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   <news:title>デコーダーを巻き込むLDPC符号設計（Decoder-in-the-Loop: Genetic Optimization-based LDPC Code Design）</news:title>
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   <news:title>マルコフ論理ネットワークのリフティッド重み学習再考（Lifted Weight Learning of Markov Logic Networks Revisited）</news:title>
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   <news:title>META-DATASET：少数例学習のためのデータセット群と新ベンチマーク（META-DATASET: A Dataset of Datasets for Learning to Learn from Few Examples）</news:title>
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   <news:title>ファンタジー型テキストアドベンチャーで「話す・行動する」を学ぶ（Learning to Speak and Act in a Fantasy Text Adventure Game）</news:title>
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   <news:title>ドメイン特化の短文から自動で語彙体系を作る技術（Automatic Ontology Learning from Domain-Specific Short Unstructured Text Data）</news:title>
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   <news:title>Pyquilを用いた量子アルゴリズム入門（Introduction to Coding Quantum Algorithms: A Tutorial Series Using Pyquil）</news:title>
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    <news:language>ja</news:language>
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   <news:title>ラベル埋め込み型辞書学習による画像分類 (Label Embedded Dictionary Learning for Image Classification)</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>階層的強化学習で未知の非線形系を連続制御する仕組み（RLOC: Neurobiologically Inspired Hierarchical Reinforcement Learning Algorithm for Continuous Control of Nonlinear Dynamical Systems）</news:title>
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    <news:language>ja</news:language>
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   <news:title>スパースCNNのための集中量子化（FOCUSED QUANTIZATION FOR SPARSE CNNS）</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>量子的潜在意味分析の実務的意義（Quantum Latent Semantic Analysis）</news:title>
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   <news:title>エッジキャッシュにおける人気度学習のためのベイズ的ポアソン・ガウス過程モデル（A Bayesian Poisson-Gaussian Process Model for Popularity Learning in Edge-Caching 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>相互作用を持つクォーク方程状態による異方性クォーク星の解析（Anisotropic Quark Stars with an Interacting Quark Equation of State）</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>識別的畳み込み解析辞書学習の効率化（ANALYSIS DICTIONARY LEARNING: AN EFFICIENT AND DISCRIMINATIVE SOLUTION）</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>Posidonia oceanicaの葉の空気組織解析（CHARACTERIZATION OF Posidonia Oceanica SEAGRASS AERENCHYMA THROUGH WHOLE SLIDE IMAGING）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>複雑さから単純さへ：ブラックボックス最適化のための適応的ESアクティブ部分空間（From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>計算流体力学における観測量の深層学習（Deep learning observables in computational fluid dynamics）</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>敵対的画像の視覚的品質改善（Attack Type Agnostic Perceptual Enhancement of Adversarial 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>属性付きネットワークの双曲埋め込み（HEAT: Hyperbolic Embedding of Attributed Networks）</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>海上対流圏境界層における蒸発ダクトの特徴付け（CHARACTERIZING EVAPORATION DUCTS WITHIN THE MARINE ATMOSPHERIC BOUNDARY LAYER USING ARTIFICIAL NEURAL NETWORKS）</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>OLTPトランザクションのスケジューリングを機械学習で行う（Scheduling OLTP Transactions via Machine Learning）</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>堅牢性を備えたブラックボックス最適化による強化学習の進展（Provably Robust Blackbox Optimization for Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-15T07:49:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>EBSDデータの高精度再構築と歪み補正（Accurate reconstruction of EBSD datasets by a multimodal data approach using an evolutionary algorithm）</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>予測変分ナチュラル勾配（The Variational Predictive Natural Gradient）</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>進化的アルゴリズムによるEBSD歪み補正（Correction of Electron Back-scattered Diffraction datasets using an evolutionary algorithm）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>リー群上の分布の再パラメタリゼーション（Reparameterizing Distributions on Lie Groups）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>ウェブページの見た目で検索順位を学習する（ViTOR: Learning to Rank Webpages Based on Visual Features）</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>ソノグラファー視線をモデル化した超音波画像表現学習 (Ultrasound Image Representation Learning by Modeling Sonographer Visual Attention)</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>機械学習による高度マルウェア検出の実務的意義（Detection of Advanced Malware by Machine Learning Techniques）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T06:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/723383</loc>
  <lastmod>2026-08-15T06:55:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news: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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  <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>2026-08-15T06:55:28Z</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>
   </news:publication>
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   <news:publication_date>2026-08-15T06:54:41Z</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>2026-08-15T06:54:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news: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>2026-08-15T06:03:01Z</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>
   </news:publication>
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   <news:publication_date>2026-08-15T06:02:56Z</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>2026-08-15T06:02:34Z</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>2026-08-15T06:02:07Z</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>2026-08-15T06:02:01Z</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>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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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>
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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>
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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>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/723319</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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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:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T02:19:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>並列化で学ぶメタ強化学習の新潮流（Concurrent Meta Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T02:19:11Z</news:publication_date>
   <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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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T01:26:54Z</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>
   </news:publication>
   <news:title>触覚で拡張する物理シミュレーション：コリオリの力（Haptics-Augmented Physics Simulation: Coriolis Effect）</news:title>
   <news:publication_date>2026-08-15T01:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T01:25:48Z</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>ランク1スケッチによる行列乗算重み法の高速化（A Rank-1 Sketch for Matrix Multiplicative Weights）</news:title>
   <news:publication_date>2026-08-15T01:25:41Z</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>チャネルを学習するGANで開くエンドツーエンド無線通信（Deep Learning based End-to-End Wireless Communication Systems with Conditional GAN as Unknown Channel）</news:title>
   <news:publication_date>2026-08-15T01:25:35Z</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>古代コイン画像の理解（Understanding Ancient Coin Images）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T00:33:29Z</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: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>同一質問に対する複数回答から学ぶKBQAの堅牢化（Multi-Instance Learning for End-to-End Knowledge Base Question Answering）</news:title>
   <news:publication_date>2026-08-15T00:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T00:31:20Z</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>
   <news:title>継続学習のための世界モデルと疑似リハーサル（Continual Learning Using World Models for Pseudo-Rehearsal）</news:title>
   <news:publication_date>2026-08-15T00:31:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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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>2026-08-14T23:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-14T23:38:06Z</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>2026-08-14T23:37:22Z</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>分散オンライン凸最適化と時間変動結合不等式制約（Distributed Online Convex Optimization with Time-Varying Coupled Inequality Constraints）</news:title>
   <news:publication_date>2026-08-14T23:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723265</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>BatchNormが学習を安定化する仕組みを読み解く（MEAN-FIELD ANALYSIS OF BATCH NORMALIZATION）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723263</loc>
  <lastmod>2026-08-14T23:36:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723261</loc>
  <lastmod>2026-08-14T23:35:47Z</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>
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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>2026-08-14T22:44:38Z</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>永続的学習下の文埋め込み整合が変える関係抽出の実務応用（Sentence Embedding Alignment for Lifelong Relation Extraction）</news:title>
   <news:publication_date>2026-08-14T22:35:12Z</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>
   <news:title>Tactical Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation（Tactical Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超新星スペクトル自動分類の深層学習（DASH: Deep Learning for the Automated Spectral Classification of Supernovae and their Hosts）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-14T22:33:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QCD因子分解のための機械学習テンプレート（Machine Learning Templates for QCD Factorization in the Search for Physics Beyond the Standard Model）</news:title>
   <news:publication_date>2026-08-14T22:33:38Z</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>事後選択（ポストセレクション）による量子メトロロジーの優位性（Quantum Advantage in Postselected Metrology）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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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>時系列予測のための自己回帰畳み込み再帰ニューラルネットワーク（Autoregressive Convolutional Recurrent Neural Network）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>非微分モデルのための低レベル一次確率プログラミング言語（LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models）</news:title>
   <news:publication_date>2026-08-14T20:46:17Z</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:publication_date>2026-08-14T20:46:11Z</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:publication_date>2026-08-14T20:45:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news: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>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <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:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news: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>
 <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>
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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: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:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news: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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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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    <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: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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   <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>オートエンコーダによる頑健な異常検出法（A robust anomaly finder based on autoencoders）</news:title>
   <news:publication_date>2026-08-14T11:42:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723094</loc>
  <lastmod>2026-08-14T11:42:01Z</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>2026-08-14T11:42:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723092</loc>
