T01:40:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-05T01:40:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>可変計量過緩和ハイブリッド近接外勾配法のアルゴリズム枠組み（An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686596</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:title>特徴アフィニティに基づく疑似ラベリングによる半教師あり人物再識別（Feature Affinity based Pseudo-Labeling for Semi-supervised Person Re-identification）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686594</loc>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>画像ピラミッドでスケールを適応的に融合する群衆カウント法（Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid）</news:title>
   <news:publication_date>2026-05-05T00:37:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686592</loc>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>非負テンソル分解に基づく教師なし機械学習による反応性混合解析（Unsupervised Machine Learning Based on Non-Negative Tensor Factorization for Analyzing Reactive-Mixing）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686590</loc>
  <lastmod>2026-05-05T00:37:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>堅牢でプライバシー保護されたテキスト表現の学習（Towards Robust and Privacy-preserving Text Representations）</news:title>
   <news:publication_date>2026-05-05T00:37:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686588</loc>
  <lastmod>2026-05-05T00:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ドメインに含まれる要素とは（What’s in a Domain? Learning Domain-Robust Text Representations using Adversarial Training）</news:title>
   <news:publication_date>2026-05-05T00:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686586</loc>
  <lastmod>2026-05-04T23:44:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>協調的判別器による長文生成の改善（Learning to Write with Cooperative Discriminators）</news:title>
   <news:publication_date>2026-05-04T23:44:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686584</loc>
  <lastmod>2026-05-04T23:44:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ化クリッピング活性化による量子化ニューラルネットワーク（PACT: PARAMETERIZED CLIPPING ACTIVATION FOR QUANTIZED NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-05-04T23:44:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-04T23:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>シーン非依存な人物再識別の評価（An Evaluation of Deep CNN Baselines for Scene-Independent Person Re-Identiﬁcation）</news:title>
   <news:publication_date>2026-05-04T23:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-04T23:42:28Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>SoPaによるCNN・RNN・WFSAの橋渡し（SoPa: Bridging CNNs, RNNs, and Weighted Finite-State Machines）</news:title>
   <news:publication_date>2026-05-04T23:42:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686578</loc>
  <lastmod>2026-05-04T23:42:20Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ケック・ライマン連続スペクトル調査（KLCS）が示す高赤方偏移銀河のイオン化放射（THE KECK LYMAN CONTINUUM SPECTROSCOPIC SURVEY (KLCS): THE EMERGENT IONIZING SPECTRUM OF GALAXIES AT Z ∼3）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686576</loc>
  <lastmod>2026-05-04T23:42:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味ターゲット駆動ナビゲーションのための視覚表現（Visual Representations for Semantic Target Driven Navigation）</news:title>
   <news:publication_date>2026-05-04T23:42:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-04T23:41:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Spark-MPIが拓く第5のパラダイム（Spark-MPI: Approaching the Fifth Paradigm of Cognitive Applications）</news:title>
   <news:publication_date>2026-05-04T23:41:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-04T22:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交絡因子の因果効果共変（Causal-effect Covariability of Confounders）</news:title>
   <news:publication_date>2026-05-04T22:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686570</loc>
  <lastmod>2026-05-04T22:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習エージェントは意図をモデル化するか（Do deep reinforcement learning agents model intentions?）</news:title>
   <news:publication_date>2026-05-04T22:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686568</loc>
  <lastmod>2026-05-04T22:48:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移銀河のフィードバックを探る：拡張された紫外線光度関数による検証（Probing feedback in high-z galaxies using extended UV luminosity functions）</news:title>
   <news:publication_date>2026-05-04T22:48:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686566</loc>
  <lastmod>2026-05-04T22:47:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙初期の透明度を測る新しい指標――CHORUSによるz=7でのLyα輝線宇宙論的解析（CHORUS II. SUBARU/HSC DETERMINATION OF THE LYα LUMINOSITY FUNCTION AT Z = 7.0: CONSTRAINTS ON COSMIC REIONIZATION MODEL PARAMETER）</news:title>
   <news:publication_date>2026-05-04T22:47:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/686564</loc>
  <lastmod>2026-05-04T22:46:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイグナス領域に対する超高エネルギーγ線サーベイ（A VERY HIGH ENERGY γ-RAY SURVEY TOWARDS THE CYGNUS REGION OF THE GALAXY）</news:title>
   <news:publication_date>2026-05-04T22:46:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686562</loc>
  <lastmod>2026-05-04T22:46:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相秩序を教師なしで識別する方法（Identifying topological order through unsupervised machine learning）</news:title>
   <news:publication_date>2026-05-04T22:46:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686560</loc>
  <lastmod>2026-05-04T22:46:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二足歩行ロボットにおける動的歩行の単純化と制御分解（Dynamic Walking of Legged Machines）</news:title>
   <news:publication_date>2026-05-04T22:46:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686558</loc>
  <lastmod>2026-05-04T21:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深宇宙航法におけるX線パルサを用いた自律ナビゲーションの実現可能性（Feasibility and performance assessment of a practical autonomous deep space navigation system based on X-ray pulsar timing）</news:title>
   <news:publication_date>2026-05-04T21:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686556</loc>
  <lastmod>2026-05-04T21:53:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限状態・有限時間の平均場ゲームと学習収束の橋渡し（Finite mean field games: fictitious play and convergence to a first order continuous mean field game）</news:title>
   <news:publication_date>2026-05-04T21:53:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686554</loc>
  <lastmod>2026-05-04T21:52:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純な堆積モデルから学ぶ普遍性とスケーリング（Learning universality and scaling from simple deposition models）</news:title>
   <news:publication_date>2026-05-04T21:52:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686552</loc>
  <lastmod>2026-05-04T21:51:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Federated Learningにおける匿名性の崩壊とその制御（Understanding and Controlling Deanonymization in Federated Learning）</news:title>
   <news:publication_date>2026-05-04T21:51:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686550</loc>
  <lastmod>2026-05-04T21:51:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推論問題における「ハードフェーズ」のガラス性の解明（On the glassy nature of the hard phase in inference problems）</news:title>
   <news:publication_date>2026-05-04T21:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686548</loc>
  <lastmod>2026-05-04T21:51:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信念の濃淡を扱う社会的学習モデル（Naive Bayesian Learning in Social Networks）</news:title>
   <news:publication_date>2026-05-04T21:51:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686546</loc>
  <lastmod>2026-05-04T20:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球を「系外惑星」として観測する実証実験（Using Deep Space Climate Observatory Measurements to Study the Earth as An Exoplanet）</news:title>
   <news:publication_date>2026-05-04T20:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686544</loc>
  <lastmod>2026-05-04T20:58:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ信号のサンプリングを強化学習として解く（Graph Signal Sampling via Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-04T20:58:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686542</loc>
  <lastmod>2026-05-04T20:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合音声から直接読み取る 完全エンドツーエンド多人数音声認識（A Purely End-to-end System for Multi-speaker Speech Recognition）</news:title>
   <news:publication_date>2026-05-04T20:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686540</loc>
  <lastmod>2026-05-04T20:56:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子化可能な埋め込み表現の効率的なエンドツーエンド学習（Efficient end-to-end learning for quantizable representations）</news:title>
   <news:publication_date>2026-05-04T20:56:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686538</loc>
  <lastmod>2026-05-04T20:56:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的マルチスケールニューラルネットワークにおける継続学習（Continuous Learning in a Hierarchical Multiscale Neural Network）</news:title>
   <news:publication_date>2026-05-04T20:56:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686536</loc>
  <lastmod>2026-05-04T20:55:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表形式強化学習における人間知の活用（Leveraging human knowledge in tabular reinforcement learning）</news:title>
   <news:publication_date>2026-05-04T20:55:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686534</loc>
  <lastmod>2026-05-04T20:54:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頑健で効率的なグラフ対応転送による人物再識別（Robust and Efficient Graph Correspondence Transfer for Person Re-identification）</news:title>
   <news:publication_date>2026-05-04T20:54:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686532</loc>
  <lastmod>2026-05-04T20:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所鞍点最適化：曲率を利用した脱出手法（Local Saddle Point Optimization: A Curvature Exploitation Approach）</news:title>
   <news:publication_date>2026-05-04T20:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686530</loc>
  <lastmod>2026-05-04T20:00:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内在次元と連関ルールへの応用（Intrinsic dimension and its application to association rules）</news:title>
   <news:publication_date>2026-05-04T20:00:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686528</loc>
  <lastmod>2026-05-04T20:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的に使われる投票規則のプライバシーはどれほどか（How Private Are Commonly-Used Voting Rules?）</news:title>
   <news:publication_date>2026-05-04T20:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686526</loc>
  <lastmod>2026-05-04T20:00:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療文書の連続表現を生成する手法（Generating Continuous Representations of Medical Texts）</news:title>
   <news:publication_date>2026-05-04T20:00:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686524</loc>
  <lastmod>2026-05-04T19:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的適応忘却変分フィルタ（The Hierarchical Adaptive Forgetting Variational Filter）</news:title>
   <news:publication_date>2026-05-04T19:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686522</loc>
  <lastmod>2026-05-04T19:59:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布に基づくラベル空間変換によるマルチラベル学習（Distribution-based Label Space Transformation for Multi-label Learning）</news:title>
   <news:publication_date>2026-05-04T19:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686520</loc>
  <lastmod>2026-05-04T19:06:57Z</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による散乱光制御の実用化可能性（Light scattering control with neural networks in transmission and reflection）</news:title>
   <news:publication_date>2026-05-04T19:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686518</loc>
  <lastmod>2026-05-04T19:06:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的深層ハッシングのためのセマンティッククラスタ単一損失（Semantic Cluster Unary Loss for Efficient Deep Hashing）</news:title>
   <news:publication_date>2026-05-04T19:06:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686516</loc>
  <lastmod>2026-05-04T19:06:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NEURON: 自然言語で学ぶクエリ最適化（NEURON: Query Optimization Meets Natural Language Processing For Augmenting Database Education）</news:title>
   <news:publication_date>2026-05-04T19:06:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686514</loc>
  <lastmod>2026-05-04T19:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歪みに強い注目領域分割を実現するメトリック表現ネットワーク（Ro-SOS: Metric Expression Network for Robust Salient Object Segmentation）</news:title>
   <news:publication_date>2026-05-04T19:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686512</loc>
  <lastmod>2026-05-04T19:04:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロストラクチャ雑音下における非パラメトリックベイズ的ボラティリティ学習（Nonparametric Bayesian volatility learning under microstructure noise）</news:title>
   <news:publication_date>2026-05-04T19:04:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686510</loc>
  <lastmod>2026-05-04T19:04:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>悪意あるスクリプトのニューラル分類（Neural Classification of Malicious Scripts）</news:title>
   <news:publication_date>2026-05-04T19:04:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686508</loc>
  <lastmod>2026-05-04T19:04:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多モードファイバーを透かして見る学習（Learning to see through multimode fibers）</news:title>
   <news:publication_date>2026-05-04T19:04:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686506</loc>
  <lastmod>2026-05-04T18:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文体に敏感な単語ベクトルの教師なし学習（Unsupervised Learning of Style-sensitive Word Vectors）</news:title>
   <news:publication_date>2026-05-04T18:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686504</loc>
  <lastmod>2026-05-04T18:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正規表現とニューラルネットワークの結婚（Marrying Up Regular Expressions with Neural Networks）</news:title>
   <news:publication_date>2026-05-04T18:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686502</loc>
  <lastmod>2026-05-04T18:00:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Facebook投稿の影響度予測（Prediction of Facebook Post Metrics using Machine Learning）</news:title>
   <news:publication_date>2026-05-04T18:00:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686500</loc>
  <lastmod>2026-05-04T18:00:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセットが別でも学べる“つなぐ”設計――クロス接続ネットワークの可能性（Cross-connected Networks for Multi-task Learning of Detection and Segmentation）</news:title>
   <news:publication_date>2026-05-04T18:00:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686498</loc>
  <lastmod>2026-05-04T18:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔のランドマーク検出の体系的レビュー（Facial Landmark Detection: a Literature Survey）</news:title>
