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   <news:title>テキストのベクトル表現とニューラル表現の概説（Vector Representations of Text Data and Neural Representations）</news:title>
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   <news:title>機械学習で大衆を誤導する十の方法（Ten ways to fool the masses with machine learning）</news:title>
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   <news:title>ネットワークにおける半教師あり学習：不均衡・異種性への対処法（SEMI-SUPERVISED LEARNING IN UNBALANCED AND HETEROGENEOUS NETWORKS）</news:title>
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    <news:language>ja</news:language>
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   <news:title>原子層精度での黒リン（Few-layer Black Phosphorus）ウェットエッチング法（A wet etching method for few-layer black phosphorus with an atomic accuracy and compatibility with major lithography techniques）</news:title>
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   <news:title>敵対的攻撃に対する画像超解像を用いた防御（Image Super-Resolution as a Defense Against Adversarial Attacks）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>初期化からの距離が語る深層ネットワークの汎化（Generalization in Deep Networks: The Role of Distance from Initialization）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>より深く、より広いシアムネットワークによるリアルタイム視覚追跡（Deeper and Wider Siamese Networks for Real-Time Visual Tracking）</news:title>
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   <news:title>周辺密度と因子グラフの双対性（Marginal Densities, Factor Graph Duality, and High-Temperature Series Expansions）</news:title>
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   <news:title>散逸量子システムによる非線形入出力写像の学習（Learning Nonlinear Input-Output Maps with Dissipative Quantum Systems）</news:title>
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   <news:title>ランダム化テンソルリング分解と大規模データ再構成（RANDOMIZED TENSOR RING DECOMPOSITION AND ITS APPLICATION TO LARGE-SCALE DATA RECONSTRUCTION）</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>差分が導く未来予測の精度向上（Better Guider Predicts Future Better: Difference Guided Generative Adversarial Networks）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>サイクルGANによるブラインド動きブレ除去（Blind Motion Deblurring with Cycle Generative Adversarial Networks）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>シリコンの高精度・移植性を備えた機械学習原子間ポテンシャル（An Accurate and Transferable Machine-Learning Interatomic Potential for Silicon）</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>圧縮センシングを機械学習で解く構造健全性モニタリング（COMPRESSIVE-SENSING DATA RECONSTRUCTION FOR STRUCTURAL HEALTH MONITORING: A MACHINE-LEARNING APPROACH）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>反復制御ネットワークによる中央パターン生成（Recurrent Control Nets as Central Pattern Generators for Deep Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-24T05:20:07Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>非凸行列回復におけるスパリュアス局所最小解の不存在に関するシャープRIP境界（Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery）</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>ロバストなブラインドデコンボリューションの複合最適化（Composite optimization for robust blind deconvolution）</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>ネットワーク損失を利用した分散近似計算 NetApprox（Exploiting Network Loss for Distributed Approximate Computing with NetApprox）</news:title>
   <news:publication_date>2026-07-24T05:19:07Z</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:title>健康なデータから病的データへの学習転移性が示すもの（Healthy versus pathological learning transferability in shoulder muscle MRI segmentation using deep convolutional encoder-decoders）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>低コスト顕微鏡のためのシンプルな4fコールベール透過照明システム（Simple and open 4f Koehler transmitted illumination system for low-cost microscopic imaging and teaching）</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>線形計画双対による大規模マルコフ決定問題（Large-Scale Markov Decision Problems via the Linear Programming Dual）</news:title>
   <news:publication_date>2026-07-24T04:27:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-24T04:26:48Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>パラメータ数と汎化のスケーリング記述（Scaling description of generalization with number of parameters in deep learning）</news:title>
   <news:publication_date>2026-07-24T04:26:48Z</news:publication_date>
   <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>銀河内コア崩壊型超新星探索のLSSTターゲット提案（LSST Target of Opportunity proposal for locating a core collapse supernova in our galaxy triggered by a neutrino supernova alert）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-24T04:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>多尺度多孔質媒体の因果関係とベイズネットワークPDE（CAUSALITY AND BAYESIAN NETWORK PDES FOR MULTISCALE REPRESENTATIONS OF POROUS MEDIA）</news:title>
   <news:publication_date>2026-07-24T04:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-24T04:26:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己構成型人工知能の基礎（Towards Self-constructive Artificial Intelligence: Algorithmic basis (Part I))</news:title>
   <news:publication_date>2026-07-24T04:26:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/715279</loc>
  <lastmod>2026-07-24T03:35:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語逐語翻訳の無教師改善（Improving Unsupervised Word-by-Word Translation with Language Model and Denoising Autoencoder）</news:title>
   <news:publication_date>2026-07-24T03:35:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/715277</loc>
  <lastmod>2026-07-24T03:34:48Z</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固有表現抽出をブートストラップする転移学習（Named Entity Recognition in Electronic Health Records Using Transfer Learning Bootstrapped Neural Networks）</news:title>
   <news:publication_date>2026-07-24T03:34:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/715275</loc>
  <lastmod>2026-07-24T03:34:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイバー攻撃理論への展望（Toward a Theory of Cyber Attacks）</news:title>
   <news:publication_date>2026-07-24T03:34:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715273</loc>
  <lastmod>2026-07-24T03:33:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大語彙辞書を用いた教師なし翻訳の拡張（Unsupervised Training for Large Vocabulary Translation）</news:title>
   <news:publication_date>2026-07-24T03:33:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-07-24T03:33:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中等学校におけるICT活用と管理の促進（PROMOTING EFFECTIVE APPLICATION AND MANAGEMENT OF ICT TO ENHANCE PERFORMANCE IN SECONDARY SCHOOLS）</news:title>
   <news:publication_date>2026-07-24T03:33:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-07-24T03:33:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>L1正則化SVMと大規模線形計画の再考（Solving L1-regularized SVMs and related linear programs: Revisiting the effectiveness of Column and Constraint Generation）</news:title>
   <news:publication_date>2026-07-24T03:33:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-07-24T03:33:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PyOD: スケーラブルな異常検知のためのPythonツールボックス（PyOD: A Python Toolbox for Scalable Outlier Detection）</news:title>
   <news:publication_date>2026-07-24T03:33:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715265</loc>
  <lastmod>2026-07-24T02:42:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚構造制約を用いた推論型ゼロショット学習（Transductive Zero-Shot Learning with Visual Structure Constraint）</news:title>
   <news:publication_date>2026-07-24T02:42:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715263</loc>
  <lastmod>2026-07-24T02:41:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習不要のボリューム的虹彩セグメンテーションの再考（Learning-Free Iris Segmentation Revisited: A First Step Toward Fast Volumetric Operation Over Video Samples）</news:title>
   <news:publication_date>2026-07-24T02:41:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715261</loc>
  <lastmod>2026-07-24T02:41:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セグメンテーション誘導型画像翻訳（Segmentation Guided Image-to-Image Translation with Adversarial Networks）</news:title>
   <news:publication_date>2026-07-24T02:41:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715259</loc>
  <lastmod>2026-07-24T02:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>慢性足関節不安定性の運動ダイナミクスを識別する自己表現サブスペースクラスタリング（Self-Expressive Subspace Clustering to Recognize Motion Dynamics for Chronic Ankle Instability）</news:title>