  <lastmod>2026-08-14T11:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性推定の評価を見直し、モデル複雑性とのトレードオフを探る（Revisiting the Evaluation of Uncertainty Estimation and Its Application to Explore Model Complexity–Uncertainty Trade-Off）</news:title>
   <news:publication_date>2026-08-14T11:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723090</loc>
  <lastmod>2026-08-14T11:41:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子プランナーの制御セットを学習する方法（Learning a Lattice Planner Control Set for Autonomous Vehicles）</news:title>
   <news:publication_date>2026-08-14T11:41:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-14T11:41:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正常のみを学習して異常肺X線を識別する手法（ABNORMAL CHEST X-RAY IDENTIFICATION WITH GENERATIVE ADVERSARIAL ONE-CLASS CLASSIFIER）</news:title>
   <news:publication_date>2026-08-14T11:41:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723086</loc>
  <lastmod>2026-08-14T10:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像レジストレーションにおける深層学習の概観（Deep Learning in Medical Image Registration: A Survey）</news:title>
   <news:publication_date>2026-08-14T10:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723084</loc>
  <lastmod>2026-08-14T10:49:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケール認識型アテンションネットワークによる群衆カウント（Crowd Counting Using Scale-Aware Attention Networks）</news:title>
   <news:publication_date>2026-08-14T10:49:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723082</loc>
  <lastmod>2026-08-14T10:48:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語を用いた強化学習の報酬設計（Using Natural Language for Reward Shaping in Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-14T10:48:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723080</loc>
  <lastmod>2026-08-14T10:48:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話型オンデマンドHPCから得た教訓（Lessons Learned from a Decade of Providing Interactive, On-Demand High Performance Computing to Scientists and Engineers）</news:title>
   <news:publication_date>2026-08-14T10:48:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723078</loc>
  <lastmod>2026-08-14T10:47:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的情報を取り入れた深層学習による重力波パラメータ推定（Statistically-informed deep learning for gravitational wave parameter estimation）</news:title>
   <news:publication_date>2026-08-14T10:47:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723076</loc>
  <lastmod>2026-08-14T10:47:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的正則化が示す「過学習しない理由」 — Implicit Regularization in Over-parameterized Neural Networks（Implicit Regularization in Over-parameterized Neural Networks）</news:title>
   <news:publication_date>2026-08-14T10:47:46Z</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>PROPSによる黒箱系列モデルの確率的個人化（PROPS: Probabilistic personalization of black-box sequence models）</news:title>
   <news:publication_date>2026-08-14T10:47:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723072</loc>
  <lastmod>2026-08-14T09:54:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Playデータから学ぶ潜在プラン学習（Learning Latent Plans from Play）</news:title>
   <news:publication_date>2026-08-14T09:54:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723070</loc>
  <lastmod>2026-08-14T09:44:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズニューラルネットワークの堅牢性に対する統計的保証（Statistical Guarantees for the Robustness of Bayesian Neural Networks）</news:title>
   <news:publication_date>2026-08-14T09:44:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723068</loc>
  <lastmod>2026-08-14T09:44:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタリングとマルチメッセージ通信を用いた勾配符号化（Gradient Coding with Clustering and Multi-message Communication）</news:title>
   <news:publication_date>2026-08-14T09:44:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723066</loc>
  <lastmod>2026-08-14T09:43:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナビゲーションのための探索ポリシー学習（Learning Exploration Policies for Navigation）</news:title>
   <news:publication_date>2026-08-14T09:43:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723064</loc>
  <lastmod>2026-08-14T09:43:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PDP：制約充足問題ソルバーを学習する汎用ニューラルフレームワーク（PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers）</news:title>
   <news:publication_date>2026-08-14T09:43:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723062</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>拡張現実による義手訓練環境の効果検証（Augmented Reality Prosthesis Training Setup for Motor Skill Enhancement）</news:title>
   <news:publication_date>2026-08-14T09:42:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723058</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>2026-08-14T08:50:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723056</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>2026-08-14T08:50:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723054</loc>
  <lastmod>2026-08-14T08:50:01Z</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>2026-08-14T08:50:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723052</loc>
  <lastmod>2026-08-14T08:49:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>O-GAN: 判別器をそのままエンコーダにする簡潔な仕組み（O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-14T08:49:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723050</loc>
  <lastmod>2026-08-14T08:49:15Z</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>2026-08-14T08:49:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723048</loc>
  <lastmod>2026-08-14T08:48:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドにおけるVM挙動識別のための深層学習アプローチ（A Deep Learning based approach to VM behavior identification in cloud systems）</news:title>
   <news:publication_date>2026-08-14T08:48:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723046</loc>
  <lastmod>2026-08-14T08:48:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-14T08:48:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723044</loc>
  <lastmod>2026-08-14T07:57:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元流体データと作用素から本質的ダイナミクスを明らかにする（Revealing essential dynamics from high-dimensional fluid flow data and operators）</news:title>
   <news:publication_date>2026-08-14T07:57:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723042</loc>
  <lastmod>2026-08-14T07:56:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ時系列を扱うGated Graph Convolutional Recurrent Neural Networks（Gated Graph Convolutional Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-08-14T07:56:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723040</loc>
  <lastmod>2026-08-14T07:56:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実務に効くスキル管理ツールの運用知見（Practical Knowledge Management Tool Use in a Software Consulting Company）</news:title>
   <news:publication_date>2026-08-14T07:56:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723038</loc>
  <lastmod>2026-08-14T07:55:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VUDSによる高赤方偏移銀河のUV・Lyα輝度関数と星形成率密度の評価（The UV and Lyα Luminosity Functions of galaxies and the Star Formation Rate Density at the end of HI reionization from the VIMOS Ultra-Deep Survey (VUDS)）</news:title>
   <news:publication_date>2026-08-14T07:55:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723036</loc>
  <lastmod>2026-08-14T07:55:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小型銀河の未来研究と望遠鏡の発見（The Future of Dwarf Galaxy Research: What Telescopes Will Discover）</news:title>
   <news:publication_date>2026-08-14T07:55:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723034</loc>
  <lastmod>2026-08-14T07:54:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類モデルの“写し”を作る技術（COPYING MACHINE LEARNING CLASSIFIERS）</news:title>
   <news:publication_date>2026-08-14T07:54:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723032</loc>
  <lastmod>2026-08-14T07:54:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>滑らかなカーネル正則化を学習する（Learning a smooth kernel regularizer for convolutional neural networks）</news:title>
   <news:publication_date>2026-08-14T07:54:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723030</loc>
  <lastmod>2026-08-14T07:03:37Z</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>2026-08-14T07:03:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723028</loc>
  <lastmod>2026-08-14T07:03:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-14T07:03:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-14T07:02:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723022</loc>
  <lastmod>2026-08-14T07:02:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸・非滑らか最適化のための慣性ブロック近接法（Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization）</news:title>
   <news:publication_date>2026-08-14T07:02:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723020</loc>
  <lastmod>2026-08-14T07:02:24Z</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>2026-08-14T07:02:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723018</loc>
  <lastmod>2026-08-14T07:02:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>miniTimeCubeによる中性子散乱カメラ（miniTimeCube as a neutron scatter camera）</news:title>
   <news:publication_date>2026-08-14T07:02:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723016</loc>
  <lastmod>2026-08-14T06:10:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>六角格子データをそのまま扱う畳み込み（HexagDLy — Processing hexagonally sampled data with CNNs in PyTorch）</news:title>
   <news:publication_date>2026-08-14T06:10:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723014</loc>
  <lastmod>2026-08-14T06:10:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>床図を使ったロボット位置推定と部屋境界抽出ネットワーク（Robot Localization in Floor Plans Using a Room Layout Edge Extraction Network）</news:title>
   <news:publication_date>2026-08-14T06:10:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723012</loc>
  <lastmod>2026-08-14T06:10:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多ブロックADMMにおけるランダム化の管理（Managing Randomization in the Multi-Block Alternating Direction Method of Multipliers for Quadratic Optimization）</news:title>
   <news:publication_date>2026-08-14T06:10:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723010</loc>
  <lastmod>2026-08-14T06:09:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Shape Completionを活用した3D Siameseトラッキングの実用性（Leveraging Shape Completion for 3D Siamese Tracking）</news:title>
   <news:publication_date>2026-08-14T06:09:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723008</loc>
  <lastmod>2026-08-14T06:09:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国チェッカーを理解するための探索と学習の統合（Towards Understanding Chinese Checkers with Heuristics, Monte Carlo Tree Search, and Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-14T06:09:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723006</loc>
  <lastmod>2026-08-14T06:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>金融時系列予測のためのデータ駆動型ニューラルアーキテクチャ学習（Data-driven Neural Architecture Learning for Financial Time-series Forecasting）</news:title>
   <news:publication_date>2026-08-14T06:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723004</loc>
  <lastmod>2026-08-14T06:08:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Maximal Leakageによる適応的データ解析の新しい枠組み（A New Approach to Adaptive Data Analysis and Learning via Maximal Leakage）</news:title>
   <news:publication_date>2026-08-14T06:08:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723002</loc>
  <lastmod>2026-08-14T05:17:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能な人工知能のためのデータに基づく対話プロトコル（A Grounded Interaction Protocol for Explainable Artificial Intelligence）</news:title>
   <news:publication_date>2026-08-14T05:17:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723000</loc>
  <lastmod>2026-08-14T05:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SZZ Unleashed：SZZアルゴリズムの公開実装とJenkinsを用いたJITバグ予測の適用事例（SZZ Unleashed: An Open Implementation of the SZZ Algorithm）</news:title>
   <news:publication_date>2026-08-14T05:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722998</loc>
  <lastmod>2026-08-14T05:16:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルの所有権を証明する手法（Your Model Belongs to You: A Blind-Watermark based Framework to Protect Intellectual Property of DNN）</news:title>
   <news:publication_date>2026-08-14T05:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722996</loc>
  <lastmod>2026-08-14T05:15:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新規性検出の確率的モデリングと不正検知への応用（Probabilistic Modeling for Novelty Detection with Applications to Fraud Identification）</news:title>