   <news:publication_date>2026-05-04T18:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686496</loc>
  <lastmod>2026-05-04T18:00:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響ランドマークを用いた多目的学習による資源乏しい言語のASR改善（Improved ASR for Under-Resourced Languages Through Multi-Task Learning with Acoustic Landmarks）</news:title>
   <news:publication_date>2026-05-04T18:00:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686494</loc>
  <lastmod>2026-05-04T17:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>世代学習で育てる深層ニューラルネットワーク（Training Deep Neural Networks in Generations: A More Tolerant Teacher Educates Better Students）</news:title>
   <news:publication_date>2026-05-04T17:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686492</loc>
  <lastmod>2026-05-04T17:00:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軌道フェッシュバッハ共鳴を用いた希土類フェルミ気体の単粒子励起と強結合効果（Single-particle Excitations and Strong Coupling Effects in the BCS-BEC Crossover Regime of a Rare-Earth Fermi Gas with an Orbital Feshbach Resonance）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686490</loc>
  <lastmod>2026-05-04T17:00:08Z</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>2026-05-04T17:00:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686488</loc>
  <lastmod>2026-05-04T16:59:00Z</lastmod>
  <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/686486</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: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>動的ニューラルネットワークによるロボットの新奇動作生成（A Dynamic Neural Network Approach to Generating Robot’s Novel Actions: A Simulation Experiment）</news:title>
   <news:publication_date>2026-05-04T16:58:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686482</loc>
  <lastmod>2026-05-04T16:57:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Radio Galaxy Zoo におけるラジオ源の銀河ホスト同定と機械学習による自動化（Radio Galaxy Zoo: Machine learning for radio source host galaxy cross-identification）</news:title>
   <news:publication_date>2026-05-04T16:57:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686480</loc>
  <lastmod>2026-05-04T16:06:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定境界を支持する敵対的サンプルを用いた知識蒸留（Knowledge Distillation with Adversarial Samples Supporting Decision Boundary）</news:title>
   <news:publication_date>2026-05-04T16:06:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686478</loc>
  <lastmod>2026-05-04T16:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験再生の進歩（Advances in Experience Replay）</news:title>
   <news:publication_date>2026-05-04T16:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686476</loc>
  <lastmod>2026-05-04T16:06:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識におけるパッチ間相関を学習する完全結合型1対Nマッチング手法（Fully Associative Patch-based 1-to-N Matcher for Face Recognition）</news:title>
   <news:publication_date>2026-05-04T16:06:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686474</loc>
  <lastmod>2026-05-04T16:05:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車両軌跡予測における畳み込みソーシャルプーリングの意義（Convolutional Social Pooling for Vehicle Trajectory Prediction）</news:title>
   <news:publication_date>2026-05-04T16:05:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686472</loc>
  <lastmod>2026-05-04T16:04:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形次元削減による複数データセットの判別分析（Nonlinear Dimensionality Reduction for Discriminative Analytics of Multiple Datasets）</news:title>
   <news:publication_date>2026-05-04T16:04:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686470</loc>
  <lastmod>2026-05-04T16:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインメトリック学習の多層フレームワーク（A Multilayer Framework for Online Metric Learning）</news:title>
   <news:publication_date>2026-05-04T16:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686468</loc>
  <lastmod>2026-05-04T16:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔画像のブレ除去を学ぶ（Learning to Deblur Images with Exemplars）</news:title>
   <news:publication_date>2026-05-04T16:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686466</loc>
  <lastmod>2026-05-04T15:12:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的多様性が情報カスケードを抑える仕組み（Social diversity for reducing the impact of information cascades on social learning）</news:title>
   <news:publication_date>2026-05-04T15:12:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686464</loc>
  <lastmod>2026-05-04T15:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルは本当に「質問」を理解しているか（Did the Model Understand the Question?）</news:title>
   <news:publication_date>2026-05-04T15:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686462</loc>
  <lastmod>2026-05-04T15:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Crowdbreaksによる公衆衛生トレンド追跡（Crowdbreaks: Tracking Health Trends using Public Social Media Data and Crowdsourcing）</news:title>
   <news:publication_date>2026-05-04T15:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686460</loc>
  <lastmod>2026-05-04T15:09:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑高次元データと限られたシミュレーション下の近似ベイズ計算に向けて（ABC-CDE: Towards Approximate Bayesian Computation with Complex High-Dimensional Data and Limited Simulations）</news:title>
   <news:publication_date>2026-05-04T15:09:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686458</loc>
  <lastmod>2026-05-04T15:09:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同質的リーマン多様体上のCNNとその神経画像への応用（A CNN for homogeneous Riemannian manifolds with applications to Neuroimaging）</news:title>
   <news:publication_date>2026-05-04T15:09:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686456</loc>
  <lastmod>2026-05-04T15:07:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SkyLensによる重力レンズ像シミュレーションの実務的意義（Image simulations for gravitational lensing with SkyLens）</news:title>
   <news:publication_date>2026-05-04T15:07:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686454</loc>
  <lastmod>2026-05-04T15:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Schema.org Actionsによる機械可読Web API（Machine Readable Web APIs with Schema.org Action Annotations）</news:title>
   <news:publication_date>2026-05-04T15:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686452</loc>
  <lastmod>2026-05-04T14:15:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブルの音声とIMUを融合したショット検出（WEARABLE AUDIO AND IMU BASED SHOT DETECTION IN RACQUET SPORTS）</news:title>
   <news:publication_date>2026-05-04T14:15:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686450</loc>
  <lastmod>2026-05-04T14:12:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランキング説明の忠実な手法（Faithfully Explaining Rankings in a News Recommender System）</news:title>
   <news:publication_date>2026-05-04T14:12:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686448</loc>
  <lastmod>2026-05-04T14:11:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー効率の高いハダマードニューラルネットワーク（Energy Efficient Hadamard Neural Networks）</news:title>
   <news:publication_date>2026-05-04T14:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686446</loc>
  <lastmod>2026-05-04T14:09:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意を取り入れた構造表現学習が変える視覚認識（Deep Attentional Structured Representation Learning for Visual Recognition）</news:title>
   <news:publication_date>2026-05-04T14:09:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686444</loc>
  <lastmod>2026-05-04T14:09:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼度スコアの白箱メタモデルと線形分類器プローブ（Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes）</news:title>
   <news:publication_date>2026-05-04T14:09:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686442</loc>
  <lastmod>2026-05-04T14:09:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>A La Carte Embeddingの実務的意義（A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors）</news:title>
   <news:publication_date>2026-05-04T14:09:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686440</loc>
  <lastmod>2026-05-04T14:08:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脊椎動物パラログにおける「親－子」関係の深い歴史の再構築（Reconstruction of the deep history of “Parent-Daughter” relationships among vertebrate paralogs）</news:title>
   <news:publication_date>2026-05-04T14:08:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686438</loc>
  <lastmod>2026-05-04T13:15:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間ベイズ・オンライン変化点検出とモデル選択（Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection）</news:title>
   <news:publication_date>2026-05-04T13:15:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686436</loc>
  <lastmod>2026-05-04T13:14:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AMORE-UPFのBiLSTMとエンティティライブラリ（AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library）</news:title>
   <news:publication_date>2026-05-04T13:14:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686434</loc>
  <lastmod>2026-05-04T13:14:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師ありデータで肺結節を検出するDeepEM（DeepEM: Deep 3D ConvNets With EM For Weakly Supervised Pulmonary Nodule Detection）</news:title>
   <news:publication_date>2026-05-04T13:14:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686432</loc>
  <lastmod>2026-05-04T13:12:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NASH: 生成的セマンティックハッシュのためのエンドツーエンドニューラルアーキテクチャ（NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing）</news:title>
   <news:publication_date>2026-05-04T13:12:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686430</loc>
  <lastmod>2026-05-04T13:12:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ALMAによるSCUBA-2サーベイのz∼4.5 [C II]候補検出（AN ALMA SURVEY OF THE SCUBA-2 COSMOLOGY LEGACY SURVEY UKIDSS/UDS FIELD: IDENTIFYING CANDIDATE z ∼4.5 [C II] EMITTERS）</news:title>
   <news:publication_date>2026-05-04T13:12:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686428</loc>
  <lastmod>2026-05-04T13:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ALMAによるSCUBA-2コスモロジーサーベイUDS領域のサブミリ波銀河数カウント（An ALMA survey of the SCUBA-2 Cosmology Legacy Survey UKIDSS/UDS field: Number counts of submillimeter galaxies）</news:title>
   <news:publication_date>2026-05-04T13:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686426</loc>
  <lastmod>2026-05-04T13:11:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SAR ATRのための検証支援付きCNN「SAVERS」の提案（SAR ATR with verification support (SAVERS))</news:title>
   <news:publication_date>2026-05-04T13:11:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686424</loc>
  <lastmod>2026-05-04T12:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データと人間の知見を活かした野生動物密猟予測（Exploiting Data and Human Knowledge for Predicting Wildlife Poaching）</news:title>
   <news:publication_date>2026-05-04T12:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686422</loc>
  <lastmod>2026-05-04T12:18:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化された材料特性計算の体系化（Automated computation of materials properties）</news:title>
   <news:publication_date>2026-05-04T12:18:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686420</loc>
  <lastmod>2026-05-04T12:17:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cycle-Dehazeによる単一画像のデヘイズ（Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing）</news:title>
   <news:publication_date>2026-05-04T12:17:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686418</loc>
  <lastmod>2026-05-04T12:16:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正規類似ネットワークによる生成モデリング（Normal Similarity Network for Generative Modelling）</news:title>
   <news:publication_date>2026-05-04T12:16:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686416</loc>
  <lastmod>2026-05-04T12:16:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子イオンコライダーで探るグルーオン・シベルス関数（Accessing the Gluon Sivers Function at a future Electron-Ion Collider）</news:title>
   <news:publication_date>2026-05-04T12:16:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686414</loc>
  <lastmod>2026-05-04T12:16:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>費用対効果の高い選好取得と集約の枠組み（A Cost-Effective Framework for Preference Elicitation and Aggregation）</news:title>
   <news:publication_date>2026-05-04T12:16:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686412</loc>
  <lastmod>2026-05-04T12:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電波宇宙の実践的シミュレーションが示したもの（The Tiered Radio Extragalactic Continuum Simulation (T-RECS)）</news:title>
   <news:publication_date>2026-05-04T12:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686410</loc>
  <lastmod>2026-05-04T11:24:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepMutation: 深層学習のためのミューテーションテスト（DeepMutation: Mutation Testing of Deep Learning Systems）</news:title>
   <news:publication_date>2026-05-04T11:24:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686408</loc>
  <lastmod>2026-05-04T11:23:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SHADE：情報ベースの正則化による深層学習の安定化（SHADE: INFORMATION-BASED REGULARIZATION FOR DEEP LEARNING）</news:title>
   <news:publication_date>2026-05-04T11:23:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686406</loc>
  <lastmod>2026-05-04T11:22:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変再構成可能な可視ナノフォトニクスによる深部脳神経刺激の新展開（A Reconfigurable Nanophotonics Platform for Sub-Millisecond, Deep Brain Neural Stimulation）</news:title>
   <news:publication_date>2026-05-04T11:22:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686404</loc>
  <lastmod>2026-05-04T11:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定木を組み込んだGANで学習を安定化する手法（Generative Adversarial Forests for Better Conditioned Adversarial Learning）</news:title>
   <news:publication_date>2026-05-04T11:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686402</loc>
  <lastmod>2026-05-04T11:20:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン適応における敵対的学習とグラフ埋め込みの統合（Domain Adaptation with Adversarial Training and Graph Embeddings）</news:title>
   <news:publication_date>2026-05-04T11:20:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686400</loc>
  <lastmod>2026-05-04T11:20:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情文の“翻訳”を非対向データで実現する方法（Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-05-04T11:20:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686398</loc>
  <lastmod>2026-05-04T11:20:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハリケーン災害時のTwitterデータ分析が示した実務的知見（A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria）</news:title>
   <news:publication_date>2026-05-04T11:20:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686396</loc>
  <lastmod>2026-05-04T10:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルネットワークにおける不正ドローン検知の機械学習的アプローチ（Rogue Drone Detection: A Machine Learning Approach）</news:title>
