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   <news:title>部分木カーネルの重み関数が決定的である（The Weight Function in the Subtree Kernel is Decisive）</news:title>
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   <news:title>低資源言語向けの根拠ある教師なし品詞タグ付け（A Grounded Unsupervised Universal Part-of-Speech Tagger for Low-Resource Languages）</news:title>
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   <news:title>球面回帰による連続値推定の安定化（Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>板情報に基づく中間価格予測のための特徴エンジニアリング（Feature Engineering for Mid-Price Prediction with Deep Learning）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>重みの転送なしで深層学習を可能にする仕組み（Deep Learning without Weight Transport）</news:title>
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   <news:title>Trusted CIによるオープンサイエンス向けサイバーセキュリティの実務モデル（Trusted CI Experiences in Cybersecurity and Service to Open Science）</news:title>
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   <news:title>ピクセル適応畳み込みニューラルネットワーク（Pixel-Adaptive Convolutional Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>スキャナー不変表現による拡散MRIのハーモナイズ（Scanner Invariant Representations for Diffusion MRI Harmonization）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>ReinBoによるパイプライン探索と設定の統合（ReinBo: Machine Learning pipeline search and configuration with Bayesian Optimization embedded Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>深層学習の選択的概観（A Selective Overview of Deep Learning）</news:title>
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   <news:title>StegaStamp: 物理写真に埋め込む不可視ハイパーリンクの可能性（StegaStamp: Invisible Hyperlinks in Physical Photographs）</news:title>
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   <news:title>ClinicalBERTによる臨床ノートの表現化と再入院予測（ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>ハイパーパーティザンニュース検出におけるBERTの実用性（Harvey Mudd College at SemEval-2019 Task 4: The Clint Buchanan Hyperpartisan News Detector）</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>希少特徴の選択と集約のための正則化回帰の新しい計算的・統計的側面（New Computational and Statistical Aspects of Regularized Regression with Application to Rare Feature Selection and Aggregation）</news:title>
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   <news:title>ツイート中の薬物言及を検出する深層ニューラルネットワークのアンサンブル（Deep Neural Networks Ensemble for Detecting Medication Mentions in Tweets）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>リアルタイムでの非線形弾性材料シミュレーションをDeep Learningで実現する（Simulation of hyperelastic materials in real-time using Deep Learning）</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>反復残差改良による光学フローとオクルージョンの共同推定（Iterative Residual Refinement for Joint Optical Flow and Occlusion Estimation）</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>自然言語質問応答の進展（Advances in Natural Language Question Answering）</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>クラスタ－ブースターによるアプリケーション性能改善（Application performance on a Cluster-Booster system）</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>スキップ接続を持つ深層ニューラルネットワークモデルに対する勾配降下法の解析（Analysis of the Gradient Descent Algorithm for a Deep Neural Network Model with Skip-connections）</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>電気抵抗率データのディープラーニング反転（Deep Learning Inversion of Electrical Resistivity Data）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>不均衡な観測データからの意思決定に効く能動学習（Active Learning for Decision-Making from Imbalanced Observational Data）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ワンショット音声変換で見えた「話者」と「内容」の分離（One-shot Voice Conversion by Separating Speaker and Content Representations with Instance Normalization）</news:title>
   <news:publication_date>2026-08-29T22:47:55Z</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>
   </news:publication>
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   <news:publication_date>2026-08-29T21:56:04Z</news:publication_date>
   <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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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ロボットのペグ挿入戦略：接触モデルベース制御とモデルフリー学習の比較（Compare Contact Model-based Control and Contact Model-free Learning: A Survey of Robotic Peg-in-hole Assembly Strategies）</news:title>
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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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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>攻撃的表現分類のための言語学的強化深層学習アンサンブル（NLPR@SRPOL at SemEval-2019 Task 6 and Task 5: Linguistically enhanced deep learning offensive sentence classifier）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <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:title>知識絞り込み型敵対的ネットワーク圧縮（Knowledge Squeezed Adversarial Network Compression）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neuralogramによる音声理解の新しい表現（NEURALOGRAM: A NEURAL NETWORK BASED REPRESENTATION FOR UNDERSTANDING AUDIO SIGNALS）</news:title>
   <news:publication_date>2026-08-29T17:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728631</loc>
  <lastmod>2026-08-29T17:11:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低コスト分光器を用いた偽造医薬品および汚染食品の検出（Low-cost spectrogram based counterfeit medicine and contaminated food detection）</news:title>
   <news:publication_date>2026-08-29T17:11:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728629</loc>
  <lastmod>2026-08-29T17:10:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子系の固有モード抽出のための一般化独立成分分析（Generalized Independent Component Analysis for Extracting Eigen-Modes of a Quantum System）</news:title>
   <news:publication_date>2026-08-29T17:10:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728627</loc>
  <lastmod>2026-08-29T17:10:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子版カクテルパーティ問題の登場（The Quantum Cocktail Party Problem）</news:title>
   <news:publication_date>2026-08-29T17:10:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728625</loc>
  <lastmod>2026-08-29T17:10:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係的知識蒸留（Relational Knowledge Distillation）</news:title>
   <news:publication_date>2026-08-29T17:10:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728623</loc>
  <lastmod>2026-08-29T17:10:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Turing Machineの総説（A review on Neural Turing Machine）</news:title>
   <news:publication_date>2026-08-29T17:10:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728621</loc>
  <lastmod>2026-08-29T16:18:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小型モデルで年齢推定の精度限界に挑む — C3AE（C3AE: Exploring the Limits of Compact Model for Age Estimation）</news:title>
   <news:publication_date>2026-08-29T16:18:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728619</loc>
  <lastmod>2026-08-29T16:18:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり変分アプローチによる文書レベル多側面感情分類（A Variational Approach to Weakly Supervised Document-Level Multi-Aspect Sentiment Classification）</news:title>
   <news:publication_date>2026-08-29T16:18:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728617</loc>
  <lastmod>2026-08-29T16:17:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズだらけの短文からサイバー攻撃を見つける技術（Detecting Cybersecurity Events from Noisy Short Text）</news:title>
   <news:publication_date>2026-08-29T16:17:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728615</loc>
  <lastmod>2026-08-29T16:17:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数例から学ぶ機械学習の概観（Generalizing from a Few Examples: A Survey on Few-Shot Learning）</news:title>
   <news:publication_date>2026-08-29T16:17:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728613</loc>