   <news:publication_date>2026-08-14T05:15:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722994</loc>
  <lastmod>2026-08-14T05:15:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OMPベースのスパース部分空間クラスタリングに対するデータ適応型の効率的アプローチ（A Novel Efficient Approach with Data-Adaptive Capability for OMP-based Sparse Subspace Clustering）</news:title>
   <news:publication_date>2026-08-14T05:15:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722992</loc>
  <lastmod>2026-08-14T05:15:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク零和ゲームにおけるマルチエージェント学習はハミルトン系である（Multi-Agent Learning in Network Zero-Sum Games is a Hamiltonian System）</news:title>
   <news:publication_date>2026-08-14T05:15:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722990</loc>
  <lastmod>2026-08-14T05:14:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病理報告の自動分類とTF‑IDFの現実適用（Automatic Classification of Pathology Reports using TF-IDF Features）</news:title>
   <news:publication_date>2026-08-14T05:14:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722988</loc>
  <lastmod>2026-08-14T04:22:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教育におけるブロックチェーンの可能性（Blockchain and its Potential in Education）</news:title>
   <news:publication_date>2026-08-14T04:22:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722986</loc>
  <lastmod>2026-08-14T04:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ埋め込みが与信・不正検知に与える実証的効果（Empirical effect of graph embeddings on fraud detection/ risk mitigation）</news:title>
   <news:publication_date>2026-08-14T04:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722984</loc>
  <lastmod>2026-08-14T04:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>L1-normダブルバックプロパゲーションによる敵対的防御（L1-norm double backpropagation adversarial defense）</news:title>
   <news:publication_date>2026-08-14T04:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722982</loc>
  <lastmod>2026-08-14T04:21:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称に緩和した分布整合によるドメイン適応（Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment）</news:title>
   <news:publication_date>2026-08-14T04:21:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722980</loc>
  <lastmod>2026-08-14T04:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EdgeStereoによるステレオマッチングとエッジ検出の統合（EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection）</news:title>
   <news:publication_date>2026-08-14T04:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722978</loc>
  <lastmod>2026-08-14T04:21:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転車の時空間LSTMによる深層学習モーションプランニング（Deep Learning Based Motion Planning For Autonomous Vehicle Using Spatiotemporal LSTM Network）</news:title>
   <news:publication_date>2026-08-14T04:21:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722976</loc>
  <lastmod>2026-08-14T04:21:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道徳性の複雑性：マルコフブランケットとグラフの道徳性の検査（The Complexity of Morality: Checking Markov Blanket Consistency with DAGs via Morality）</news:title>
   <news:publication_date>2026-08-14T04:21:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722974</loc>
  <lastmod>2026-08-14T03:29:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種／非定常データからの因果発見と独立変化の原理（Causal Discovery from Heterogeneous/Nonstationary Data with Independent Changes）</news:title>
   <news:publication_date>2026-08-14T03:29:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722972</loc>
  <lastmod>2026-08-14T03:21:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共益特徴量の凸的クラスタリングによる分類改善（Convex Covariate Clustering for Classification）</news:title>
   <news:publication_date>2026-08-14T03:21:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722970</loc>
  <lastmod>2026-08-14T03:20:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多車線交通速度予測における二流多チャネル畳み込みニューラルネットワーク（Two‑Stream Multi‑Channel Convolutional Neural Network (TM‑CNN) for Multi‑Lane Traffic Speed Prediction Considering Traffic Volume Impact）</news:title>
   <news:publication_date>2026-08-14T03:20:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722968</loc>
  <lastmod>2026-08-14T03:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U統計量のための濃度に基づく信頼区間（Concentration-based confidence intervals for U-statistics）</news:title>
   <news:publication_date>2026-08-14T03:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722966</loc>
  <lastmod>2026-08-14T03:19:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的深層局所化（Deep Active Localization）</news:title>
   <news:publication_date>2026-08-14T03:19:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722964</loc>
  <lastmod>2026-08-14T03:19:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインデータポイズニング攻撃（Online Data Poisoning Attacks）</news:title>
   <news:publication_date>2026-08-14T03:19:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722962</loc>
  <lastmod>2026-08-14T03:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HEVC向け多フレームIn-Loopフィルタ（A DenseNet Based Approach for Multi-Frame In-Loop Filter in HEVC）</news:title>
   <news:publication_date>2026-08-14T03:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722960</loc>
  <lastmod>2026-08-14T02:27:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配降下―上昇の収束解析（Convergence of gradient descent-ascent analyzed as a Newtonian dynamical system with dissipation）</news:title>
   <news:publication_date>2026-08-14T02:27:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722958</loc>
  <lastmod>2026-08-14T02:26:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェア向けストリーミング低ランク更新法（Streaming Batch Eigenupdates for Hardware Neuromorphic Networks）</news:title>
   <news:publication_date>2026-08-14T02:26:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722956</loc>
  <lastmod>2026-08-14T02:26:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NVDLAをRISC-V SoCに統合しFireSimで評価する意義（Integrating NVIDIA Deep Learning Accelerator (NVDLA) with RISC-V SoC on FireSim）</news:title>
   <news:publication_date>2026-08-14T02:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722954</loc>
  <lastmod>2026-08-14T02:26:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習初期の「再ウィンド（rewinding）」で当たりくじを安定化する方法（Stabilizing the Lottery Ticket Hypothesis）</news:title>
   <news:publication_date>2026-08-14T02:26:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722952</loc>
  <lastmod>2026-08-14T02:25:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェブ規模最近傍検索を用いた敵対的画像に対する防御（Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search）</news:title>
   <news:publication_date>2026-08-14T02:25:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722950</loc>
  <lastmod>2026-08-14T02:25:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初代星（Population III）の対崩壊（Pair-Instability）超新星探索の展望（Searches for Population III pair-instability supernovae: Predictions for ULTIMATE-Subaru and WFIRST）</news:title>
   <news:publication_date>2026-08-14T02:25:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722948</loc>
  <lastmod>2026-08-14T02:25:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損特徴を伴うロジスティック回帰の期待予測と埋め込み手法（What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features）</news:title>
   <news:publication_date>2026-08-14T02:25:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722946</loc>
  <lastmod>2026-08-14T01:34:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在拡散過程を用いる生成モデルの理論的保証（Theoretical guarantees for sampling and inference in generative models with latent diffusions）</news:title>
   <news:publication_date>2026-08-14T01:34:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722944</loc>
  <lastmod>2026-08-14T01:33:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフデータに対する敵対的事例の攻防（Adversarial Examples on Graph Data: Deep Insights into Attack and Defense）</news:title>
   <news:publication_date>2026-08-14T01:33:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722942</loc>
  <lastmod>2026-08-14T01:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超高エネルギー中性ニュートリノの探索を目指すARIANNA実験（Targeting ultra-high energy neutrinos with the ARIANNA experiment）</news:title>
   <news:publication_date>2026-08-14T01:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722940</loc>
  <lastmod>2026-08-14T01:33:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>後悔するエージェント：進捗推定を用いたヒューリスティック支援ナビゲーション（The Regretful Agent: Heuristic-Aided Navigation through Progress Estimation）</news:title>
   <news:publication_date>2026-08-14T01:33:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722938</loc>
  <lastmod>2026-08-14T01:32:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期的未来を取り入れた強化学習における動力学モデル学習（LEARNING DYNAMICS MODEL IN REINFORCEMENT LEARNING BY INCORPORATING THE LONG TERM FUTURE）</news:title>
   <news:publication_date>2026-08-14T01:32:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722936</loc>
  <lastmod>2026-08-14T01:32:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PRIDEを用いた金星探査機の電波掩蔽観測（Venus Express radio occultation observed by PRIDE）</news:title>
   <news:publication_date>2026-08-14T01:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722934</loc>
  <lastmod>2026-08-14T01:32:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かなロボットシステムのための制御ラプノフ関数を用いたエピソディック学習（Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems）</news:title>
   <news:publication_date>2026-08-14T01:32:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722932</loc>
  <lastmod>2026-08-14T00:41:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群体フォトメトリック赤方偏移（Ensemble Photometric Redshifts）</news:title>
   <news:publication_date>2026-08-14T00:41:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722930</loc>
  <lastmod>2026-08-14T00:41:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>V2X向けハイブリッドGaussian Processベース通信アーキテクチャ（V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structures）</news:title>
   <news:publication_date>2026-08-14T00:41:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722928</loc>
  <lastmod>2026-08-14T00:41:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QickStopによる誤情報の最速検出（QuickStop: A Markov Optimal Stopping Approach for Quickest Misinformation Detection）</news:title>
   <news:publication_date>2026-08-14T00:41:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722926</loc>
  <lastmod>2026-08-14T00:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルプリミティブ階層的ライフロング強化学習（Model Primitive Hierarchical Lifelong Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-14T00:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722924</loc>
  <lastmod>2026-08-14T00:40:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模画像検索のための教師なしランク保存ハッシング（Unsupervised Rank-Preserving Hashing for Large-Scale Image Retrieval）</news:title>
   <news:publication_date>2026-08-14T00:40:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722922</loc>
  <lastmod>2026-08-14T00:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的トラストリージョン法による非凸最適化の効率化（A Stochastic Trust Region Method for Non-convex Minimization）</news:title>
   <news:publication_date>2026-08-14T00:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722920</loc>
  <lastmod>2026-08-14T00:39:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期宇宙の“最初の爆発”をELTで追う意義（ELT Contributions to The First Explosions）</news:title>
   <news:publication_date>2026-08-14T00:39:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722918</loc>
  <lastmod>2026-08-13T23:48:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択的センサフュージョンによるニューラル視覚慣性測位（Selective Sensor Fusion for Neural Visual-Inertial Odometry）</news:title>
   <news:publication_date>2026-08-13T23:48:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722916</loc>
  <lastmod>2026-08-13T23:48:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転車の希少事象サンプリングに対する行動駆動アプローチ（A behavior driven approach for sampling rare event situations for autonomous vehicles）</news:title>
   <news:publication_date>2026-08-13T23:48:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722914</loc>
  <lastmod>2026-08-13T23:48:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群体認知と多主体対話の計算モデル（MGPI: A Computational Model of Multiagent Group Perception and Interaction）</news:title>
   <news:publication_date>2026-08-13T23:48:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722912</loc>
  <lastmod>2026-08-13T23:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きな横方向運動量の半包摂的深陽電子散乱における2次摂動の再検証（Large Transverse Momentum in Semi-Inclusive Deeply Inelastic Scattering Beyond Lowest Order）</news:title>
