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   <news:title>動画行動認識における時間情報と特徴融合の革新（Information Fused Temporal Transformation Network）</news:title>
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   <news:title>サンプリングバイアス下における二群間効果推定（Effect Inference from Two-Group Data with Sampling Bias）</news:title>
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   <news:title>Region Deformer Networksを用いた単眼無監督深度推定（Region Deformer Networks for Unsupervised Depth Estimation from Unconstrained Monocular Videos）</news:title>
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   <news:title>トップ粒子識別の機械学習の全景（The Machine Learning Landscape of Top Taggers）</news:title>
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   <news:title>大規模な敵対的データに効率的に対応するオンラインカーネル学習（EFFICIENT ONLINE LEARNING WITH KERNELS FOR ADVERSARIAL LARGE SCALE PROBLEMS）</news:title>
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    <news:language>ja</news:language>
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   <news:title>HexaGANによる実世界分類問題への統合的対処（HexaGAN: Generative Adversarial Nets for Real World Classification）</news:title>
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    <news:language>ja</news:language>
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   <news:title>3D顔形状の分離表現学習（Disentangled Representation Learning for 3D Face Shape）</news:title>
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    <news:language>ja</news:language>
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   <news:title>海草（シーグラス）検出とマッピングのための撮像と分類技術（Imaging and Classification Techniques for Seagrass Mapping and Monitoring: A Comprehensive Survey）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>仮定・拡張・学習：ランダムラベルとデータ拡張による教師なし少数ショットメタ学習（Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation）</news:title>
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   <news:title>太陽光発電の翌日時間別出力予測（Day-Ahead Hourly Forecasting of Power Generation from Photovoltaic Plants）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>文脈ベクトルは単語ベクトルの半分の次元での反射である（Context Vectors are Reflections of Word Vectors in Half the Dimensions）</news:title>
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    <news:language>ja</news:language>
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   <news:title>3D人間姿勢推定の弱教師あり再投影ネットワーク（RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>シンボリック伝播による深層ニューラルネットワーク検証の高精度化と高速化（Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>FliPerClassによるTESSデータの自動分類の実用性（FliPerClass: In search of solar-like pulsators among TESS targets）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>少ないデータで学ぶ：条件付きPGGANによる脳転移検出のデータ拡張（Learning More with Less: Conditional PGGAN-based Data Augmentation for Brain Metastases Detection Using Highly-Rough Annotation on MR Images）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>点群におけるインスタンスと意味の相互分割（Associatively Segmenting Instances and Semantics in Point Clouds）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>超音波センサの現実的環境シミュレーション（Realistic Ultrasonic Environment Simulation Using Conditional Generative Adversarial Networks）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>学習率に動的境界を設けた適応的勾配法（ADAPTIVE GRADIENT METHODS WITH DYNAMIC BOUND OF LEARNING RATE）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-11T09:40:54Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>マルチスケールQuasi-RNNによる次アイテム推薦の要点解説（Multi-Scale Quasi-RNN for Next Item Recommendation）</news:title>
   <news:publication_date>2026-08-11T09:40:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-11T08:49:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>専門家の知見を少ないデータで活かす方法（Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>評価可能なゲーム戦略においてメタ解釈学習は深層強化学習を超えられるか（Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies?）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>宇宙ニュートリノで探る強い相互作用の振る舞い（Probing strong dynamics with cosmic neutrinos）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-11T08:48:23Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>運転操作予測のドメイン適応型RNN（Robust and Subject-Independent Driving Manoeuvre Anticipation through Domain-Adversarial Recurrent Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-11T08:48:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>LaSOによる多ラベル少数例学習のためのラベル集合操作ネットワーク（LaSO: Label-Set Operations networks for multi-label few-shot learning）</news:title>
   <news:publication_date>2026-08-11T08:48:17Z</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>リンク属性を適切に組み込むGCN（GCN-LASE: Towards Adequately Incorporating Link Attributes in Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-11T08:48:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-11T08:47:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>生成的視覚対話システムの学習手法（Generative Visual Dialogue System via Weighted Likelihood Estimation）</news:title>
   <news:publication_date>2026-08-11T08:47:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-11T07:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>パラメータ不要なオンラインロジスティック回帰に対する対数後悔の理論（Logarithmic Regret for Parameter-Free Online Logistic Regression）</news:title>
   <news:publication_date>2026-08-11T07:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/721930</loc>
  <lastmod>2026-08-11T07:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰畳み込みによる圧縮とコスト可変化（Recurrent Convolution for Compact and Cost-Adjustable Neural Networks）</news:title>
   <news:publication_date>2026-08-11T07:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/721928</loc>
  <lastmod>2026-08-11T07:55:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BMSTとテールバイティング畳み込み符号の統計学習支援復号（Statistical Learning Aided Decoding of BMST of Tail-Biting Convolutional Code）</news:title>
   <news:publication_date>2026-08-11T07:55:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/721926</loc>
  <lastmod>2026-08-11T07:54:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト表現学習のためのセマンティック・ヒルベルト空間（Semantic Hilbert Space for Text Representation Learning）</news:title>
   <news:publication_date>2026-08-11T07:54:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/721924</loc>
  <lastmod>2026-08-11T07:54:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BoostGANによる横顔かつ遮蔽された顔の正面化と認識（BoostGAN for Occlusive Profile Face Frontalization and Recognition）</news:title>
   <news:publication_date>2026-08-11T07:54:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/721922</loc>
  <lastmod>2026-08-11T07:54:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの分片平面3D再構築（Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding）</news:title>
   <news:publication_date>2026-08-11T07:54:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/721920</loc>
  <lastmod>2026-08-11T07:54:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次分解可能な部分モジュラ関数の最適化（Quadratic Decomposable Submodular Function Minimization）</news:title>
   <news:publication_date>2026-08-11T07:54:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/721918</loc>
  <lastmod>2026-08-11T07:03:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数空間における粒子最適化法が切り拓くベイズニューラルネットワークの新地平（Function Space Particle Optimization for Bayesian Neural Networks）</news:title>
   <news:publication_date>2026-08-11T07:03:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-11T06:02:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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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>
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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>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>部分観測下での多エージェント相互作用の確率的予測（Stochastic Prediction of Multi-Agent Interactions from Partial Observations）</news:title>
   <news:publication_date>2026-08-11T02:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721844</loc>
  <lastmod>2026-08-11T02:19:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TraVeLGANによる画像変換の新展開（TraVeLGAN: Image-to-image Translation by Transformation Vector Learning）</news:title>
   <news:publication_date>2026-08-11T02:19:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721842</loc>
  <lastmod>2026-08-11T02:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低線量CTの深層学習によるノイズ除去（Deep Learning for Low-Dose CT Denoising）</news:title>
   <news:publication_date>2026-08-11T02:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721840</loc>
  <lastmod>2026-08-11T02:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハチドリ並みの機敏さを小型ロボで実現する（Learning Extreme Hummingbird Maneuvers on Flapping Wing Robots）</news:title>
   <news:publication_date>2026-08-11T02:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721838</loc>
  <lastmod>2026-08-11T02:18:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>羽ばたき飛行ロボットの高精度シミュレーションがもたらす変化（Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and Animals）</news:title>
   <news:publication_date>2026-08-11T02:18:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721836</loc>
  <lastmod>2026-08-11T02:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化されたIntersection over Union（Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression）</news:title>
   <news:publication_date>2026-08-11T02:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721834</loc>
  <lastmod>2026-08-11T01:25:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビン分割散布図の評価と改善（On Binscatter）</news:title>
   <news:publication_date>2026-08-11T01:25:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721832</loc>
  <lastmod>2026-08-11T01:25:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練データ選択の情報損失理論的解析（Analyzing Data Selection Techniques with Tools from the Theory of Information Losses）</news:title>
   <news:publication_date>2026-08-11T01:25:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721830</loc>
  <lastmod>2026-08-11T01:25:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ネットワークにおける短期道路交通予測（Short-term Road Traffic Prediction based on Deep Cluster at Large-scale Networks）</news:title>
   <news:publication_date>2026-08-11T01:25:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721828</loc>
  <lastmod>2026-08-11T01:23:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンソース深層学習フレームワークの詳細比較（A Detailed Comparative Study of Open Source Deep Learning Frameworks）</news:title>
   <news:publication_date>2026-08-11T01:23:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721826</loc>
  <lastmod>2026-08-11T01:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバスト性を超えた仕様検証（Specifications Beyond Robustness）</news:title>
   <news:publication_date>2026-08-11T01:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721824</loc>
  <lastmod>2026-08-11T01:23:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全データから学習するGANフレームワーク（MISGAN: LEARNING FROM INCOMPLETE DATA WITH GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-08-11T01:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721822</loc>
  <lastmod>2026-08-11T01:23:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし学習に基づく長期スーパーピクセルトラッキング（Unsupervised learning-based long-term superpixel tracking）</news:title>
   <news:publication_date>2026-08-11T01:23:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721815</loc>
  <lastmod>2026-08-11T00:31:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PolyDroidによるモバイルアプリ最適化（PolyDroid: Learning-Driven Specialization of Mobile Applications）</news:title>
   <news:publication_date>2026-08-11T00:31:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721813</loc>
  <lastmod>2026-08-11T00:31:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BERTで読み解く噂の立場判定（Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers）</news:title>
   <news:publication_date>2026-08-11T00:31:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721811</loc>
  <lastmod>2026-08-11T00:30:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークにおけるスパース化の現状（The State of Sparsity in Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-11T00:30:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721809</loc>
  <lastmod>2026-08-11T00:29:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Eコマース価格システムの異常検知（Anomaly Detection for an E-commerce Pricing System）</news:title>
   <news:publication_date>2026-08-11T00:29:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721807</loc>
  <lastmod>2026-08-11T00:29:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像分類パイプラインにおける誤差寄与の定量化（Quantifying error contributions of computational steps, algorithms and hyperparameter choices in image classification pipelines）</news:title>
   <news:publication_date>2026-08-11T00:29:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721805</loc>
  <lastmod>2026-08-11T00:29:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOSDEFサーベイに見る高赤方偏移星形成銀河の運動学と構造進化（The MOSDEF Survey: Kinematic and Structural Evolution of Star-Forming Galaxies at 1.4 ≤ z ≤ 3.8）</news:title>
   <news:publication_date>2026-08-11T00:29:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721803</loc>
  <lastmod>2026-08-11T00:29:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期宇宙における「休止」銀河の実在確認（Passive galaxies in the early Universe: ALMA confirmation of z ∼3–5 candidates in the CANDELS GOODS-South field）</news:title>
   <news:publication_date>2026-08-11T00:29:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721801</loc>
  <lastmod>2026-08-10T23:37:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>消光と銀河コンフォーミティの一般的手法 (A general approach to quenching and galactic conformity)</news:title>
   <news:publication_date>2026-08-10T23:37:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721799</loc>
  <lastmod>2026-08-10T23:37:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FEELVOSによる高速エンドツーエンド埋め込み学習で変わる動画物体セグメンテーション（FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation）</news:title>
   <news:publication_date>2026-08-10T23:37:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721797</loc>
  <lastmod>2026-08-10T23:36:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件不変なマルチビュー場所認識の実務的インパクト（Condition-Invariant Multi-View Place Recognition）</news:title>
   <news:publication_date>2026-08-10T23:36:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721795</loc>