  <lastmod>2026-08-29T16:17:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大雨画像のレストア：物理モデルと条件付き敵対学習の統合（Heavy Rain Image Restoration: Integrating Physics Model and Conditional Adversarial Learning）</news:title>
   <news:publication_date>2026-08-29T16:17:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728611</loc>
  <lastmod>2026-08-29T16:16:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質のシグナル機能を予測する星型グラフ記述子と機械学習（Classification of signaling proteins based on molecular star graph descriptors using Machine Learning models）</news:title>
   <news:publication_date>2026-08-29T16:16:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728609</loc>
  <lastmod>2026-08-29T16:16:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像ラベルのみで個別物体を分割する技術の要点解説（Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations）</news:title>
   <news:publication_date>2026-08-29T16:16:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728607</loc>
  <lastmod>2026-08-29T15:24:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サムネイル一枚ですべて足りる認識（ThumbNet: One Thumbnail Image Contains All You Need for Recognition）</news:title>
   <news:publication_date>2026-08-29T15:24:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728605</loc>
  <lastmod>2026-08-29T15:13:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布モデリングと安定化制御の実現に向けて（Distribution Modeling and Stabilization Control for Discrete-Time Linear Random Dynamical Systems Using Ensemble Kalman Filter）</news:title>
   <news:publication_date>2026-08-29T15:13:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728603</loc>
  <lastmod>2026-08-29T15:13:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>n-グラム情報を切り離すことで改善される単語埋め込み（Better Word Embeddings by Disentangling Contextual n-Gram Information）</news:title>
   <news:publication_date>2026-08-29T15:13:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728601</loc>
  <lastmod>2026-08-29T15:12:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤文訂正のためのコーパス生成（Corpora Generation for Grammatical Error Correction）</news:title>
   <news:publication_date>2026-08-29T15:12:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728599</loc>
  <lastmod>2026-08-29T15:12:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファジィ適応型TLBOによる混合強度t-wayテスト生成（Fuzzy Adaptive TLBO for Mixed-Strength t-way Test Suite Generation）</news:title>
   <news:publication_date>2026-08-29T15:12:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728597</loc>
  <lastmod>2026-08-29T15:12:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所記述子学習のための二次類似性正則化（SOSNet: Second Order Similarity Regularization for Local Descriptor Learning）</news:title>
   <news:publication_date>2026-08-29T15:12:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728595</loc>
  <lastmod>2026-08-29T15:12:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DSNet: 軽量で高速な道路シーン分割の実践的設計（DSNet: An Efficient CNN for Road Scene Segmentation）</news:title>
   <news:publication_date>2026-08-29T15:12:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728593</loc>
  <lastmod>2026-08-29T14:20:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特権情報を用いた計量学習による人物再識別（Person Re-identification with Metric Learning using Privileged Information）</news:title>
   <news:publication_date>2026-08-29T14:20:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728591</loc>
  <lastmod>2026-08-29T14:20:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>硬X線立波光電子分光が明らかにするエピタキシャルFe/MgO多層磁気トンネル接合の界面構造（Hard x-ray standing-wave photoemission insights into the structure of an epitaxial Fe/MgO multilayer magnetic tunnel junction）</news:title>
   <news:publication_date>2026-08-29T14:20:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728589</loc>
  <lastmod>2026-08-29T14:20:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野生動画からの深度推定（Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras）</news:title>
   <news:publication_date>2026-08-29T14:20:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728587</loc>
  <lastmod>2026-08-29T14:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空撮映像の動的サリエンシー推定のための時空間ナレッジディスティレーション (Spatiotemporal Knowledge Distillation for Efficient Estimation of Aerial Video Saliency)</news:title>
   <news:publication_date>2026-08-29T14:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728585</loc>
  <lastmod>2026-08-29T14:19:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン人気の時間的パターンの発見（Discovering patterns of online popularity from time series）</news:title>
   <news:publication_date>2026-08-29T14:19:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728583</loc>
  <lastmod>2026-08-29T14:19:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FAMNetによるオンライン多対象追跡の統合学習（FAMNet: Joint Learning of Feature, Affinity and Multi-dimensional Assignment for Online Multiple Object Tracking）</news:title>
   <news:publication_date>2026-08-29T14:19:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728581</loc>
  <lastmod>2026-08-29T14:18:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテとメモリネットワークで明らかにするAKIのサブフェノタイプ（Identifying Sub-Phenotypes of Acute Kidney Injury using Structured and Unstructured Electronic Health Record Data with Memory Networks）</news:title>
   <news:publication_date>2026-08-29T14:18:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728579</loc>
  <lastmod>2026-08-29T13:27:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動美術解析のための文脈対応埋め込み（Context-Aware Embeddings for Automatic Art Analysis）</news:title>
   <news:publication_date>2026-08-29T13:27:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728577</loc>
  <lastmod>2026-08-29T13:27:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動精算に向けたデータプライミングネットワーク（Data Priming Network for Automatic Check-Out）</news:title>
   <news:publication_date>2026-08-29T13:27:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728575</loc>
  <lastmod>2026-08-29T13:26:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>財務ポートフォリオのモデルフリー強化学習の概観（Model-Free Reinforcement Learning for Financial Portfolios: A Brief Survey）</news:title>
   <news:publication_date>2026-08-29T13:26:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728573</loc>
  <lastmod>2026-08-29T13:26:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WiFiフィンガープリントで活動認識と屋内位置推定を同時に行う（Joint Activity Recognition and Indoor Localization with WiFi Fingerprints）</news:title>
   <news:publication_date>2026-08-29T13:26:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728571</loc>
  <lastmod>2026-08-29T13:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>年齢不変顔認識のデコリレート敵対学習（Decorrelated Adversarial Learning for Age-Invariant Face Recognition）</news:title>
   <news:publication_date>2026-08-29T13:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728569</loc>
  <lastmod>2026-08-29T13:25:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向注意エンティティグラフ畳み込みネットワーク（Bi-directional Attention Entity Graph Convolutional Network）</news:title>
   <news:publication_date>2026-08-29T13:25:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728567</loc>
  <lastmod>2026-08-29T13:25:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力に応じて重みを変える畳み込み — CondConv: Conditionally Parameterized Convolutions for Efficient Inference (CondConv: Conditionally Parameterized Convolutions for Efficient Inference)</news:title>
   <news:publication_date>2026-08-29T13:25:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728565</loc>