   <news:publication_date>2026-08-13T23:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722910</loc>
  <lastmod>2026-08-13T23:46:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列知識蒸留による能動的知覚の効率化（TKD: Temporal Knowledge Distillation for Active Perception）</news:title>
   <news:publication_date>2026-08-13T23:46:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722908</loc>
  <lastmod>2026-08-13T23:46:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像のデヘイジングをセグメンテーション向けに学習する意義（Learning of Image Dehazing Models for Segmentation Tasks）</news:title>
   <news:publication_date>2026-08-13T23:46:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722906</loc>
  <lastmod>2026-08-13T23:46:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約の厳しいIoT向け三値ハイブリッドニューラル・ツリーネットワーク（Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications）</news:title>
   <news:publication_date>2026-08-13T23:46:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722904</loc>
  <lastmod>2026-08-13T22:54:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットで導く強線酸素同位体較正（A Machine Learning Artificial Neural Network Calibration of the Strong-Line Oxygen Abundance）</news:title>
   <news:publication_date>2026-08-13T22:54:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722902</loc>
  <lastmod>2026-08-13T22:53:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルCPU向けWinograd／Cook‑Toom畳み込みの高効率実装（Efficient Winograd or Cook‑Toom Convolution Kernel Implementation on Widely Used Mobile CPUs）</news:title>
   <news:publication_date>2026-08-13T22:53:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722900</loc>
  <lastmod>2026-08-13T22:53:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再イオン化期の銀河で大量のLyman連続放射（LyC）漏洩を見つける方法（Identifying reionization-epoch galaxies with extreme levels of Lyman continuum leakage in James Webb Space Telescope surveys）</news:title>
   <news:publication_date>2026-08-13T22:53:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722898</loc>
  <lastmod>2026-08-13T22:52:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習と量子物理の融合（Machine Learning meets Quantum Physics）</news:title>
   <news:publication_date>2026-08-13T22:52:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722896</loc>
  <lastmod>2026-08-13T22:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OPT-AMSGradによる非凸最適化の楽観的加速（An Optimistic Acceleration of AMSGrad for Nonconvex Optimization）</news:title>
   <news:publication_date>2026-08-13T22:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722894</loc>
  <lastmod>2026-08-13T22:51:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズに強いデータ圧縮で尤度フリー推論を高速化する手法（Nuisance hardened data compression for fast likelihood-free inference）</news:title>
   <news:publication_date>2026-08-13T22:51:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722892</loc>
  <lastmod>2026-08-13T22:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きフローに基づく確率的動画生成（VIDEOFLOW: A CONDITIONAL FLOW-BASED MODEL FOR STOCHASTIC VIDEO GENERATION）</news:title>
   <news:publication_date>2026-08-13T22:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722890</loc>
  <lastmod>2026-08-13T22:00:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ増幅による性質推定の最適化（Data Amplification: Instance-Optimal Property Estimation）</news:title>
   <news:publication_date>2026-08-13T22:00:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722888</loc>
  <lastmod>2026-08-13T21:59:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球状混合pスピンモデルにおける平均場ガラス動力学の再考（Rethinking mean-field glassy dynamics and its relation with the energy landscape: the awkward case of the spherical mixed p-spin model）</news:title>
   <news:publication_date>2026-08-13T21:59:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722886</loc>
  <lastmod>2026-08-13T21:58:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス特徴を用いたデータベース整合（Database Alignment with Gaussian Features）</news:title>
   <news:publication_date>2026-08-13T21:58:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722884</loc>
  <lastmod>2026-08-13T21:58:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドラム音源の転写に効くデータ拡張の実践（Data Augmentation for Drum Transcription with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-13T21:58:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722882</loc>
  <lastmod>2026-08-13T21:58:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量等高回帰とHardy-Krause変動の拡張（Multivariate extensions of isotonic regression and total variation denoising via entire monotonicity and Hardy-Krause variation）</news:title>
   <news:publication_date>2026-08-13T21:58:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722880</loc>
  <lastmod>2026-08-13T21:57:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep U-NetとWave-U-Netによる歌声分離の改善（Improving singing voice separation using Deep U-Net and Wave-U-Net with data augmentation）</news:title>
   <news:publication_date>2026-08-13T21:57:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722878</loc>
  <lastmod>2026-08-13T21:57:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二足歩行のシミュレーションから現実世界への転送（Sim-to-Real Transfer for Biped Locomotion）</news:title>
   <news:publication_date>2026-08-13T21:57:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722876</loc>
  <lastmod>2026-08-13T21:05:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚と制御を推論として統合する（Joint Perception and Control as Inference with an Object-Based Implementation）</news:title>
   <news:publication_date>2026-08-13T21:05:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722874</loc>
  <lastmod>2026-08-13T21:05:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフィカル計算による積と畳み込み（Graphical Calculus for products and convolutions）</news:title>
   <news:publication_date>2026-08-13T21:05:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722872</loc>
  <lastmod>2026-08-13T21:05:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市規模ITSにおける効率的なミリ波インフラ配置（Efficient Millimeter-Wave Infrastructure Placement for City-Scale ITS）</news:title>
   <news:publication_date>2026-08-13T21:05:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722870</loc>
  <lastmod>2026-08-13T21:04:24Z</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深層強化学習による微視的交通シミュレーション (Microscopic Traffic Simulation by Cooperative Multi-agent Deep Reinforcement Learning)</news:title>
   <news:publication_date>2026-08-13T21:04:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722868</loc>
  <lastmod>2026-08-13T21:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>置換なし確率的勾配降下法の収束改善（SGD Without Replacement: Sharper Rates for General Smooth Convex Functions）</news:title>
   <news:publication_date>2026-08-13T21:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722866</loc>
  <lastmod>2026-08-13T21:04:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機会的ビューのマテリアライゼーションを深層強化学習で学ぶ（Opportunistic View Materialization with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-13T21:04:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722864</loc>
  <lastmod>2026-08-13T21:03:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デモンストレーションから学ぶ感覚–運動連合の自律化（Learning Sensory-Motor Associations from Demonstration）</news:title>
   <news:publication_date>2026-08-13T21:03:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722862</loc>
  <lastmod>2026-08-13T20:12:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反転授業と視線計測を用いたHCIデザイン教育（Teaching HCI Design in a Flipped Learning M.Sc. Course Using Eye-Tracking Peer Evaluation Data）</news:title>
   <news:publication_date>2026-08-13T20:12:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722860</loc>
  <lastmod>2026-08-13T20:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲルマニウム検出器のパルス形状識別に基づく深層学習（Deep learning based pulse shape discrimination for germanium detectors）</news:title>
   <news:publication_date>2026-08-13T20:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722858</loc>
  <lastmod>2026-08-13T20:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ化アクション空間におけるハイブリッドActor–Critic（Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Space）</news:title>
   <news:publication_date>2026-08-13T20:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722856</loc>
  <lastmod>2026-08-13T20:10:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StreetLearn：Google Street Viewを用いた学習環境とデータセット（The StreetLearn Environment and Dataset）</news:title>
   <news:publication_date>2026-08-13T20:10:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722854</loc>
  <lastmod>2026-08-13T20:10:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜血管の動脈／静脈同時分割と分類（Joint Segmentation and Classification of Retinal Arteries/Veins from Fundus Images）</news:title>
   <news:publication_date>2026-08-13T20:10:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722852</loc>
  <lastmod>2026-08-13T20:10:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファジーROCと不確実性領域の可視化（The Fuzzy ROC）</news:title>
   <news:publication_date>2026-08-13T20:10:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722850</loc>
  <lastmod>2026-08-13T20:09:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア工学倫理を教えるシリアスゲームの実践と検証（A Serious Game for Introducing Software Engineering Ethics to University Students）</news:title>
   <news:publication_date>2026-08-13T20:09:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722848</loc>
  <lastmod>2026-08-13T19:18:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常性下での最適化とヘッジ（Learning to Optimize under Non-Stationarity）</news:title>
   <news:publication_date>2026-08-13T19:18:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722846</loc>
  <lastmod>2026-08-13T19:18:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列のブラインドソース分離を動的モード分解で実現する（Time Series Source Separation using Dynamic Mode Decomposition）</news:title>
   <news:publication_date>2026-08-13T19:18:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722844</loc>
  <lastmod>2026-08-13T19:18:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロングテール関係抽出に知識グラフ埋め込みとグラフ畳み込みネットワークを組み合わせる方法（Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks）</news:title>
   <news:publication_date>2026-08-13T19:18:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722842</loc>
  <lastmod>2026-08-13T19:17:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの安全性検証とロバストネス解析（Safety Verification and Robustness Analysis of Neural Networks via Quadratic Constraints and Semidefinite Programming）</news:title>
   <news:publication_date>2026-08-13T19:17:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722840</loc>
  <lastmod>2026-08-13T19:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>秋季における亜熱帯カナリア海盆の深海散乱層の観測（Autumnal deep scattering layer from moored acoustic sensing in the subtropical Canary Basin）</news:title>
   <news:publication_date>2026-08-13T19:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722838</loc>
  <lastmod>2026-08-13T19:16:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ可変再帰によるGCNNの一般化（Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs）</news:title>
   <news:publication_date>2026-08-13T19:16:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722836</loc>
  <lastmod>2026-08-13T19:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>従来型機械学習によるピッチ検出の実務インパクト（Traditional Machine Learning for Pitch Detection）</news:title>
   <news:publication_date>2026-08-13T19:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722834</loc>
  <lastmod>2026-08-13T18:24:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知神経科学のための深層学習（Deep Learning for Cognitive Neuroscience）</news:title>
   <news:publication_date>2026-08-13T18:24:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722832</loc>
  <lastmod>2026-08-13T18:24:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デモから仕様を学ぶ因果分析（Using Causal Analysis to Learn Specifications from Task Demonstrations）</news:title>
   <news:publication_date>2026-08-13T18:24:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722830</loc>
  <lastmod>2026-08-13T18:24:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラグエール過程と分割上の動的関係を結ぶゲートウェイ（ON A GATEWAY BETWEEN THE LAGUERRE PROCESS AND DYNAMICS ON PARTITIONS）</news:title>
   <news:publication_date>2026-08-13T18:24:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722828</loc>
  <lastmod>2026-08-13T18:23:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交通参加者の相互作用をグラフで捉える（Graph Neural Networks for Modelling Traffic Participant Interaction）</news:title>