  <lastmod>2026-08-10T23:36:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>流入境界に基づくNavier–Stokes数値波槽：平坦底と傾斜底上の波伝播に関する検証と妥当性検証（An inflow-boundary-based Navier-Stokes wave tank: verification and validation for waves propagating over flat and inclined bottoms）</news:title>
   <news:publication_date>2026-08-10T23:36:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721793</loc>
  <lastmod>2026-08-10T23:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GQA：実世界の視覚的推論のための新データセット（GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering）</news:title>
   <news:publication_date>2026-08-10T23:36:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721791</loc>
  <lastmod>2026-08-10T23:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体の深層特徴のみを用いた画像記述（Using Deep Features of Only Objects to Describe Images）</news:title>
   <news:publication_date>2026-08-10T23:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721789</loc>
  <lastmod>2026-08-10T23:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成ノイズによる機械翻訳の堅牢化（Improving Robustness of Machine Translation with Synthetic Noise）</news:title>
   <news:publication_date>2026-08-10T23:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721784</loc>
  <lastmod>2026-08-10T22:44:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頭蓋内高血圧の早期予測を目指す多階層波形解析（Forecasting intracranial hypertension using multi-scale waveform metrics）</news:title>
   <news:publication_date>2026-08-10T22:44:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721782</loc>
  <lastmod>2026-08-10T22:44:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈依存型単語埋め込みの言語間整合とゼロショット構文解析への応用（Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing）</news:title>
   <news:publication_date>2026-08-10T22:44:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721780</loc>
  <lastmod>2026-08-10T22:43:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚質問応答のためのマルチモーダル関係推論（MUREL: Multimodal Relational Reasoning for Visual Question Answering）</news:title>
   <news:publication_date>2026-08-10T22:43:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721778</loc>
  <lastmod>2026-08-10T22:43:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似k近傍探索における適応的推定の考え方（Adaptive Estimation for Approximate k-Nearest-Neighbor Computations）</news:title>
   <news:publication_date>2026-08-10T22:43:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721776</loc>
  <lastmod>2026-08-10T22:42:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付き損失関数と異種信号のための行列デノイジング（Matrix denoising for weighted loss functions and heterogeneous signals）</news:title>
   <news:publication_date>2026-08-10T22:42:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721774</loc>
  <lastmod>2026-08-10T22:42:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸特異値しきい値によるロジスティック主成分分析（Logistic principal component analysis via non-convex singular value thresholding）</news:title>
   <news:publication_date>2026-08-10T22:42:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721772</loc>
  <lastmod>2026-08-10T22:42:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MedMentions：UMLSで注釈された大規模バイオ医療コーパスの公開（MedMentions: A Large Biomedical Corpus Annotated with UMLS Concepts）</news:title>
   <news:publication_date>2026-08-10T22:42:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721770</loc>
  <lastmod>2026-08-10T21:51:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長距離屋内ナビゲーションを実現するPRM-RL（Long-Range Indoor Navigation with PRM-RL）</news:title>
   <news:publication_date>2026-08-10T21:51:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721768</loc>
  <lastmod>2026-08-10T21:50:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>S-TRIGGER：自己トリガー型生成リプレイによる継続的状態表現学習（S-TRIGGER: Continual State Representation Learning via Self-Triggered Generative Replay）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-10T21:50:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-10T21:49:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-10T21:49:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-10T20:49:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習された変換によるワンショット医療画像セグメンテーションのデータ拡張（Data augmentation using learned transformations for one-shot medical image segmentation）</news:title>
   <news:publication_date>2026-08-10T20:49:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-10T20:48:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721748</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>コンパクトファジーモデル構築のための分散ルール導出アルゴリズムCFM-BD（CFM-BD: a distributed rule induction algorithm for building Compact Fuzzy Models in Big Data classification problems）</news:title>
   <news:publication_date>2026-08-10T20:47:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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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>半教師付き・弱教師付き階層テキスト分類のための効率的パス予測 (Efficient Path Prediction for Semi-Supervised and Weakly Supervised Hierarchical Text Classification)</news:title>
   <news:publication_date>2026-08-10T20:47:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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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>履歴を重視する視覚対話学習（Making History Matter: History-Advantage Sequence Training for Visual Dialog）</news:title>
   <news:publication_date>2026-08-10T20:47:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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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>重み付きパーソナライズ行列因子分解によるマルチラベルネットワーク分類（Multi-Label Network Classification via Weighted Personalized Factorizations）</news:title>
   <news:publication_date>2026-08-10T19:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-10T19:53:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news: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>2026-08-10T19:52:48Z</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>2026-08-10T19:52:36Z</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>
   </news:publication>
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   <news:publication_date>2026-08-10T19:01:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-10T18:52:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721722</loc>
  <lastmod>2026-08-10T18:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モジュール化によるニューラルネットワークの複雑性管理（Modularity as a Means for Complexity Management in Neural Networks Learning）</news:title>
   <news:publication_date>2026-08-10T18:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721720</loc>
  <lastmod>2026-08-10T18:51:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度表現学習による人物姿勢推定の刷新（Deep High-Resolution Representation Learning for Human Pose Estimation）</news:title>
   <news:publication_date>2026-08-10T18:51:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721718</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-10T18:51:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721716</loc>
  <lastmod>2026-08-10T18:51:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-10T18:51:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721714</loc>
  <lastmod>2026-08-10T17:58:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-10T17:58:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721712</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実生活下における鏡像系の皮質活動（Cortical Mirror-System Activation During Real-Life Game Playing: An Intracranial Electroencephalography (EEG) Study）</news:title>
   <news:publication_date>2026-08-10T17:58:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/721710</loc>
  <lastmod>2026-08-10T17:57:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>応答の多様性を高める周波数対応交差エントロピー損失（Improving Neural Response Diversity with Frequency-Aware Cross-Entropy Loss）</news:title>
   <news:publication_date>2026-08-10T17:57:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721708</loc>
  <lastmod>2026-08-10T17:57:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙の塵に覆われた星形成銀河の統計的性質—Herschelデータの多波長de-blend解析 (A multi-wavelength de-blended Herschel view of the statistical properties of dusty star-forming galaxies across cosmic time)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721706</loc>
  <lastmod>2026-08-10T17:56:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数領域を同時に学習する短答自動採点（Joint Multi-Domain Learning for Automatic Short Answer Grading）</news:title>
   <news:publication_date>2026-08-10T17:56:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721704</loc>
  <lastmod>2026-08-10T17:56:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転におけるコーナーケース検出の実装と評価（Towards Corner Case Detection for Autonomous Driving）</news:title>
   <news:publication_date>2026-08-10T17:56:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/721702</loc>
  <lastmod>2026-08-10T17:56:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GFCN：並列フローに基づく新しいグラフ畳み込みネットワーク（GFCN: A New Graph Convolutional Network Based on Parallel Flows）</news:title>
   <news:publication_date>2026-08-10T17:56:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721700</loc>
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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>医療画像解析におけるクラウドソーシングの概観（A Survey of Crowdsourcing in Medical Image Analysis）</news:title>
   <news:publication_date>2026-08-10T17:05:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news: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>
  <loc>https://aibr.jp/archives/721694</loc>
  <lastmod>2026-08-10T17:04:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長読みに基づくウイルスゲノム進化の未来的方法（Futuristic methods in virus genome evolution using the Third-Generation DNA sequencing and artificial neural networks）</news:title>
   <news:publication_date>2026-08-10T17:04:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721692</loc>
  <lastmod>2026-08-10T17:04:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチグリッド偏微分方程式（PDE）ソルバーの最適化を学習する（Learning to Optimize Multigrid PDE Solvers）</news:title>
   <news:publication_date>2026-08-10T17:04:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721690</loc>
  <lastmod>2026-08-10T17:03:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Bayesian Multi-Target Learningによる推薦最適化の実務的理解（Deep Bayesian Multi-Target Learning for Recommender Systems）</news:title>
   <news:publication_date>2026-08-10T17:03:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721688</loc>
  <lastmod>2026-08-10T17:03:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DDFlow: ラベルなしデータから学ぶ光学フローの蒸留学習（DDFlow: Learning Optical Flow with Unlabeled Data Distillation）</news:title>
   <news:publication_date>2026-08-10T17:03:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721686</loc>
  <lastmod>2026-08-10T16:12:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフの集合を“点”で扱う時代へ（Unsupervised Network Embedding for Graph Visualization, Clustering and Classification）</news:title>
   <news:publication_date>2026-08-10T16:12:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721684</loc>
  <lastmod>2026-08-10T16:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を備えたグラフ畳み込みLSTMによるスケルトン動作認識（An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition）</news:title>
   <news:publication_date>2026-08-10T16:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721682</loc>
  <lastmod>2026-08-10T16:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリップされたバイナリのニューラル逆解析（Neural Reverse Engineering of Stripped Binaries using Augmented Control Flow Graphs）</news:title>
   <news:publication_date>2026-08-10T16:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721680</loc>
  <lastmod>2026-08-10T16:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル誤差を超えて: 自己教師ありエゴモーション推定における幾何学的マッチングの導入 (Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation)</news:title>
   <news:publication_date>2026-08-10T16:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721678</loc>
  <lastmod>2026-08-10T16:10:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク生成モデルによる動画表現と再構成（Generative Models for Low-Rank Video Representation and Reconstruction）</news:title>
   <news:publication_date>2026-08-10T16:10:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721676</loc>
  <lastmod>2026-08-10T16:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可視化、判別性、解釈可能なSaak特徴の応用（Visualization, Discriminability and Applications of Interpretable Saak Features）</news:title>
   <news:publication_date>2026-08-10T16:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721674</loc>
  <lastmod>2026-08-10T16:09:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Marathon Environments：商用ゲームエンジン上での連続制御ベンチマーク（Marathon Environments: Multi-Agent Continuous Control Benchmarks in a Modern Video Game Engine）</news:title>
   <news:publication_date>2026-08-10T16:09:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721672</loc>
  <lastmod>2026-08-10T15:18:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGA上のグラフ処理の分類と課題（Graph Processing on FPGAs: Taxonomy, Survey, Challenges）</news:title>
   <news:publication_date>2026-08-10T15:18:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721670</loc>
  <lastmod>2026-08-10T15:09:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィールド対応ニューラル因子分解機によるクリック率予測（Field-aware Neural Factorization Machine for Click-Through Rate Prediction）</news:title>
   <news:publication_date>2026-08-10T15:09:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721668</loc>
  <lastmod>2026-08-10T15:09:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DRAMの電源立ち上げ特性を機器認証に使う新手法（DRAMNet: Authentication based on Physical Unique Features of DRAM Using Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-10T15:09:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721666</loc>
  <lastmod>2026-08-10T15:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系列データの転移学習：単語の共起を学んで移す（TRANSFER LEARNING FOR SEQUENCES VIA LEARNING TO COLLOCATE）</news:title>
   <news:publication_date>2026-08-10T15:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721664</loc>
  <lastmod>2026-08-10T15:08:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極端温度下で動作する自己整流BFOメモリスタの学習・記憶機能（Synaptic Learning and Memory Functions Achieved in Self-rectifying BFO Memristor under Extreme Environmental Temperature）</news:title>
   <news:publication_date>2026-08-10T15:08:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721662</loc>