  <lastmod>2026-08-29T12:34:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用物体のゼロショット認識に関する研究（On zero-shot recognition of generic objects）</news:title>
   <news:publication_date>2026-08-29T12:34:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728563</loc>
  <lastmod>2026-08-29T12:34:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一パラメータ収益最大化のサンプル複雑度の確定（Settling the Sample Complexity of Single-parameter Revenue Maximization）</news:title>
   <news:publication_date>2026-08-29T12:34:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728561</loc>
  <lastmod>2026-08-29T12:33:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散深層学習による音声認識の高速化（Distributed Deep Learning Strategies For Automatic Speech Recognition）</news:title>
   <news:publication_date>2026-08-29T12:33:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728559</loc>
  <lastmod>2026-08-29T12:33:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高精細な非線形3次元顔モーファブルモデル（Towards High-fidelity Nonlinear 3D Face Morphable Model）</news:title>
   <news:publication_date>2026-08-29T12:33:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728557</loc>
  <lastmod>2026-08-29T12:33:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ジェスチャ認識を1枚の画像に凝縮する手法（Dynamic Gesture Recognition by Using CNNs and star RGB: a Temporal Information Condensation）</news:title>
   <news:publication_date>2026-08-29T12:33:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728555</loc>
  <lastmod>2026-08-29T12:33:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテにおける時系列情報の扱いと有害事象検出への応用（Handling temporality of clinical events with application to Adverse Drug Event detection in Electronic Health Records: A scoping review）</news:title>
   <news:publication_date>2026-08-29T12:33:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728553</loc>
  <lastmod>2026-08-29T12:32:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応学習型エキスパートシステムによるウイルス性肝炎診断支援（Adaptive Learning Expert System for Diagnosis and Management of Viral Hepatitis）</news:title>
   <news:publication_date>2026-08-29T12:32:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728551</loc>
  <lastmod>2026-08-29T11:41:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習アンサンブルの新しい不確実性フレームワーク（Novel Uncertainty Framework for Deep Learning Ensembles）</news:title>
   <news:publication_date>2026-08-29T11:41:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728549</loc>
  <lastmod>2026-08-29T11:31:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩容認識における分離表現学習（Gait Recognition via Disentangled Representation Learning）</news:title>
   <news:publication_date>2026-08-29T11:31:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728547</loc>
  <lastmod>2026-08-29T11:31:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>液体水の同位体効果を深層ポテンシャル分子動力学で調べる（Isotope Effects in Liquid Water via Deep Potential Molecular Dynamics）</news:title>
   <news:publication_date>2026-08-29T11:31:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728545</loc>
  <lastmod>2026-08-29T11:30:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Momentum Networks（Enhancing Time Series Momentum Strategies Using Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-29T11:30:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728543</loc>
  <lastmod>2026-08-29T11:30:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数領域で盗み出しを見つける――単クラス学習によるデータ流出検知（Malicious Overtones: hunting data theft in the frequency domain with one-class learning）</news:title>
   <news:publication_date>2026-08-29T11:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728541</loc>
  <lastmod>2026-08-29T11:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教育におけるクリックベイトの是非（Clickbait in Education – Positive or Negative? Machine Learning Answers）</news:title>
   <news:publication_date>2026-08-29T11:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728539</loc>
  <lastmod>2026-08-29T11:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現実世界でのローカリゼーションを伴うFew-Shot学習（Few-Shot Learning with Localization in Realistic Settings）</news:title>
   <news:publication_date>2026-08-29T11:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728537</loc>
  <lastmod>2026-08-29T10:39:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小世界ニューラルネットワークと高速収束（SWNet: Small-World Neural Networks and Rapid Convergence）</news:title>
   <news:publication_date>2026-08-29T10:39:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728535</loc>
  <lastmod>2026-08-29T10:38:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込みの幾何学的性質が示す本質（Characterizing the impact of geometric properties of word embeddings on task performance）</news:title>
   <news:publication_date>2026-08-29T10:38:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728533</loc>
  <lastmod>2026-08-29T10:38:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Knowledge Distillation を用いた行動予測の知見（KNOWLEDGE DISTILLATION FOR HUMAN ACTION ANTICIPATION）</news:title>
   <news:publication_date>2026-08-29T10:38:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728531</loc>
  <lastmod>2026-08-29T10:37:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有界深さニューラルネットにおける普遍的リプシッツ近似（Universal Lipschitz Approximation in Bounded Depth Neural Networks）</news:title>
   <news:publication_date>2026-08-29T10:37:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728529</loc>
  <lastmod>2026-08-29T10:37:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形差分CNNレンダリングモジュールによる3Dデータ強化（A Non-linear Differential CNN-Rendering Module for 3D Data Enhancement）</news:title>
   <news:publication_date>2026-08-29T10:37:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728527</loc>
  <lastmod>2026-08-29T10:37:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノードごとに受容野を選ぶ動的近隣集約（JUST JUMP: DYNAMIC NEIGHBORHOOD AGGREGATION IN GRAPH NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-08-29T10:37:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728525</loc>
  <lastmod>2026-08-29T10:37:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的マージンを用いたトリプレット損失による3D物体インスタンス認識と姿勢推定（3D Object Instance Recognition and Pose Estimation Using Triplet Loss with Dynamic Margin）</news:title>
   <news:publication_date>2026-08-29T10:37:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728523</loc>
  <lastmod>2026-08-29T09:45:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画から学習する深層畳み込みLSTMネットワーク（LEARNING FROM VIDEOS WITH DEEP CONVOLUTIONAL LSTM NETWORKS）</news:title>
   <news:publication_date>2026-08-29T09:45:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728521</loc>
  <lastmod>2026-08-29T09:45:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何学的自己監督による教師なし3D姿勢推定（Unsupervised 3D Pose Estimation with Geometric Self-Supervision）</news:title>
   <news:publication_date>2026-08-29T09:45:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728519</loc>
  <lastmod>2026-08-29T09:45:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体検出におけるプライムサンプル注意（Prime Sample Attention in Object Detection）</news:title>
   <news:publication_date>2026-08-29T09:45:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728517</loc>
  <lastmod>2026-08-29T09:43:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>具現化されたニューロモルフィック視覚とイベント駆動ランダム逆伝播（Embodied Neuromorphic Vision with Event-Driven Random Backpropagation）</news:title>
   <news:publication_date>2026-08-29T09:43:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728515</loc>