   <news:publication_date>2026-05-04T10:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686394</loc>
  <lastmod>2026-05-04T10:27:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な単一ショット3D細胞追跡を実現する深層学習法（Fast 3D cell tracking with wide-field fluorescence microscopy through deep learning）</news:title>
   <news:publication_date>2026-05-04T10:27:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686392</loc>
  <lastmod>2026-05-04T10:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモード光ファイバーを深層学習で制御する（Multimode Optical Fiber Transmission with a Deep Learning Network）</news:title>
   <news:publication_date>2026-05-04T10:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686390</loc>
  <lastmod>2026-05-04T10:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Functional Baby Talk: 初学者Haskellコードの誤り分析（Functional Baby Talk: Analysis of Code Fragments from Novice Haskell Programmers）</news:title>
   <news:publication_date>2026-05-04T10:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686388</loc>
  <lastmod>2026-05-04T10:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル処理を学ぶ構造的帰納法の入門（Vector Programming Using Structural Recursion）</news:title>
   <news:publication_date>2026-05-04T10:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686386</loc>
  <lastmod>2026-05-04T10:25:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Garrett近似を用いた非対称矩形井戸のエネルギー近似と応用（Garrett approximation for asymmetric rectangular potentials and its applications to quantum well infrared photodetectors）</news:title>
   <news:publication_date>2026-05-04T10:25:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686384</loc>
  <lastmod>2026-05-04T10:24:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lasso-Zeroによるモデル選択：過剰適合と閾値で針を見つける（Model selection with Lasso-Zero: adding straw to the haystack to better find needles）</news:title>
   <news:publication_date>2026-05-04T10:24:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686382</loc>
  <lastmod>2026-05-04T09:33:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェア・ソフトウェア協調によるニューラルネットワーク攻撃フレームワーク（Hu-Fu: Hardware and Software Collaborative Attack Framework against Neural Networks）</news:title>
   <news:publication_date>2026-05-04T09:33:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686380</loc>
  <lastmod>2026-05-04T09:31:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>σ Orionis星団の視差と固有運動の網羅的測定（Parallactic distances and proper motions of virtually all stars in the σ Orionis cluster）</news:title>
   <news:publication_date>2026-05-04T09:31:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686378</loc>
  <lastmod>2026-05-04T09:31:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rによるハイパースペクトルデータ解析を現場へ橋渡しするhsdarの意義（hsdar: Hyperspectral Data Analysis in R）</news:title>
   <news:publication_date>2026-05-04T09:31:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686376</loc>
  <lastmod>2026-05-04T09:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Atlas Location Autocontextによる3D CTランドマーク検出の到達点（Attaining human-level performance with atlas location autocontext for anatomical landmark detection in 3D CT data）</news:title>
   <news:publication_date>2026-05-04T09:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686374</loc>
  <lastmod>2026-05-04T09:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物語的イベント進化グラフによる脚本イベント予測（Constructing Narrative Event Evolutionary Graph for Script Event Prediction）</news:title>
   <news:publication_date>2026-05-04T09:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686372</loc>
  <lastmod>2026-05-04T09:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KL-UCB-Switchの二重最適性（KL-UCB-Switch: Optimal Regret Bounds for Stochastic Bandits from Both a Distribution-Dependent and a Distribution-Free Viewpoints）</news:title>
   <news:publication_date>2026-05-04T09:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686370</loc>
  <lastmod>2026-05-04T09:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生映像から学ぶ直感的物理学（Unsupervised Intuitive Physics from Visual Observations）</news:title>
   <news:publication_date>2026-05-04T09:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686368</loc>
  <lastmod>2026-05-04T08:38:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラッソを用いた処置効果推定の有限標本性能（The Finite Sample Performance of Treatment Effects Estimators based on the Lasso）</news:title>
   <news:publication_date>2026-05-04T08:38:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686366</loc>
  <lastmod>2026-05-04T08:38:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子QCDとハミルトン有効場理論による核子励起状態の解析（Nucleon Excited States from Lattice QCD and Hamiltonian Effective Field Theory）</news:title>
   <news:publication_date>2026-05-04T08:38:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686364</loc>
  <lastmod>2026-05-04T08:38:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河団強レンズ像が示す超大質量ブラックホールの直接測定（A LIKELY SUPER MASSIVE BLACK HOLE REVEALED BY ITS EINSTEIN RADIUS IN HUBBLE FRONTIER FIELDS IMAGES）</news:title>
   <news:publication_date>2026-05-04T08:38:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686362</loc>
  <lastmod>2026-05-04T08:38:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分ベイズによる混合モデルの推定とモデル選択の一貫性（Consistency of Variational Bayes Inference for Estimation and Model Selection in Mixtures）</news:title>
   <news:publication_date>2026-05-04T08:38:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686360</loc>
  <lastmod>2026-05-04T08:37:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密度推定に基づくワン・クラス決定木（A One-Class Classification Decision Tree Based on Kernel Density Estimation）</news:title>
   <news:publication_date>2026-05-04T08:37:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686358</loc>
  <lastmod>2026-05-04T08:36:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を備えた深層学習による自動睡眠段階分類（A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification）</news:title>
   <news:publication_date>2026-05-04T08:36:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686356</loc>
  <lastmod>2026-05-04T08:36:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習の基礎と実務的理解（Machine Learning: The Basics）</news:title>
   <news:publication_date>2026-05-04T08:36:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686354</loc>
  <lastmod>2026-05-04T07:44:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DualCNNによる低レベルビジョンの再定義（Learning Dual Convolutional Neural Networks for Low-Level Vision）</news:title>
   <news:publication_date>2026-05-04T07:44:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686352</loc>
  <lastmod>2026-05-04T07:44:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェネレーターネットワークによるActive Appearance Model再現（Replicating Active Appearance Model by Generator Network）</news:title>
   <news:publication_date>2026-05-04T07:44:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686350</loc>
  <lastmod>2026-05-04T07:43:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変化に敏感な敵対的サンプルを見抜く――Mutation Testingによる検知法（Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing）</news:title>
   <news:publication_date>2026-05-04T07:43:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686348</loc>
  <lastmod>2026-05-04T07:43:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>避難訓練における没入型バーチャルリアリティを活用したシリアスゲームの体系的レビュー（Immersive Virtual Reality Serious Games for Evacuation Training and Research: A Systematic Literature Review）</news:title>
   <news:publication_date>2026-05-04T07:43:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686346</loc>
  <lastmod>2026-05-04T07:43:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的マルチエージェント軌跡からの識別的辞書学習のための深い決定木（Deep Decision Trees for Discriminative Dictionary Learning with Adversarial Multi-Agent Trajectories）</news:title>
   <news:publication_date>2026-05-04T07:43:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686344</loc>
  <lastmod>2026-05-04T07:43:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ショックとICMEの複合構造が地磁気嵐を増幅する仕組み（Why the Shock-ICME Complex Structure is Important: Learning From the Early 2007 September CMEs）</news:title>
   <news:publication_date>2026-05-04T07:43:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686342</loc>
  <lastmod>2026-05-04T06:51:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語と構文が紡ぐ仮説──子どもの語学習における統語–意味のオーバーハイポセシス（Word learning and the acquisition of syntactic–semantic overhypotheses）</news:title>
   <news:publication_date>2026-05-04T06:51:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686340</loc>
  <lastmod>2026-05-04T06:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノードの“中身”を埋め込む時代へ — 異種ネットワークのためのコンテント対応表現学習（CARL: Content-Aware Representation Learning for Heterogeneous Networks）</news:title>
   <news:publication_date>2026-05-04T06:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686338</loc>
  <lastmod>2026-05-04T06:51:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多次元周期カーネルを近似する指標集合フーリエ級数特徴（Index Set Fourier Series Features for Approximating Multi-dimensional Periodic Kernels）</news:title>
   <news:publication_date>2026-05-04T06:51:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686336</loc>
  <lastmod>2026-05-04T06:50:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存の学習済み深層ニューラルネットワークの統合とマージ（Unifying and Merging Well-trained Deep Neural Networks for Inference Stage）</news:title>
   <news:publication_date>2026-05-04T06:50:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686334</loc>
  <lastmod>2026-05-04T06:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非矩形スキャンにおける走査透過電子顕微鏡の圧縮センシング（Compressed Sensing of Scanning Transmission Electron Microscopy (STEM) on Non-Rectangular Scans）</news:title>
   <news:publication_date>2026-05-04T06:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686332</loc>
  <lastmod>2026-05-04T06:49:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAP推論におけるメッセージ伝播の高速化とBenders分解（Accelerating Message Passing for MAP with Benders Decomposition）</news:title>
   <news:publication_date>2026-05-04T06:49:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686330</loc>
  <lastmod>2026-05-04T06:49:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列戦略関係を学習する生成的敵対的模倣学習（Learning Temporal Strategic Relationships using Generative Adversarial Imitation Learning）</news:title>
   <news:publication_date>2026-05-04T06:49:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686328</loc>
  <lastmod>2026-05-04T05:58:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>浅い線形ニューラルネットワークの最適化幾何学（The Global Optimization Geometry of Shallow Linear Neural Networks）</news:title>
   <news:publication_date>2026-05-04T05:58:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686326</loc>
  <lastmod>2026-05-04T05:50:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低域通過リカレントニューラルネットワーク（Low-pass Recurrent Neural Networks – A memory architecture for longer-term correlation discovery）</news:title>
   <news:publication_date>2026-05-04T05:50:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686324</loc>
  <lastmod>2026-05-04T05:50:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dセマンティック地図を用いた同時自己位置推定とセグメンテーション（DeLS-3D: Deep Localization and Segmentation with a 3D Semantic Map）</news:title>
   <news:publication_date>2026-05-04T05:50:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686322</loc>
  <lastmod>2026-05-04T05:50:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像改ざん検出のためのリッチ特徴学習（Learning Rich Features for Image Manipulation Detection）</news:title>
   <news:publication_date>2026-05-04T05:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686320</loc>
  <lastmod>2026-05-04T05:48:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像キャプショニング（Image Captioning）</news:title>
   <news:publication_date>2026-05-04T05:48:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686318</loc>
  <lastmod>2026-05-04T05:48:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dyna：確率的最適化のための運動量法（Dyna: A Method of Momentum for Stochastic Optimization）</news:title>
   <news:publication_date>2026-05-04T05:48:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686316</loc>
  <lastmod>2026-05-04T05:47:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不可能を可能にする理由：ニューラルネットワークはなぜ学習できるのか（Doing the impossible: Why neural networks can be trained at all）</news:title>
   <news:publication_date>2026-05-04T05:47:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686314</loc>
  <lastmod>2026-05-04T04:55:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張可能なニューラル行列補完（EXTENDABLE NEURAL MATRIX COMPLETION）</news:title>
   <news:publication_date>2026-05-04T04:55:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686312</loc>
  <lastmod>2026-05-04T04:44:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑系における階層構造の出現と進化（Emergence and Evolution of Hierarchical Structure in Complex Systems）</news:title>
   <news:publication_date>2026-05-04T04:44:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686310</loc>
  <lastmod>2026-05-04T04:44:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種走行データベースの統合を目指す研究──交通プリミティブによるデータ統一（A Tempt to Unify Heterogeneous Driving Databases using Traffic Primitives）</news:title>
   <news:publication_date>2026-05-04T04:44:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686308</loc>
  <lastmod>2026-05-04T04:44:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lehmer変換とその理論的性質（Lehmer Transform and Its Theoretical Properties）</news:title>
   <news:publication_date>2026-05-04T04:44:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686306</loc>
  <lastmod>2026-05-04T04:43:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>氷嵐を計算で捉える枠組み（A Computational Framework for Modelling and Analyzing Ice Storms）</news:title>
   <news:publication_date>2026-05-04T04:43:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686304</loc>
  <lastmod>2026-05-04T03:52:02Z</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非線形微分方程式の一般解法（General solutions for nonlinear differential equations: a rule-based self-learning approach using deep reinforcement learning）</news:title>
   <news:publication_date>2026-05-04T03:52:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686302</loc>
  <lastmod>2026-05-04T03:51:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共同検出とクラスタリングによるニューラル共参照解決（Neural Coreference Resolution with Deep Biaffine Attention by Joint Mention Detection and Mention Clustering）</news:title>