  <lastmod>2026-08-10T15:07:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レンズレスな秘匿映像で行動認識を可能にする技術（Privacy-Preserving Action Recognition using Coded Aperture Videos）</news:title>
   <news:publication_date>2026-08-10T15:07:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721660</loc>
  <lastmod>2026-08-10T15:07:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識ベースを活用するLSTMによる機械読解の向上（Leveraging Knowledge Bases in LSTMs for Improving Machine Reading）</news:title>
   <news:publication_date>2026-08-10T15:07:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721658</loc>
  <lastmod>2026-08-10T14:15:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩行者検出における意味的自己注意による精度向上（SSA-CNN: Semantic Self-Attention CNN for Pedestrian Detection）</news:title>
   <news:publication_date>2026-08-10T14:15:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721656</loc>
  <lastmod>2026-08-10T14:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャネル敵対的学習によるクロスチャネル話者認識の改善（Channel Adversarial Training for Cross-Channel Text-Independent Speaker Recognition）</news:title>
   <news:publication_date>2026-08-10T14:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721654</loc>
  <lastmod>2026-08-10T14:15:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CFD駆動機械学習によるRANS乱流モデル開発（RANS Turbulence Model Development using CFD-Driven Machine Learning）</news:title>
   <news:publication_date>2026-08-10T14:15:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721652</loc>
  <lastmod>2026-08-10T14:14:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルゴンにおける39Arと37Arの宇宙生成（Cosmogenic production of 39Ar and 37Ar in argon）</news:title>
   <news:publication_date>2026-08-10T14:14:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721650</loc>
  <lastmod>2026-08-10T14:13:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wasserstein GANがPCAを実現する可能性（Wasserstein GAN Can Perform PCA）</news:title>
   <news:publication_date>2026-08-10T14:13:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721648</loc>
  <lastmod>2026-08-10T14:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転意図予測の実用的アプローチ（A Driving Intention Prediction Method Based on Hidden Markov Model for Autonomous Driving）</news:title>
   <news:publication_date>2026-08-10T14:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721646</loc>
  <lastmod>2026-08-10T14:13:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アフリカ森林ゾウの受動音響モニタリングにおける自動検出と圧縮（Automatic Detection and Compression for Passive Acoustic Monitoring of the African Forest Elephant）</news:title>
   <news:publication_date>2026-08-10T14:13:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721644</loc>
  <lastmod>2026-08-10T13:21:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測下における自律型コンピュータネットワーク防御のための敵対的強化学習（Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence）</news:title>
   <news:publication_date>2026-08-10T13:21:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721642</loc>
  <lastmod>2026-08-10T13:21:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル演算による高価なベイズ計算の高速化（Vector operations for accelerating expensive Bayesian computations – a tutorial guide）</news:title>
   <news:publication_date>2026-08-10T13:21:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721640</loc>
  <lastmod>2026-08-10T13:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動ロボットによる堅牢で適応的なドア操作（Robust and Adaptive Door Operation with a Mobile Robot）</news:title>
   <news:publication_date>2026-08-10T13:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721638</loc>
  <lastmod>2026-08-10T13:20:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最急適応モーメント推定（Rapidly Adapting Moment Estimation）</news:title>
   <news:publication_date>2026-08-10T13:20:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721636</loc>
  <lastmod>2026-08-10T13:20:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単調単一インデックスモデルの非線形一般化（Nonlinear generalization of the monotone single index model）</news:title>
   <news:publication_date>2026-08-10T13:20:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721634</loc>
  <lastmod>2026-08-10T13:19:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一前向きステップによる射影分割：ココーシビティの活用（Single-Forward-Step Projective Splitting: Exploiting Cocoercivity）</news:title>
   <news:publication_date>2026-08-10T13:19:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721632</loc>
  <lastmod>2026-08-10T13:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的推定器は深層ニューラルネットの情報圧縮を示す（Adaptive Estimators Show Information Compression in Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-10T13:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721630</loc>
  <lastmod>2026-08-10T12:26:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>役割と充填子の結合学習（Learning to Perform Role-Filler Binding with Schematic Knowledge）</news:title>
   <news:publication_date>2026-08-10T12:26:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721628</loc>
  <lastmod>2026-08-10T12:24:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エアリービームを用いた蛍光イメージングの深部透過（Deep penetration fluorescence imaging through dense yeast cells suspensions using Airy beams）</news:title>
   <news:publication_date>2026-08-10T12:24:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721626</loc>
  <lastmod>2026-08-10T12:24:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きなマージンを持つ半空間の差分プライバシー学習アルゴリズム（Efficient Private Algorithms for Learning Large-Margin Halfspaces）</news:title>
   <news:publication_date>2026-08-10T12:24:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721624</loc>
  <lastmod>2026-08-10T12:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無制約オンライン学習のための人工的制約とリプシッツヒント（Artificial Constraints and Lipschitz Hints for Unconstrained Online Learning）</news:title>
   <news:publication_date>2026-08-10T12:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721622</loc>
  <lastmod>2026-08-10T12:22:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元制約付き連合モデル選択と分布シフト下の多目的ベイズ最適化 (High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions)</news:title>
   <news:publication_date>2026-08-10T12:22:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721620</loc>
  <lastmod>2026-08-10T12:22:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AgentBuddy: 顧客対応支援のための文脈型バンディット（AgentBuddy: A Contextual Bandit based Decision Support System for Customer Support Agents）</news:title>
   <news:publication_date>2026-08-10T12:22:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721618</loc>
  <lastmod>2026-08-10T12:21:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数のオンライン学習アルゴリズムを安全に組み合わせる方法（Combining Online Learning Guarantees）</news:title>
   <news:publication_date>2026-08-10T12:21:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721616</loc>
  <lastmod>2026-08-10T11:29:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U-NetPlusによる手術器具セグメンテーションの改良（U-NetPlus: A Modified Encoder-Decoder U-Net Architecture for Semantic and Instance Segmentation of Surgical Instrument）</news:title>
   <news:publication_date>2026-08-10T11:29:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721614</loc>
  <lastmod>2026-08-10T11:28:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部位を超えた深層学習によるがん検出の移植性（Transferability of Deep Learning Algorithms for Malignancy Detection in Confocal Laser Endomicroscopy Images from Different Anatomical Locations of the Upper Gastrointestinal Tract）</news:title>
   <news:publication_date>2026-08-10T11:28:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721612</loc>
  <lastmod>2026-08-10T11:28:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>慢性疼痛における防護的行動の深層学習による検出（Chronic-Pain Protective Behavior Detection with Deep Learning）</news:title>
   <news:publication_date>2026-08-10T11:28:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721610</loc>
  <lastmod>2026-08-10T11:28:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習に基づくモデル予測制御（An Online Learning Approach to Model Predictive Control）</news:title>
   <news:publication_date>2026-08-10T11:28:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721608</loc>
  <lastmod>2026-08-10T11:27:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同期双方向推論が変える系列生成の常識（Synchronous Bidirectional Inference for Neural Sequence Generation）</news:title>
   <news:publication_date>2026-08-10T11:27:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721606</loc>
  <lastmod>2026-08-10T11:27:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>車載CANログからのセンサ信号抽出による運転者再識別（Extracting vehicle sensor signals from CAN logs for driver re-identification）</news:title>
   <news:publication_date>2026-08-10T11:27:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721604</loc>
  <lastmod>2026-08-10T11:27:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>類似度に基づく自然勾配法の一般化（A Formalization of The Natural Gradient Method for General Similarity Measures）</news:title>
   <news:publication_date>2026-08-10T11:27:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/721602</loc>
  <lastmod>2026-08-10T10:35:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-10T10:35:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721600</loc>
  <lastmod>2026-08-10T10:35:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠心加速度でGANの学習を安定化する（Training GANs with Centripetal Acceleration）</news:title>
   <news:publication_date>2026-08-10T10:35:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721598</loc>
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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>モデルレスな能動コンプライアンス：リカレントニューラルネットワークによる連続体ロボット制御（Model-less Active Compliance for Continuum Robots using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-08-10T10:34:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-10T10:34:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-10T10:34:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>健康経済評価における非遵守と欠測データ（Non-compliance and missing data in health economic evaluation）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721592</loc>
  <lastmod>2026-08-10T10:33:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置情報データ公開における機械学習ベース匿名化の実務的意義（Privacy Preserving Location Data Publishing: A Machine Learning Approach）</news:title>
   <news:publication_date>2026-08-10T10:33:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/721590</loc>
  <lastmod>2026-08-10T10:33:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-10T10:33:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721588</loc>
  <lastmod>2026-08-10T09:41:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動きブレ補正を高速化するBi-Skipと自己ペース学習（Bi-Skip: A Motion Deblurring Network Using Self-paced Learning）</news:title>
   <news:publication_date>2026-08-10T09:41:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721586</loc>
  <lastmod>2026-08-10T09:41:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-10T09:41:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721584</loc>
  <lastmod>2026-08-10T09:41:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MaskDGAによるDGA検出回避の実務的インパクト（MaskDGA: A Black-box Evasion Technique Against DGA Classifiers and Adversarial Defenses）</news:title>
   <news:publication_date>2026-08-10T09:41:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721582</loc>
  <lastmod>2026-08-10T09:40:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限ファイル寿命を考慮したキャッシュ補助無線ネットワークにおけるファイル配置と配信の同時ダウンリンクスケジューリング（Joint Downlink Scheduling for File Placement and Delivery in Cache-Assisted Wireless Networks with Finite File Lifetime）</news:title>
   <news:publication_date>2026-08-10T09:40:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721580</loc>
  <lastmod>2026-08-10T09:40:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D誘導による細粒度顔操作（3D Guided Fine-Grained Face Manipulation）</news:title>
   <news:publication_date>2026-08-10T09:40:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721578</loc>
  <lastmod>2026-08-10T09:40:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絵文字を利用した感情分類器の学習手法（On the Use of Emojis to Train Emotion Classifiers）</news:title>
   <news:publication_date>2026-08-10T09:40:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721576</loc>
  <lastmod>2026-08-10T09:39:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子によるツインSVMの高速化（Quantum Speedup of Twin Support Vector Machines）</news:title>
   <news:publication_date>2026-08-10T09:39:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721574</loc>
  <lastmod>2026-08-10T08:48:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTエッジ機器上での画像分類の実務的評価（Image Classification on IoT Edge Devices: Profiling and Modeling）</news:title>
   <news:publication_date>2026-08-10T08:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721572</loc>
  <lastmod>2026-08-10T08:48:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像を使った結核診断に関する深層学習研究の意義（TBNet: Pulmonary Tuberculosis Diagnosing System using Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-10T08:48:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721570</loc>
  <lastmod>2026-08-10T08:47:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療マルチモーダル分類器の低データ環境における性能（Medical Multimodal Classifiers Under Low Data Situations）</news:title>
   <news:publication_date>2026-08-10T08:47:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721568</loc>
  <lastmod>2026-08-10T08:47:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lassoのバイアス補正と自由度補正の意義（De-Biasing The Lasso With Degrees-of-Freedom Adjustment）</news:title>
   <news:publication_date>2026-08-10T08:47:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721566</loc>
  <lastmod>2026-08-10T08:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種ソースを階層強化学習で統合するEコマース検索（Aggregating E-commerce Search Results from Heterogeneous Sources via Hierarchical Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-10T08:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721564</loc>
  <lastmod>2026-08-10T08:46:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実務で評価する差分プライバシー機械学習の意味（Evaluating Differentially Private Machine Learning in Practice）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721562</loc>
  <lastmod>2026-08-10T08:46:09Z</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/721560</loc>
  <lastmod>2026-08-10T07:54:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所集約単語埋め込みベクトル（Vector of Locally-Aggregated Word Embeddings: VLAWE）</news:title>