   <news:publication_date>2026-08-13T18:23:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722826</loc>
  <lastmod>2026-08-13T18:23:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デジタル人文学領域におけるロシア語コーパスと単語埋め込みの評価（Russian Language Datasets in the Digital Humanities Domain and Their Evaluation with Word Embeddings）</news:title>
   <news:publication_date>2026-08-13T18:23:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722824</loc>
  <lastmod>2026-08-13T18:22:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習監視機構の体系的評価枠組み（Towards Structured Evaluation of Deep Neural Network Supervisors）</news:title>
   <news:publication_date>2026-08-13T18:22:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722822</loc>
  <lastmod>2026-08-13T18:22:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり学習を用いた脳病変セグメンテーションの実用性（Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher Model）</news:title>
   <news:publication_date>2026-08-13T18:22:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722820</loc>
  <lastmod>2026-08-13T17:31:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を用いた車線変更予測（Attention-based Lane Change Prediction）</news:title>
   <news:publication_date>2026-08-13T17:31:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722818</loc>
  <lastmod>2026-08-13T17:31:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスクパラメータ化された動作学習の一般化を高める枠組み重み付き軌道生成（Improving Task-Parameterised Movement Learning Generalisation with Frame-Weighted Trajectory Generation）</news:title>
   <news:publication_date>2026-08-13T17:31:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722816</loc>
  <lastmod>2026-08-13T17:30:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病理組織画像における病変検出の深層学習フレームワークの機構理解（Understanding the Mechanism of Deep Learning Framework for Lesion Detection in Pathological Images with Breast Cancer）</news:title>
   <news:publication_date>2026-08-13T17:30:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722814</loc>
  <lastmod>2026-08-13T17:29:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしドメイン適応によるRGB-D階段認識（Unsupervised Domain Adaptation Learning Algorithm for RGB-D Staircase Recognition）</news:title>
   <news:publication_date>2026-08-13T17:29:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722812</loc>
  <lastmod>2026-08-13T17:29:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画行動認識のための協調時空間特徴学習（Collaborative Spatiotemporal Feature Learning for Video Action Recognition）</news:title>
   <news:publication_date>2026-08-13T17:29:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722810</loc>
  <lastmod>2026-08-13T17:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補完目的トレーニング（COMPLEMENT OBJECTIVE TRAINING）</news:title>
   <news:publication_date>2026-08-13T17:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722808</loc>
  <lastmod>2026-08-13T17:29:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルゴリズム判断が社会を変える長期影響（On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning）</news:title>
   <news:publication_date>2026-08-13T17:29:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722806</loc>
  <lastmod>2026-08-13T16:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的時間伸縮距離を伸縮不変にする方法（Making the Dynamic Time Warping Distance Warping-Invariant）</news:title>
   <news:publication_date>2026-08-13T16:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722804</loc>
  <lastmod>2026-08-13T16:29:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子理論に触発された二値分類器の実務的意義（Binary Classifier Inspired by Quantum Theory）</news:title>
   <news:publication_date>2026-08-13T16:29:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722802</loc>
  <lastmod>2026-08-13T16:29:31Z</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を進化させる非線形制御問題への応用（Evolving Spiking Neural Networks for Nonlinear Control Problems）</news:title>
   <news:publication_date>2026-08-13T16:29:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722800</loc>
  <lastmod>2026-08-13T16:29:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌声合成のスペクトル包絡予測に関する深層学習手法の比較（Analysing Deep Learning–Spectral Envelope Prediction Methods for Singing Synthesis）</news:title>
   <news:publication_date>2026-08-13T16:29:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722798</loc>
  <lastmod>2026-08-13T16:27:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度距離学習と条件付き確率場を組み合わせたハイパースペクトル画像分類（Hyperspectral Image Classification with Deep Metric Learning and Conditional Random Field）</news:title>
   <news:publication_date>2026-08-13T16:27:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722796</loc>
  <lastmod>2026-08-13T16:27:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による水理データの再構築（Reconstruction of Hydraulic Data by Machine Learning）</news:title>
   <news:publication_date>2026-08-13T16:27:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722794</loc>
  <lastmod>2026-08-13T16:27:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>STRIPSアクションモデルの学習（Learning STRIPS Action Models with Classical Planning）</news:title>
   <news:publication_date>2026-08-13T16:27:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722792</loc>
  <lastmod>2026-08-13T15:35:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習データが無くてもタスクモデルを作る考え方（Zero-Shot Task Transfer）</news:title>
   <news:publication_date>2026-08-13T15:35:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722790</loc>
  <lastmod>2026-08-13T15:35:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延トレースによる微分可能な因果計算（Differentiable Causal Computations via Delayed Trace）</news:title>
   <news:publication_date>2026-08-13T15:35:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722788</loc>
  <lastmod>2026-08-13T15:35:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パ ン クロマティックモデリングから学ぶ教訓（Challenges in Panchromatic Modelling with Next Generation Facilities）</news:title>
   <news:publication_date>2026-08-13T15:35:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722786</loc>
  <lastmod>2026-08-13T15:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペアなし学習で低線量CTのノイズを除去するGAN（Unpaired image denoising using a generative adversarial network in X-ray CT）</news:title>
   <news:publication_date>2026-08-13T15:34:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722784</loc>
  <lastmod>2026-08-13T15:33:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的グラフフィードバックによる確率的オンライン学習の拡張（Stochastic Online Learning with Probabilistic Graph Feedback）</news:title>
   <news:publication_date>2026-08-13T15:33:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722782</loc>
  <lastmod>2026-08-13T15:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成学習による教師なしクロススペクトルステレオマッチング (Unsupervised Cross-spectral Stereo Matching by Learning to Synthesize)</news:title>
   <news:publication_date>2026-08-13T15:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722780</loc>
  <lastmod>2026-08-13T15:33:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層監督付き密度回帰による自動顕微鏡細胞計数（Automatic Microscopic Cell Counting by Use of Deeply-Supervised Density Regression Model）</news:title>
   <news:publication_date>2026-08-13T15:33:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722778</loc>
  <lastmod>2026-08-13T14:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習エクス・ニーヒロ（Learning Ex Nihilo）</news:title>
   <news:publication_date>2026-08-13T14:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722776</loc>
  <lastmod>2026-08-13T14:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然画像で訓練されたニューラルネットワークはゲシュタルトの閉合を示す（Neural Networks Trained on Natural Scenes Exhibit Gestalt Closure）</news:title>
   <news:publication_date>2026-08-13T14:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722774</loc>
  <lastmod>2026-08-13T14:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートブラックボックス：価値駆動の高帯域車載イベントデータレコーダ（The Smart Black Box: A Value-Driven High-Bandwidth Automotive Event Data Recorder）</news:title>
   <news:publication_date>2026-08-13T14:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722772</loc>
  <lastmod>2026-08-13T14:40:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬なしで環境に適応するメタ学習（No-Reward Meta Learning）</news:title>
   <news:publication_date>2026-08-13T14:40:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722770</loc>
  <lastmod>2026-08-13T14:40:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変インピーダンス制御器を用いた強化学習による高精度ロボット組み立て（Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly）</news:title>
   <news:publication_date>2026-08-13T14:40:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722768</loc>
  <lastmod>2026-08-13T14:40:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Straight-Through Estimatorを使わない低精度ニューラルネットワーク学習（Learning low-precision neural networks without Straight-Through Estimator (STE))</news:title>
   <news:publication_date>2026-08-13T14:40:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722766</loc>
  <lastmod>2026-08-13T14:40:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カロリトロニクスに基づくモットニューロスター（A caloritronics-based Mott neuristor）</news:title>
   <news:publication_date>2026-08-13T14:40:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722764</loc>
  <lastmod>2026-08-13T13:49:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多ブロックADMMを用いたアイソトニック回帰への応用（THE APPLICATION OF MULTI-BLOCK ADMM ON ISOTONIC REGRESSION PROBLEMS）</news:title>
   <news:publication_date>2026-08-13T13:49:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722762</loc>
  <lastmod>2026-08-13T13:48:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>米国におけるインフルエンザ流行の早期検知手法（Early Detection of Influenza outbreaks in the United States）</news:title>
   <news:publication_date>2026-08-13T13:48:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722760</loc>
  <lastmod>2026-08-13T13:48:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超大規模データに効くスペクトルクラスタリングの実用化（Ultra-Scalable Spectral Clustering and Ensemble Clustering）</news:title>
   <news:publication_date>2026-08-13T13:48:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722758</loc>
  <lastmod>2026-08-13T13:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CodeNetによる誤り耐性を持つ大規模ニューラルネットワーク訓練（CodeNet: Training Large Scale Neural Networks in Presence of Soft-Errors）</news:title>
   <news:publication_date>2026-08-13T13:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722756</loc>
  <lastmod>2026-08-13T13:47:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接続モバイル端末からの頑健な通勤者移動推定（Robust commuter movement inference from connected mobile devices）</news:title>
   <news:publication_date>2026-08-13T13:47:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722754</loc>
  <lastmod>2026-08-13T13:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床自然言語処理における埋め込み表現の総覧（SECNLP: A Survey of Embeddings in Clinical Natural Language Processing）</news:title>
   <news:publication_date>2026-08-13T13:47:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722752</loc>
  <lastmod>2026-08-13T13:47:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏心球の壁効果と機械学習による高速近似（Wall effects of eccentric spheres machine learning for convenient computation）</news:title>
   <news:publication_date>2026-08-13T13:47:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722750</loc>
  <lastmod>2026-08-13T12:54:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間ピラミッドネットワークによる動画行動認識（Spatiotemporal Pyramid Network for Video Action Recognition）</news:title>
   <news:publication_date>2026-08-13T12:54:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722748</loc>
  <lastmod>2026-08-13T12:53:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二項分類における精度と頑健性の根本的制約（A Fundamental Performance Limitation for Adversarial Classification）</news:title>
   <news:publication_date>2026-08-13T12:53:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722746</loc>
  <lastmod>2026-08-13T12:53:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダで正則化したCNNによるワン・クラス認証（Active Authentication using an Autoencoder regularized CNN-based One-Class Classifier）</news:title>
   <news:publication_date>2026-08-13T12:53:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722744</loc>
  <lastmod>2026-08-13T12:52:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMによる短期電力需要予測の実務適用可能性（Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting）</news:title>
   <news:publication_date>2026-08-13T12:52:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722742</loc>