   <news:publication_date>2026-05-04T03:51:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686300</loc>
  <lastmod>2026-05-04T03:50:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Spark-MPIによる準リアルタイム処理パイプラインの構築（Building Near-Real-Time Processing Pipelines with the Spark-MPI Platform）</news:title>
   <news:publication_date>2026-05-04T03:50:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686298</loc>
  <lastmod>2026-05-04T03:50:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ応答のためのオンザフライ表生成（On-the-fly Table Generation）</news:title>
   <news:publication_date>2026-05-04T03:50:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686296</loc>
  <lastmod>2026-05-04T03:50:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字列カーネルで方言を見抜く手法の勝因（UnibucKernel Reloaded）</news:title>
   <news:publication_date>2026-05-04T03:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686294</loc>
  <lastmod>2026-05-04T02:58:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>要約自己符号化器による表現監督 — Chinese Social Media Text Summarization（Autoencoder as Assistant Supervisor: Improving Text Representation for Chinese Social Media Text Summarization）</news:title>
   <news:publication_date>2026-05-04T02:58:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686292</loc>
  <lastmod>2026-05-04T02:58:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔表情認識のための共分散プーリング（Covariance Pooling for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-05-04T02:58:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686290</loc>
  <lastmod>2026-05-04T02:57:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門家は皆同じくらい優れているか？アナリスト業績予測の評価（Are All Experts Equally Good? A Study of Analyst Earnings Estimates）</news:title>
   <news:publication_date>2026-05-04T02:57:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686288</loc>
  <lastmod>2026-05-04T02:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア工学における深層学習の実務的意義（Deep Learning in Software Engineering）</news:title>
   <news:publication_date>2026-05-04T02:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686286</loc>
  <lastmod>2026-05-04T02:56:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンドメイン対話システムにおける質問生成の型付きデコーダ学習（Learning to Ask Questions in Open-domain Conversational Systems with Typed Decoders）</news:title>
   <news:publication_date>2026-05-04T02:56:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686284</loc>
  <lastmod>2026-05-04T02:04:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的品揃え最適化の最適方策（An Optimal Policy for Dynamic Assortment Planning Under Uncapacitated Multinomial Logit Models）</news:title>
   <news:publication_date>2026-05-04T02:04:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686282</loc>
  <lastmod>2026-05-04T01:58:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性推定攻撃に対する実践的防御法：AttriGuardの要点と経営的含意 (AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning)</news:title>
   <news:publication_date>2026-05-04T01:58:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686280</loc>
  <lastmod>2026-05-04T01:57:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zero-Shot Dialog Generation with Cross-Domain Latent Actions（Zero-Shot Dialog Generation with Cross-Domain Latent Actions）</news:title>
   <news:publication_date>2026-05-04T01:57:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686278</loc>
  <lastmod>2026-05-04T01:57:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カリキュラム敵対的訓練（Curriculum Adversarial Training）</news:title>
   <news:publication_date>2026-05-04T01:57:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686276</loc>
  <lastmod>2026-05-04T01:55:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>述語と項を同時に予測するニューラル意味役割付与（Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling）</news:title>
   <news:publication_date>2026-05-04T01:55:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686274</loc>
  <lastmod>2026-05-04T01:55:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習のための引用データセットと参照文字列からの要素抽出（Citation Data-set for Machine Learning Citation Styles and Entity Extraction from Citation Strings）</news:title>
   <news:publication_date>2026-05-04T01:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686272</loc>
  <lastmod>2026-05-04T01:55:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学物理教育における学習の公平性を問う（Equity in College Physics Student Learning: a Critical Quantitative Intersectionality Investigation）</news:title>
   <news:publication_date>2026-05-04T01:55:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686270</loc>
  <lastmod>2026-05-04T01:02:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティックセグメンテーションにおける畳み込みCRFの実用化（Convolutional CRFs for Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-04T01:02:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686268</loc>
  <lastmod>2026-05-04T01:02:01Z</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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   <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: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:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドを使った増分学習フレームワーク（Incremental Learning Framework Using Cloud Computing）</news:title>
   <news:publication_date>2026-05-04T00:58:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686256</loc>
  <lastmod>2026-05-04T00:07:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習と認知アーキテクチャによるリアルタイム再スケジューリング（Generating Rescheduling Knowledge using Reinforcement Learning in a Cognitive Architecture）</news:title>
   <news:publication_date>2026-05-04T00:07:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/686254</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>SOARを用いたリアルタイム再スケジューリングの認知的アプローチ（A Cognitive Approach to Real-time Rescheduling using SOAR-RL）</news:title>
   <news:publication_date>2026-05-04T00:06:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686252</loc>
  <lastmod>2026-05-04T00:05:40Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張されたコンテンツベースの特徴エンジニアリングパイプライン（EXTENDED PIPELINE FOR CONTENT-BASED FEATURE ENGINEERING IN MUSIC GENRE RECOGNITION）</news:title>
   <news:publication_date>2026-05-04T00:05:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同意率初期化最尤推定器による分類器アンサンブルの統合（Agreement Rate Initialized Maximum Likelihood Estimator for Ensemble Classifier Aggregation and Its Application in Brain-Computer Interface）</news:title>
   <news:publication_date>2026-05-04T00:04:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686248</loc>
  <lastmod>2026-05-04T00:04:15Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGを用いた運転者の眠気推定とEBMAL（Enhanced Batch-Mode Active Learning）</news:title>
   <news:publication_date>2026-05-04T00:04:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/686246</loc>
  <lastmod>2026-05-04T00:04:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフラインBCIキャリブレーションのための能動半教師付き転移学習（Active Semi-supervised Transfer Learning (ASTL) for Offline BCI Calibration）</news:title>
   <news:publication_date>2026-05-04T00:04:03Z</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>強化学習のハイパーパラメータ自動設定（Towards Autonomous Reinforcement Learning: Automatic Setting of Hyper-parameters using Bayesian Optimization）</news:title>
   <news:publication_date>2026-05-04T00:03:34Z</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>外れ値は協調学習を台無しにするか（Do Outliers Ruin Collaboration?）</news:title>
   <news:publication_date>2026-05-03T23:11:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/686240</loc>
  <lastmod>2026-05-03T23:03:05Z</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>2026-05-03T23:03:05Z</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>物体中心とシーン中心のCNN特徴の相補性がもたらす変化（Exploring object-centric and scene-centric CNN features and their complementarity for human rights violations recognition in images）</news:title>
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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>
  <loc>https://aibr.jp/archives/686234</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>2026-05-03T23:00:49Z</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>2026-05-03T23:00:30Z</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>
  <loc>https://aibr.jp/archives/686228</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>AdvEntuRe: 知識誘導型生成を用いたテキスト含意の敵対的学習（AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples）</news:title>
   <news:publication_date>2026-05-03T22:00:34Z</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>一般相対論的磁気流体力学シミュレーションによる相対論的ジェットの多波長観測（Multiwavelength Observations of Relativistic Jets from General Relativistic Magnetohydrodynamic Simulations）</news:title>
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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>2026-05-03T21:59:49Z</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>明瞭化質問のランク付けで対話の質を上げる（Learning to Ask Good Questions: Ranking Clarification Questions using Neural Expected Value of Perfect Information）</news:title>
   <news:publication_date>2026-05-03T21:58:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686220</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>学習によって変わる「知覚」の神経基盤（Neural correlates of learned categorical perception）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/686218</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>2026-05-03T21:06:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-03T21:06:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>硬い粒子の運動における初期境界値問題 II：非一意性に関する研究 (On the Initial Boundary-Value Problem in the Kinetic Theory of Hard Particles II: Non-uniqueness)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-03T21:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterユーザーの位置推定を深層マルチビュー学習で行う（Twitter User Geolocation using Deep Multiview Learning）</news:title>
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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>
   <news:title>欠測値を含むロジスティック回帰の統一的扱い（Logistic Regression with Missing Covariates – Parameter Estimation, Model Selection and Prediction within a Joint-Modeling Framework）</news:title>
   <news:publication_date>2026-05-03T21:05:30Z</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>高速で確率的なディフェオモルフィック画像登録の無監督学習（Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration）</news:title>
   <news:publication_date>2026-05-03T21:05:21Z</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>二重埋め込みとCNNによるアスペクト抽出（Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction）</news:title>
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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>
   <news:title>テキスト領域で「問い合わせ生成」を行う手法の要点（Textual Membership Queries）</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>
   </news:publication>
   <news:title>時系列フローフィールドによる多人数姿勢追跡の実装的意義（JointFlow: Temporal Flow Fields for Multi-Person Pose Tracking）</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>
   </news:publication>
   <news:title>ブール代数に基づく確率的テンソル分解の実装と有用性（TensOrMachine: Probabilistic Boolean Tensor Decomposition）</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>
   </news:publication>
   <news:title>τ崩壊による二中間子生成の体系化（τ −→ντM1M2, with M1, M2 pseudoscalar or vector mesons）</news:title>
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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>拡張畳み込みを見直す：弱教師あり・半教師ありセマンティックセグメンテーションへの単純アプローチ（Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation）</news:title>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差境界条件に適応するERMと確率近似の高速収束（Fast Rates of ERM and Stochastic Approximation）</news:title>
   <news:publication_date>2026-05-03T20:12:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/686194</loc>
  <lastmod>2026-05-03T20:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計モデルと意味モデルを組み合わせた多文書要約（Using Statistical and Semantic Models for Multi-Document Summarization）</news:title>
   <news:publication_date>2026-05-03T20:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686192</loc>
  <lastmod>2026-05-03T19:20:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によって生じるカテゴリ知覚（Learning-induced categorical perception in a neural network model）</news:title>
   <news:publication_date>2026-05-03T19:20:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686190</loc>
  <lastmod>2026-05-03T19:19:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質結晶化X線画像の分類にCNNを使う効能（Classification of Protein Crystallization X-Ray Images Using Major Convolutional Neural Network Architectures）</news:title>
   <news:publication_date>2026-05-03T19:19:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686188</loc>
  <lastmod>2026-05-03T19:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ContextNetによる文脈と詳細の両立で実用化するリアルタイム意味分割（ContextNet: Exploring Context and Detail for Semantic Segmentation in Real-time）</news:title>
   <news:publication_date>2026-05-03T19:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686186</loc>
  <lastmod>2026-05-03T19:18:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コホモロジー定式化における欠落したビアンキ恒等式（On Missing Bianchi Identities in Cohomology Formulation）</news:title>
   <news:publication_date>2026-05-03T19:18:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686184</loc>
  <lastmod>2026-05-03T19:18:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河団中心における最も明るい銀河の協調的組み立て（Coordinated Assembly of Brightest Cluster Galaxies）</news:title>
   <news:publication_date>2026-05-03T19:18:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686182</loc>
  <lastmod>2026-05-03T19:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボリューム型深層畳み込みニューラルネットワークによるダークマターハロー模擬カタログ生成（A volumetric deep Convolutional Neural Network for simulation of mock dark matter halo catalogues）</news:title>
   <news:publication_date>2026-05-03T19:18:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686180</loc>
  <lastmod>2026-05-03T19:17:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインバンディット線形最適化の基礎とSCRiBLe（ONLINE BANDIT LINEAR OPTIMIZATION: A STUDY）</news:title>
   <news:publication_date>2026-05-03T19:17:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686178</loc>
  <lastmod>2026-05-03T18:26:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタラクティブ強化学習における既存知識の動的再利用（Interactive Reinforcement Learning with Dynamic Reuse of Prior Knowledge）</news:title>
   <news:publication_date>2026-05-03T18:26:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686176</loc>
  <lastmod>2026-05-03T18:26:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地下フォーラムの私的やり取りを予測する方法（Under the Underground: Predicting Private Interactions in Underground Forums）</news:title>