   <news:publication_date>2026-08-10T07:54:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-10T05:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:publication_date>2026-08-10T03:07:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-10T03:06:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721476</loc>
  <lastmod>2026-08-10T02:15:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的汚染に強い確率的バンディットの新アルゴリズム（Better Algorithms for Stochastic Bandits with Adversarial Corruptions）</news:title>
   <news:publication_date>2026-08-10T02:15:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721474</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>コードワードを用いたハッシュ関数学習（Learning Hash Function through Codewords）</news:title>
   <news:publication_date>2026-08-10T02:15:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721472</loc>
  <lastmod>2026-08-10T02:15:21Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OpenKiwi: 翻訳品質推定のオープンソース基盤（OpenKiwi: An Open Source Framework for Quality Estimation）</news:title>
   <news:publication_date>2026-08-10T02:15:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721470</loc>
  <lastmod>2026-08-10T02:14:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スカルプター矮小楕円銀河におけるX線源のマルチ波長調査（Multiwavelength survey of X-ray sources in the Sculptor Dwarf Spheroidal Galaxy）</news:title>
   <news:publication_date>2026-08-10T02:14:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721468</loc>
  <lastmod>2026-08-10T02:14:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトロ光度距離とGaia DR2パララックスゼロポイントの同時較正（Simultaneous calibration of spectro-photometric distances and the Gaia DR2 parallax zero-point offset with deep learning）</news:title>
   <news:publication_date>2026-08-10T02:14:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-10T02:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>惑星表面の熱物性を機械学習で推定する手法（Constraining the Thermal Properties of Planetary Surfaces using Machine Learning: Application to Airless Bodies）</news:title>
   <news:publication_date>2026-08-10T02:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721464</loc>
  <lastmod>2026-08-10T02:13:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル性能予測器（MPP: Model Performance Predictor）</news:title>
   <news:publication_date>2026-08-10T02:13:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721462</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>ガス圧縮と消耗によるクエンチング（Quenching by gas compression and consumption）</news:title>
   <news:publication_date>2026-08-10T01:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721460</loc>
  <lastmod>2026-08-10T01:22:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長距離相互作用ハミルトニアンにおける動的臨界性とドメインウォール結合（Dynamical criticality and domain-wall coupling in long-range Hamiltonians）</news:title>
   <news:publication_date>2026-08-10T01:22:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721458</loc>
  <lastmod>2026-08-10T01:22:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>測定不確実性下でのベイズ的異常検知と分類（Bayesian Anomaly Detection and Classification）</news:title>
   <news:publication_date>2026-08-10T01:22:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721456</loc>
  <lastmod>2026-08-10T01:20:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期依存を扱う混合型ニューラル推薦モデルの実務的理解（Towards Neural Mixture Recommender for Long Range Dependent User Sequences）</news:title>
   <news:publication_date>2026-08-10T01:20:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721454</loc>
  <lastmod>2026-08-10T01:20:45Z</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層を通したキャパシティ配分（Capacity allocation through neural network layers）</news:title>
   <news:publication_date>2026-08-10T01:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721452</loc>
  <lastmod>2026-08-10T01:20:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショット学習ベンチマークは本当に難しいか（Are Few-Shot Learning Benchmarks too Simple ? Solving them without Test-Time Labels）</news:title>
   <news:publication_date>2026-08-10T01:20:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721450</loc>
  <lastmod>2026-08-10T01:20:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常報酬と遅延フィードバックに強いバンディット戦略の設計（Multi-Armed Bandit Strategies for Non-Stationary Reward Distributions and Delayed Feedback Processes）</news:title>
   <news:publication_date>2026-08-10T01:20:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721448</loc>
  <lastmod>2026-08-10T00:27:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-10T00:27:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721446</loc>
  <lastmod>2026-08-10T00:27:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子クラウドによるジェット識別（Jet Tagging via Particle Clouds）</news:title>
   <news:publication_date>2026-08-10T00:27:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721444</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>多言語文埋め込みの改良（Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax）</news:title>
   <news:publication_date>2026-08-10T00:26:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721442</loc>
  <lastmod>2026-08-10T00:26:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既製の深層モデルから抽出した複合特徴による画像美学評価（Image Aesthetics Assessment Using Composite Features from Off-the-Shelf Deep Models）</news:title>
   <news:publication_date>2026-08-10T00:26:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721440</loc>
  <lastmod>2026-08-10T00:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TESS惑星候補の迅速分類（Rapid Classification of TESS Planet Candidates with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-10T00:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721438</loc>
  <lastmod>2026-08-10T00:26:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助知識整合による敵対的モデル反転の実行手法（Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment）</news:title>
   <news:publication_date>2026-08-10T00:26:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721436</loc>
  <lastmod>2026-08-10T00:25:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パルス渦電流の終端から終端の分類と回帰へのCNN（Towards end-to-end pulsed eddy current classification and regression with CNN）</news:title>
   <news:publication_date>2026-08-10T00:25:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721434</loc>
  <lastmod>2026-08-09T23:35:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2Dレーザで走行位置を推定するLSTMベースのリアルタイム走行推定（An LSTM Network for Real-Time Odometry Estimation）</news:title>
   <news:publication_date>2026-08-09T23:35:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721432</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロトコル非依存のグラフベース異常検知によるボット検出（Anomaly- and Graph-Based Bot Detection）</news:title>
   <news:publication_date>2026-08-09T23:34:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721430</loc>
  <lastmod>2026-08-09T23:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冷媒漏れのオンライントラブル診断を変えるスケーリング則（Fault Diagnosis Method Based on Scaling Law for On-line Refrigerant Leak Detection）</news:title>
   <news:publication_date>2026-08-09T23:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721428</loc>
  <lastmod>2026-08-09T23:33:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数運転モードを持つ産業システムの故障検知に向けたソフトセンサ半教師あり手法（Semi-supervised Approach to Soft Sensor Modeling for Fault Detection in Industrial Systems with Multiple Operation Modes）</news:title>
   <news:publication_date>2026-08-09T23:33:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721426</loc>
  <lastmod>2026-08-09T23:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク内集約による分散学習の高速化（Scaling Distributed Machine Learning with In-Network Aggregation）</news:title>
   <news:publication_date>2026-08-09T23:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721424</loc>
  <lastmod>2026-08-09T23:33:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低コントラスト・高形状多様性MRデータからの3D上腕骨・肩甲骨抽出の有効手法（Effective 3D Humerus and Scapula Extraction using Low-contrast and High-shape-variability MR Data）</news:title>
   <news:publication_date>2026-08-09T23:33:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721422</loc>
  <lastmod>2026-08-09T23:32:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AReSとMaRS—SDE推定の敵対的・MMD最小化回帰（AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs）</news:title>
   <news:publication_date>2026-08-09T23:32:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721420</loc>
  <lastmod>2026-08-09T22:40:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速多言語LSTMベースのオンライン手書き認識（Fast Multi-language LSTM-based Online Handwriting Recognition）</news:title>
   <news:publication_date>2026-08-09T22:40:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721418</loc>
  <lastmod>2026-08-09T22:40:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元でのモデルベースクラスタリングと適応射影（Model-based clustering in very high dimensions via adaptive projections）</news:title>
   <news:publication_date>2026-08-09T22:40:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721416</loc>
  <lastmod>2026-08-09T22:40:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データストリーム分類におけるアンサンブルの多様性（Diversity of Ensembles for Data Stream Classification）</news:title>
   <news:publication_date>2026-08-09T22:40:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721414</loc>
  <lastmod>2026-08-09T22:39:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>詳細な探索空間分類による集合問題の列挙困難変種の高速化 (Fine-grained Search Space Classification for Hard Enumeration Variants of Subset Problems)</news:title>
   <news:publication_date>2026-08-09T22:39:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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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>非凸分布の効率的サンプリング手法の改善（Nonconvex sampling with the Metropolis-adjusted Langevin algorithm）</news:title>
   <news:publication_date>2026-08-09T22:38:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-09T22:38:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン異常検知がHPC運用を変える（Online Anomaly Detection in HPC Systems）</news:title>
   <news:publication_date>2026-08-09T22:38:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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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>サイバーフィジカル生産システムにおける認知アーキテクチャの評価（Evaluation of Cognitive Architectures for Cyber-Physical Production Systems）</news:title>
   <news:publication_date>2026-08-09T22:38:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721406</loc>
  <lastmod>2026-08-09T21:47:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインメタラーニングの教科書的解説（Online Meta-Learning）</news:title>
   <news:publication_date>2026-08-09T21:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721404</loc>
  <lastmod>2026-08-09T21:47:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズのあるリンク重みを扱うロバストなグラフ埋め込み（Robust Graph Embedding with Noisy Link Weights）</news:title>
   <news:publication_date>2026-08-09T21:47:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721402</loc>
  <lastmod>2026-08-09T21:46:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分非対称を用いたトランスベシティ分布の抽出（Transversity distributions from difference asymmetries in semi-inclusive DIS）</news:title>
   <news:publication_date>2026-08-09T21:46:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721400</loc>
  <lastmod>2026-08-09T21:46:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓病学における深層学習（Deep Learning in Cardiology）</news:title>
   <news:publication_date>2026-08-09T21:46:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721398</loc>
  <lastmod>2026-08-09T21:46:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>整列名義集合上の高速計算（Fast Computations on Ordered Nominal Sets）</news:title>
   <news:publication_date>2026-08-09T21:46:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721396</loc>
  <lastmod>2026-08-09T21:46:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ゲート制御に深層強化学習を使う意義（Deep Reinforcement Learning for Quantum Gate Control）</news:title>
   <news:publication_date>2026-08-09T21:46:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721394</loc>
  <lastmod>2026-08-09T21:45:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレーン・カプセルネットワークの実務的理解（The Multi-Lane Capsule Network）</news:title>
   <news:publication_date>2026-08-09T21:45:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721392</loc>
  <lastmod>2026-08-09T20:54:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ学習を用いたグラフニューラルネットワークへの敵対的攻撃（ADVERSARIAL ATTACKS ON GRAPH NEURAL NETWORKS VIA META LEARNING）</news:title>
   <news:publication_date>2026-08-09T20:54:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721390</loc>
  <lastmod>2026-08-09T20:53:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模皮質モデルの活動状態と並列シミュレーション性能のスケーリング（Scaling of a Large-Scale Simulation of Synchronous Slow-Wave and Asynchronous Awake-Like Activity of a Cortical Model With Long-Range Interconnections）</news:title>
   <news:publication_date>2026-08-09T20:53:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721388</loc>
  <lastmod>2026-08-09T20:52:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークによる二値マルコフ確率場の確率的推論（Probabilistic Inference of Binary Markov Random Fields in Spiking Neural Networks through Mean-field Approximation）</news:title>
   <news:publication_date>2026-08-09T20:52:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721386</loc>
  <lastmod>2026-08-09T20:52:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PhysNetによる分子エネルギーと力の高精度予測（PHYSNET: A NEURAL NETWORK FOR PREDICTING ENERGIES, FORCES, DIPOLE MOMENTS AND PARTIAL CHARGES）</news:title>
   <news:publication_date>2026-08-09T20:52:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721384</loc>
  <lastmod>2026-08-09T20:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル・コンディショナーによる指数的条件分布学習（Learning about an exponential amount of conditional distributions）</news:title>
   <news:publication_date>2026-08-09T20:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721382</loc>
  <lastmod>2026-08-09T20:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的テンソル表現とカプセルネットワークによるグラフ分類（Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations）</news:title>
   <news:publication_date>2026-08-09T20:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-09T20:51:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>autoAxによる近似回路ライブラリを用いた自動設計空間探索と回路構築（autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components）</news:title>