  <lastmod>2026-08-13T12:52:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>触覚ロボットガイドに従う人の軌道予測（Prediction of Human Trajectory Following a Haptic Robotic Guide Using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-08-13T12:52:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722740</loc>
  <lastmod>2026-08-13T12:52:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己検査型ビジョンによる障害物回避（Introspective Vision for Obstacle Avoidance）</news:title>
   <news:publication_date>2026-08-13T12:52:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722738</loc>
  <lastmod>2026-08-13T12:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンディット設定におけるモジュラー安全方策学習（Learning Modular Safe Policies in the Bandit Setting with Application to Adaptive Clinical Trials）</news:title>
   <news:publication_date>2026-08-13T12:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722736</loc>
  <lastmod>2026-08-13T12:00:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートインバータの無効電力制御ルール設計（Designing Reactive Power Control Rules for Smart Inverters using Support Vector Machines）</news:title>
   <news:publication_date>2026-08-13T12:00:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722734</loc>
  <lastmod>2026-08-13T12:00:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強い漸近的最適性を示す汎用環境下のエージェント（A Strongly Asymptotically Optimal Agent in General Environments）</news:title>
   <news:publication_date>2026-08-13T12:00:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722732</loc>
  <lastmod>2026-08-13T12:00:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的摂動の影響を低減するカーネル化マニホールド写像（A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations）</news:title>
   <news:publication_date>2026-08-13T12:00:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722730</loc>
  <lastmod>2026-08-13T11:59:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続状態空間における予算付き強化学習（Budgeted Reinforcement Learning in Continuous State Space）</news:title>
   <news:publication_date>2026-08-13T11:59:20Z</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>
   <news:title>動画における顔クラスタリングのための自己教師あり顔表現学習（Self-Supervised Learning of Face Representations for Video Face Clustering）</news:title>
   <news:publication_date>2026-08-13T11:59:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722726</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>Reinforcement LearningでreCAPTCHA v3を回避する手法（Hacking Google reCAPTCHA v3 using Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-13T11:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722724</loc>
  <lastmod>2026-08-13T11:58:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手部姿勢推定の総合的概説（Hand Pose Estimation: A Survey）</news:title>
   <news:publication_date>2026-08-13T11:58:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722722</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>断面厚み予測によるRGB-D融合強化（X-Section: Cross-Section Prediction for Enhanced RGB-D Fusion）</news:title>
   <news:publication_date>2026-08-13T11:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722720</loc>
  <lastmod>2026-08-13T11:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DEPAMの開発詳細と計算ベンチマーク（Development details and computational benchmarking of DEPAM）</news:title>
   <news:publication_date>2026-08-13T11:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722718</loc>
  <lastmod>2026-08-13T11:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所多様体近似による分類（Classification via local manifold approximation）</news:title>
   <news:publication_date>2026-08-13T11:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722716</loc>
  <lastmod>2026-08-13T11:05:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス混合モデルに対する一般化期待値最大化アルゴリズムの制御系的解析（Analysis of a Generalized Expectation-Maximization Algorithm for Gaussian Mixture Models: A Control Systems Perspective）</news:title>
   <news:publication_date>2026-08-13T11:05:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722714</loc>
  <lastmod>2026-08-13T11:05:32Z</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>2026-08-13T11:05:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722712</loc>
  <lastmod>2026-08-13T11:05:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Anytime online-to-batch変換、楽観主義、加速化（Anytime Online-to-Batch Conversions, Optimism, and Acceleration）</news:title>
   <news:publication_date>2026-08-13T11:05:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722710</loc>
  <lastmod>2026-08-13T11:05:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚的不確かさを管理する枠組みの提案（Towards a Framework to Manage Perceptual Uncertainty for Safe Automated Driving）</news:title>
   <news:publication_date>2026-08-13T11:05:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722708</loc>
  <lastmod>2026-08-13T10:13:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サーマル顔画像から可視顔画像を合成するセマンティックガイド付きGAN（Matching Thermal to Visible Face Images Using a Semantic-Guided Generative Adversarial Network）</news:title>
   <news:publication_date>2026-08-13T10:13:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722706</loc>
  <lastmod>2026-08-13T10:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DESK：外科ロボット技能データセットとシミュレーションから現実世界への知識移転（DESK: A Robotic Activity Dataset for Dexterous Surgical Skills Transfer to Medical Robots）</news:title>
   <news:publication_date>2026-08-13T10:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722704</loc>
  <lastmod>2026-08-13T10:13:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希薄高次元線形回帰における予測のための経験的事前分布（Empirical priors for prediction in sparse high-dimensional linear regression）</news:title>
   <news:publication_date>2026-08-13T10:13:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722702</loc>
  <lastmod>2026-08-13T10:11:37Z</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>2026-08-13T10:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-13T10:11:25Z</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>2026-08-13T10:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-13T10:11:18Z</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>2026-08-13T10:11:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722696</loc>
  <lastmod>2026-08-13T10:11:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>防御の期待効用を直接最大化する学習手法（End-to-End Game-Focused Learning of Adversary Behavior in Security Games）</news:title>
   <news:publication_date>2026-08-13T10:11:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722694</loc>
  <lastmod>2026-08-13T09:19:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然保護区におけるルリノドヒタキの個体数減少の謎を可視化で解く（Addressing The Mystery of Population Decline of The Rose-Crested Blue Pipit In A Nature Preserve Using Data Visualization）</news:title>
   <news:publication_date>2026-08-13T09:19:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722692</loc>
  <lastmod>2026-08-13T09:19:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Origins Space Telescopeの遠赤外分光サーベイの予測（Origins Space Telescope: predictions for far-IR spectroscopic surveys）</news:title>
   <news:publication_date>2026-08-13T09:19:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722690</loc>
  <lastmod>2026-08-13T09:18:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的教師ありによる非局所文法依存関係の学習改善（Structural Supervision Improves Learning of Non-Local Grammatical Dependencies）</news:title>
   <news:publication_date>2026-08-13T09:18:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722688</loc>
  <lastmod>2026-08-13T09:17:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タイのClassStartを用いたオンライン学習受容の要因分析（Investigating factors affecting learner&amp;#039;s perception toward online learning: Evidence from ClassStart Application in Thailand）</news:title>
   <news:publication_date>2026-08-13T09:17:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722686</loc>
  <lastmod>2026-08-13T09:17:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベルヌーイ・レース粒子フィルタ（Bernoulli Race Particle Filters）</news:title>
   <news:publication_date>2026-08-13T09:17:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722684</loc>
  <lastmod>2026-08-13T09:17:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>標準化損失による深層ニューラルネットワーク学習の高速化（Accelerating Training of Deep Neural Networks with a Standardization Loss）</news:title>
   <news:publication_date>2026-08-13T09:17:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722682</loc>
  <lastmod>2026-08-13T09:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列コーパスからの転移学習による中国語での認知症検出（Detecting Dementia in Mandarin Chinese using Transfer Learning from a Parallel Corpus）</news:title>
   <news:publication_date>2026-08-13T09:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722680</loc>
  <lastmod>2026-08-13T08:25:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D時空間グラフ畳み込みによる交通予測の新枠組み（3D Graph Convolutional Networks with Temporal Graphs: A Spatial Information Free Framework For Traffic Forecasting）</news:title>
   <news:publication_date>2026-08-13T08:25:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722678</loc>
  <lastmod>2026-08-13T08:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一枚の静止画からの双方向フローに基づく教師なし動画生成（Unsupervised Bi-directional Flow-based Video Generation from one Snapshot）</news:title>
   <news:publication_date>2026-08-13T08:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722676</loc>
  <lastmod>2026-08-13T08:25:13Z</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>2026-08-13T08:25:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722674</loc>
  <lastmod>2026-08-13T08:24:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書きストロークの角点・接線点検出を堅牢にする深層学習手法（Robust corner and tangent point detection for strokes with deep learning approach）</news:title>
   <news:publication_date>2026-08-13T08:24:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722672</loc>
  <lastmod>2026-08-13T08:24:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MILDNet: 軽量単一スケール深層ランキングアーキテクチャ（MILDNet: A Lightweight Single Scaled Deep Ranking Architecture）</news:title>
   <news:publication_date>2026-08-13T08:24:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722670</loc>
  <lastmod>2026-08-13T08:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競争的ブリッジ入札における深層ニューラルネットワーク（Competitive Bridge Bidding with Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-13T08:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722668</loc>
  <lastmod>2026-08-13T08:23:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己対抗的変分オートエンコーダによる異常検知とガウス異常事前知識（adVAE: a Self-adversarial Variational Autoencoder with Gaussian Anomaly Prior Knowledge for Anomaly Detection）</news:title>
   <news:publication_date>2026-08-13T08:23:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/722664</loc>
  <lastmod>2026-08-13T07:32:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈認識型深層学習によるソースコードモデリング（CodeGRU: Context-aware Deep Learning with Gated Recurrent Unit for Source Code Modeling）</news:title>
   <news:publication_date>2026-08-13T07:32:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722662</loc>
  <lastmod>2026-08-13T07:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超音波舌画像からの頑健な特徴抽出—Denoising Convolutional Autoencoderの応用（Denoising Convolutional Autoencoder Based B-Mode Ultrasound Tongue Image Feature Extraction）</news:title>
   <news:publication_date>2026-08-13T07:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722660</loc>
  <lastmod>2026-08-13T07:30:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きカーネル平均埋め込みを用いたベイズ学習による自動化された尤度フリー推論（Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference）</news:title>
   <news:publication_date>2026-08-13T07:30:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722658</loc>
  <lastmod>2026-08-13T07:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックス問題の可視化枠組み（Solving the Black Box Problem: A Normative Framework for Explainable Artificial Intelligence）</news:title>
   <news:publication_date>2026-08-13T07:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722656</loc>
  <lastmod>2026-08-13T07:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画長さで学ぶハイライト検出（Less is More: Learning Highlight Detection from Video Duration）</news:title>
   <news:publication_date>2026-08-13T07:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722654</loc>
  <lastmod>2026-08-13T07:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Meta-SR: 単一モデルで任意倍率の超解像を可能にする手法（Meta-SR: A Magnification-Arbitrary Network for Super-Resolution）</news:title>