   <news:publication_date>2026-05-03T18:26:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686174</loc>
  <lastmod>2026-05-03T18:25:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情解析システムに潜む性別・人種バイアスの実態（Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems）</news:title>
   <news:publication_date>2026-05-03T18:25:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686172</loc>
  <lastmod>2026-05-03T18:24:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー収穫型IoTにおけるアクセス制御とバッテリ予測の強化学習的統合（Reinforcement Learning based Multi-Access Control and Battery Prediction with Energy Harvesting in IoT Systems）</news:title>
   <news:publication_date>2026-05-03T18:24:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686170</loc>
  <lastmod>2026-05-03T18:24:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続的インテグレーションの設定を静的に検証する（Statically Verifying Continuous Integration Configurations）</news:title>
   <news:publication_date>2026-05-03T18:24:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686168</loc>
  <lastmod>2026-05-03T18:24:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学校におけるアプリ作成教育の実践と示唆（APP CREATION IN SCHOOLS FOR DIFFERENT CURRICULA SUBJECTS - LESSONS LEARNED）</news:title>
   <news:publication_date>2026-05-03T18:24:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686166</loc>
  <lastmod>2026-05-03T18:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pocket Game Jams：学校における構成主義的アプローチ（Pocket Game Jams: a Constructionist Approach at Schools）</news:title>
   <news:publication_date>2026-05-03T18:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686164</loc>
  <lastmod>2026-05-03T17:32:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲームジャムが育む計算思考と非公式学習の力（THE ROLE OF GAME JAMS IN DEVELOPING INFORMAL LEARNING OF COMPUTATIONAL THINKING: A CROSS-EUROPEAN CASE STUDY）</news:title>
   <news:publication_date>2026-05-03T17:32:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686162</loc>
  <lastmod>2026-05-03T17:32:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲーム開発を通じた学習とジェンダー差（Game Development-Based Learning Experience: Gender Differences in Game Design）</news:title>
   <news:publication_date>2026-05-03T17:32:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686160</loc>
  <lastmod>2026-05-03T17:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手術中データ埋め込み解析による急性腎障害予測の向上（Improved Predictive Models for Acute Kidney Injury with IDEAs: Intraoperative Data Embedded Analytics）</news:title>
   <news:publication_date>2026-05-03T17:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686158</loc>
  <lastmod>2026-05-03T17:31:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小マゼラン雲の空間分解星形成履歴の再構築（The spatially resolved star formation history of the main body of the Small Magellanic Cloud）</news:title>
   <news:publication_date>2026-05-03T17:31:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686156</loc>
  <lastmod>2026-05-03T17:31:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自発性電位間隔の分布に関して（On the distribution of spontaneous potentials intervals in nervous transmission）</news:title>
   <news:publication_date>2026-05-03T17:31:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686154</loc>
  <lastmod>2026-05-03T17:31:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学校におけるプログラミング活動を支援するゲームテンプレートの評価（Evaluation of Game Templates to support Programming Activities in Schools）</news:title>
   <news:publication_date>2026-05-03T17:31:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686152</loc>
  <lastmod>2026-05-03T16:40:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交通標識検出におけるカプセルネットワークの提案（Novel Deep Learning Model for Traffic Sign Detection Using Capsule Networks）</news:title>
   <news:publication_date>2026-05-03T16:40:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686150</loc>
  <lastmod>2026-05-03T16:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正規化ワッサースタイン距離による越境文書検索（Cross-lingual Document Retrieval using Regularized Wasserstein Distance）</news:title>
   <news:publication_date>2026-05-03T16:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686148</loc>
  <lastmod>2026-05-03T16:40:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公共行政研究における機械学習と組織評判の計測（Machine Learning for Public Administration Research, with Application to Organizational Reputation）</news:title>
   <news:publication_date>2026-05-03T16:40:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686146</loc>
  <lastmod>2026-05-03T16:39:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感覚運動的視点から見る視覚特徴の基底付け（A Sensorimotor Perspective on Grounding the Semantic of Simple Visual Features）</news:title>
   <news:publication_date>2026-05-03T16:39:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686144</loc>
  <lastmod>2026-05-03T16:39:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測マルコフ決定過程における深い階層型強化学習（Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes）</news:title>
   <news:publication_date>2026-05-03T16:39:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686142</loc>
  <lastmod>2026-05-03T16:39:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復学習で支援する対話型画像分割（Iteratively Trained Interactive Segmentation）</news:title>
   <news:publication_date>2026-05-03T16:39:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686140</loc>
  <lastmod>2026-05-03T16:38:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PAD-Netによる同時深度推定とシーン解析の統合（PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing）</news:title>
   <news:publication_date>2026-05-03T16:38:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686138</loc>
  <lastmod>2026-05-03T15:47:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>力覚相互作用スキルの評価を学習する手法（Learning Movement Assessment Primitives for Force Interaction Skills）</news:title>
   <news:publication_date>2026-05-03T15:47:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686136</loc>
  <lastmod>2026-05-03T15:39:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構による弱教師ありドメイン特化色名推定（Weakly Supervised Domain-Specific Color Naming Based on Attention）</news:title>
   <news:publication_date>2026-05-03T15:39:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686134</loc>
  <lastmod>2026-05-03T15:39:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像を活用して動画認識を強化する階層型生成対抗ネットワーク（Exploiting Images for Video Recognition with Hierarchical Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-03T15:39:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686132</loc>
  <lastmod>2026-05-03T15:38:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>女性ティーンとコーディング：性差に配慮した創造的学習環境（Female Teenagers and Coding: Create Gender Sensitive and Creative Learning Environments）</news:title>
   <news:publication_date>2026-05-03T15:38:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686130</loc>
  <lastmod>2026-05-03T15:38:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pocket Codeを用いたゲームデザインが学校の学びを変える（Game Design with Pocket Code: Providing a Constructionist Environment for Girls in the School Context）</news:title>
   <news:publication_date>2026-05-03T15:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686128</loc>
  <lastmod>2026-05-03T15:38:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超信頼・低遅延V2V通信におけるフェデレーテッド学習の実装と意義（Federated Learning for Ultra-Reliable Low-Latency V2V Communications）</news:title>
   <news:publication_date>2026-05-03T15:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686126</loc>
  <lastmod>2026-05-03T15:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ML搭載自律システムのための定量的k投影カバレッジ（Quantitative Projection Coverage for Testing ML-enabled Autonomous Systems）</news:title>
   <news:publication_date>2026-05-03T15:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686124</loc>
  <lastmod>2026-05-03T14:46:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所銀河群の若い矮小銀河レオAにおける統合光解析と色等級図の比較（Integrated-light analyses vs. colour-magnitude diagrams - II. Leo A, an extremely young dwarf in the Local Group）</news:title>
   <news:publication_date>2026-05-03T14:46:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686122</loc>
  <lastmod>2026-05-03T14:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルなパターンベース最適化への道（Towards scalable pattern-based optimization for dense linear algebra）</news:title>
   <news:publication_date>2026-05-03T14:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686120</loc>
  <lastmod>2026-05-03T14:44:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数の例から細かなカテゴリを識別する仕組みを作る（Piecewise classifier mappings: Learning fine-grained learners for novel categories with few examples）</news:title>
   <news:publication_date>2026-05-03T14:44:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686118</loc>
  <lastmod>2026-05-03T14:44:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習を使ったO(N)ソートアルゴリズム（An O(N) Sorting Algorithm: Machine Learning Sort）</news:title>
   <news:publication_date>2026-05-03T14:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686116</loc>
  <lastmod>2026-05-03T14:44:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空中映像におけるエイ（stingray）検出と合成データ増強（Stingray Detection of Aerial Images Using Augmented Training Images）</news:title>
   <news:publication_date>2026-05-03T14:44:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686114</loc>
  <lastmod>2026-05-03T14:43:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文法と強化学習を活用したニューラルプログラム合成（LEVERAGING GRAMMAR AND REINFORCEMENT LEARNING FOR NEURAL PROGRAM SYNTHESIS）</news:title>
   <news:publication_date>2026-05-03T14:43:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686112</loc>
  <lastmod>2026-05-03T14:43:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルによるオープン情報抽出（Neural Open Information Extraction）</news:title>
   <news:publication_date>2026-05-03T14:43:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686110</loc>
  <lastmod>2026-05-03T13:52:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み機器における深層学習モデルの適応的選択（Adaptive Selection of Deep Learning Models on Embedded Systems）</news:title>
   <news:publication_date>2026-05-03T13:52:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686108</loc>
  <lastmod>2026-05-03T13:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PALM: データストリーム回帰のためのハイパープレーン逐次構築（PALM: An Incremental Construction of Hyperplanes for Data Stream Regression）</news:title>
   <news:publication_date>2026-05-03T13:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686106</loc>
  <lastmod>2026-05-03T13:41:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸最適化に基づくスペクトルクラスタリング（Convex Programming Based Spectral Clustering）</news:title>
   <news:publication_date>2026-05-03T13:41:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686104</loc>
  <lastmod>2026-05-03T13:41:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散Deep Forestと大規模不正検知への応用（Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud）</news:title>
   <news:publication_date>2026-05-03T13:41:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686102</loc>
  <lastmod>2026-05-03T13:40:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模非滑らか凸最適化のためのランダム化平滑化SVRG（Randomized Smoothing SVRG for Large-scale Nonsmooth Convex Optimization）</news:title>
   <news:publication_date>2026-05-03T13:40:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686100</loc>
  <lastmod>2026-05-03T13:40:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リスク志向マルコフ意思決定過程の確率近似法（Stochastic approximation for risk-aware Markov decision processes）</news:title>
   <news:publication_date>2026-05-03T13:40:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686098</loc>
  <lastmod>2026-05-03T13:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイリンガル資源が乏しい状況におけるニューラル機械翻訳：深層マルチタスク学習アプローチ（Neural Machine Translation for Bilingually Scarce Scenarios: A Deep Multi-task Learning Approach）</news:title>
   <news:publication_date>2026-05-03T13:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686096</loc>
  <lastmod>2026-05-03T12:49:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフレットとnode2vec/struc2vecの比較：ネットワークアラインメントにおける性能検証（Graphlets versus node2vec and struc2vec in the task of network alignment）</news:title>
   <news:publication_date>2026-05-03T12:49:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686094</loc>
  <lastmod>2026-05-03T12:48:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>家庭用給湯器群を使った需要応答の実運用手法（Trajectory Tracking with an Aggregation of Domestic Hot Water Heaters: Combining Model-Based and Model-Free Control in a Commercial Deployment）</news:title>
   <news:publication_date>2026-05-03T12:48:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686092</loc>
  <lastmod>2026-05-03T12:47:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANAX: MIMD-SIMD統合でGANを高速化するハードウェア設計（GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-03T12:47:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686090</loc>
  <lastmod>2026-05-03T12:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚なしでつかむ技術の実用性と示唆（Learning to Grasp without Seeing）</news:title>
   <news:publication_date>2026-05-03T12:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686088</loc>
  <lastmod>2026-05-03T12:47:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間と機械の協働最適化——Apprenticeship SchedulingによるCOVASの提案 (Human-Machine Collaborative Optimization via Apprenticeship Scheduling)</news:title>
   <news:publication_date>2026-05-03T12:47:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686086</loc>
  <lastmod>2026-05-03T12:47:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層RNNはやわらかな階層的構文を内部表現として獲得する（Deep RNNs Encode Soft Hierarchical Syntax）</news:title>
   <news:publication_date>2026-05-03T12:47:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686084</loc>
  <lastmod>2026-05-03T11:55:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジレスグラフェンにおける分数量子ホールのエネルギーギャップの輸送測定（Quantitative transport measurements of fractional quantum Hall energy gaps in edgeless graphene devices）</news:title>
   <news:publication_date>2026-05-03T11:55:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686082</loc>
  <lastmod>2026-05-03T11:55:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期太陽放射予測のための教師なしクラスタリングとマルチモデル融合（An Unsupervised Clustering-Based Short-Term Solar Forecasting Methodology Using Multi-Model Machine Learning Blending）</news:title>
   <news:publication_date>2026-05-03T11:55:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686080</loc>