   <news:publication_date>2026-08-09T20:51:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721378</loc>
  <lastmod>2026-08-09T20:00:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMによる極性符号のSCフリップ復号学習（Learning to Flip Successive Cancellation Decoding of Polar Codes with LSTM Networks）</news:title>
   <news:publication_date>2026-08-09T20:00:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721376</loc>
  <lastmod>2026-08-09T19:59:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド自己符号化器通信系に対する物理的敵対的攻撃（Physical Adversarial Attacks Against End-to-End Autoencoder Communication Systems）</news:title>
   <news:publication_date>2026-08-09T19:59:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721374</loc>
  <lastmod>2026-08-09T19:59:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何的輸送問題の前処理（Preconditioning for the Geometric Transportation Problem）</news:title>
   <news:publication_date>2026-08-09T19:59:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721372</loc>
  <lastmod>2026-08-09T19:58:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ℓ1最小化における唯一の鋭い局所最小点（Unique Sharp Local Minimum in ℓ1-minimization Complete Dictionary Learning）</news:title>
   <news:publication_date>2026-08-09T19:58:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721370</loc>
  <lastmod>2026-08-09T19:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語監督から学ぶセマンティックパーサの学習（Learning to Learn Semantic Parsers from Natural Language Supervision）</news:title>
   <news:publication_date>2026-08-09T19:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721368</loc>
  <lastmod>2026-08-09T19:57:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超臨界流体における普遍性・スケーリング・崩壊（Universality, scaling and collapse in supercritical fluids）</news:title>
   <news:publication_date>2026-08-09T19:57:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721366</loc>
  <lastmod>2026-08-09T19:57:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>揮発性ディープユーテクトリック溶媒からの結晶化（Crystallisation From Volatile Deep Eutectic Solvents）</news:title>
   <news:publication_date>2026-08-09T19:57:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721364</loc>
  <lastmod>2026-08-09T19:06:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非自己回帰翻訳と補助正則化の実用的意義（Non-Autoregressive Machine Translation with Auxiliary Regularization）</news:title>
   <news:publication_date>2026-08-09T19:06:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721362</loc>
  <lastmod>2026-08-09T19:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模版・質問者の心の中にいる回答者による視覚対話質問生成（LARGE-SCALE ANSWERER IN QUESTIONER’S MIND FOR VISUAL DIALOG QUESTION GENERATION）</news:title>
   <news:publication_date>2026-08-09T19:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721360</loc>
  <lastmod>2026-08-09T19:05:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データの因子分離を可能にするFAVAE（FAVAE: Sequence Disentanglement using Information Bottleneck Principle）</news:title>
   <news:publication_date>2026-08-09T19:05:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721358</loc>
  <lastmod>2026-08-09T19:04:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力データ分布に対する敵対的頑健性の感度（On the Sensitivity of Adversarial Robustness to Input Data Distributions）</news:title>
   <news:publication_date>2026-08-09T19:04:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721356</loc>
  <lastmod>2026-08-09T19:04:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ネットワークのリンク予測を変えるE-LSTM-D（E-LSTM-D: A Deep Learning Framework for Dynamic Network Link Prediction）</news:title>
   <news:publication_date>2026-08-09T19:04:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721354</loc>
  <lastmod>2026-08-09T19:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間データに対する深層階層モデルと深層ニューラルモデルの比較（Comparison of Deep Neural Networks and Deep Hierarchical Models for Spatio-Temporal Data）</news:title>
   <news:publication_date>2026-08-09T19:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721352</loc>
  <lastmod>2026-08-09T19:03:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械ネットワークにおける学習された多安定性（Learned multi-stability in mechanical networks）</news:title>
   <news:publication_date>2026-08-09T19:03:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721350</loc>
  <lastmod>2026-08-09T18:12:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書に基づくRobust PCAの一般化とハイパースペクトル画像におけるターゲット局所化（A Dictionary-Based Generalization of Robust PCA with Applications to Target Localization in Hyperspectral Imaging）</news:title>
   <news:publication_date>2026-08-09T18:12:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721348</loc>
  <lastmod>2026-08-09T18:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NIGENS 一般音イベントデータベースの意義（NIGENS general sound events database）</news:title>
   <news:publication_date>2026-08-09T18:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721346</loc>
  <lastmod>2026-08-09T18:03:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的距離尺度学習の効率化と縮約（Reduced-Rank Local Distance Metric Learning for k-NN Classification）</news:title>
   <news:publication_date>2026-08-09T18:03:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721344</loc>
  <lastmod>2026-08-09T18:01:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復一階法による非凸ミンマックス問題の解法（Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods）</news:title>
   <news:publication_date>2026-08-09T18:01:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721342</loc>
  <lastmod>2026-08-09T18:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ再最適化で性能問題を克服する方法（How I Learned to Stop Worrying and Love Re-optimization）</news:title>
   <news:publication_date>2026-08-09T18:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721340</loc>
  <lastmod>2026-08-09T18:01:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一方非凸ミンマックス問題に対するハイブリッドブロック逐次近似（Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications）</news:title>
   <news:publication_date>2026-08-09T18:01:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721338</loc>
  <lastmod>2026-08-09T18:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lingvo: シーケンス・ツー・シーケンス研究のためのモジュラー・フレームワーク（Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling）</news:title>
   <news:publication_date>2026-08-09T18:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-09T17:08:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721326</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>2026-08-09T17:06:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721324</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>2026-08-09T17:06:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-09T16:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721320</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>畳み込み解析オペレータ学習と訓練データ依存性（Convolutional Analysis Operator Learning: Dependence on Training Data）</news:title>
   <news:publication_date>2026-08-09T16:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的例の知覚歪みの定量化（Quantifying Perceptual Distortion of Adversarial Examples）</news:title>
   <news:publication_date>2026-08-09T16:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721316</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-09T16:12:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721314</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>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模バッチSGDに構造化共分散ノイズを加える手法（Large-Batch Stochastic Gradient Descent with Structured Covariance Noise）</news:title>
   <news:publication_date>2026-08-09T15:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-09T15:19:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-09T15:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news: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>2026-08-09T15:18:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-09T15:18:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-09T14:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-09T14:26:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-09T13:33:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <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>画像から計画可能な一階述語論理表現を無教師で定着させる（Unsupervised Grounding of Plannable First-Order Logic Representation from Images）</news:title>
   <news:publication_date>2026-08-09T12:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721261</loc>
  <lastmod>2026-08-09T12:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習可能な単調点ごとの非線形性によるSoftmaxボトルネックの打破 (Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities)</news:title>
   <news:publication_date>2026-08-09T12:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721259</loc>
  <lastmod>2026-08-09T12:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像分類パイプラインにおける誤差寄与と伝播の定量化 (Quantifying contribution and propagation of error from computational steps, algorithms and hyperparameter choices in image classification pipelines)</news:title>
   <news:publication_date>2026-08-09T12:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721257</loc>
  <lastmod>2026-08-09T12:36:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会議録音の話者分離を速くする手法（INCREMENTAL TRANSFER LEARNING IN TWO-PASS INFORMATION BOTTLENECK BASED SPEAKER DIARIZATION SYSTEM FOR MEETINGS）</news:title>
   <news:publication_date>2026-08-09T12:36:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721255</loc>
  <lastmod>2026-08-09T12:36:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳児の周産期脳卒中スクリーニングのための一般運動評価の自動化（Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers）</news:title>
   <news:publication_date>2026-08-09T12:36:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721253</loc>
  <lastmod>2026-08-09T12:35:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識注入注意による短文分類（Deep Short Text Classification with Knowledge Powered Attention）</news:title>
   <news:publication_date>2026-08-09T12:35:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721251</loc>
  <lastmod>2026-08-09T11:44:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散Apriori類頻出アイテムセットの性能解析（Performance study of distributed Apriori-like frequent itemsets mining）</news:title>
   <news:publication_date>2026-08-09T11:44:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721249</loc>
  <lastmod>2026-08-09T11:43:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的オンライン学習で二値パーセプトロンを解く（Active online learning in the binary perceptron problem）</news:title>
   <news:publication_date>2026-08-09T11:43:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721247</loc>
  <lastmod>2026-08-09T11:43:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多人数バンディットの敵対的事例 (Multi-Player Bandits: The Adversarial Case)</news:title>
   <news:publication_date>2026-08-09T11:43:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721245</loc>
  <lastmod>2026-08-09T11:42:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高度なデジタルフォレンジックのタイムライン分析のための形式化知識表現モデル（A complete formalized knowledge representation model for advanced digital forensics timeline analysis）</news:title>
   <news:publication_date>2026-08-09T11:42:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721243</loc>
  <lastmod>2026-08-09T11:42:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等価関係構造の漸進学習（LIMIT LEARNING EQUIVALENCE STRUCTURES）</news:title>
   <news:publication_date>2026-08-09T11:42:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721241</loc>
  <lastmod>2026-08-09T11:42:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全体としての装いを学ぶ：ノード別グラフニューラルネットワークによるアウトフィット互換性学習（Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks）</news:title>
   <news:publication_date>2026-08-09T11:42:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721239</loc>
  <lastmod>2026-08-09T11:41:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索・推論・予測の役割を整理する（Exploration, inference and prediction in neuroscience and biomedicine）</news:title>
   <news:publication_date>2026-08-09T11:41:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721237</loc>
  <lastmod>2026-08-09T10:50:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心血管MRIの動きアーティファクト補正に敵対的生成ネットワークを使う（CMR Motion Artifact Correction using Generative Adversarial Nets）</news:title>
   <news:publication_date>2026-08-09T10:50:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721235</loc>
  <lastmod>2026-08-09T10:50:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不整形検出器ジオメトリの表現学習（Learning representations of irregular particle-detector geometry with distance-weighted graph networks）</news:title>
   <news:publication_date>2026-08-09T10:50:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721233</loc>
  <lastmod>2026-08-09T10:49:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化された肝臓および腫瘍セグメンテーションの共同深層学習アプローチ（A Joint Deep Learning Approach for Automated Liver and Tumor Segmentation）</news:title>
   <news:publication_date>2026-08-09T10:49:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721231</loc>
  <lastmod>2026-08-09T10:49:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助変数を選ぶ情報量基準と欠測データ解析（An information criterion for auxiliary variable selection in incomplete data analysis）</news:title>
   <news:publication_date>2026-08-09T10:49:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721229</loc>
  <lastmod>2026-08-09T10:48:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所変位場を用いたスパース弾性率再構築とクラスタリング（Sparse Elasticity Reconstruction and Clustering using Local Displacement Fields）</news:title>
   <news:publication_date>2026-08-09T10:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721227</loc>
  <lastmod>2026-08-09T10:48:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データの深層学習型射影（Deep Learning Multidimensional Projections）</news:title>
   <news:publication_date>2026-08-09T10:48:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721225</loc>
  <lastmod>2026-08-09T10:48:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注目マップを用いた深い識別表現学習（Deep Discriminative Representation Learning with Attention Map for Scene Classification）</news:title>
   <news:publication_date>2026-08-09T10:48:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721223</loc>