   <news:publication_date>2026-08-13T07:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722652</loc>
  <lastmod>2026-08-13T06:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期予測可能な車両行動の推定手法：Behavior Interaction Network（Predicting Vehicle Behaviors Over An Extended Horizon Using Behavior Interaction Network）</news:title>
   <news:publication_date>2026-08-13T06:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722650</loc>
  <lastmod>2026-08-13T06:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CAD-Netによるリモートセンシング画像の文脈対応物体検出（CAD-Net: A Context-Aware Detection Network for Objects in Remote Sensing Imagery）</news:title>
   <news:publication_date>2026-08-13T06:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722648</loc>
  <lastmod>2026-08-13T06:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市環境でのオンライン車両軌跡予測の二層フレームワーク（Online Vehicle Trajectory Prediction using Policy Anticipation Network and Optimization-based Context Reasoning）</news:title>
   <news:publication_date>2026-08-13T06:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722646</loc>
  <lastmod>2026-08-13T06:27:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Texture Transferによる画像超解像（Image Super-Resolution by Neural Texture Transfer）</news:title>
   <news:publication_date>2026-08-13T06:27:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722644</loc>
  <lastmod>2026-08-13T06:27:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTの階層別セキュリティとプライバシーの概観（A survey of security and privacy issues in the Internet of Things from the layered context）</news:title>
   <news:publication_date>2026-08-13T06:27:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722642</loc>
  <lastmod>2026-08-13T06:26:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全なデータから生成モデルを学ぶための変分オートデコーダ（Variational Auto-Decoder）</news:title>
   <news:publication_date>2026-08-13T06:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722640</loc>
  <lastmod>2026-08-13T06:26:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データ回帰のためのMultiple Learning（Multiple Learning for Regression in Big Data）</news:title>
   <news:publication_date>2026-08-13T06:26:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722638</loc>
  <lastmod>2026-08-13T05:35:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膵臓セグメンテーションのためのモデル主導スタック型全畳み込みネットワーク（A Model-Driven Stack-Based Fully Convolutional Network for Pancreas Segmentation）</news:title>
   <news:publication_date>2026-08-13T05:35:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722636</loc>
  <lastmod>2026-08-13T05:34:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラミング問題のアルゴリズム分類を自動予測する試み（Predicting Algorithm Classes for Programming Word Problems）</news:title>
   <news:publication_date>2026-08-13T05:34:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722634</loc>
  <lastmod>2026-08-13T05:34:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算負荷の高い環境における連続制御のための非同期エピソディックDDPG（Asynchronous Episodic Deep Deterministic Policy Gradient）</news:title>
   <news:publication_date>2026-08-13T05:34:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722632</loc>
  <lastmod>2026-08-13T05:33:41Z</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再正規化群による機械学習ホログラフィック写像（Machine Learning Holographic Mapping by Neural Network Renormalization Group）</news:title>
   <news:publication_date>2026-08-13T05:33:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722630</loc>
  <lastmod>2026-08-13T05:33:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループラッソ規範を持つベクトル値再生核バナッハ空間（Vector-valued Reproducing Kernel Banach Spaces with Group Lasso Norms）</news:title>
   <news:publication_date>2026-08-13T05:33:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722628</loc>
  <lastmod>2026-08-13T05:33:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を考慮した視覚ベース自動運転の実装手法（Visual-based Autonomous Driving Deployment from a Stochastic and Uncertainty-aware Perspective）</news:title>
   <news:publication_date>2026-08-13T05:33:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722626</loc>
  <lastmod>2026-08-13T05:32:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定木とロジスティック回帰の安定性（STABILITY OF DECISION TREES AND LOGISTIC REGRESSION）</news:title>
   <news:publication_date>2026-08-13T05:32:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722624</loc>
  <lastmod>2026-08-13T04:41:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンコーダ・デコーダ翻訳モデルの較正（CALIBRATION OF ENCODER DECODER MODELS FOR NEURAL MACHINE TRANSLATION）</news:title>
   <news:publication_date>2026-08-13T04:41:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722622</loc>
  <lastmod>2026-08-13T04:41:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共有意味表現の変換転送（Let’s Transfer Transformations of Shared Semantic Representations）</news:title>
   <news:publication_date>2026-08-13T04:41:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722620</loc>
  <lastmod>2026-08-13T04:41:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非ダウンサンプリング・クォータニオン・ウェーブレットによるスペクトル解析（Non-decimated Quaternion Wavelet Spectral Tools with Applications）</news:title>
   <news:publication_date>2026-08-13T04:41:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722618</loc>
  <lastmod>2026-08-13T04:40:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の言い換え検出を敵対的視点で再定義する（AIRD: Adversarial Learning Framework for Image Repurposing Detection）</news:title>
   <news:publication_date>2026-08-13T04:40:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722616</loc>
  <lastmod>2026-08-13T04:40:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural MMO（Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents）</news:title>
   <news:publication_date>2026-08-13T04:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722614</loc>
  <lastmod>2026-08-13T04:40:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推薦システムにおけるランキング公平性を測る手法と実装（Fairness in Recommendation Ranking through Pairwise Comparisons）</news:title>
   <news:publication_date>2026-08-13T04:40:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722612</loc>
  <lastmod>2026-08-13T04:39:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意に基づく選択的可塑性（Attention-Based Selective Plasticity）</news:title>
   <news:publication_date>2026-08-13T04:39:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722610</loc>
  <lastmod>2026-08-13T03:48:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱ラベルAudioSetに対する注意機構付き音声タグ付け（Weakly Labelled AudioSet Tagging with Attention Neural Networks）</news:title>
   <news:publication_date>2026-08-13T03:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722608</loc>
  <lastmod>2026-08-13T03:47:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的シーンのぼかし除去のための極端チャネル事前埋め込みネットワーク（Extreme Channel Prior Embedded Network for Dynamic Scene Deblurring）</news:title>
   <news:publication_date>2026-08-13T03:47:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722606</loc>
  <lastmod>2026-08-13T03:47:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空機衝突回避ニューラルネットの検証と線形近似による安全領域の定義（Verifying Aircraft Collision Avoidance Neural Networks Through Linear Approximations of Safe Regions）</news:title>
   <news:publication_date>2026-08-13T03:47:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722604</loc>
  <lastmod>2026-08-13T03:46:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Equilibrated Recurrent Neural Networkを読み解く：時差自己フィードバックがもたらす安定性と精度の向上（Equilibrated Recurrent Neural Network: Neuronal Time-Delayed Self-Feedback Improves Accuracy and Stability）</news:title>
   <news:publication_date>2026-08-13T03:46:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722602</loc>
  <lastmod>2026-08-13T03:46:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による予測モデル自動化（Automating Predictive Modeling Process using Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-13T03:46:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722600</loc>
  <lastmod>2026-08-13T03:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書順で優先順位をつける多目的クラスタリング（Lexicographically Ordered Multi-Objective Clustering）</news:title>
   <news:publication_date>2026-08-13T03:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722598</loc>
  <lastmod>2026-08-13T03:46:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GraphViteによる大規模ノード埋め込みの高速化（GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding）</news:title>
   <news:publication_date>2026-08-13T03:46:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722596</loc>
  <lastmod>2026-08-13T02:54:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深いReLUネットワークが帯域制限関数の次元の呪いを克服する（Deep ReLU networks overcome the curse of dimensionality for generalized bandlimited functions）</news:title>
   <news:publication_date>2026-08-13T02:54:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722594</loc>
  <lastmod>2026-08-13T02:54:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発話が無い、あるいは雑音だらけの環境での音声認識（SPEECH RECOGNITION WITH NO SPEECH OR WITH NOISY SPEECH）</news:title>
   <news:publication_date>2026-08-13T02:54:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722592</loc>
  <lastmod>2026-08-13T02:53:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化によるスパース最適方策のアプローチ（A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-13T02:53:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722590</loc>
  <lastmod>2026-08-13T02:53:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠方太陽系天体の恒星掩蔽の将来展望（The future of stellar occultations by distant solar system bodies: perspectives from the Gaia astrometry and the deep sky surveys）</news:title>
   <news:publication_date>2026-08-13T02:53:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722588</loc>
  <lastmod>2026-08-13T02:53:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効用最大化二値予測におけるモデル選択（Model Selection in Utility-Maximizing Binary Prediction）</news:title>
   <news:publication_date>2026-08-13T02:53:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722586</loc>
  <lastmod>2026-08-13T02:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知語（OOV）に対する埋め込み予測と解釈（Predicting and interpreting embeddings for out of vocabulary words in downstream tasks）</news:title>
   <news:publication_date>2026-08-13T02:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722584</loc>
  <lastmod>2026-08-13T02:53:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴寄与区間による解釈可能かつ対話的なデータ探索（FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration）</news:title>
   <news:publication_date>2026-08-13T02:53:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722582</loc>
  <lastmod>2026-08-13T02:02:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑物流ネットワークにおける資源バランスのための協調型マルチエージェント強化学習フレームワーク (A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network)</news:title>
   <news:publication_date>2026-08-13T02:02:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722580</loc>
  <lastmod>2026-08-13T02:02:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PartNetによる階層的3D形状分割の革新（PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation）</news:title>
   <news:publication_date>2026-08-13T02:02:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722578</loc>
  <lastmod>2026-08-13T02:01:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル検索とランキングのためのneuralRank（neuralRank: Searching and ranking ANN-based model repositories）</news:title>
   <news:publication_date>2026-08-13T02:01:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722576</loc>
  <lastmod>2026-08-13T02:01:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>#MeTooはジェンダー規範を変えたか（USING ARTIFICIAL INTELLIGENCE TO RECAPTURE NORMS: DID #METOO CHANGE GENDER NORMS IN SWEDEN?）</news:title>
   <news:publication_date>2026-08-13T02:01:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722574</loc>
  <lastmod>2026-08-13T02:01:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スクリーンコンテンツ画像の画質評価に向けた深層最適化モデル（Deep Optimization Model for Screen Content Image Quality Assessment using Neural Networks）</news:title>
   <news:publication_date>2026-08-13T02:01:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722572</loc>
  <lastmod>2026-08-13T02:00:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸正則化による行列補完と近接勾配法の収束解析（Matrix Completion via Nonconvex Regularization: Convergence of the Proximal Gradient Algorithm）</news:title>
   <news:publication_date>2026-08-13T02:00:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722570</loc>