   <news:publication_date>2026-07-24T02:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715257</loc>
  <lastmod>2026-07-24T02:40:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部CTにおける血管セグメンテーションの自動多スケール3D特徴学習（Automated Multiscale 3D Feature Learning for Vessels Segmentation in Thorax CT Images）</news:title>
   <news:publication_date>2026-07-24T02:40:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715255</loc>
  <lastmod>2026-07-24T02:40:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像サリエンシーにおける教師なし不確かさ推定（Unsupervised Uncertainty Estimation Using Spatiotemporal Cues in Video Saliency Detection）</news:title>
   <news:publication_date>2026-07-24T02:40:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715253</loc>
  <lastmod>2026-07-24T02:39:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形混合の学習：同定性とアルゴリズム（Learning Nonlinear Mixtures: Identifiability and Algorithm）</news:title>
   <news:publication_date>2026-07-24T02:39:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715251</loc>
  <lastmod>2026-07-24T01:48:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多発スパイクに基づくオンライン教師あり学習アルゴリズム（An online supervised learning algorithm based on triple spikes for spiking neural networks）</news:title>
   <news:publication_date>2026-07-24T01:48:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715249</loc>
  <lastmod>2026-07-24T01:48:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ネットワークの幾何化による解釈性（Geometrization of deep networks for the interpretability of deep learning systems）</news:title>
   <news:publication_date>2026-07-24T01:48:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715247</loc>
  <lastmod>2026-07-24T01:48:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リングAllReduceにおける重要度重み付きプルーニングによる帯域削減（Bandwidth Reduction using Importance Weighted Pruning on Ring AllReduce）</news:title>
   <news:publication_date>2026-07-24T01:48:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715245</loc>
  <lastmod>2026-07-24T01:47:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェアの実行痕跡でマルウェアを見つける（Malware Detection Using Dynamic Birthmarks）</news:title>
   <news:publication_date>2026-07-24T01:47:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715243</loc>
  <lastmod>2026-07-24T01:47:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトラム多様性を用いた統一ニューラル表現によるニューラル進化（Spectrum-Diverse Neuroevolution with Unified Neural Models）</news:title>
   <news:publication_date>2026-07-24T01:47:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715241</loc>
  <lastmod>2026-07-24T01:47:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界自動運転システムにおける深層強化学習の応用探索 (Exploring applications of deep reinforcement learning for real-world autonomous driving systems)</news:title>
   <news:publication_date>2026-07-24T01:47:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715239</loc>
  <lastmod>2026-07-24T01:46:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RayPotentialsによる体積3D再構成の学習（RayNet: Learning Volumetric 3D Reconstruction with Ray Potentials）</news:title>
   <news:publication_date>2026-07-24T01:46:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715236</loc>
  <lastmod>2026-07-24T00:55:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢かつ高性能な顔検出器の再構築（Robust and High Performance Face Detector）</news:title>
   <news:publication_date>2026-07-24T00:55:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715234</loc>
  <lastmod>2026-07-24T00:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分制御ネットワークにおける最適ネットワーク制御（Optimal Network Control in Partially-Controllable Networks）</news:title>
   <news:publication_date>2026-07-24T00:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715232</loc>
  <lastmod>2026-07-24T00:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表層の流れ推定を数千時間から数秒へ──監督学習を用いたリングダイアグラム反演の高速化（Supervised Neural Networks for Helioseismic Ring-Diagram Inversions）</news:title>
   <news:publication_date>2026-07-24T00:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715230</loc>
  <lastmod>2026-07-24T00:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNに基づく音響シーン分類における音のテクスチャ強調（ENHANCING SOUND TEXTURE IN CNN-BASED ACOUSTIC SCENE CLASSIFICATION）</news:title>
   <news:publication_date>2026-07-24T00:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715228</loc>
  <lastmod>2026-07-24T00:54:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で高速化する連続時間量子モンテカルロ法（Accelerated Continuous time quantum Monte Carlo method with Machine Learning）</news:title>
   <news:publication_date>2026-07-24T00:54:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715226</loc>
  <lastmod>2026-07-24T00:53:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然画像分布の(非)解釈可能性を生成モデルで理解する（Understanding the (un)interpretability of natural image distributions using generative models）</news:title>
   <news:publication_date>2026-07-24T00:53:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715224</loc>
  <lastmod>2026-07-24T00:53:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直接フィードバック整合による効率的な畳み込みニューラルネットワーク訓練（EFFICIENT CONVOLUTIONAL NEURAL NETWORK TRAINING WITH DIRECT FEEDBACK ALIGNMENT）</news:title>
   <news:publication_date>2026-07-24T00:53:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715222</loc>
  <lastmod>2026-07-24T00:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互事後ダイバージェンス正則化によるVAE改善（MAE: Mutual Posterior-Divergence Regularization for Variational Autoencoders）</news:title>
   <news:publication_date>2026-07-24T00:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715220</loc>
  <lastmod>2026-07-24T00:01:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>資産クラス故障予測における教師なし学習と教師あり学習の組合せ（Combining Unsupervised and Supervised Learning for Asset Class Failure Prediction in Power Systems）</news:title>
   <news:publication_date>2026-07-24T00:01:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715218</loc>
  <lastmod>2026-07-24T00:01:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャンネル局所性ブロック：Squeeze-and-Excitationの変種 (Channel Locality Block: A Variant of Squeeze-and-Excitation)</news:title>
   <news:publication_date>2026-07-24T00:01:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715216</loc>
  <lastmod>2026-07-24T00:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランチョスネットが変えたグラフ畳み込みの常識（LANCZOSNET: MULTI-SCALE DEEP GRAPH CONVOLUTIONAL NETWORKS）</news:title>
   <news:publication_date>2026-07-24T00:00:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715214</loc>
  <lastmod>2026-07-24T00:00:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2D画像特徴に基づく双線形教師付き離散ハッシュ（Bilinear Supervised Hashing Based on 2D Image Features）</news:title>
   <news:publication_date>2026-07-24T00:00:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715212</loc>
  <lastmod>2026-07-24T00:00:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸クラスタリングの可視化と高速化を実現する手法（Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization）</news:title>
   <news:publication_date>2026-07-24T00:00:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715210</loc>
  <lastmod>2026-07-24T00:00:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚環境での計画と学習をつなぐ手法の実践的意義（What Should I Do Now? Marrying Reinforcement Learning and Symbolic Planning）</news:title>
   <news:publication_date>2026-07-24T00:00:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715208</loc>
  <lastmod>2026-07-23T23:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話に現れる対象と関係の取り扱い（Addressing Objects and Their Relations: The Conversational Entity Dialogue Model）</news:title>
   <news:publication_date>2026-07-23T23:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715206</loc>
  <lastmod>2026-07-23T23:08:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分目標と問題解決段階が織りなす複雑な相互作用（Subgoals, Problem Solving Phases, and Sources of Knowledge: A Complex Mangle）</news:title>
   <news:publication_date>2026-07-23T23:08:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715204</loc>