  <lastmod>2026-05-03T11:54:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱再帰ユニットによる高速なニューラル機械翻訳（Deep Neural Machine Translation with Weakly-Recurrent Units）</news:title>
   <news:publication_date>2026-05-03T11:54:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686078</loc>
  <lastmod>2026-05-03T11:53:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルタイルによるデータ・モデル・ハイブリッド並列性の統一（Unifying Data, Model and Hybrid Parallelism in Deep Learning via Tensor Tiling）</news:title>
   <news:publication_date>2026-05-03T11:53:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686076</loc>
  <lastmod>2026-05-03T11:53:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数サンプルからの疎最適化による構造化力学系抽出（Extracting structured dynamical systems using sparse optimization with very few samples）</news:title>
   <news:publication_date>2026-05-03T11:53:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686074</loc>
  <lastmod>2026-05-03T11:52:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乾式EEGによるSSVEP信号の分類に関する研究（On the Classification of SSVEP-Based Dry-EEG Signals via Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-03T11:52:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686072</loc>
  <lastmod>2026-05-03T11:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予算制約下でのDCNNハードウェア最適化に向けた確率的コンピューティングの検討（Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing）</news:title>
   <news:publication_date>2026-05-03T11:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686070</loc>
  <lastmod>2026-05-03T11:01:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Metatrace Actor-Criticによるオンラインステップサイズ調整（Metatrace Actor-Critic: Online Step-size Tuning by Meta-gradient Descent for Reinforcement Learning Control）</news:title>
   <news:publication_date>2026-05-03T11:01:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686068</loc>
  <lastmod>2026-05-03T10:59:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列をまたぐ意味セグメンテーションの半教師付きドメイン適応（Semi-Supervised Domain Adaptation with Representation Learning for Semantic Segmentation across Time）</news:title>
   <news:publication_date>2026-05-03T10:59:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686066</loc>
  <lastmod>2026-05-03T10:59:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算の無駄を削減する深層学習アクセラレータ（Laconic Deep Learning Computing）</news:title>
   <news:publication_date>2026-05-03T10:59:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686064</loc>
  <lastmod>2026-05-03T10:59:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観客の表情行動を捉える教師なし深層表現（Unsupervised Deep Representations for Learning Audience Facial Behaviors）</news:title>
   <news:publication_date>2026-05-03T10:59:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686062</loc>
  <lastmod>2026-05-03T10:59:22Z</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・ベストバディによる異種画像対応の発見（Neural Best-Buddies: Sparse Cross-Domain Correspondence）</news:title>
   <news:publication_date>2026-05-03T10:59:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686060</loc>
  <lastmod>2026-05-03T10:58:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Guided CNNによるシーンテキスト検出の高速化と高精度化（Boosting up Scene Text Detectors with Guided CNN）</news:title>
   <news:publication_date>2026-05-03T10:58:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686058</loc>
  <lastmod>2026-05-03T10:07:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中性子星合体GW170817のX線アフターグロウの減衰（Fading of the X-ray Afterglow of Neutron Star Merger GW170817/GRB170817A at 260 Days）</news:title>
   <news:publication_date>2026-05-03T10:07:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686056</loc>
  <lastmod>2026-05-03T09:57:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層特徴の再配置による任意スタイル転送（Arbitrary Style Transfer with Deep Feature Reshuffle）</news:title>
   <news:publication_date>2026-05-03T09:57:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686054</loc>
  <lastmod>2026-05-03T09:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hαと[NII]が欠落する場合の星形成銀河とAGNの識別（The discrimination between star-forming and AGN galaxies in the absence of Hα and [NII]: A machine learning approach）</news:title>
   <news:publication_date>2026-05-03T09:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/686052</loc>
  <lastmod>2026-05-03T09:56:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一カラー画像からの3D人体姿勢と形状推定の学習（Learning to Estimate 3D Human Pose and Shape from a Single Color Image）</news:title>
   <news:publication_date>2026-05-03T09:56:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686050</loc>
  <lastmod>2026-05-03T09:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ariadneによる機械学習プログラム解析（Ariadne: Analysis for Machine Learning Programs）</news:title>
   <news:publication_date>2026-05-03T09:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686048</loc>
  <lastmod>2026-05-03T09:55:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系列学における周辺尤度の役割（Marginal likelihoods in phylogenetics: a review of methods and applications）</news:title>
   <news:publication_date>2026-05-03T09:55:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686046</loc>
  <lastmod>2026-05-03T09:04:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共同学習における意図しない特徴漏洩の悪用（Exploiting Unintended Feature Leakage in Collaborative Learning）</news:title>
   <news:publication_date>2026-05-03T09:04:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686044</loc>
  <lastmod>2026-05-03T09:04:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>家庭用品の材質分類における分光法の活用（Classification of Household Materials via Spectroscopy）</news:title>
   <news:publication_date>2026-05-03T09:04:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686042</loc>
  <lastmod>2026-05-03T09:04:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動タクソノミー誘導のエンドツーエンド強化学習（End-to-End Reinforcement Learning for Automatic Taxonomy Induction）</news:title>
   <news:publication_date>2026-05-03T09:04:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686040</loc>
  <lastmod>2026-05-03T09:04:02Z</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>2026-05-03T09:04:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686038</loc>
  <lastmod>2026-05-03T09:03:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Netsが視覚研究にもたらしたもの（Deep Nets: What have they ever done for Vision?）</news:title>
   <news:publication_date>2026-05-03T09:03:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686036</loc>
  <lastmod>2026-05-03T09:03:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動作を「動詞だけ」で明確に表す試み（Towards an Unequivocal Representation of Actions）</news:title>
   <news:publication_date>2026-05-03T09:03:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686034</loc>
  <lastmod>2026-05-03T09:03:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>出力分布の正則化による要約生成の語義一貫性向上（Regularizing Output Distribution of Abstractive Chinese Social Media Text Summarization for Improved Semantic Consistency）</news:title>
   <news:publication_date>2026-05-03T09:03:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686032</loc>
  <lastmod>2026-05-03T08:12:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dense and Diverse Capsule Networks を用いたカプセルの学習強化（Dense and Diverse Capsule Networks: Making the Capsules Learn Better）</news:title>
   <news:publication_date>2026-05-03T08:12:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686030</loc>
  <lastmod>2026-05-03T08:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>植物フェノタイピングのための3D点群多視点セマンティックラベリング（Multi-View Semantic Labeling of 3D Point Clouds for Automated Plant Phenotyping）</news:title>
   <news:publication_date>2026-05-03T08:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686028</loc>
  <lastmod>2026-05-03T08:10:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抽象的要約のためのグローバルエンコーディング（Global Encoding for Abstractive Summarization）</news:title>
   <news:publication_date>2026-05-03T08:10:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686026</loc>
  <lastmod>2026-05-03T08:10:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1000個の偶然観測された小惑星の分類と光度曲線データ（TAXONOMY AND LIGHT-CURVE DATA OF 1000 SERENDIPITOUSLY OBSERVED MAIN-BELT ASTEROIDS）</news:title>
   <news:publication_date>2026-05-03T08:10:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686024</loc>
  <lastmod>2026-05-03T08:10:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WISER: 学術領域におけるエキスパート探索の意味論的アプローチ（WISER: A Semantic Approach for Expert Finding in Academia based on Entity Linking）</news:title>
   <news:publication_date>2026-05-03T08:10:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686022</loc>
  <lastmod>2026-05-03T08:10:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>整流ワイヤネットワークと単調学習の実践的理解（Monotone Learning with Rectified Wire Networks）</news:title>
   <news:publication_date>2026-05-03T08:10:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686020</loc>
  <lastmod>2026-05-03T07:18:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データの普遍的エンコーダの提案（Towards a Universal Neural Network Encoder for Time Series）</news:title>
   <news:publication_date>2026-05-03T07:18:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686018</loc>
  <lastmod>2026-05-03T07:18:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EM-Softmaxが変える画像分類の精度向上（Ensemble Soft-Margin Softmax Loss for Image Classification）</news:title>
   <news:publication_date>2026-05-03T07:18:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686016</loc>
  <lastmod>2026-05-03T07:18:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド状データに対するラベリングの定式化（Labelling as an unsupervised learning problem）</news:title>
   <news:publication_date>2026-05-03T07:18:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686014</loc>
  <lastmod>2026-05-03T07:17:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非形式的数学記述を形式化するニューラル翻訳の第一歩（First Experiments with Neural Translation of Informal to Formal Mathematics）</news:title>
   <news:publication_date>2026-05-03T07:17:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686012</loc>
  <lastmod>2026-05-03T07:16:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データにおける連想分類器の分散化（Scaling associative classification for very large datasets）</news:title>
   <news:publication_date>2026-05-03T07:16:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686010</loc>
  <lastmod>2026-05-03T07:16:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>損失を考慮した近似推論によるベイズニューラルネットの実務的意義（Loss-Calibrated Approximate Inference in Bayesian Neural Networks）</news:title>
   <news:publication_date>2026-05-03T07:16:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686008</loc>
  <lastmod>2026-05-03T07:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話を続けるチャットボットのための「Second Response Generation」研究（Improv Chat: Second Response Generation for Chatbot）</news:title>
   <news:publication_date>2026-05-03T07:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686006</loc>
  <lastmod>2026-05-03T06:25:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Freebase再構成から読み解く知識グラフの設計思想（OK Google, What Is Your Ontology?）</news:title>
   <news:publication_date>2026-05-03T06:25:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686004</loc>
  <lastmod>2026-05-03T06:25:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンドット手法による頑健な探索戦略の学習（Learning Robust Search Strategies Using a Bandit-Based Approach）</news:title>
   <news:publication_date>2026-05-03T06:25:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686002</loc>
  <lastmod>2026-05-03T06:24:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希薄化が非対称再帰型ニューラルネットワークに与える影響（Effect of dilution in asymmetric recurrent neural networks）</news:title>
   <news:publication_date>2026-05-03T06:24:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686000</loc>
  <lastmod>2026-05-03T06:24:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア開発における人的資本の可視化と指標化（Human Capital in Software Engineering: A Systematic Mapping of Reconceptualized Human Aspect Studies）</news:title>
   <news:publication_date>2026-05-03T06:24:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685998</loc>
  <lastmod>2026-05-03T06:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hybrid Adaptive Fuzzy Extreme Learning Machineの概説（Hybrid Adaptive Fuzzy Extreme Learning Machine for text classification）</news:title>
   <news:publication_date>2026-05-03T06:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685996</loc>
  <lastmod>2026-05-03T06:24:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔表情認識のための深層共分散記述子（Deep Covariance Descriptors for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-05-03T06:24:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685994</loc>
  <lastmod>2026-05-03T06:23:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンサンブル極限学習機によるテキスト分類（Text classification based on ensemble extreme learning machine）</news:title>
   <news:publication_date>2026-05-03T06:23:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685992</loc>
  <lastmod>2026-05-03T05:32:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン感受性と感情を考慮した単語埋め込み（Learning Domain-Sensitive and Sentiment-Aware Word Embeddings）</news:title>
   <news:publication_date>2026-05-03T05:32:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685990</loc>
  <lastmod>2026-05-03T05:32:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジスティック損失関数の普遍性（On the Universality of the Logistic Loss Function）</news:title>
   <news:publication_date>2026-05-03T05:32:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685988</loc>
  <lastmod>2026-05-03T05:32:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推論志向の読解評価：ParallelQA（Towards Inference-Oriented Reading Comprehension: ParallelQA）</news:title>
   <news:publication_date>2026-05-03T05:32:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685986</loc>
  <lastmod>2026-05-03T05:31:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイバ非線形性を含む幾何学的コンステレーションシェーピングの深層学習 (Deep Learning of Geometric Constellation Shaping including Fiber Nonlinearities)</news:title>
   <news:publication_date>2026-05-03T05:31:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-03T05:31:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軸索遅延が多層ネットワークの構造発達に与える影響（Impact of axonal delay on structure development in a multi-layered network）</news:title>
   <news:publication_date>2026-05-03T05:31:36Z</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:title>共変量優先度付けによるマッチングと機械学習による統計調整の比較（Comparing Covariate Prioritization via Matching to Machine Learning Methods for Causal Inference using Five Empirical Applications）</news:title>