  <lastmod>2026-08-09T09:57:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一粒子追跡データにおける拡散モード分類（Classification of diffusion modes in single-particle tracking data: Feature-based versus deep-learning approach）</news:title>
   <news:publication_date>2026-08-09T09:57:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721221</loc>
  <lastmod>2026-08-09T09:57:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Public Sphere 2.0: オンライン新聞におけるターゲット化コメント（Public Sphere 2.0: Targeted Commenting in Online News Media）</news:title>
   <news:publication_date>2026-08-09T09:57:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721219</loc>
  <lastmod>2026-08-09T09:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習言語モデルを用いたインドネシア語会話文の固有表現認識（Pretrained language model transfer on neural named entity recognition in Indonesian conversational texts）</news:title>
   <news:publication_date>2026-08-09T09:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721217</loc>
  <lastmod>2026-08-09T09:55:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リング版Learning With Errorsの概観と経営視点での示唆（RING LEARNING WITH ERRORS: A CROSSROADS BETWEEN POSTQUANTUM CRYPTOGRAPHY, MACHINE LEARNING AND NUMBER THEORY）</news:title>
   <news:publication_date>2026-08-09T09:55:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721215</loc>
  <lastmod>2026-08-09T09:55:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>射影Sinkhorn反復によるWasserstein敵対的事例（Wasserstein Adversarial Examples via Projected Sinkhorn Iterations）</news:title>
   <news:publication_date>2026-08-09T09:55:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721213</loc>
  <lastmod>2026-08-09T09:55:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実な入力下のベイズ最適化（Bayesian optimisation under uncertain inputs）</news:title>
   <news:publication_date>2026-08-09T09:55:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721211</loc>
  <lastmod>2026-08-09T09:54:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線ネットワークにおける決定的方策とターゲットを用いた電力制御学習（Learning Deterministic Policy with Target for Power Control in Wireless Networks）</news:title>
   <news:publication_date>2026-08-09T09:54:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721209</loc>
  <lastmod>2026-08-09T09:03:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続的ストリーミングデータの外れ値採掘とFlinkへの実装（CONTINUOUS OUTLIER MINING OF STREAMING DATA IN FLINK）</news:title>
   <news:publication_date>2026-08-09T09:03:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721207</loc>
  <lastmod>2026-08-09T09:02:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ReLUニューラルネットワークによるSobolevノルム近似誤差境界（Error bounds for approximations with deep ReLU neural networks in W^{s,p} norms）</news:title>
   <news:publication_date>2026-08-09T09:02:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721205</loc>
  <lastmod>2026-08-09T09:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラウザ履歴に基づくリンク予測とカテゴリ別推薦（Web Links Prediction And Category-Wise Recommendation Based On Browser History）</news:title>
   <news:publication_date>2026-08-09T09:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721203</loc>
  <lastmod>2026-08-09T09:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層適応入力正規化（Deep Adaptive Input Normalization for Time Series Forecasting）</news:title>
   <news:publication_date>2026-08-09T09:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721201</loc>
  <lastmod>2026-08-09T09:01:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多モダリティ全心臓セグメンテーションの評価チャレンジ（Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge）</news:title>
   <news:publication_date>2026-08-09T09:01:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721199</loc>
  <lastmod>2026-08-09T09:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>縦方向偏極核におけるSIDISの二ハドロン生成における単一スピン非対称性（Single-spin asymmetry in dihadron production in SIDIS off the longitudinally polarized nucleon target）</news:title>
   <news:publication_date>2026-08-09T09:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721197</loc>
  <lastmod>2026-08-09T09:01:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会議音声の「誰が・何人・いつ」を同時に処理する全ニューラル手法（ALL-NEURAL ONLINE SOURCE SEPARATION, COUNTING, AND DIARIZATION FOR MEETING ANALYSIS）</news:title>
   <news:publication_date>2026-08-09T09:01:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721195</loc>
  <lastmod>2026-08-09T08:10:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間周波数の視点でセンシング信号を学習する短時間フーリエニューラルネットワーク（STFNets: Learning Sensing Signals from the Time-Frequency Perspective with Short-Time Fourier Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721193</loc>
  <lastmod>2026-08-09T08:01:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-09T08:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721191</loc>
  <lastmod>2026-08-09T08:01:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話文における感情検出モデルの実践──RCNNと事前学習表現の組合せ（ntuer at SemEval-2019 Task 3: Emotion Classification with Word and Sentence Representations in RCNN）</news:title>
   <news:publication_date>2026-08-09T08:01:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721189</loc>
  <lastmod>2026-08-09T08:01:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ニューラル記号モデルによる可解性の高い視覚質問応答（Probabilistic Neural-symbolic Models for Interpretable Visual Question Answering）</news:title>
   <news:publication_date>2026-08-09T08:01:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721187</loc>
  <lastmod>2026-08-09T08:00:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗号資産投資におけるニューラルネットワーク積み上げ法（Stacking with Neural network for Cryptocurrency investment）</news:title>
   <news:publication_date>2026-08-09T08:00:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721185</loc>
  <lastmod>2026-08-09T08:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続学習に基づく堅牢な大規模推薦システム（Sequential Learning over Implicit Feedback for Robust Large-Scale Recommender Systems）</news:title>
   <news:publication_date>2026-08-09T08:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721183</loc>
  <lastmod>2026-08-09T08:00:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定性を考慮したベイズ最適化の手法（Stable Bayesian Optimisation via Direct Stability Quantification）</news:title>
   <news:publication_date>2026-08-09T08:00:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721181</loc>
  <lastmod>2026-08-09T07:09:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的特徴集約による人体姿勢推定の改良（Cascade Feature Aggregation for Human Pose Estimation）</news:title>
   <news:publication_date>2026-08-09T07:09:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721179</loc>
  <lastmod>2026-08-09T07:09:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層マルチモーダル物体検出とセマンティックセグメンテーション（Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges）</news:title>
   <news:publication_date>2026-08-09T07:09:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721177</loc>
  <lastmod>2026-08-09T07:08:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ConceptNetの経路品質予測（Predicting ConceptNet Path Quality Using Crowdsourced Assessments of Naturalness）</news:title>
   <news:publication_date>2026-08-09T07:08:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721175</loc>
  <lastmod>2026-08-09T07:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重空間─Winograd領域での同時スパース化による畳み込みニューラルネットワーク（JOINTLY SPARSE CONVOLUTIONAL NEURAL NETWORKS IN DUAL SPATIAL-WINOGRAD DOMAINS）</news:title>
   <news:publication_date>2026-08-09T07:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721173</loc>
  <lastmod>2026-08-09T07:07:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確からしさ等価が線形二次制御に効く理由（Certainty Equivalence is Efficient for Linear Quadratic Control）</news:title>
   <news:publication_date>2026-08-09T07:07:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721171</loc>
  <lastmod>2026-08-09T07:07:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定で公平な分類の設計（Stable and Fair Classification）</news:title>
   <news:publication_date>2026-08-09T07:07:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721169</loc>
  <lastmod>2026-08-09T07:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対応分析をニューラルネットで拡張する（Correspondence Analysis Using Neural Networks）</news:title>
   <news:publication_date>2026-08-09T07:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721167</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>多層プーリングによる深層スピーカー埋め込み学習（DEEP SPEAKER EMBEDDING LEARNING WITH MULTI-LEVEL POOLING FOR TEXT-INDEPENDENT SPEAKER VERIFICATION）</news:title>
   <news:publication_date>2026-08-09T06:15:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721165</loc>
  <lastmod>2026-08-09T06:14:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様な機械翻訳を実現する混合モデルの工夫（Mixture Models for Diverse Machine Translation: Tricks of the Trade）</news:title>
   <news:publication_date>2026-08-09T06:14:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721163</loc>
  <lastmod>2026-08-09T06:14:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声文の音響と言語を同時にとらえる埋め込み（AUDIO-LINGUISTIC EMBEDDINGS FOR SPOKEN SENTENCES）</news:title>
   <news:publication_date>2026-08-09T06:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721161</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>半教師あり関係抽出のための二重検索モジュール学習（Learning Dual Retrieval Module for Semi-supervised Relation Extraction）</news:title>
   <news:publication_date>2026-08-09T06:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721159</loc>
  <lastmod>2026-08-09T06:13:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機会主義的文脈的バンディット学習の実践と評価（AdaLinUCB: Opportunistic Learning for Contextual Bandits）</news:title>
   <news:publication_date>2026-08-09T06:13:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721157</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>触覚を用いた力のシミュレーション（Simulating Forces: Learning Through Touch, Virtual Laboratories）</news:title>
   <news:publication_date>2026-08-09T06:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721155</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>分散型最適潮流と電圧制御のための回帰ベースのインバータ制御（Regression-based Inverter Control for Decentralized Optimal Power Flow and Voltage Regulation）</news:title>
   <news:publication_date>2026-08-09T06:12:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721153</loc>
  <lastmod>2026-08-09T05:20:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階級体論、ディオファントス解析と漸近的フェルマーの最終定理（Class Field Theory, Diophantine Analysis and The Asymptotic Fermat’s Last Theorem）</news:title>
   <news:publication_date>2026-08-09T05:20:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721151</loc>
  <lastmod>2026-08-09T05:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>整数値関数データ解析による麻疹予測（Integer-Valued Functional Data Analysis for Measles Forecasting）</news:title>
   <news:publication_date>2026-08-09T05:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721149</loc>
  <lastmod>2026-08-09T05:20:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コーヒーショップで学ぶバイオフィジクスの教訓（Biophysics at the coffee shop: lessons learned working with George Oster）</news:title>
   <news:publication_date>2026-08-09T05:20:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721147</loc>
  <lastmod>2026-08-09T05:19:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解析的グラフィックスタティクス（Analytical graphic statics）</news:title>
   <news:publication_date>2026-08-09T05:19:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721145</loc>
  <lastmod>2026-08-09T05:19:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース精度行列を持つ確率的局所相互作用モデルによる時空間補間（Stochastic Local Interaction Model with Sparse Precision Matrix for Space-Time Interpolation）</news:title>
   <news:publication_date>2026-08-09T05:19:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721143</loc>
  <lastmod>2026-08-09T05:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚品質を保つブラックボックス攻撃（Perceptual quality-preserving black-box attack against deep learning image classifiers）</news:title>
   <news:publication_date>2026-08-09T05:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721141</loc>
  <lastmod>2026-08-09T05:18:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼内視鏡における密な深度推定（Dense Depth Estimation in Monocular Endoscopy with Self-supervised Learning Methods）</news:title>
   <news:publication_date>2026-08-09T05:18:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721139</loc>
  <lastmod>2026-08-09T04:25:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>N量子ビット系における実験的な対ペアもつれ推定（Experimental pairwise entanglement estimation for an N-qubit system）</news:title>
   <news:publication_date>2026-08-09T04:25:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721137</loc>
  <lastmod>2026-08-09T04:25:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cryptϵによる暗号支援差分プライバシー（Cryptϵ: Crypto-Assisted Differential Privacy on Untrusted Servers）</news:title>
   <news:publication_date>2026-08-09T04:25:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721135</loc>
  <lastmod>2026-08-09T04:25:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マンモグラフィ画像分類のための敵対的データ拡張（Adversarial Augmentation for Enhancing Classification of Mammography Images）</news:title>
   <news:publication_date>2026-08-09T04:25:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721133</loc>
  <lastmod>2026-08-09T04:23:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全文検索エンジン上でのハミング空間近傍探索の高速化（Fast and Exact Nearest Neighbor Search in Hamming Space on Full-Text Search Engines）</news:title>
   <news:publication_date>2026-08-09T04:23:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721131</loc>
  <lastmod>2026-08-09T04:23:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fermi検出のBCU光学分類を機械学習で評価する（Evaluating the optical classification of Fermi BCUs using machine learning）</news:title>
   <news:publication_date>2026-08-09T04:23:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721129</loc>
  <lastmod>2026-08-09T04:23:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デュアルエンド読み出しを用いた有機シンチレーターバーの位置・時間・エネルギー分解能（Interaction position, time, and energy resolution in organic scintillator bars with dual-ended readout）</news:title>
   <news:publication_date>2026-08-09T04:23:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721127</loc>
  <lastmod>2026-08-09T04:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語から目的を学ぶ：視覚ベースの指示遂行における逆強化学習（From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following）</news:title>