  <lastmod>2026-07-23T23:08:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブネット群と中央機構による再考：記憶と予測のためのニューラルネットワーク（Rethinking the Artificial Neural Networks: A Mesh of Subnets with a Central Mechanism for Storing and Predicting the Data）</news:title>
   <news:publication_date>2026-07-23T23:08:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715202</loc>
  <lastmod>2026-07-23T23:07:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNによるサイバーセキュリティ応用（RNNSecureNet: Recurrent neural networks for Cyber security use-cases）</news:title>
   <news:publication_date>2026-07-23T23:07:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715200</loc>
  <lastmod>2026-07-23T23:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海馬MRIと1年追跡認知測定を用いたアルツハイマー病早期予測（Early Prediction of Alzheimer’s Disease Dementia based on Baseline Hippocampal MRI and 1-Year Follow-Up Cognitive Measures using Deep Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-23T23:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715198</loc>
  <lastmod>2026-07-23T23:07:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床超音波画像における境界距離回帰ネットワークによる腎臓の完全自動セグメンテーション（FULLY-AUTOMATIC SEGMENTATION OF KIDNEYS IN CLINICAL ULTRASOUND IMAGES USING A BOUNDARY DISTANCE REGRESSION NETWORK）</news:title>
   <news:publication_date>2026-07-23T23:07:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715196</loc>
  <lastmod>2026-07-23T23:06:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像ベースの生存解析に深層畳み込みニューラルネットワークを適用する手法（DEEP CONVOLUTIONAL NEURAL NETWORKS FOR IMAGING DATA BASED SURVIVAL ANALYSIS OF RECTAL CANCER）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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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:publication_date>2026-07-23T22:04:42Z</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>
   </news:publication>
   <news:title>多アトラス誘導3D完全畳み込みネットワークアンサンブルによる脳領域分割（Brain segmentation based on multi-atlas guided 3D fully convolutional network ensembles）</news:title>
   <news:publication_date>2026-07-23T22:03:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-23T22:03:36Z</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>ショービジネスにおける成功の定量化と予測（Quantifying and predicting success in show business）</news:title>
   <news:publication_date>2026-07-23T22:03:28Z</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>NLPベースのフェイクニュース検出は事実改竄に弱い（Fake News Detection via NLP is Vulnerable to Adversarial Attacks）</news:title>
   <news:publication_date>2026-07-23T22:03:09Z</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>不均衡データ分類に対する深層強化学習の適用（Deep Reinforcement Learning for Imbalanced Classification）</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:publication_date>2026-07-23T21:11:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスタイルの並列データと教師−生徒学習による音声認識のノイズ耐性向上 (IMPROVING NOISE ROBUSTNESS OF AUTOMATIC SPEECH RECOGNITION VIA PARALLEL DATA AND TEACHER-STUDENT LEARNING)</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>
   </news:publication>
   <news:title>階層的強化学習のための利得重み付き情報最大化（Hierarchical Reinforcement Learning via Advantage-Weighted Information Maximization）</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>2026-07-23T20:18:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715164</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>再帰的推論機（Recurrent Inference Machines）による重力レンズ背景源再構築（Data-Driven Reconstruction of Gravitationally Lensed Galaxies Using Recurrent Inference Machines）</news:title>
   <news:publication_date>2026-07-23T20:17:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715162</loc>
  <lastmod>2026-07-23T20:17:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動重み付け型マルチビュー疎再構成埋め込み（Auto-weighted Multi-view Sparse Reconstructive Embedding）</news:title>
   <news:publication_date>2026-07-23T20:17:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715160</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>動的グラフに対するランダムウォークによる効率的表現学習（Efficient Representation Learning Using Random Walks for Dynamic Graphs）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715158</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>
  <loc>https://aibr.jp/archives/715156</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>信頼性と説明可能な機械学習による材料探索の加速（Reliable and Explainable Machine Learning Methods for Accelerated Material Discovery）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715154</loc>
  <lastmod>2026-07-23T20:15:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-23T20:15:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715152</loc>
  <lastmod>2026-07-23T19:24:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sheavesを用いたビッグデータへの位相的アプローチ（Sheaves: A Topological Approach to Big Data）</news:title>
   <news:publication_date>2026-07-23T19:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715150</loc>
  <lastmod>2026-07-23T19:24:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応重み付きDeep Forest分類器（An Adaptive Weighted Deep Forest Classifier）</news:title>
   <news:publication_date>2026-07-23T19:24:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715148</loc>
  <lastmod>2026-07-23T19:24:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715146</loc>
  <lastmod>2026-07-23T19:23:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-07-23T19:23:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715142</loc>
  <lastmod>2026-07-23T19:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドで科学計算を迅速に回す方法（The ISTI Rapid Response on Exploring Cloud Computing 2018）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715140</loc>
  <lastmod>2026-07-23T19:22:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PELICANによる光度曲線解析の新展開（PELICAN: deeP architecturE for the LIght Curve ANalysis）</news:title>
   <news:publication_date>2026-07-23T19:22:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715138</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>ヒト・ロボット相互作用におけるモデル学習の有用性（On the Utility of Model Learning in HRI）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/715136</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル特性による目標指向型強化学習の高速化（Accelerating Goal-Directed Reinforcement Learning by Model Characterization）</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>
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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>
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 </url>
 <url>
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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: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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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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   <news: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:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news: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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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </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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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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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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   <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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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </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>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <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>
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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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 <url>
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    <news:language>ja</news:language>
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   <news:title>確率的デジタルIDのオフポリシー評価（Off-Policy Evaluation of Probabilistic Identity Data in Lookalike Modeling）</news:title>
   <news:publication_date>2026-07-23T13:11:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715052</loc>