  <lastmod>2026-08-29T09:43:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハドロンキャロリメーターにおけるエネルギー堆積パターンの研究（Study of energy deposition patterns in hadron calorimeter for prompt and displaced jets using convolutional neural network）</news:title>
   <news:publication_date>2026-08-29T09:43:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728513</loc>
  <lastmod>2026-08-29T09:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルウェアの難読化による攻撃的事例生成と評価（Generation &amp;amp; Evaluation of Adversarial Examples for Malware Obfuscation）</news:title>
   <news:publication_date>2026-08-29T09:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728511</loc>
  <lastmod>2026-08-29T09:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在変数動的モデルによる生産スケジューリングとプロセス制御の統合（Integrating Production Scheduling and Process Control using Latent Variable Dynamic Models）</news:title>
   <news:publication_date>2026-08-29T09:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728509</loc>
  <lastmod>2026-08-29T08:51:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CMIR-NET：リモートセンシングにおけるクロスモーダル検索の実装と評価（CMIR-NET: A Deep Learning Based Model For Cross-Modal Retrieval In Remote Sensing）</news:title>
   <news:publication_date>2026-08-29T08:51:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728507</loc>
  <lastmod>2026-08-29T08:51:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ReLUネットワークによるLp近似の拡張（Approximation in Lp(µ) with deep ReLU neural networks）</news:title>
   <news:publication_date>2026-08-29T08:51:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728505</loc>
  <lastmod>2026-08-29T08:50:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Quizbowlに学ぶ増分型質問応答の意義（Quizbowl: The Case for Incremental Question Answering）</news:title>
   <news:publication_date>2026-08-29T08:50:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728503</loc>
  <lastmod>2026-08-29T08:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数主体を同時に見る予測の革新（Multi-Agent Tensor Fusion for Contextual Trajectory Prediction）</news:title>
   <news:publication_date>2026-08-29T08:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728501</loc>
  <lastmod>2026-08-29T08:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移クエーサーのコロナ温度測定（NuSTAR Measurement of Coronal Temperature in Two Luminous, High Redshift QSOs）</news:title>
   <news:publication_date>2026-08-29T08:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728499</loc>
  <lastmod>2026-08-29T08:50:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データの低ランク行列分解による分析（Time-Series Analysis via Low-Rank Matrix Factorization Applied to Infant-Sleep Data）</news:title>
   <news:publication_date>2026-08-29T08:50:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728497</loc>
  <lastmod>2026-08-29T08:49:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANベースのエンドツーエンド音声合成訓練アルゴリズム (A New GAN-based End-to-End TTS Training Algorithm)</news:title>
   <news:publication_date>2026-08-29T08:49:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728495</loc>
  <lastmod>2026-08-29T07:57:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚属性の非干渉かつ一般化可能な潜在表現の敵対的学習（Adversarial Learning of Disentangled and Generalizable Representations of Visual Attributes）</news:title>
   <news:publication_date>2026-08-29T07:57:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728493</loc>
  <lastmod>2026-08-29T07:57:17Z</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>2026-08-29T07:57:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728491</loc>
  <lastmod>2026-08-29T07:57:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子回路を用いた畳み込みの試み — Quanvolutional Neural Networks（Quanvolutional Neural Networks: Powering Image Recognition with Quantum Circuits）</news:title>
   <news:publication_date>2026-08-29T07:57:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-29T07:56:48Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮説集合の安定性と一般化（Hypothesis Set Stability and Generalization）</news:title>
   <news:publication_date>2026-08-29T07:56:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-29T07:56:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的ドメインランダマイゼーション（Active Domain Randomization）</news:title>
   <news:publication_date>2026-08-29T07:56:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728485</loc>
  <lastmod>2026-08-29T07:56:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による高速核磁気共鳴分光の加速（Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning）</news:title>
   <news:publication_date>2026-08-29T07:56:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728483</loc>
  <lastmod>2026-08-29T07:56:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文解析木から得た特徴量を活用したエンドツーエンドTTSの改善（Exploiting Syntactic Features in a Parsed Tree to Improve End-to-End TTS）</news:title>
   <news:publication_date>2026-08-29T07:56:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-29T07:04:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド進化システムによる自動ニューラルネットワーク生成と簡素化（A hybrid Evolutionary System for automated Artificial Neural Networks generation and simplification in biomedical applications）</news:title>
   <news:publication_date>2026-08-29T07:04:51Z</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>ユーザー制御可能なマルチテクスチャ合成（User-Controllable Multi-Texture Synthesis with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-29T07:04:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728477</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>2026-08-29T07:04:18Z</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>説明手法のソフトウェアと応用パターン（Software and application patterns for explanation methods）</news:title>
   <news:publication_date>2026-08-29T07:03:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728473</loc>
  <lastmod>2026-08-29T07:03:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seq2Biseq：出力側で双方向に判断する再帰型ニューラルネットワーク（Seq2Biseq : Bidirectional Output-wise Recurrent Neural Networks for Sequence Modelling）</news:title>
   <news:publication_date>2026-08-29T07:03:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-29T07:03:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスクとドメインをまたぐ学習（Learning Across Tasks and Domains）</news:title>
   <news:publication_date>2026-08-29T07:03:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728469</loc>
  <lastmod>2026-08-29T07:03:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイリンガルGANによる並列テキスト生成への一歩（Bilingual-GAN: A Step Towards Parallel Text Generation）</news:title>
   <news:publication_date>2026-08-29T07:03:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728467</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>Gittins指標とベイズ式上側信頼境界の等価性（A Note on the Equivalence of Upper Confidence Bounds and Gittins Indices for Patient Agents）</news:title>
   <news:publication_date>2026-08-29T06:12:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728465</loc>
  <lastmod>2026-08-29T06:11:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層半教師あり学習のラベル伝播（Label Propagation for Deep Semi-supervised Learning）</news:title>
   <news:publication_date>2026-08-29T06:11:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728463</loc>
  <lastmod>2026-08-29T06:10:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習によるロバストな量子最適化（Deep reinforcement learning for robust quantum optimization）</news:title>
   <news:publication_date>2026-08-29T06:10:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728461</loc>
  <lastmod>2026-08-29T06:10:42Z</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>2026-08-29T06:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728459</loc>