   <news:publication_date>2026-05-03T04:40:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685980</loc>
  <lastmod>2026-05-03T04:32:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間暖房の最適制御に向けた深層強化学習の応用（Deep Reinforcement Learning for Optimal Control of Space Heating）</news:title>
   <news:publication_date>2026-05-03T04:32:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685978</loc>
  <lastmod>2026-05-03T04:32:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-space深層学習による高速MRI補間（k-Space Deep Learning for Accelerated MRI）</news:title>
   <news:publication_date>2026-05-03T04:32:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685976</loc>
  <lastmod>2026-05-03T04:32:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cr2O3における原子間隙拡散の第一原理解析（A First Principles Investigation of Native Interstitial Diffusion in Cr2O3）</news:title>
   <news:publication_date>2026-05-03T04:32:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685974</loc>
  <lastmod>2026-05-03T04:31:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラジアルな方位選択性の出現：層状ネットワークにおける細胞密度変化と偏心の影響（Emergence of radial orientation selectivity: Effect of cell density changes and eccentricity in a layered network）</news:title>
   <news:publication_date>2026-05-03T04:31:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685972</loc>
  <lastmod>2026-05-03T04:30:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転写因子とDNA結合の機械学習アンサンブル（Transcription Factor-DNA Binding Via Machine Learning Ensembles）</news:title>
   <news:publication_date>2026-05-03T04:30:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685970</loc>
  <lastmod>2026-05-03T04:30:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>談話を意識したニューラル報酬による一貫性の高い文章生成（Discourse-Aware Neural Rewards for Coherent Text Generation）</news:title>
   <news:publication_date>2026-05-03T04:30:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685968</loc>
  <lastmod>2026-05-03T03:39:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンピュータネットワークトラフィックにおける異常検知のためのシーケンス集約規則（Sequence Aggregation Rules for Anomaly Detection in Computer Network Traffic）</news:title>
   <news:publication_date>2026-05-03T03:39:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685966</loc>
  <lastmod>2026-05-03T03:39:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キャッシュを計算資源に変える発想―メモリ内でDNN推論を高速化するNeural Cache（Neural Cache: Bit-Serial In-Cache Acceleration of Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-03T03:39:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685964</loc>
  <lastmod>2026-05-03T03:38:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResNeXtの構造と実践的評価（Evaluating ResNeXt Model Architecture for Image Classification）</news:title>
   <news:publication_date>2026-05-03T03:38:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685962</loc>
  <lastmod>2026-05-03T03:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細胞組織画像の高速かつ高精度な腫瘍セグメンテーション（Fast and Accurate Tumor Segmentation of Histology Images using Persistent Homology and Deep Convolutional Features）</news:title>
   <news:publication_date>2026-05-03T03:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685960</loc>
  <lastmod>2026-05-03T03:38:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブワード情報を組み込んだ行列分解型単語埋め込み（Incorporating Subword Information into Matrix Factorization Word Embeddings）</news:title>
   <news:publication_date>2026-05-03T03:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685958</loc>
  <lastmod>2026-05-03T03:37:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMは重みつき和を動的に計算する装置である（Long Short-Term Memory as a Dynamically Computed Element-wise Weighted Sum）</news:title>
   <news:publication_date>2026-05-03T03:37:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685956</loc>
  <lastmod>2026-05-03T02:46:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オリオン星雲クラスターにおける原始惑星系円盤の性質（PROTOPLANETARY DISK PROPERTIES IN THE ORION NEBULA CLUSTER: INITIAL RESULTS FROM DEEP, HIGH-RESOLUTION ALMA OBSERVATIONS）</news:title>
   <news:publication_date>2026-05-03T02:46:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685954</loc>
  <lastmod>2026-05-03T02:46:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FIGSによる大質量銀河の星形成履歴解析（FIGS: Spectral fitting constraints on the star formation history of massive galaxies since Cosmic Noon）</news:title>
   <news:publication_date>2026-05-03T02:46:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685952</loc>
  <lastmod>2026-05-03T02:46:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベケンシュタインによるブラックホール面積の量子化（Bekenstein Quantization of Black-Hole Surface Area）</news:title>
   <news:publication_date>2026-05-03T02:46:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685950</loc>
  <lastmod>2026-05-03T02:44:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしバイリンガル辞書誘導の限界（On the Limitations of Unsupervised Bilingual Dictionary Induction）</news:title>
   <news:publication_date>2026-05-03T02:44:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685948</loc>
  <lastmod>2026-05-03T02:44:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水道管破裂リスクの機械学習評価と予防（Using Machine Learning to Assess the Risk of and Prevent Water Main Breaks）</news:title>
   <news:publication_date>2026-05-03T02:44:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685946</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>2026-05-03T01:53:15Z</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>遅延宇宙膨張のモデル非依存的評価の改良（An improved model-independent assessment of the late-time cosmic expansion）</news:title>
   <news:publication_date>2026-05-03T01:51:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685942</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>測定数が変動する状況下におけるフーリエ・プチグラフィーの位相復元（Phase retrieval for Fourier Ptychography under varying amount of measurements）</news:title>
   <news:publication_date>2026-05-03T01:50:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685940</loc>
  <lastmod>2026-05-03T01:50:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマノイドにおける協調作業の強化学習（Learning Coordinated Tasks using Reinforcement Learning in Humanoids）</news:title>
   <news:publication_date>2026-05-03T01:50:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685938</loc>
  <lastmod>2026-05-03T01:49:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTにおける協調オンライン学習によるモバイルエッジコンピューティングの安全性（Secure Mobile Edge Computing in IoT via Collaborative Online Learning）</news:title>
   <news:publication_date>2026-05-03T01:49:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685936</loc>
  <lastmod>2026-05-03T01:49:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドの重奏音響イベント検出（End-to-End Polyphonic Sound Event Detection）</news:title>
   <news:publication_date>2026-05-03T01:49:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685934</loc>
  <lastmod>2026-05-03T01:49:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次優位情報を用いた方策最適化（Policy Optimization with Second-Order Advantage Information）</news:title>
   <news:publication_date>2026-05-03T01:49:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685932</loc>
  <lastmod>2026-05-03T00:58:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的マルウェアに対する堅牢性の視覚的特徴（On Visual Hallmarks of Robustness to Adversarial Malware）</news:title>
   <news:publication_date>2026-05-03T00:58:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685930</loc>
  <lastmod>2026-05-03T00:57:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層信念ネットワークによる話者認識の示唆（Speaker Recognition using Deep Belief Networks）</news:title>
   <news:publication_date>2026-05-03T00:57:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685928</loc>
  <lastmod>2026-05-03T00:57:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーカミオカンデ検出器の設計と意義（Design of the Hyper-Kamiokande Detector）</news:title>
   <news:publication_date>2026-05-03T00:57:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685926</loc>
  <lastmod>2026-05-03T00:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡散に基づくネットワーク埋め込み（Diffusion Based Network Embedding）</news:title>
   <news:publication_date>2026-05-03T00:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685924</loc>
  <lastmod>2026-05-03T00:56:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔の筋活動を同時に場所と強さで推定する手法（Joint Action Unit localisation and intensity estimation through heatmap regression）</news:title>
   <news:publication_date>2026-05-03T00:56:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685922</loc>
  <lastmod>2026-05-03T00:56:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カプセルによる深層ニューラルネットワークの統一枠組み（A Unified Framework of Deep Neural Networks by Capsules）</news:title>
   <news:publication_date>2026-05-03T00:56:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685920</loc>
  <lastmod>2026-05-03T00:56:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sparse SfM深度事前知識を用いたDeep 2.5D車両分類（Deep 2.5D Vehicle Classification with Sparse SfM Depth Prior for Automated Toll Systems）</news:title>
   <news:publication_date>2026-05-03T00:56:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685918</loc>
  <lastmod>2026-05-03T00:04:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子状態識別のための最適普遍学習機（Optimal universal learning machines for quantum state discrimination）</news:title>
   <news:publication_date>2026-05-03T00:04:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685916</loc>
  <lastmod>2026-05-03T00:04:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習で光学情報記録の限界を押し広げる（Pushing the limits of optical information storage using deep learning）</news:title>
   <news:publication_date>2026-05-03T00:04:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685914</loc>
  <lastmod>2026-05-03T00:04:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテゴリ変数と整数変数を含むベイズ最適化の扱い（Dealing with Categorical and Integer-valued Variables in Bayesian Optimization with Gaussian Processes）</news:title>
   <news:publication_date>2026-05-03T00:04:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685912</loc>
  <lastmod>2026-05-03T00:03:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパイラ最適化における機械学習の適用（Machine Learning in Compiler Optimisation）</news:title>
   <news:publication_date>2026-05-03T00:03:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685910</loc>
  <lastmod>2026-05-03T00:03:39Z</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>2026-05-03T00:03:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685908</loc>
  <lastmod>2026-05-03T00:03:26Z</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>2026-05-03T00:03:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685906</loc>
  <lastmod>2026-05-02T23:12:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みプロトタイプ学習による頑健な分類（Robust Classification with Convolutional Prototype Learning）</news:title>
   <news:publication_date>2026-05-02T23:12:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685904</loc>
  <lastmod>2026-05-02T23:11:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デコーディング・デコーダー：教師なし類似性タスクのための最適表現空間の探索（DECODING DECODERS: FINDING OPTIMAL REPRESENTATION SPACES FOR UNSUPERVISED SIMILARITY TASKS）</news:title>
   <news:publication_date>2026-05-02T23:11:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685902</loc>
  <lastmod>2026-05-02T23:11:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>方向データに強い確率的深層モデルによる姿勢推定（Deep Directional Statistics: Pose Estimation with Uncertainty Quantification）</news:title>
   <news:publication_date>2026-05-02T23:11:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685900</loc>
  <lastmod>2026-05-02T23:10:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTボットネット攻撃のネットワーク検知に関する自動検出手法の要点（N-BaIoT: Network-based Detection of IoT Botnet Attacks Using Deep Autoencoders）</news:title>
   <news:publication_date>2026-05-02T23:10:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685898</loc>
  <lastmod>2026-05-02T23:10:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽フレア予測の深層学習モデル（DEEP FLARE NET (DeFN) MODEL FOR SOLAR FLARE PREDICTION）</news:title>
   <news:publication_date>2026-05-02T23:10:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685896</loc>
  <lastmod>2026-05-02T23:10:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノ溝における連続的凝縮（Continuous condensation in nanogrooves）</news:title>
   <news:publication_date>2026-05-02T23:10:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685894</loc>
  <lastmod>2026-05-02T23:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルランキングモデルのドメイン横断正則化（Cross Domain Regularization for Neural Ranking Models using Adversarial Learning）</news:title>
   <news:publication_date>2026-05-02T23:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685892</loc>
  <lastmod>2026-05-02T22:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像の高解像度化をGANで実現する試み（PSGAN: A Generative Adversarial Network for Remote Sensing Image Pan-sharpening）</news:title>
   <news:publication_date>2026-05-02T22:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685890</loc>
  <lastmod>2026-05-02T22:09:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>判別器の表現を多様化してGANの学習を安定化する手法（IMPROVING GAN TRAINING VIA BINARIZED REPRESENTATION ENTROPY (BRE) REGULARIZATION）</news:title>
   <news:publication_date>2026-05-02T22:09:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685888</loc>
  <lastmod>2026-05-02T22:08:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダとニューラル決定森林による意見不正検出（Opinion Fraud Detection via Neural Autoencoder Decision Forest）</news:title>
   <news:publication_date>2026-05-02T22:08:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685886</loc>
  <lastmod>2026-05-02T22:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HMIの疑似連続光解釈（Understanding the HMI pseudocontinuum in white-light solar flares）</news:title>
   <news:publication_date>2026-05-02T22:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685884</loc>
  <lastmod>2026-05-02T22:07:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的コントラスト推定（Adversarial Contrastive Estimation）</news:title>
   <news:publication_date>2026-05-02T22:07:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685882</loc>
  <lastmod>2026-05-02T22:07:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepWalkingによるスマートフォン歩行速度推定（DeepWalking: Enabling Smartphone-based Walking Speed Estimation Using Deep Learning）</news:title>
   <news:publication_date>2026-05-02T22:07:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685880</loc>