  <lastmod>2026-07-23T13:10:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波における端末アンテナ配置と手による遮蔽の性能トレードオフ（Antenna Placement and Performance Tradeoffs with Hand Blockage in Millimeter Wave Systems）</news:title>
   <news:publication_date>2026-07-23T13:10:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715050</loc>
  <lastmod>2026-07-23T13:10:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆行的訓練によるグラフ埋め込み学習（Learning Graph Embedding with Adversarial Training Methods）</news:title>
   <news:publication_date>2026-07-23T13:10:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715048</loc>
  <lastmod>2026-07-23T13:10:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QFlowによるワイヤレス端での高QoEビデオ配信学習手法（QFlow: A Learning Approach to High QoE Video Streaming at the Wireless Edge）</news:title>
   <news:publication_date>2026-07-23T13:10:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715046</loc>
  <lastmod>2026-07-23T13:09:45Z</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適応型信号制御（Adaptive Traffic Signal Control with Deep Reinforcement Learning – An Exploratory Investigation）</news:title>
   <news:publication_date>2026-07-23T13:09:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715044</loc>
  <lastmod>2026-07-23T13:09:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの透明な機械教育による群制御（Transparent Machine Education of Neural Networks for Swarm Shepherding Using Curriculum Design）</news:title>
   <news:publication_date>2026-07-23T13:09:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715042</loc>
  <lastmod>2026-07-23T13:09:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群れを導く報酬設計の教え方（Machine Teaching in Hierarchical Genetic Reinforcement Learning: Curriculum Design of Reward Functions for Swarm Shepherding）</news:title>
   <news:publication_date>2026-07-23T13:09:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715040</loc>
  <lastmod>2026-07-23T12:18:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全データベースから同時に複数物性を学習する方法（Simultaneous Learning of Several Materials Properties from Incomplete Databases with Multi-Task SISSO）</news:title>
   <news:publication_date>2026-07-23T12:18:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715038</loc>
  <lastmod>2026-07-23T12:17:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜から皮質までの初期視覚表現の統一理論（A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs）</news:title>
   <news:publication_date>2026-07-23T12:17:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715036</loc>
  <lastmod>2026-07-23T12:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師ありで学ぶ画像埋め込みと連続制御（Self-supervised Learning of Image Embedding for Continuous Control）</news:title>
   <news:publication_date>2026-07-23T12:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715034</loc>
  <lastmod>2026-07-23T12:16:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカル領域変換によるモダリティ頑健な対応付け（Local Area Transform for Modality-Robust Correspondence）</news:title>
   <news:publication_date>2026-07-23T12:16:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715032</loc>
  <lastmod>2026-07-23T12:16:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚と強化学習による差し迫った衝突軽減（Imminent Collision Mitigation with Reinforcement Learning and Vision）</news:title>
   <news:publication_date>2026-07-23T12:16:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715030</loc>
  <lastmod>2026-07-23T12:15:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質構造解析に深層学習を使う試み（A deep learning approach to the structural analysis of proteins）</news:title>
   <news:publication_date>2026-07-23T12:15:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715028</loc>
  <lastmod>2026-07-23T12:15:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習型ブルームフィルタのモデル化とサンドイッチ最適化（A Model for Learned Bloom Filters, and Optimizing by Sandwiching）</news:title>
   <news:publication_date>2026-07-23T12:15:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715026</loc>
  <lastmod>2026-07-23T11:23:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理イベント生成と統計サンプリングを深層生成モデルと密度情報バッファで改善する（Event Generation and Statistical Sampling for Physics with Deep Generative Models and a Density Information Buffer）</news:title>
   <news:publication_date>2026-07-23T11:23:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715024</loc>
  <lastmod>2026-07-23T11:15:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間制約イベントにおけるハッキングとモノづくりワークショップの位置づけ（The 2nd Workshop on Hacking and Making at Time-Bounded Events）</news:title>
   <news:publication_date>2026-07-23T11:15:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715022</loc>
  <lastmod>2026-07-23T11:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極性熱画像から可視顔への属性保持合成による照合（Polarimetric Thermal to Visible Face Verification via Attribute Preserved Synthesis）</news:title>
   <news:publication_date>2026-07-23T11:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715020</loc>
  <lastmod>2026-07-23T11:15:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブスペースマッチは学習表現の類似性を正確に評価していない可能性（SUBSPACE MATCH PROBABLY DOES NOT ACCURATELY ASSESS THE SIMILARITY OF LEARNED REPRESENTATIONS）</news:title>
   <news:publication_date>2026-07-23T11:15:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715018</loc>
  <lastmod>2026-07-23T11:14:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生体情報の多モーダル融合による動的相互作用の可視化（A Network-based Multimodal Data Fusion Approach for Characterizing Dynamic Multimodal Physiological Patterns）</news:title>
   <news:publication_date>2026-07-23T11:14:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715016</loc>
  <lastmod>2026-07-23T11:13:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>作業経験を取り入れたベイズ事前分布による溶接作業者の品質評価強化（Enhanced Welding Operator Quality Performance Measurement: Work Experience-Integrated Bayesian Prior Determination）</news:title>
   <news:publication_date>2026-07-23T11:13:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715014</loc>
  <lastmod>2026-07-23T10:22:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力波信号のノイズ除去における深層学習の実用化（Gravitational Wave Denoising of Binary Black Hole Mergers with Deep Learning）</news:title>
   <news:publication_date>2026-07-23T10:22:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715012</loc>
  <lastmod>2026-07-23T10:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照表現による視覚推論の診断（CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions）</news:title>
   <news:publication_date>2026-07-23T10:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715010</loc>
  <lastmod>2026-07-23T10:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational quantum generators: Generative adversarial quantum machine learning for continuous distributions（Variational quantum generators: Generative adversarial quantum machine learning for continuous distributions）</news:title>
   <news:publication_date>2026-07-23T10:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715008</loc>
  <lastmod>2026-07-23T10:21:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロサム連続ゲームにおける局所ナッシュ均衡の探索法（On Finding Local Nash Equilibria (and Only Local Nash Equilibria) in Zero-Sum Continuous Games）</news:title>
   <news:publication_date>2026-07-23T10:21:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715006</loc>
  <lastmod>2026-07-23T10:21:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全な二者間特徴選択の実務的意義（Secure Two-Party Feature Selection）</news:title>
   <news:publication_date>2026-07-23T10:21:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715004</loc>
  <lastmod>2026-07-23T10:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hamiltonianを用いたSequential Monte Carloによる非線形状態空間モデル学習（Learning Nonlinear State Space Models with Hamiltonian Sequential Monte Carlo Sampler）</news:title>
   <news:publication_date>2026-07-23T10:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715002</loc>
  <lastmod>2026-07-23T10:20:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイヤレスエッジでの機械学習：分散確率的勾配降下法の無線「オーバーザエア」実装（Machine learning at the wireless edge: Distributed stochastic gradient descent over-the-air）</news:title>