  <lastmod>2026-08-29T06:10:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数対象を扱うエンボディード質問応答の拡張（Multi-Target Embodied Question Answering）</news:title>
   <news:publication_date>2026-08-29T06:10:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728457</loc>
  <lastmod>2026-08-29T06:09:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド学習による超音波画像再構成（End-to-End Learning-Based Ultrasound Reconstruction）</news:title>
   <news:publication_date>2026-08-29T06:09:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728455</loc>
  <lastmod>2026-08-29T06:09:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実用的なオープンループ楽観的プランニング（Practical Open-Loop Optimistic Planning）</news:title>
   <news:publication_date>2026-08-29T06:09:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728453</loc>
  <lastmod>2026-08-29T05:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層レーベンバーグ＝マルカート法で学習したニューラルネットによる偏微分方程式解の近似（On the approximation of the solution of partial differential equations by artificial neural networks trained by a multilevel Levenberg-Marquardt method）</news:title>
   <news:publication_date>2026-08-29T05:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-29T05:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Block Neural Autoregressive Flow（Block Neural Autoregressive Flow）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728449</loc>
  <lastmod>2026-08-29T05:18:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン対称ネットワークによる敵対的ドメイン適応（Domain-Symmetric Networks for Adversarial Domain Adaptation）</news:title>
   <news:publication_date>2026-08-29T05:18:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728447</loc>
  <lastmod>2026-08-29T05:17:25Z</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>2026-08-29T05:17:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728445</loc>
  <lastmod>2026-08-29T05:17:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的回帰子選択の適合度評価（Evaluating Competence Measures for Dynamic Regressor Selection）</news:title>
   <news:publication_date>2026-08-29T05:17:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728443</loc>
  <lastmod>2026-08-29T05:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械視覚に導かれた3D医療画像圧縮の意義（Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurate Segmentation in the Clouds）</news:title>
   <news:publication_date>2026-08-29T05:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728441</loc>
  <lastmod>2026-08-29T05:16:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CycleGAN-VC2による非並列音声変換の改善（Improved CycleGAN-based Non-Parallel Voice Conversion）</news:title>
   <news:publication_date>2026-08-29T05:16:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728439</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>2026-08-29T04:24:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728437</loc>
  <lastmod>2026-08-29T04:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNNの意味的ロバストネス解析へ（Towards Analyzing Semantic Robustness of Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-29T04:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728435</loc>
  <lastmod>2026-08-29T04:23:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像と言語の埋め込み検索における不確実性の定量化（Exploring Uncertainty Measures for Image-Caption Embedding-and-Retrieval Task）</news:title>
   <news:publication_date>2026-08-29T04:23:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728433</loc>
  <lastmod>2026-08-29T04:23:18Z</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>2026-08-29T04:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728431</loc>
  <lastmod>2026-08-29T04:23:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定化する経済型MPCの実用的強化学習（Practical Reinforcement Learning of Stabilizing Economic MPC）</news:title>
   <news:publication_date>2026-08-29T04:23:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728429</loc>
  <lastmod>2026-08-29T04:22:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実画像の雨を合成して除去する二段階データ蒸留法（Rain O&amp;#039;er Me: Synthesizing real rain to derain with data distillation）</news:title>
   <news:publication_date>2026-08-29T04:22:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728427</loc>
  <lastmod>2026-08-29T04:22:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-29T04:22:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728425</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>2026-08-29T03:31:49Z</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:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-29T03:30:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <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:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <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:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <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>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news: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>
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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:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を使った能動学習によるイベント認識の継続学習フレームワーク（Context-Aware Query Selection for Active Learning in Event Recognition）</news:title>
   <news:publication_date>2026-08-28T21:53:47Z</news:publication_date>
   <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:title>低x領域における縦構造関数FLの抽出手法（Extracting the longitudinal structure function FL(x, Q2) at small x from a Froissart-bounded parametrization of F2(x, Q2))</news:title>
   <news:publication_date>2026-08-28T21:53:37Z</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>
   </news:publication>
   <news:title>集合、数、その他数学的対象の構成要素（The Constituents of Sets, Numbers, and Other Mathematical Objects）</news:title>
   <news:publication_date>2026-08-28T21:52:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-28T21:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-28T20:59:23Z</news:publication_date>
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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>
 <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>
   </news:publication>
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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>
   </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>
  <loc>https://aibr.jp/archives/728299</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショット学習のための埋め込み集約とメタレベルドロップアウト（L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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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>
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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>
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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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 </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>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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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>
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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>
    <news:language>ja</news:language>