  <lastmod>2026-08-13T02:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モーションキャプチャの細粒度意味セグメンテーション（Fine-Grained Semantic Segmentation of Motion Capture Data using Dilated Temporal Fully-Convolutional Networks）</news:title>
   <news:publication_date>2026-08-13T02:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722568</loc>
  <lastmod>2026-08-13T01:09:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク復旧の競合的浸透戦略（Competitive percolation strategies for network recovery）</news:title>
   <news:publication_date>2026-08-13T01:09:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722566</loc>
  <lastmod>2026-08-13T01:09:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆問題と機械学習の統一的リプレゼンター定理（A unifying representer theorem for inverse problems and machine learning）</news:title>
   <news:publication_date>2026-08-13T01:09:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722564</loc>
  <lastmod>2026-08-13T01:08:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業用ロボット向け完全畳み込みワンショット物体セグメンテーション（Fully Convolutional One–Shot Object Segmentation for Industrial Robotics）</news:title>
   <news:publication_date>2026-08-13T01:08:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722562</loc>
  <lastmod>2026-08-13T01:08:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OmniDRLによる全周カメラでの歩行者検出の頑健化（OmniDRL: Robust Pedestrian Detection using Deep Reinforcement Learning on Omnidirectional Cameras）</news:title>
   <news:publication_date>2026-08-13T01:08:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722560</loc>
  <lastmod>2026-08-13T01:08:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディアにおける攻撃的発言検出の実践（Towards NLP with Deep Learning: Convolutional Neural Networks and Recurrent Neural Networks for Offensive Language Identification in Social Media）</news:title>
   <news:publication_date>2026-08-13T01:08:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722558</loc>
  <lastmod>2026-08-13T01:08:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Surrogate出力間の低ランク関係を利活用する構造化予測（Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction）</news:title>
   <news:publication_date>2026-08-13T01:08:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722556</loc>
  <lastmod>2026-08-13T01:08:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepGiniによるテスト優先化で実務的なDNN品質向上を狙う（DeepGini: Prioritizing Massive Tests to Enhance the Robustness of Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-13T01:08:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722554</loc>
  <lastmod>2026-08-13T00:16:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音の振動で注ぎの高さを推定する（Making Sense of Audio Vibration for Liquid Height Estimation in Robotic Pouring）</news:title>
   <news:publication_date>2026-08-13T00:16:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722552</loc>
  <lastmod>2026-08-13T00:16:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四元数畳み込みニューラルネットワークの要点（Quaternion Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-13T00:16:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722550</loc>
  <lastmod>2026-08-13T00:15:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wasserstein距離に基づく深層敵対的転移学習による機械故障診断（Wasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis）</news:title>
   <news:publication_date>2026-08-13T00:15:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722548</loc>
  <lastmod>2026-08-13T00:14:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンパスで大規模・欠損混在データを扱う実務的手法の提示（One-Pass Incomplete Multi-view Clustering）</news:title>
   <news:publication_date>2026-08-13T00:14:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722546</loc>
  <lastmod>2026-08-13T00:14:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実な形状補完を踏まえた堅牢な把持計画（Robust Grasp Planning Over Uncertain Shape Completions）</news:title>
   <news:publication_date>2026-08-13T00:14:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722544</loc>
  <lastmod>2026-08-13T00:14:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市環境における模倣学習と安全性強化（Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safety）</news:title>
   <news:publication_date>2026-08-13T00:14:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722542</loc>
  <lastmod>2026-08-13T00:14:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の敵対行為を利用したロボット学習（Robot Learning via Human Adversarial Games）</news:title>
   <news:publication_date>2026-08-13T00:14:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722540</loc>
  <lastmod>2026-08-12T23:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Bayesが大規模VARの実務を変える（Approximation Properties of Variational Bayes for Vector Autoregressions）</news:title>
   <news:publication_date>2026-08-12T23:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722538</loc>
  <lastmod>2026-08-12T23:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットの手と目をつなぐ「状態表現」の評価（Evaluation of state representation methods in robot hand-eye coordination learning from demonstration）</news:title>
   <news:publication_date>2026-08-12T23:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722536</loc>
  <lastmod>2026-08-12T23:21:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似スパース性下の高次元学習と非滑らか推定および正則化ニューラルネットワークへの応用 (High-Dimensional Learning under Approximate Sparsity with Applications to Nonsmooth Estimation and Regularized Neural Networks)</news:title>
   <news:publication_date>2026-08-12T23:21:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722534</loc>
  <lastmod>2026-08-12T23:21:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子力学的データ同化の枠組み（Quantum mechanics and data assimilation）</news:title>
   <news:publication_date>2026-08-12T23:21:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/722532</loc>
  <lastmod>2026-08-12T23:21:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎化可能な近似グラフ分割フレームワーク（GAP: Generalizable Approximate Graph Partitioning Framework）</news:title>
   <news:publication_date>2026-08-12T23:21:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722530</loc>
  <lastmod>2026-08-12T23:21:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>稀な暴力事象の予測に対するアルゴリズム的アプローチ（An Algorithmic Approach to Forecasting Rare Violent Events: An Illustration Based in IPV Perpetration）</news:title>
   <news:publication_date>2026-08-12T23:21:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722528</loc>
  <lastmod>2026-08-12T23:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カバー時間を最小化して探索の選択肢を発見する（Discovering Options for Exploration by Minimizing Cover Time）</news:title>
   <news:publication_date>2026-08-12T23:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722526</loc>
  <lastmod>2026-08-12T22:29:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模半正定値計画問題を分割して解く実践法（Block-Coordinate Minimization for Large SDPs with Block-Diagonal Constraints）</news:title>
   <news:publication_date>2026-08-12T22:29:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-12T22:28:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>表層統計を除去して頑健な表現を学ぶ（Learning Robust Representations by Projecting Superficial Statistics Out）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-12T22:28:33Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-12T22:28:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-12T22:27:54Z</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>
   </news:publication>
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   <news:publication_date>2026-08-12T22:27:47Z</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>PuVAEによる敵対的例の浄化（PuVAE: A Variational Autoencoder to Purify Adversarial Examples）</news:title>
   <news:publication_date>2026-08-12T22:27:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-12T22:26:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/722512</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>グラフ構造操作による分類器攻撃の実態（Attacking Graph-based Classification via Manipulating the Graph Structure）</news:title>
   <news:publication_date>2026-08-12T21:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722510</loc>
  <lastmod>2026-08-12T21:27:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Plackett-LuceモデルにおけるPACからインスタンス最適なサンプル複雑度へ（From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model）</news:title>
   <news:publication_date>2026-08-12T21:27:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722508</loc>
  <lastmod>2026-08-12T21:27:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GRPモデルによる感覚運動学習（GRP Model for Sensorimotor Learning）</news:title>
   <news:publication_date>2026-08-12T21:27:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722506</loc>
  <lastmod>2026-08-12T21:26:50Z</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>2026-08-12T21:26:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/722504</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-12T21:26:01Z</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>
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   <news:publication_date>2026-08-12T21:25:55Z</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>2026-08-12T21:25:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-12T20:33:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T20:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T20:33:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news: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>2026-08-12T20:32:10Z</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>2026-08-12T20:32:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T20:31:49Z</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:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722482</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>2026-08-12T19:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722480</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>2026-08-12T19:39:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722478</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>ミューズ超深宇宙観測によるクエーサー対に伴うLyαネビュラ群の発見（The MUSE Ultra Deep Field (MUDF). I. Discovery of a group of Lyα nebulae associated with a bright z ≈3.23 quasar pair）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復的変分推論による多物体表現学習（Multi-Object Representation Learning with Iterative Variational Inference）</news:title>
   <news:publication_date>2026-08-12T19:38:10Z</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>
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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>2026-08-12T18:45:47Z</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>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news: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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 <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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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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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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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-12T16:58:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news: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: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: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:publication_date>2026-08-12T16:56:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/722432</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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  <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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  <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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  <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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  <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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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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   <news: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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  <loc>https://aibr.jp/archives/722418</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/722416</loc>
  <lastmod>2026-08-12T15:52:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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