   <news:publication_date>2026-07-23T10:20:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/715000</loc>
  <lastmod>2026-07-23T09:29:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索から制御へ：ノベルティ探索と局所適応による物体操作スキルの獲得（From exploration to control: learning object manipulation skills through novelty search and local adaptation）</news:title>
   <news:publication_date>2026-07-23T09:29:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714998</loc>
  <lastmod>2026-07-23T09:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アプリケーション定義型OSがデータセンターを変える（XOS: An Application-Defined Operating System for Datacenter Computing）</news:title>
   <news:publication_date>2026-07-23T09:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714996</loc>
  <lastmod>2026-07-23T09:29:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細胞内の濃度勾配が物質輸送を変える：拡散泳動という新しい視点（Diffusiophoresis in Cells: a General Non-Equilibrium, Non-Motor Mechanism for the Metabolism-Dependent Transport of Particles in Cells）</news:title>
   <news:publication_date>2026-07-23T09:29:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714994</loc>
  <lastmod>2026-07-23T09:28:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>端子バスデータから発電機モデルを学習する方法（Learning a Generator Model from Terminal Bus Data）</news:title>
   <news:publication_date>2026-07-23T09:28:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714992</loc>
  <lastmod>2026-07-23T09:28:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>A2-NetによるクライオEMからの分子構造推定（A2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes）</news:title>
   <news:publication_date>2026-07-23T09:28:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714990</loc>
  <lastmod>2026-07-23T09:28:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合領域を読むためのネットワーク指標入門（Network Measures of Mixing）</news:title>
   <news:publication_date>2026-07-23T09:28:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714988</loc>
  <lastmod>2026-07-23T09:27:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>X線吸収スペクトルから局所化学環境を分類する手法（Classification of Local Chemical Environments from X-ray Absorption Spectra using Supervised Machine Learning）</news:title>
   <news:publication_date>2026-07-23T09:27:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714986</loc>
  <lastmod>2026-07-23T08:36:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人化された説明（Personalized Explanation for Machine Learning）</news:title>
   <news:publication_date>2026-07-23T08:36:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714984</loc>
  <lastmod>2026-07-23T08:36:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数物体を任意の位置に生成するGANの設計（GENERATING MULTIPLE OBJECTS AT SPATIALLY DISTINCT LOCATIONS）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714982</loc>
  <lastmod>2026-07-23T08:36:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多面的ビデオ要約の実務的示唆（Demystifying Multi-Faceted Video Summarization）</news:title>
   <news:publication_date>2026-07-23T08:36:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714980</loc>
  <lastmod>2026-07-23T08:35:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデータで学ぶ方法（Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision）</news:title>
   <news:publication_date>2026-07-23T08:35:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714978</loc>
  <lastmod>2026-07-23T08:35:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張カルマンフィルタは軌跡空間における自然勾配降下である（The Extended Kalman Filter is a Natural Gradient Descent in Trajectory Space）</news:title>
   <news:publication_date>2026-07-23T08:35:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714976</loc>
  <lastmod>2026-07-23T08:34:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四足歩行研究プラットフォーム「Stoch」の設計と実験的実現（Design, Development and Experimental Realization of a Quadrupedal Research Platform: Stoch）</news:title>
   <news:publication_date>2026-07-23T08:34:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714974</loc>
  <lastmod>2026-07-23T08:34:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型食料品店画像データセット（A Hierarchical Grocery Store Image Dataset with Visual and Semantic Labels）</news:title>
   <news:publication_date>2026-07-23T08:34:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714972</loc>
  <lastmod>2026-07-23T07:43:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GeoNet: 点群解析のための深層測地ネットワーク（GeoNet: Deep Geodesic Networks for Point Cloud Analysis）</news:title>
   <news:publication_date>2026-07-23T07:43:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714970</loc>
  <lastmod>2026-07-23T07:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TensorBoard Projectorを用いた能動学習による画像アノテーション高速化（Active Learning with TensorBoard Projector）</news:title>
   <news:publication_date>2026-07-23T07:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714968</loc>
  <lastmod>2026-07-23T07:43:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度分光器TOUのデータ処理パイプラインとサブm/s性能の達成（Data Reduction Pipeline of the TOU Optical Very High Resolution Spectrograph and Its sub-m s−1 Performance）</news:title>
   <news:publication_date>2026-07-23T07:43:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714966</loc>
  <lastmod>2026-07-23T07:42:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残響と雑音を伴う音声の深層強調におけるワイド残差ネットワーク（Deep Speech Enhancement for Reverberated and Noisy Signals using Wide Residual Networks）</news:title>
   <news:publication_date>2026-07-23T07:42:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714964</loc>
  <lastmod>2026-07-23T07:41:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重みのないニューラルネットと転移学習で道路ひび割れを検出する（Weightless Neural Network with Transfer Learning to Detect Distress in Asphalt）</news:title>
   <news:publication_date>2026-07-23T07:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714962</loc>
  <lastmod>2026-07-23T07:41:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運動技能学習の計算枠組み (A Computational Framework for Motor Skill Learning)</news:title>
   <news:publication_date>2026-07-23T07:41:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714960</loc>
  <lastmod>2026-07-23T07:41:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測データを用いた個別化治療規則の効率的推定（Efficient augmentation and relaxation learning for individualized treatment rules using observational data）</news:title>
   <news:publication_date>2026-07-23T07:41:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714958</loc>
  <lastmod>2026-07-23T06:49:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>標準化されていない分布からサンプラーを学習する逆行学習（Adversarial Learning of a Sampler Based on an Unnormalized Distribution）</news:title>
   <news:publication_date>2026-07-23T06:49:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714956</loc>
  <lastmod>2026-07-23T06:41:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>室内レイアウト推定のためのエッジ・セマンティック学習戦略（Edge-Semantic Learning Strategy for Layout Estimation in Indoor Environment）</news:title>
   <news:publication_date>2026-07-23T06:41:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714954</loc>
  <lastmod>2026-07-23T06:40:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リレーショナル誘導ニューラルネットワークによるマイクロ波集積回路設計（Microwave Integrated Circuits Design with Relational Induction Neural Network）</news:title>
   <news:publication_date>2026-07-23T06:40:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714952</loc>
  <lastmod>2026-07-23T06:40:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次元削減で「ランダムよりも上手く投影する方法」（Projecting &amp;quot;better than randomly&amp;quot;: How to reduce the dimensionality of very large datasets in a way that outperforms random projections）</news:title>
   <news:publication_date>2026-07-23T06:40:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714950</loc>
  <lastmod>2026-07-23T06:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単位球における体積畳み込み（VOLUMETRIC CONVOLUTION: AUTOMATIC REPRESENTATION LEARNING IN UNIT BALL）</news:title>
   <news:publication_date>2026-07-23T06:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714948</loc>
  <lastmod>2026-07-23T06:39:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メッシュフリー深層学習による境界面問題の解法（A mesh-free method for interface problems using the deep learning approach）</news:title>