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 <url>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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  <news: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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 </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>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </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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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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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:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>変化する密度を捉える頑健なクラスタリング手法（CRAD: Clustering with Robust Autocuts and Depth）</news:title>
   <news:publication_date>2026-08-28T12:45:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/728199</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>Jensen-Shannon発散の一般化（On a generalization of the Jensen-Shannon divergence and the JS-symmetrization of distances relying on abstract means）</news:title>
   <news:publication_date>2026-08-28T12:44:57Z</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>
   <news:title>集合知の浸透現象としての相互知識の出現（Coupling agent based simulation with dynamic networks analysis to study the emergence of mutual knowledge as a percolation phenomenon）</news:title>
   <news:publication_date>2026-08-28T12:44:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル空間特徴の同時選択と抽出（Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images）</news:title>
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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>
   </news:publication>
   <news:title>人間行動を組み込む大気汚染シミュレーション（A Multi-Agent based Approach for Simulating the Impact of Human Behaviours on Air Pollution）</news:title>
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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>
   </news:publication>
   <news:title>メルスペクトログラムからの音声合成を高速化するGAN励起線形予測（GELP: GAN-Excited Linear Prediction for Speech Synthesis from Mel-spectrogram）</news:title>
   <news:publication_date>2026-08-28T12:43:23Z</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>採卵生産曲線における早期警報の実装（Early warning in egg production curves from commercial hens: A SVM approach）</news:title>
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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>
   </news:publication>
   <news:title>AdaBoostを特徴学習の観点で見る意義とAdaBoost+SVMの実装可能性（Feature Learning Viewpoint of AdaBoost and a New Algorithm）</news:title>
   <news:publication_date>2026-08-28T11:51:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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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>2026-08-28T11:42:56Z</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>
   <news:title>多様性と品質を同時に評価する指標の提案（Jointly Measuring Diversity and Quality in Text Generation Models）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-28T11:42:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-28T11:42:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像分類の頑健性を高めるフィルタ選択型ファインチューニング（Improving Image Classification Robustness through Selective CNN-Filters Fine-Tuning）</news:title>
   <news:publication_date>2026-08-28T11:41:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SIPAによるモデル非依存型解釈の統一的フレームワーク（Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations）</news:title>
   <news:publication_date>2026-08-28T11:41:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数出力予測のためのターゲット逐次ブースティング（Component-Wise Boosting of Targets for Multi-Output Prediction）</news:title>
   <news:publication_date>2026-08-28T10:50:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルノイズに強い学習のためのワッサースタイン敵対的正則化（Wasserstein Adversarial Regularization for learning with label noise）</news:title>
   <news:publication_date>2026-08-28T10:50:04Z</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>
   <news:title>銀河の局所的な星形成率と金属量の関係の実証（Characterizing the local SFR − Zg relation in MaNGA spiral galaxies）</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>オンライン変分推論の一般化境界（A Generalization Bound for Online Variational Inference）</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>文書横断の言語不変表現：縮小ランクリッジ回帰による埋め込み（Crosslingual Document Embedding as Reduced-Rank Ridge Regression）</news:title>
   <news:publication_date>2026-08-28T10:49:04Z</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>
   <news:title>密度認識埋め込みの学習（On Learning Density Aware Embeddings）</news:title>
   <news:publication_date>2026-08-28T10:48:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー・ベクトル値マニフォールド正則化によるマルチラベル画像分類（Multi-view Vector-valued Manifold Regularization for Multi-label Image Classification）</news:title>
   <news:publication_date>2026-08-28T10:48:22Z</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>Dual Question-Answer Extractionを用いた半教師あり少数ショット学習の実務的意義（Semi-Supervised Few-Shot Learning for Dual Question-Answer Extraction）</news:title>
   <news:publication_date>2026-08-28T09:56:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化された能動学習と統計実験設計（Generalized active learning and design of statistical experiments for manifold-valued data）</news:title>
   <news:publication_date>2026-08-28T09:47:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習に基づくCT再構成の現状と課題（Deep Learning Based Computed Tomography: Whys and Wherefores）</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>マルチビュー行列補完による多ラベル画像分類（Multi-View Matrix Completion for Multi-Label Image Classification）</news:title>
   <news:publication_date>2026-08-28T09:47:33Z</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>
   </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>パッチから画像分割へ ― 完全畳み込みネットワークの網羅的応用（From Patch to Image Segmentation using Fully Convolutional Networks - Application to Retinal Images）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D屋内ナビゲーションのためのシム・リアル共同強化学習転移（Sim-Real Joint Reinforcement Transfer for 3D Indoor 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>
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   <news:publication_date>2026-08-28T08:53:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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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>2026-08-28T08:53:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </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>
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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>
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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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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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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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 <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:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news: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>
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 </url>
 <url>
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 </url>
 <url>
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 </url>
 <url>
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  <news:news>
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    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
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 </url>
 <url>
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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>