   <news:publication_date>2026-08-09T04:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721125</loc>
  <lastmod>2026-08-09T03:31:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雑音下の行列補完と凸緩和の統計的保証（Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization）</news:title>
   <news:publication_date>2026-08-09T03:31:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-09T03:31:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非平滑・非凸正則化問題に対する確率的手法の非漸近解析（Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems）</news:title>
   <news:publication_date>2026-08-09T03:31:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/721121</loc>
  <lastmod>2026-08-09T03:31:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識に基づくCT画像からの死亡率予測（Knowledge-based Analysis for Mortality Prediction from CT Images）</news:title>
   <news:publication_date>2026-08-09T03:31:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721119</loc>
  <lastmod>2026-08-09T03:30:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習率を自動で見つけるlossgrad（lossgrad: automatic learning rate in gradient descent）</news:title>
   <news:publication_date>2026-08-09T03:30:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721117</loc>
  <lastmod>2026-08-09T03:30:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続Q関数の学習と一般化ベンダーズカット（Learning continuous Q-functions using generalized Benders cuts）</news:title>
   <news:publication_date>2026-08-09T03:30:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721115</loc>
  <lastmod>2026-08-09T03:29:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序回帰における特徴関連性境界の提示（Feature Relevance Bounds for Ordinal Regression）</news:title>
   <news:publication_date>2026-08-09T03:29:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721113</loc>
  <lastmod>2026-08-09T03:29:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>年齢知覚バイアスが実年齢回帰に与える影響（On the effect of age perception biases for real age regression）</news:title>
   <news:publication_date>2026-08-09T03:29:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721111</loc>
  <lastmod>2026-08-09T02:38:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>貢献的社会資本の抽出（Contributive Social Capital Extraction）</news:title>
   <news:publication_date>2026-08-09T02:38:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721109</loc>
  <lastmod>2026-08-09T02:37:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期視覚系の輪郭統合を捉えるSparse Deep Predictive Coding（Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system）</news:title>
   <news:publication_date>2026-08-09T02:37:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721107</loc>
  <lastmod>2026-08-09T02:36:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点ターゲットのオンライン学習によるフィルタリング（Filtering Point Targets via Online Learning of Motion Models）</news:title>
   <news:publication_date>2026-08-09T02:36:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721105</loc>
  <lastmod>2026-08-09T02:36:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>調査における能動的行列因子分解（Active Matrix Factorization for Surveys）</news:title>
   <news:publication_date>2026-08-09T02:36:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721103</loc>
  <lastmod>2026-08-09T02:36:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>advertorch: PyTorchベースの敵対的堅牢性ツールボックス（advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch）</news:title>
   <news:publication_date>2026-08-09T02:36:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721101</loc>
  <lastmod>2026-08-09T02:36:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>A最適サブサンプリングによる適応反復ヘッシアン・スケッチ（Adaptive Iterative Hessian Sketch via A-Optimal Subsampling）</news:title>
   <news:publication_date>2026-08-09T02:36:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721099</loc>
  <lastmod>2026-08-09T01:44:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼領域を超えて：ロバストMDPのためのタイトなベイズ的あいまい性集合（Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs）</news:title>
   <news:publication_date>2026-08-09T01:44:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721097</loc>
  <lastmod>2026-08-09T01:43:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガイアDR2を用いたρオフィクス星域の会員候補調査（Census of ρ Oph candidate members from Gaia Data Release 2）</news:title>
   <news:publication_date>2026-08-09T01:43:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721095</loc>
  <lastmod>2026-08-09T01:43:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒルベルト空間はもっと小さくできるのか（Could the Hilbert Space Be a Smaller Place? A Neural Network Perspective）</news:title>
   <news:publication_date>2026-08-09T01:43:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721093</loc>
  <lastmod>2026-08-09T01:42:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の発達段階を模倣するベイズニューラルネットワーク（Emulating Human Developmental Stages with Bayesian Neural Networks）</news:title>
   <news:publication_date>2026-08-09T01:42:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721091</loc>
  <lastmod>2026-08-09T01:42:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光ネットワークにおけるジャミング攻撃の検出と防御を機械学習で強化する方法（On Detecting and Preventing Jamming Attacks with Machine Learning in Optical Networks）</news:title>
   <news:publication_date>2026-08-09T01:42:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721089</loc>
  <lastmod>2026-08-09T01:42:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列に対する能動確率的推論による確率的最適化の前処理（Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization）</news:title>
   <news:publication_date>2026-08-09T01:42:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721087</loc>
  <lastmod>2026-08-09T01:41:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューリスティクはどこから来るのか（Where Do Heuristics Come From?）</news:title>
   <news:publication_date>2026-08-09T01:41:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721085</loc>
  <lastmod>2026-08-09T00:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散データのデータ協調解析（Data collaboration analysis for distributed datasets）</news:title>
   <news:publication_date>2026-08-09T00:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721083</loc>
  <lastmod>2026-08-09T00:50:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケール不変の適応オンライン学習法（Adaptive scale-invariant online algorithms for learning linear models）</news:title>
   <news:publication_date>2026-08-09T00:50:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721081</loc>
  <lastmod>2026-08-09T00:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験のレア度で学習を優先する好奇心駆動型優先付け（Curiosity-Driven Experience Prioritization via Density Estimation）</news:title>
   <news:publication_date>2026-08-09T00:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721079</loc>
  <lastmod>2026-08-09T00:49:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なハプティック形状探索の学習（LEARNING EFFICIENT HAPTIC SHAPE EXPLORATION WITH A RIGID TACTILE SENSOR ARRAY）</news:title>
   <news:publication_date>2026-08-09T00:49:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721077</loc>
  <lastmod>2026-08-09T00:49:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズのあるマルチラベル半教師付き次元削減（Noisy multi-label semi-supervised dimensionality reduction）</news:title>
   <news:publication_date>2026-08-09T00:49:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721075</loc>
  <lastmod>2026-08-09T00:49:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチベース出力空間敵対学習による視神経乳頭と杯の同時セグメンテーション（Patch-based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation）</news:title>
   <news:publication_date>2026-08-09T00:49:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721073</loc>
  <lastmod>2026-08-09T00:48:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>C2UCBの後悔境界の検証（A Note on Bounding Regret of the C2UCB Contextual Combinatorial Bandit）</news:title>
   <news:publication_date>2026-08-09T00:48:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721071</loc>
  <lastmod>2026-08-08T23:55:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調型マルチエージェント強化学習における行動価値ネットワークの因子分解の解析（Analysing Factorizations of Action-Value Networks for Cooperative Multi-Agent Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-08T23:55:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721069</loc>
  <lastmod>2026-08-08T23:55:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能なニューラル注意型推薦システム（NAIRS: A Neural Attentive Interpretable Recommendation System）</news:title>
   <news:publication_date>2026-08-08T23:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721067</loc>
  <lastmod>2026-08-08T23:54:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Petaﬂops級スーパーコンピュータ「Zhores」の設計と初期評価（“Zhores” —Petaﬂops supercomputer for data-driven modeling, machine learning and artificial intelligence）</news:title>
   <news:publication_date>2026-08-08T23:54:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721065</loc>
  <lastmod>2026-08-08T23:54:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間適応型フィルタユニットによるコンパクトで効率的な深層ニューラルネットワーク（Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-08T23:54:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721063</loc>
  <lastmod>2026-08-08T23:53:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声映像イベント局所化のための二重モダリティSeq2Seqネットワーク（DUAL-MODALITY SEQ2SEQ NETWORK FOR AUDIO-VISUAL EVENT LOCALIZATION）</news:title>
   <news:publication_date>2026-08-08T23:53:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721061</loc>
  <lastmod>2026-08-08T23:53:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Windows向けTLS実装の状態機械学習による脆弱性検出（Identification of Bugs and Vulnerabilities in TLS Implementation for Windows Operating System Using State Machine Learning）</news:title>
   <news:publication_date>2026-08-08T23:53:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721059</loc>
  <lastmod>2026-08-08T23:53:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テクスチャ画像や属性からの触覚振動生成（Vibrotactile Signal Generation from Texture Images or Attributes using Generative Adversarial Network）</news:title>
   <news:publication_date>2026-08-08T23:53:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721057</loc>
  <lastmod>2026-08-08T23:02:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGAベースCNNアクセラレータのためのエンドツーエンドコンパイラDNNVM（DNNVM: End-to-End Compiler Leveraging Heterogeneous Optimizations on FPGA-Based CNN Accelerators）</news:title>
   <news:publication_date>2026-08-08T23:02:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721055</loc>
  <lastmod>2026-08-08T23:01:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形解析による超新星コア内の高速対生成ニュートリノ振動の検討（Linear Analysis of Fast-Pairwise Collective Neutrino Oscillations in Core-Collapse Supernovae based on the Results of Boltzmann Simulations）</news:title>
   <news:publication_date>2026-08-08T23:01:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721053</loc>
  <lastmod>2026-08-08T23:01:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド負荷予測における簡便で実用的な時系列手法（Easily implementable time series forecasting techniques for resource provisioning in cloud computing）</news:title>
   <news:publication_date>2026-08-08T23:01:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721051</loc>
  <lastmod>2026-08-08T23:00:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>携帯電話データに基づく顧客の性別・年齢予測（Predicting customer&amp;#039;s gender and age depending on mobile phone data）</news:title>
   <news:publication_date>2026-08-08T23:00:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721049</loc>
  <lastmod>2026-08-08T23:00:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全で誤った教師付き情報下での学習（Learning with Inadequate and Incorrect Supervision）</news:title>
   <news:publication_date>2026-08-08T23:00:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721047</loc>
  <lastmod>2026-08-08T23:00:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンザフライ適応による非線形二重スケールシミュレーション（On-the-fly adaptivity for nonlinear twoscale simulations using artificial neural networks and reduced order modeling）</news:title>
   <news:publication_date>2026-08-08T23:00:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721045</loc>
  <lastmod>2026-08-08T23:00:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸ペナルティと非凸性制御による希薄信号の完全復元（Perfect reconstruction of sparse signals with piecewise continuous nonconvex penalties and nonconvexity control）</news:title>
   <news:publication_date>2026-08-08T23:00:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721043</loc>
  <lastmod>2026-08-08T22:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差記号有限オートマトンのクエリ学習アルゴリズム (Query Learning Algorithm for Residual Symbolic Finite Automata)</news:title>
   <news:publication_date>2026-08-08T22:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721041</loc>
  <lastmod>2026-08-08T22:08:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メキシカンハットウェーブレットカーネルELMによる多クラス分類（Mexican Hat Wavelet Kernel ELM for Multiclass Classification）</news:title>
   <news:publication_date>2026-08-08T22:08:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721039</loc>
  <lastmod>2026-08-08T22:08:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ℓ0とTℓ1によるスパースニューラルネット学習（Learning Sparse Neural Networks via ℓ0 and Tℓ1）</news:title>
   <news:publication_date>2026-08-08T22:08:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721037</loc>
  <lastmod>2026-08-08T22:06:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフにおける敵対的訓練（Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure）</news:title>
   <news:publication_date>2026-08-08T22:06:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721035</loc>
  <lastmod>2026-08-08T22:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散TD(0)の有限時間解析（Finite-Time Analysis of Distributed TD(0) with Linear Function Approximation for Multi-Agent Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-08T22:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721033</loc>
  <lastmod>2026-08-08T22:06:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LipschitzLR: 理論に基づく適応学習率で学習を速くする（LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence）</news:title>
   <news:publication_date>2026-08-08T22:06:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721031</loc>
  <lastmod>2026-08-08T22:06:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果フォレストによる処置効果推定（Estimating Treatment Effects with Causal Forests）</news:title>