   <news:publication_date>2026-07-23T06:39:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714946</loc>
  <lastmod>2026-07-23T06:39:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造学習の汎用フレームワーク：カーネルベースM回帰による発見（Structure learning via unstructured kernel-based M-regression）</news:title>
   <news:publication_date>2026-07-23T06:39:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714944</loc>
  <lastmod>2026-07-23T05:48:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンビエント・バックスキャッタ通信のスループット最大化（Throughput Maximization for Ambient Backscatter Communication: A Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-07-23T05:48:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714942</loc>
  <lastmod>2026-07-23T05:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リモートセンシング画像の雲除去データセット RICE（A Remote Sensing Image Dataset for Cloud Removal）</news:title>
   <news:publication_date>2026-07-23T05:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714940</loc>
  <lastmod>2026-07-23T05:47:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数文書からの証拠を統合する質問応答モデル（Coarse-Grain Fine-Grain Coattention Network）</news:title>
   <news:publication_date>2026-07-23T05:47:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714938</loc>
  <lastmod>2026-07-23T05:47:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多次元空間変動データのベイズテンソル補完（Prediction of Multi-Dimensional Spatial Variation Data via Bayesian Tensor Completion）</news:title>
   <news:publication_date>2026-07-23T05:47:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714936</loc>
  <lastmod>2026-07-23T05:47:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークの包括的レビュー（A Comprehensive Survey on Graph Neural Networks）</news:title>
   <news:publication_date>2026-07-23T05:47:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714934</loc>
  <lastmod>2026-07-23T05:46:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterにおける事象検出：キーワードボリューム手法（Event Detection in Twitter: A Keyword Volume Approach）</news:title>
   <news:publication_date>2026-07-23T05:46:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714932</loc>
  <lastmod>2026-07-23T05:46:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反応型システムの合成実装を記述・説明する上での課題（The Challenges in Specifying and Explaining Synthesized Implementations of Reactive Systems）</news:title>
   <news:publication_date>2026-07-23T05:46:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714930</loc>
  <lastmod>2026-07-23T04:55:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間らしい自動車追従モデルの提案（Human-Like Autonomous Car-Following Model with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-23T04:55:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714928</loc>
  <lastmod>2026-07-23T04:55:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adaptive Locality Preserving Regression（Adaptive Locality Preserving Regression）</news:title>
   <news:publication_date>2026-07-23T04:55:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714926</loc>
  <lastmod>2026-07-23T04:54:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮説検定に基づくインスタンスベース分類（Instance-Based Classification through Hypothesis Testing）</news:title>
   <news:publication_date>2026-07-23T04:54:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714924</loc>
  <lastmod>2026-07-23T04:54:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファノの不等式による統計推定の限界（An Introductory Guide to Fano’s Inequality with Applications in Statistical Estimation）</news:title>
   <news:publication_date>2026-07-23T04:54:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714922</loc>
  <lastmod>2026-07-23T04:53:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチラベルに対する敵対的摂動（Multi-Label Adversarial Perturbations）</news:title>
   <news:publication_date>2026-07-23T04:53:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714920</loc>
  <lastmod>2026-07-23T04:53:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球面構造による三次元サブ波長局在と時間反転の実現（Three-dimensional-subwavelength field localization, time reversal of sources, and infinite-asymptotic degeneracy in spherical structures）</news:title>
   <news:publication_date>2026-07-23T04:53:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714918</loc>
  <lastmod>2026-07-23T04:53:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2次元電荷密度波デバイスによる陽子線耐性電子機器の実証（Proton-Irradiation-Immune Electronics Implemented with Two-Dimensional Charge-Density-Wave Devices）</news:title>
   <news:publication_date>2026-07-23T04:53:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714916</loc>
  <lastmod>2026-07-23T04:02:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラスラベルなしで学ぶマルチクラス分類（Multi-Class Classification Without Multi-Class Labels）</news:title>
   <news:publication_date>2026-07-23T04:02:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714914</loc>
  <lastmod>2026-07-23T04:02:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像から輪郭スケッチを推定する（Photo-Sketching: Inferring Contour Drawings from Images）</news:title>
   <news:publication_date>2026-07-23T04:02:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714912</loc>
  <lastmod>2026-07-23T04:02:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層類似度ネットワークの可視化（Visualizing Deep Similarity Networks）</news:title>
   <news:publication_date>2026-07-23T04:02:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714910</loc>
  <lastmod>2026-07-23T04:01:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news: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>2026-07-23T04:01:45Z</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>2026-07-23T04:01:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純さと対立することがある敵対的堅牢性（Adversarial Robustness May Be at Odds With Simplicity）</news:title>
   <news:publication_date>2026-07-23T04:01:19Z</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>太陽に接近する天体が教えてくれること（TURNING UP THE HEAT ON ‘OUMUAMUA）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714900</loc>
  <lastmod>2026-07-23T03:09:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動き（モーション）を使って注釈を削減する画素埋め込み学習（Flow Based Self-supervised Pixel Embedding for Image Segmentation）</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>リアルタイムEEG分類におけるコアセット応用（Real-Time EEG Classiﬁcation via Coresets for BCI Applications）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714896</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>マイクロデータの開示リスク評価の新指標（A Novel Microdata Privacy Disclosure Risk Measure）</news:title>
   <news:publication_date>2026-07-23T03:09:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/714894</loc>
  <lastmod>2026-07-23T03:08:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層材料ネットワークによる3次元多階層材料モデリング（Exploring the 3D architectures of deep material network in data-driven multiscale mechanics）</news:title>
   <news:publication_date>2026-07-23T03:08:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714892</loc>
  <lastmod>2026-07-23T03:08:28Z</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>2026-07-23T03:08:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714890</loc>
  <lastmod>2026-07-23T03:08:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D仮想合成による顔のなりすまし防止の改善 (Improving Face Anti-Spooﬁng by 3D Virtual Synthesis)</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剛体の一般化可能な物理ダイナミクス学習（Learning Generalizable Physical Dynamics of 3D Rigid Objects）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超新星の光度曲線を深層学習で識別する手法（Photometric Supernova Classification with Convolutional Neural Networks）</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>変動コスト下での変数選択を解く：モデル列のアンサンブルによる予算制約学習（Cost-sensitive Selection of Variables by Ensemble of Model Sequences）</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>SGDが深層学習で大域最小に収束する理由（SGD CONVERGES TO GLOBAL MINIMUM IN DEEP LEARNING VIA STAR-CONVEX PATH）</news:title>
   <news:publication_date>2026-07-23T02:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/714878</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光フリンジパターンのノイズ除去に向けた多段畳み込みニューラルネットワーク（Optical Fringe Patterns Filtering Based on Multi-stage Convolution Neural Network）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714868</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>評価者を評価する：オンラインレビュー生成における大規模比較研究（Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation）</news:title>