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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: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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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-28T03:32:48Z</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>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-28T03:32:07Z</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>2026-08-28T03:31:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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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>2026-08-28T03:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトルX線投影画像における教師なし材料セグメンテーションの実証（Unsupervised Learning Methods in X-ray Spectral Imaging Material Segmentation）</news:title>
   <news:publication_date>2026-08-28T02:40:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>患者別シリコーン製僧帽弁モデルによる外科トレーニングの革新（Flexible and Comprehensive Patient-Specific Mitral Valve Silicone Models with Chordae Tendinae Made From 3D-Printable Molds）</news:title>
   <news:publication_date>2026-08-28T02:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-28T02:40:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neoに学ぶ学習型クエリ最適化（Neo: A Learned Query Optimizer）</news:title>
   <news:publication_date>2026-08-28T02:40:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-28T02:39:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728039</loc>
  <lastmod>2026-08-28T02:39:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アペックス・タイムネットワークによるクロスデータセット微表情認識（A Novel Apex-Time Network for Cross-Dataset Micro-Expression Recognition）</news:title>
   <news:publication_date>2026-08-28T02:39:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸機械学習における局所最小値は全局最小値である（Every Local Minimum Value Is the Global Minimum Value of Induced Model in Nonconvex Machine Learning）</news:title>
   <news:publication_date>2026-08-28T02:38:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所化された関連ベクトル機械によるパターン分類（Proposing a Localized Relevance Vector Machine for Pattern Classification）</news:title>
   <news:publication_date>2026-08-28T02:38:44Z</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>高加速度の弾道運動を筋肉駆動ロボットで学習制御する（Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots）</news:title>
   <news:publication_date>2026-08-28T01:46:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声モデル事前学習によるエンドツーエンド音声理解の改善（Speech Model Pre-training for End-to-End Spoken Language Understanding）</news:title>
   <news:publication_date>2026-08-28T01:46:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728029</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>大規模アンテナアレイのためのビームフォーミング設計を深層学習で（Beamforming Design for Large-Scale Antenna Arrays Using Deep Learning）</news:title>
   <news:publication_date>2026-08-28T01:46:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/728027</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>ベイズ推定による混合多項ロジットモデルの実務的意義（Bayesian Estimation of Mixed Multinomial Logit Models: Advances and Simulation-Based Evaluations）</news:title>
   <news:publication_date>2026-08-28T01:46:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/728025</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>抵抗性RAMベースの2値ニューラルネットワークの卓越したビット誤り耐性（Outstanding Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks）</news:title>
   <news:publication_date>2026-08-28T01:45:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728023</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>探索木を使わないオンライン計画とExpert Iterationの革新（Policy Gradient Search: Online Planning and Expert Iteration without Search Trees）</news:title>
   <news:publication_date>2026-08-28T01:45:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728021</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>系列→要約→復元の自己符号化で学ぶ教師なし文圧縮（Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression）</news:title>
   <news:publication_date>2026-08-28T01:45:29Z</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>
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   <news:title>小児MRIのリアルタイム画質評価（Real-Time Quality Assessment of Pediatric MRI via Semi-Supervised Deep Nonlocal Residual Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728017</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要人物検出のための関係学習（Learning to Learn Relation for Important People Detection in Still Images）</news:title>
   <news:publication_date>2026-08-28T00:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/728013</loc>
  <lastmod>2026-08-28T00:51:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル形式スケッチを学習するGANの手法（Teaching GANS to Sketch in Vector Format）</news:title>
   <news:publication_date>2026-08-28T00:51:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/728011</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>教師から学ぶ距離学習：小型ネットワークで高品質な画像埋め込みを得る方法（Learning Metrics from Teachers: Compact Networks for Image Embedding）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VAEを用いた深層話者埋め込みの正則化（VAE-based regularization for deep speaker embedding）</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:title>カリキュラム学習が深層ネットワークの訓練にもたらす力（On The Power of Curriculum Learning in Training Deep Networks）</news:title>
   <news:publication_date>2026-08-28T00:51:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>頭蓋内脳波と自動特徴学習によるてんかん発作予測（Human Intracranial EEG Quantitative Analysis and Automatic Feature Learning for Epileptic Seizure Prediction）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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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: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>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news: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: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>
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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: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: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>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </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>
   </news:publication>
   <news:title>コスト認識型チャンネル選択による逐次ネットワーク剪定（C2S2: Cost-aware Channel Sparse Selection for Progressive Network Pruning）</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>
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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>2026-08-27T19:21:42Z</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>2026-08-27T19:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-27T19:21:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-27T19:21:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>クロスタスク学習による音響タギング・音イベント検出・空間局在化の共通基盤（CROSS-TASK LEARNING FOR AUDIO TAGGING, SOUND EVENT DETECTION AND SPATIAL LOCALIZATION: DCASE 2019 BASELINE SYSTEMS）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/727927</loc>
  <lastmod>2026-08-27T19:20:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>サリエンシーで補完する少数ショット学習（Few-shot Learning via Saliency-guided Hallucination of Samples）</news:title>
   <news:publication_date>2026-08-27T19:20:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-27T19:20:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>フォトリアリスティック環境における点群認識を用いたエンボディド質問応答（Embodied Question Answering in Photorealistic Environments with Point Cloud Perception）</news:title>