  <lastmod>2026-05-02T22:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教えることを学ぶ――Learning to Teach（Learning to Teach）</news:title>
   <news:publication_date>2026-05-02T22:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685878</loc>
  <lastmod>2026-05-02T21:15:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低資源言語の語彙埋め込みを学習するPU学習の提案（Learning Word Embeddings for Low-resource Languages by PU Learning）</news:title>
   <news:publication_date>2026-05-02T21:15:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685876</loc>
  <lastmod>2026-05-02T21:15:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるアトラクタ再構築（Attractor Reconstruction by Machine Learning）</news:title>
   <news:publication_date>2026-05-02T21:15:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685874</loc>
  <lastmod>2026-05-02T21:15:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイジアンネットワーク分類器の説明に関する記号的アプローチ（A Symbolic Approach to Explaining Bayesian Network Classifiers）</news:title>
   <news:publication_date>2026-05-02T21:15:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685872</loc>
  <lastmod>2026-05-02T21:13:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意認識合成ネットワークによる人物再識別（Attention-Aware Compositional Network for Person Re-identification）</news:title>
   <news:publication_date>2026-05-02T21:13:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685870</loc>
  <lastmod>2026-05-02T21:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPG-Net: セグメンテーション予測と誘導による画像インペインティング（SPG-Net: Segmentation Prediction and Guidance Network for Image Inpainting）</news:title>
   <news:publication_date>2026-05-02T21:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685868</loc>
  <lastmod>2026-05-02T21:12:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メムリスタを用いた教師なしニューロモルフィックシステムによる高速・省電力GAN実現（A Memristor based Unsupervised Neuromorphic System Towards Fast and Energy-Efficient GAN）</news:title>
   <news:publication_date>2026-05-02T21:12:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685866</loc>
  <lastmod>2026-05-02T21:12:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬推定による深層強化学習の分散削減（Reward Estimation for Variance Reduction in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-02T21:12:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685864</loc>
  <lastmod>2026-05-02T20:20:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間とロボットの協働を守る「監督者の安全集合」を学ぶ（Modeling Supervisor Safe Sets for Improving Collaboration in Human-Robot Teams）</news:title>
   <news:publication_date>2026-05-02T20:20:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685862</loc>
  <lastmod>2026-05-02T20:19:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多尺度計量による自己組織化マップの構造解析（Multi-scale metrics and self-organizing maps: a computational approach to the structure of sensory maps）</news:title>
   <news:publication_date>2026-05-02T20:19:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685860</loc>
  <lastmod>2026-05-02T20:19:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Network Enhancementによる生物ネットワークのノイズ除去（Network Enhancement: a general method to denoise weighted biological networks）</news:title>
   <news:publication_date>2026-05-02T20:19:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685858</loc>
  <lastmod>2026-05-02T20:18:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程予測のVecchia近似 (Vecchia approximations of Gaussian-process predictions)</news:title>
   <news:publication_date>2026-05-02T20:18:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685856</loc>
  <lastmod>2026-05-02T20:17:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>子ども向け音声認識への成人モデルの転移学習（Transfer Learning from Adult to Children for Speech Recognition: Evaluation, Analysis and Recommendations）</news:title>
   <news:publication_date>2026-05-02T20:17:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685854</loc>
  <lastmod>2026-05-02T20:17:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス正規化が示した単一画像デヘイズの有効性（The Effectiveness of Instance Normalization: a Strong Baseline for Single Image Dehazing）</news:title>
   <news:publication_date>2026-05-02T20:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685852</loc>
  <lastmod>2026-05-02T19:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数帯域フィルタを用いた高い拡張性を持つ画像再構成（Highly Scalable Image Reconstruction using Deep Neural Networks with Bandpass Filtering）</news:title>
   <news:publication_date>2026-05-02T19:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685850</loc>
  <lastmod>2026-05-02T19:25:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド注意機構による音声認識の改善（Improved training of end-to-end attention models for speech recognition）</news:title>
   <news:publication_date>2026-05-02T19:25:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685848</loc>
  <lastmod>2026-05-02T19:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適なチーム編成のための深層ニューラルネットワーク（Deep Neural Networks for Optimal Team Composition）</news:title>
   <news:publication_date>2026-05-02T19:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685846</loc>
  <lastmod>2026-05-02T19:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙資源に未収録の語へ意味情報を広げる後処理（Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources）</news:title>
   <news:publication_date>2026-05-02T19:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685844</loc>
  <lastmod>2026-05-02T19:24:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ属性を取り込むネットワーク埋め込みの進化（Capturing Edge Attributes via Network Embedding）</news:title>
   <news:publication_date>2026-05-02T19:24:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685842</loc>
  <lastmod>2026-05-02T19:24:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜OCT画像における高反射小斑点の完全自動セグメンテーション（Fully Automated Segmentation of Hyperreflective Foci in Optical Coherence Tomography Images）</news:title>
   <news:publication_date>2026-05-02T19:24:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685840</loc>
  <lastmod>2026-05-02T19:23:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジャンプを伴うランダムウォークの緩和時間の解析（Analysis of Relaxation Time in Random Walk with Jumps）</news:title>
   <news:publication_date>2026-05-02T19:23:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685838</loc>
  <lastmod>2026-05-02T18:32:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ペア付きと非ペア付きトレーニングを同時に用いた画像変換学習（Learning image-to-image translation using paired and unpaired training samples）</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>
   </news:publication>
   <news:title>礼節を保つ対話生成――並列データなしで礼儀正しい応答を作る方法（Polite Dialogue Generation Without Parallel Data）</news:title>
   <news:publication_date>2026-05-02T18:32:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>高解像度医用画像合成における漸進的生成対向ネットワークの応用（High-resolution medical image synthesis using progressively grown generative adversarial networks）</news:title>
   <news:publication_date>2026-05-02T18:32:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-02T18:31:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ガウス確率場の局所的代数的簡約化（Local, algebraic simplifications of Gaussian random fields）</news:title>
   <news:publication_date>2026-05-02T18:31:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-02T18:31:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模空間データにおける確率密度関数の並列計算（Parallel Computation of PDFs on Big Spatial Data Using Spark）</news:title>
   <news:publication_date>2026-05-02T18:31:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/685828</loc>
  <lastmod>2026-05-02T18:31:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深紫外から中赤外までのスーパーコンティニューム生成（Deep-UV to mid-IR supercontinuum generation driven by mid-IR ultrashort pulses in a gas-filled fiber）</news:title>
   <news:publication_date>2026-05-02T18:31:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/685826</loc>
  <lastmod>2026-05-02T18:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合イニシアティブとマルチモーダルフィードバックによる画像検索（Image Retrieval with Mixed Initiative and Multimodal Feedback）</news:title>
   <news:publication_date>2026-05-02T18:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/685824</loc>
  <lastmod>2026-05-02T17:39:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Connection Tableauxにおける機械学習ガイダンスと証明認証（Machine Learning Guidance and Proof Certification for Connection Tableaux）</news:title>
   <news:publication_date>2026-05-02T17:39:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/685822</loc>
  <lastmod>2026-05-02T17:39:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界で学習するCNN（Learning on the Edge: Explicit Boundary Handling in CNNs）</news:title>
   <news:publication_date>2026-05-02T17:39:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/685820</loc>
  <lastmod>2026-05-02T17:39:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身体を自己学習するロボット：予測符号化による自己推定の実装（Adaptive robot body learning and estimation through predictive coding）</news:title>
   <news:publication_date>2026-05-02T17:39:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/685818</loc>
  <lastmod>2026-05-02T17:38:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プーリングやストライドを含むCNNでの高速な密な特徴抽出（Fast Dense Feature Extraction with CNNs that have Pooling or Striding Layers）</news:title>
   <news:publication_date>2026-05-02T17:38:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/685816</loc>
  <lastmod>2026-05-02T17:38:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>行動データにおける興味深いパターンの発見にSimpsonのパラドックスを用いる（Using Simpson’s Paradox to Discover Interesting Patterns in Behavioral Data）</news:title>
   <news:publication_date>2026-05-02T17:38:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/685814</loc>
  <lastmod>2026-05-02T17:38:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M49のハローにおける三つの動的に異なる恒星集団（Three dynamically distinct stellar populations in the halo of M49）</news:title>
   <news:publication_date>2026-05-02T17:38:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/685812</loc>
  <lastmod>2026-05-02T17:38:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適制御における欺瞞（Deception in Optimal Control）</news:title>
   <news:publication_date>2026-05-02T17:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/685810</loc>
  <lastmod>2026-05-02T16:47:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的視点計画による物体再構成（Active Object Reconstruction Using a Guided View Planner）</news:title>
   <news:publication_date>2026-05-02T16:47:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/685808</loc>
  <lastmod>2026-05-02T16:47:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>データ量子化を意識した深層ネットワークによる高精度・高速スパイキングニューロモーフィックシステム（Towards Accurate and High-Speed Spiking Neuromorphic Systems with Data Quantization-Aware Deep Networks）</news:title>
   <news:publication_date>2026-05-02T16:47:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/685806</loc>
  <lastmod>2026-05-02T16:46:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Recurrent CNNによる3D視線推定（Recurrent CNN for 3D Gaze Estimation using Appearance and Shape Cues）</news:title>
   <news:publication_date>2026-05-02T16:46:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685804</loc>
  <lastmod>2026-05-02T16:45:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光の軌道角運動量を誘起する非吸収光学素子の研究（Orbital Angular Momentum Induced by Nonabsorbing Optical Elements through Space-variant Polarization-state Manipulations）</news:title>
   <news:publication_date>2026-05-02T16:45:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/685802</loc>
  <lastmod>2026-05-02T16:45:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値化された測定からのスパース復元を扱うBSBL（Binary Sparse Bayesian Learning Algorithm for One-bit Compressed Sensing）</news:title>
   <news:publication_date>2026-05-02T16:45:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/685800</loc>
  <lastmod>2026-05-02T16:45:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MWC 758の円盤における塵の渦捕獲の可視化（Cm-wavelength observations of MWC 758: resolved dust trapping in a vortex）</news:title>
   <news:publication_date>2026-05-02T16:45:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/685798</loc>
  <lastmod>2026-05-02T16:44:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gaia DR2における新たな散開星団発見手法（A new method for unveiling Open Clusters in Gaia）</news:title>
   <news:publication_date>2026-05-02T16:44:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/685796</loc>
  <lastmod>2026-05-02T15:53:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>E-Commerceレビューの統計解析と双方向RNNによる感情分類（Statistical Analysis on E-Commerce Reviews, with Sentiment Classification using Bidirectional Recurrent Neural Network）</news:title>
   <news:publication_date>2026-05-02T15:53:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/685794</loc>
  <lastmod>2026-05-02T15:45:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ペプチド同定のための効率的オンライン学習（Eﬃcient online learning for large-scale peptide identification）</news:title>
   <news:publication_date>2026-05-02T15:45:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/685792</loc>
  <lastmod>2026-05-02T15:45:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテゴリーに基づく深層CCAによる細粒度会場探索（Category-Based Deep CCA for Fine-Grained Venue Discovery from Multimodal Data）</news:title>
   <news:publication_date>2026-05-02T15:45:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/685790</loc>
  <lastmod>2026-05-02T15:44:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モアレ模様除去のためのマルチレゾリューション畳み込みニューラルネットワーク（Moiré Photo Restoration Using Multiresolution Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-02T15:44:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/685788</loc>
  <lastmod>2026-05-02T15:44:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期アルゴリズムを記述する微分方程式（Differential Equations for Modeling Asynchronous Algorithms）</news:title>
   <news:publication_date>2026-05-02T15:44:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/685786</loc>
  <lastmod>2026-05-02T15:44:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形効用を持つ多項ロジット・バンディット（Multinomial Logit Bandit with Linear Utility Functions）</news:title>
   <news:publication_date>2026-05-02T15:44:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/685784</loc>
  <lastmod>2026-05-02T15:43:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>セッションベース推薦におけるユーザー静的コンテキストの活用（Augmenting Recurrent Neural Networks with High-Order User-Contextual Preference for Session-Based Recommendation）</news:title>
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   <news:genres>Blog</news:genres>
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