   <news:publication_date>2026-07-23T01:05:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714866</loc>
  <lastmod>2026-07-23T01:05:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イエス／ノー形式クラウドソーシングの全確率モデル（A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification）</news:title>
   <news:publication_date>2026-07-23T01:05:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714864</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>属性に配慮した注意機構による微細表現学習（Attribute-Aware Attention Model for Fine-grained Representation Learning）</news:title>
   <news:publication_date>2026-07-23T01:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714862</loc>
  <lastmod>2026-07-23T01:03:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり適応蒸留による効率的検出器学習（Learning Efficient Detector with Semi-supervised Adaptive Distillation）</news:title>
   <news:publication_date>2026-07-23T01:03:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714860</loc>
  <lastmod>2026-07-23T00:12:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MISOダウンリンクビームフォーミング最適化の深層学習フレームワーク（A Deep Learning Framework for Optimization of MISO Downlink Beamforming）</news:title>
   <news:publication_date>2026-07-23T00:12:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714858</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>進化的手法による畳み込みニューラルネットワークの構築（Evolutionary Construction of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-23T00:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714856</loc>
  <lastmod>2026-07-23T00:11:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル密度推定のバイアスと最小条件（Kernel Density Estimation Bias under Minimal Assumptions）</news:title>
   <news:publication_date>2026-07-23T00:11:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714854</loc>
  <lastmod>2026-07-23T00:11:16Z</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>2026-07-23T00:11:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714852</loc>
  <lastmod>2026-07-23T00:11:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPDZを用いた機械学習の安全計算（Secure Computation for Machine Learning With SPDZ）</news:title>
   <news:publication_date>2026-07-23T00:11:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714850</loc>
  <lastmod>2026-07-23T00:10:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的な証拠を用いた推論のためのPlugin Networks（Plugin Networks for Inference under Partial Evidence）</news:title>
   <news:publication_date>2026-07-23T00:10:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714848</loc>
  <lastmod>2026-07-23T00:10:34Z</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>2026-07-23T00:10:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714846</loc>
  <lastmod>2026-07-22T23:19:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様で一貫した反事実説明の効率的探索（Efficient Search for Diverse Coherent Explanations）</news:title>
   <news:publication_date>2026-07-22T23:19:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714844</loc>
  <lastmod>2026-07-22T23:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異値空間の正規近似と信頼領域（Normal Approximation and Confidence Region of Singular Subspaces）</news:title>
   <news:publication_date>2026-07-22T23:18:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714842</loc>
  <lastmod>2026-07-22T23:17:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SIXrayによるX線手荷物検査のベンチマーク刷新（SIXray: A Large-scale Security Inspection X-ray Benchmark for Prohibited Item Discovery in Overlapping Images）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-07-22T23:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/714838</loc>
  <lastmod>2026-07-22T23:17:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所最適解をすべて消す手法の本質（Elimination of All Bad Local Minima in Deep Learning）</news:title>
   <news:publication_date>2026-07-22T23:17:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714836</loc>
  <lastmod>2026-07-22T23:17:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似言語・方言に対する深層学習アプローチ（A Deep Learning Approach for Similar Languages, Varieties and Dialects）</news:title>
   <news:publication_date>2026-07-22T23:17:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714834</loc>
  <lastmod>2026-07-22T23:17:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小差異推定に基づく深層ドメイン適応（On Minimum Discrepancy Estimation for Deep Domain Adaptation）</news:title>
   <news:publication_date>2026-07-22T23:17:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714832</loc>
  <lastmod>2026-07-22T22:26:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺結節分類における多段階CNNとガウス過程支援ハイパーパラメータ最適化（Multi-level CNN for lung nodule classification with Gaussian Process assisted hyperparameter optimization）</news:title>
   <news:publication_date>2026-07-22T22:26:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714830</loc>
  <lastmod>2026-07-22T22:25:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブポピュレーションフレームワークが変える集団内の対立の扱い方（General Subpopulation Framework and Taming the Conflict Inside Populations）</news:title>
   <news:publication_date>2026-07-22T22:25:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714828</loc>
  <lastmod>2026-07-22T22:25:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマノイドの動作学習を深層ニューラルで行う意義（LEARNING HUMANOID ROBOT MOTIONS THROUGH DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-07-22T22:25:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714826</loc>
  <lastmod>2026-07-22T22:24:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CHAIDとロジスティック回帰のハイブリッドによる銀行カード応答分類の改良（An Automatic Interaction Detection Hybrid Model for Bankcard Response Classification）</news:title>
   <news:publication_date>2026-07-22T22:24:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714824</loc>
  <lastmod>2026-07-22T22:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ出力学習の概観（A Survey on Multi-output Learning）</news:title>
   <news:publication_date>2026-07-22T22:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714822</loc>
  <lastmod>2026-07-22T22:24:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習機を用いた相転移の新戦略（A New Strategy in Applying the Learning Machine to Study Phase Transitions）</news:title>
   <news:publication_date>2026-07-22T22:24:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714820</loc>
  <lastmod>2026-07-22T22:23:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短く疎な畳み込みの幾何と対称性（Geometry and Symmetry in Short-and-Sparse Deconvolution）</news:title>
   <news:publication_date>2026-07-22T22:23:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714818</loc>
  <lastmod>2026-07-22T21:32:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な機械学習の原点に立ち返る提案（Natively Interpretable Machine Learning and Artificial Intelligence）</news:title>
   <news:publication_date>2026-07-22T21:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714816</loc>
  <lastmod>2026-07-22T21:32:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機会的学習による予算制約下の特徴獲得戦略（OPPORTUNISTIC LEARNING: BUDGETED COST-SENSITIVE LEARNING FROM DATA STREAMS）</news:title>
   <news:publication_date>2026-07-22T21:32:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714814</loc>
  <lastmod>2026-07-22T21:31:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子に基づく説明可能な追跡署名（Accountable Tracing Signatures from Lattices）</news:title>
   <news:publication_date>2026-07-22T21:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714812</loc>
  <lastmod>2026-07-22T21:31:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散K-meansとコアセットによる効率化（Distributed K-means with Coresets）</news:title>
   <news:publication_date>2026-07-22T21:31:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714810</loc>
  <lastmod>2026-07-22T21:30:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>筋収縮強度のばらつきに強いEMGベースの姿勢認識（Analysis of Contraction Effort Level in EMG-Based Gesture Recognition Using Hyperdimensional Computing）</news:title>