   <news:publication_date>2026-08-27T19:20:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-27T19:19:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>深層スタック型階層多重パッチネットワークによる画像ブレ補正（Deep Stacked Hierarchical Multi-patch Network for Image Deblurring）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/727915</loc>
  <lastmod>2026-08-27T18:26:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種行動空間における強化付き模倣（Reinforced Imitation in Heterogeneous Action Space）</news:title>
   <news:publication_date>2026-08-27T18:26:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/727913</loc>
  <lastmod>2026-08-27T18:26:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Iterative Normalizationによる効率的なホワイトニングの実現（Iterative Normalization: Beyond Standardization towards Efficient Whitening）</news:title>
   <news:publication_date>2026-08-27T18:26:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/727911</loc>
  <lastmod>2026-08-27T18:26:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バスの所要時間予測（Bus Travel Time Prediction: A log-normal Auto-Regressive (AR) Modeling Approach）</news:title>
   <news:publication_date>2026-08-27T18:26:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/727909</loc>
  <lastmod>2026-08-27T18:25:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルの潜在空間における特徴ベース補間と測地線（Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models）</news:title>
   <news:publication_date>2026-08-27T18:25:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/727907</loc>
  <lastmod>2026-08-27T17:34:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラを意識した教師なしドメイン適応による人物再識別（A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identiﬁcation）</news:title>
   <news:publication_date>2026-08-27T17:34:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/727905</loc>
  <lastmod>2026-08-27T17:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リングメッシュ：多数コアアクセラレータ向けのスケーラブルで高性能な接続方式 (Ring-Mesh: A Scalable and High-Performance Approach for Manycore Accelerators)</news:title>
   <news:publication_date>2026-08-27T17:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/727903</loc>
  <lastmod>2026-08-27T17:33:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ拡張不変性と広がりを利用した教師なし埋め込み学習（Unsupervised Embedding Learning via Invariant and Spreading Instance Feature）</news:title>
   <news:publication_date>2026-08-27T17:33:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727901</loc>
  <lastmod>2026-08-27T17:32:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ネットワーク埋め込みの増分学習フレームワーク（FILDNE: A Framework for Incremental Learning of Dynamic Networks Embeddings）</news:title>
   <news:publication_date>2026-08-27T17:32:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727899</loc>
  <lastmod>2026-08-27T17:32:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化された音声強調を目指すGAN（Towards Generalized Speech Enhancement with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-27T17:32:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727897</loc>
  <lastmod>2026-08-27T17:32:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の自己教師ありタスクから学ぶ問題非依存な音声表現（Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks）</news:title>
   <news:publication_date>2026-08-27T17:32:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727895</loc>
  <lastmod>2026-08-27T17:32:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈認識型の人間運動予測（Context-aware Human Motion Prediction）</news:title>
   <news:publication_date>2026-08-27T17:32:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727893</loc>
  <lastmod>2026-08-27T16:40:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的RGB-D融合による深層表面法線推定（Deep Surface Normal Estimation with Hierarchical RGB-D Fusion）</news:title>
   <news:publication_date>2026-08-27T16:40:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727891</loc>
  <lastmod>2026-08-27T16:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バックトラックレス整列空間グラフ畳み込みネットワークの図解（Learning Backtrackless Aligned-Spatial Graph Convolutional Networks for Graph Classification）</news:title>
   <news:publication_date>2026-08-27T16:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727889</loc>
  <lastmod>2026-08-27T16:40:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みニューラルネットワークのための効率的かつ有効なドロップアウト（Efficient and Effective Dropout for Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-27T16:40:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727887</loc>
  <lastmod>2026-08-27T16:39:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼深度推定のCNN可視化（Visualization of Convolutional Neural Networks for Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-08-27T16:39:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727885</loc>
  <lastmod>2026-08-27T16:39:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再識別を用いたテクスチャ生成（Re-Identification Supervised Texture Generation）</news:title>
   <news:publication_date>2026-08-27T16:39:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727883</loc>
  <lastmod>2026-08-27T16:39:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゾーニング特徴を用いたパシュトー手書き文字の認識（KNN and ANN-based Recognition of Handwritten Pashto Letters using Zoning Features）</news:title>
   <news:publication_date>2026-08-27T16:39:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727881</loc>
  <lastmod>2026-08-27T16:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在次元とコミュニティ数のベイジアン推定（Bayesian estimation of the latent dimension and communities in stochastic blockmodels）</news:title>
   <news:publication_date>2026-08-27T16:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727879</loc>
  <lastmod>2026-08-27T15:47:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復カーネル補正によるブラインド超解像（Blind Super-Resolution With Iterative Kernel Correction）</news:title>
   <news:publication_date>2026-08-27T15:47:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727877</loc>
  <lastmod>2026-08-27T15:47:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラレンズ超解像（Camera Lens Super-Resolution）</news:title>
   <news:publication_date>2026-08-27T15:47:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727875</loc>
  <lastmod>2026-08-27T15:47:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味解析を用いた教師なし人物画像生成（Unsupervised Person Image Generation with Semantic Parsing Transformation）</news:title>
   <news:publication_date>2026-08-27T15:47:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727873</loc>
  <lastmod>2026-08-27T15:46:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所一貫性を目指した物体計数の制約付き多段畳み込みニューラルネットワーク（Towards Locally Consistent Object Counting with Constrained Multi-stage Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-27T15:46:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727871</loc>
  <lastmod>2026-08-27T15:46:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話システムの一貫性評価における含意手法（Evaluating Coherence in Dialogue Systems using Entailment）</news:title>
   <news:publication_date>2026-08-27T15:46:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727869</loc>
  <lastmod>2026-08-27T15:45:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己注意とガンベル部分集合サンプリングによる点群処理の革新（Modeling Point Clouds with Self-Attention and Gumbel Subset Sampling）</news:title>
   <news:publication_date>2026-08-27T15:45:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727867</loc>
  <lastmod>2026-08-27T15:45:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能する注意機構を持つ強化学習（Reinforcement Learning with Attention that Works: A Self-Supervised Approach）</news:title>
   <news:publication_date>2026-08-27T15:45:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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