   <news:publication_date>2026-08-08T22:06:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721029</loc>
  <lastmod>2026-08-08T21:15:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>保存-散逸形式とDoiの変分法の同値性の意義（Conservation-Dissipation Formalism for Soft Matter Physics: I. Equivalence with Doi’s Variational Approach）</news:title>
   <news:publication_date>2026-08-08T21:15:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721027</loc>
  <lastmod>2026-08-08T21:15:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダを用いた学習型画像圧縮の実装と評価（An Autoencoder-based Learned Image Compressor: Description of Challenge Proposal by NCTU）</news:title>
   <news:publication_date>2026-08-08T21:15:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721025</loc>
  <lastmod>2026-08-08T21:14:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均ケース最適還元によるスパースPCAの計算困難性の確立（Optimal Average-Case Reductions to Sparse PCA: From Weak Assumptions to Strong Hardness）</news:title>
   <news:publication_date>2026-08-08T21:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721023</loc>
  <lastmod>2026-08-08T21:13:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発話単位のエンドツーエンド言語識別（UTTERANCE-LEVEL END-TO-END LANGUAGE IDENTIFICATION USING ATTENTION-BASED CNN-BLSTM）</news:title>
   <news:publication_date>2026-08-08T21:13:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721021</loc>
  <lastmod>2026-08-08T21:13:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプル重み付けを自動で学ぶMeta-Weight-Net（Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting）</news:title>
   <news:publication_date>2026-08-08T21:13:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721019</loc>
  <lastmod>2026-08-08T21:13:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gaussian Processを用いた動的ペア比較モデル（Gaussian Process Priors for Dynamic Paired Comparison Modelling）</news:title>
   <news:publication_date>2026-08-08T21:13:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721017</loc>
  <lastmod>2026-08-08T21:13:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-08T21:13:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721015</loc>
  <lastmod>2026-08-08T20:21:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-08T20:21:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721013</loc>
  <lastmod>2026-08-08T20:13:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所構造表現と時間的依存性の学習による人体運動予測（Human Motion Prediction via Learning Local Structure Representations and Temporal Dependencies）</news:title>
   <news:publication_date>2026-08-08T20:13:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721011</loc>
  <lastmod>2026-08-08T20:13:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未トリミング動画における行動認識のための転移可能な自己注意表現学習（Learning Transferable Self-attentive Representations for Action Recognition in Untrimmed Videos with Weak Supervision）</news:title>
   <news:publication_date>2026-08-08T20:13:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721009</loc>
  <lastmod>2026-08-08T20:13:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られたセンサからの流体場復元を簡潔に実現する浅層ニューラルネットワーク（Shallow Neural Networks for Fluid Flow Reconstruction with Limited Sensors）</news:title>
   <news:publication_date>2026-08-08T20:13:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721007</loc>
  <lastmod>2026-08-08T20:12:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーボリック群における方程式解集合の形式言語化（Solutions sets to systems of equations in hyperbolic groups are EDT0L in PSPACE）</news:title>
   <news:publication_date>2026-08-08T20:12:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721005</loc>
  <lastmod>2026-08-08T20:12:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XONNによる秘匿推論の効率化（XONN: XNOR-based Oblivious Deep Neural Network Inference）</news:title>
   <news:publication_date>2026-08-08T20:12:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721003</loc>
  <lastmod>2026-08-08T20:11:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショットで物体を分割する適応マスク型プロキシ（Adaptive Masked Proxies for Few-Shot Segmentation）</news:title>
   <news:publication_date>2026-08-08T20:11:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/721001</loc>
  <lastmod>2026-08-08T19:20:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画顔認識における成分別特徴集約ネットワーク（Video Face Recognition: Component-wise Feature Aggregation Network (C-FAN))</news:title>
   <news:publication_date>2026-08-08T19:20:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720999</loc>
  <lastmod>2026-08-08T19:19:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模マンモグラフィCADにおける変形畳み込みネットワークの活用（Large-scale mammography CAD with Deformable Conv-Nets）</news:title>
   <news:publication_date>2026-08-08T19:19:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720997</loc>
  <lastmod>2026-08-08T19:19:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化オンライン適応による運動学的シナジーのパーソナライズ（Personalized On-line Adaptation of Kinematic Synergies for Human-Prosthesis Interfaces）</news:title>
   <news:publication_date>2026-08-08T19:19:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720995</loc>
  <lastmod>2026-08-08T19:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木星のアンモニア分布とVLAマップによる解析（Jupiter’s Ammonia Distribution Derived from VLA Maps at 3–37 GHz）</news:title>
   <news:publication_date>2026-08-08T19:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720993</loc>
  <lastmod>2026-08-08T19:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>扁桃体の高精度自動分割と不確実性推定を可能にするベイズ型FCNN（Accurate Automatic Segmentation of Amygdala Subnuclei and Modeling of Uncertainty via Bayesian Fully Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-08T19:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720991</loc>
  <lastmod>2026-08-08T19:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデータで歌声をコピーする技術（DATA EFFICIENT VOICE CLONING FOR NEURAL SINGING SYNTHESIS）</news:title>
   <news:publication_date>2026-08-08T19:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720989</loc>
  <lastmod>2026-08-08T19:17:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepBall: ボール検出のための深層ニューラルネットワーク（DeepBall: Deep Neural-Network Ball Detector）</news:title>
   <news:publication_date>2026-08-08T19:17:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720987</loc>
  <lastmod>2026-08-08T18:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続変動下のオンライン学習：動的敗北（ダイナミックリグレット）と削減（Online Learning with Continuous Variations: Dynamic Regret and Reductions）</news:title>
   <news:publication_date>2026-08-08T18:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720985</loc>
  <lastmod>2026-08-08T18:26:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一部特徴の敵対的破壊に強いサブスペース法（Subspace Methods That Are Resistant to a Limited Number of Features Corrupted by an Adversary）</news:title>
   <news:publication_date>2026-08-08T18:26:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720983</loc>
  <lastmod>2026-08-08T18:25:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EPICによる敗血症予測モデルの実装と有効性の検証（Accuracy of the Epic Sepsis Prediction Model in a Regional Health System）</news:title>
   <news:publication_date>2026-08-08T18:25:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720981</loc>
  <lastmod>2026-08-08T18:25:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シャドウプライスによる高速ニューラルネットワーク検証（Fast Neural Network Verification via Shadow Prices）</news:title>
   <news:publication_date>2026-08-08T18:25:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/720979</loc>
  <lastmod>2026-08-08T18:24:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNにおける記憶の理解と制御（Understanding and Controlling Memory in Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-08-08T18:24:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720977</loc>
  <lastmod>2026-08-08T18:24:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DOM-Q-NET：構造化言語でのグラウンド強化学習 (DOM-Q-NET: Grounded RL on Structured Language)</news:title>
   <news:publication_date>2026-08-08T18:24:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720975</loc>
  <lastmod>2026-08-08T18:24:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ最適化のための遺伝的アルゴリズムを用いた深層強化学習（Deep Reinforcement Learning using Genetic Algorithm for Parameter Optimization）</news:title>
   <news:publication_date>2026-08-08T18:24:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720973</loc>
  <lastmod>2026-08-08T17:32:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャル推薦のためのグラフニューラルネットワーク（Graph Neural Networks for Social Recommendation）</news:title>
   <news:publication_date>2026-08-08T17:32:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720971</loc>
  <lastmod>2026-08-08T17:31:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な線形正則化の学習（Learning Optimal Linear Regularizers）</news:title>
   <news:publication_date>2026-08-08T17:31:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720969</loc>
  <lastmod>2026-08-08T17:31:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適輸送によるスケーラブルなトンプソンサンプリング（Scalable Thompson Sampling via Optimal Transport）</news:title>
   <news:publication_date>2026-08-08T17:31:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720967</loc>
  <lastmod>2026-08-08T17:31:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河合体率の測定：z≈2クラスターにおけるHST観測解析（Galaxy Merger Fractions in Two Clusters at z ∼2 Using the Hubble Space Telescope）</news:title>
   <news:publication_date>2026-08-08T17:31:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720965</loc>
  <lastmod>2026-08-08T17:31:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習を用いた指向性タンパク質進化（Machine Learning-Assisted Directed Protein Evolution with Combinatorial Libraries）</news:title>
   <news:publication_date>2026-08-08T17:31:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720963</loc>
  <lastmod>2026-08-08T17:30:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル特徴選択による高精度パラメータ推定（Feature Selection for Better Spectral Characterization or: How I Learned to Start Worrying and Love Ensembles）</news:title>
   <news:publication_date>2026-08-08T17:30:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720961</loc>
  <lastmod>2026-08-08T17:30:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河中心に存在する高齢星の“カスプ”の分光学的検出（Spectroscopic Detection of a Cusp of Late-type Stars around the Central Black Hole in the Milky Way）</news:title>
   <news:publication_date>2026-08-08T17:30:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720959</loc>
  <lastmod>2026-08-08T16:39:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互作用するAubry‑Andreモデルにおけるバタフライ効果（Butterfly effect in interacting Aubry‑Andre model: thermalization, slow scrambling, and many‑body localization）</news:title>
   <news:publication_date>2026-08-08T16:39:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720957</loc>
  <lastmod>2026-08-08T16:39:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き凸ポテンシャルによる2-ワッサースタイン近似（2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs）</news:title>
   <news:publication_date>2026-08-08T16:39:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720955</loc>
  <lastmod>2026-08-08T16:38:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希薄かつ不十分な報酬からの一般化学習（Learning to Generalize from Sparse and Underspecified Rewards）</news:title>
   <news:publication_date>2026-08-08T16:38:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720953</loc>
  <lastmod>2026-08-08T16:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PDS 70の遷移円盤は単一惑星で形成されうる（PDS 70: A TRANSITION DISK SCULPTED BY A SINGLE PLANET）</news:title>
   <news:publication_date>2026-08-08T16:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720951</loc>
  <lastmod>2026-08-08T16:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現学習における合成性の測定（MEASURING COMPOSITIONALITY IN REPRESENTATION LEARNING）</news:title>
   <news:publication_date>2026-08-08T16:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720949</loc>
  <lastmod>2026-08-08T16:37:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的RNNによる非線形ダイナミクス同定とfMRI応用（Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI）</news:title>
   <news:publication_date>2026-08-08T16:37:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720947</loc>
  <lastmod>2026-08-08T16:37:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>持続化図に対する写像の近似（Approximating Maps on Persistence Diagrams）</news:title>
   <news:publication_date>2026-08-08T16:37:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720945</loc>
  <lastmod>2026-08-08T15:46:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるジェット観測量の自動構築（Automating the Construction of Jet Observables with Machine Learning）</news:title>
   <news:publication_date>2026-08-08T15:46:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720943</loc>
  <lastmod>2026-08-08T15:45:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みネットワークの簡素化（Simplifying Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-08T15:45:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720941</loc>
  <lastmod>2026-08-08T15:45:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声認識におけるスペリング補正モデルの提案（A SPELLING CORRECTION MODEL FOR END-TO-END SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-08-08T15:45:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720939</loc>
  <lastmod>2026-08-08T15:44:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>和集合ノルムクラスタリングによるガウス混合モデルの回復（Recovery of a mixture of Gaussians by sum-of-norms clustering）</news:title>
   <news:publication_date>2026-08-08T15:44:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720937</loc>
  <lastmod>2026-08-08T15:43:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競争を通じて協調が生まれる仕組み（EMERGENT COORDINATION THROUGH COMPETITION）</news:title>
   <news:publication_date>2026-08-08T15:43:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720935</loc>
  <lastmod>2026-08-08T15:43:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種エージェントによるベイズ的探索と推奨政策（Bayesian Exploration with Heterogeneous Agents）</news:title>
   <news:publication_date>2026-08-08T15:43:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/720933</loc>
  <lastmod>2026-08-08T15:43:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療データに強いエントロピック特徴選択法の実務的意義（An entropic feature selection method in perspective of Turing’s formula）</news:title>
   <news:publication_date>2026-08-08T15:43:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>