   <news:publication_date>2026-07-22T21:30:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714808</loc>
  <lastmod>2026-07-22T21:30:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付けランダムサバイバルフォレスト（A weighted random survival forest）</news:title>
   <news:publication_date>2026-07-22T21:30:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714806</loc>
  <lastmod>2026-07-22T21:30:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RPとSPデータを統合するマルチタスク学習（Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data）</news:title>
   <news:publication_date>2026-07-22T21:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714804</loc>
  <lastmod>2026-07-22T20:39:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EdgeConnectによる画像インペインティングの革新（EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning）</news:title>
   <news:publication_date>2026-07-22T20:39:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714802</loc>
  <lastmod>2026-07-22T20:39:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>価値関数の範囲を使って環境依存の後悔（regret）を小さくする方法（Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds）</news:title>
   <news:publication_date>2026-07-22T20:39:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714800</loc>
  <lastmod>2026-07-22T20:38:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意見最大化のための賢い情報拡散（Smart Information Spreading for Opinion Maximization in Social Networks）</news:title>
   <news:publication_date>2026-07-22T20:38:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714798</loc>
  <lastmod>2026-07-22T20:38:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能なエージェントに向けた補助的強化学習（COMPLEMENTARY REINFORCEMENT LEARNING TOWARDS EXPLAINABLE AGENTS）</news:title>
   <news:publication_date>2026-07-22T20:38:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714796</loc>
  <lastmod>2026-07-22T20:38:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡なネットワークトラフィック分類に対するデータ拡張法（Augmentation Scheme for Dealing with Imbalanced Network Traffic Classification Using Deep Learning）</news:title>
   <news:publication_date>2026-07-22T20:38:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714794</loc>
  <lastmod>2026-07-22T20:37:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語モデルから画像キャプション生成器への転移学習（Transfer learning from language models to image caption generators: Better models may not transfer better）</news:title>
   <news:publication_date>2026-07-22T20:37:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714792</loc>
  <lastmod>2026-07-22T20:37:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希ガスが機能的ドーパントになり得るという発見（Noble gas as a functional dopant in ZnO）</news:title>
   <news:publication_date>2026-07-22T20:37:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714790</loc>
  <lastmod>2026-07-22T19:46:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Metric Temporal Logicを用いたオンライン監視とSequential Networksの構築（ONLINE MONITORING OF METRIC TEMPORAL LOGIC USING SEQUENTIAL NETWORKS）</news:title>
   <news:publication_date>2026-07-22T19:46:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714788</loc>
  <lastmod>2026-07-22T19:46:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Spatial Interaction Networksのための教師あり多重スケール次元削減（Supervised Multiscale Dimension Reduction for Spatial Interaction Networks）</news:title>
   <news:publication_date>2026-07-22T19:46:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714786</loc>
  <lastmod>2026-07-22T19:45:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスプラットフォーム推薦における差異保存型深層結合（Disparity-preserved Deep Cross-platform Association）</news:title>
   <news:publication_date>2026-07-22T19:45:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714784</loc>
  <lastmod>2026-07-22T19:45:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランキングスコア推定を速める反復法の改善（Accelerated MM Algorithms for Ranking Scores Inference from Comparison Data）</news:title>
   <news:publication_date>2026-07-22T19:45:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714782</loc>
  <lastmod>2026-07-22T19:45:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>六角相MASnI3の紫外線吸収特性（Hexagonal MASnI3 exhibiting strong absorption of ultraviolet photons）</news:title>
   <news:publication_date>2026-07-22T19:45:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714780</loc>
  <lastmod>2026-07-22T19:44:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外れ値を適応的に扱う低ランク行列分解（Adaptive Quantile Low-Rank Matrix Factorization）</news:title>
   <news:publication_date>2026-07-22T19:44:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714778</loc>
  <lastmod>2026-07-22T19:44:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト補完（Text Inﬁlling）の一般化と自己注意モデルの効果（Text Inﬁlling）</news:title>
   <news:publication_date>2026-07-22T19:44:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714776</loc>
  <lastmod>2026-07-22T18:53:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層Q学習（A Theoretical Analysis of Deep Q-Learning）</news:title>
   <news:publication_date>2026-07-22T18:53:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714774</loc>
  <lastmod>2026-07-22T18:53:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散推論を一つにまとめるMonte Carlo Fusion（Monte Carlo Fusion）</news:title>
   <news:publication_date>2026-07-22T18:53:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714772</loc>
  <lastmod>2026-07-22T18:52:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ネットワークが「データ特徴」を実現する力（Realizing data features by deep nets）</news:title>
   <news:publication_date>2026-07-22T18:52:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714770</loc>
  <lastmod>2026-07-22T18:52:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGAを用いた深層学習アクセラレータの総覧（FPGA-based Accelerators of Deep Learning Networks for Learning and Classification: A Review）</news:title>
   <news:publication_date>2026-07-22T18:52:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714768</loc>
  <lastmod>2026-07-22T18:52:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なロバスト方策探索のための能動学習フレームワーク（An Active Learning Framework for Efficient Robust Policy Search）</news:title>
   <news:publication_date>2026-07-22T18:52:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714766</loc>
  <lastmod>2026-07-22T18:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gated-Dilatedネットワークによる肺結節分類の革新（Gated-Dilated Network for Lung Nodule Classification）</news:title>
   <news:publication_date>2026-07-22T18:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714764</loc>
  <lastmod>2026-07-22T18:51:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MaD：ニューロモルフィックチップへのネットワーク実装とデバッグ枠組み（MaD: Mapping and debugging framework for implementing deep neural network onto a neuromorphic chip with crossbar array of synapses）</news:title>
   <news:publication_date>2026-07-22T18:51:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714762</loc>
  <lastmod>2026-07-22T18:00:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド自動運転システムのギャップを埋める（Closing the gap towards end-to-end autonomous vehicle system）</news:title>
   <news:publication_date>2026-07-22T18:00:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714760</loc>
  <lastmod>2026-07-22T18:00:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形態学的ネットワークの到達可能性（Morphological Network: How Far Can We Go with Morphological Neurons?）</news:title>
   <news:publication_date>2026-07-22T18:00:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714758</loc>
  <lastmod>2026-07-22T18:00:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DECT-MULTRAに学ぶ画像分解の新潮流（DECT-MULTRA: Dual-Energy CT Image Decomposition With Learned Mixed Material Models and Efficient Clustering）</news:title>
   <news:publication_date>2026-07-22T18:00:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714756</loc>
  <lastmod>2026-07-22T17:59:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的安全回廊によるサンプリングベース運動計画の誘導（Probabilistically Safe Corridors to Guide Sampling-Based Motion Planning）</news:title>
   <news:publication_date>2026-07-22T17:59:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714754</loc>
  <lastmod>2026-07-22T17:58:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ感受性解析に基づくテスト優先化手法（A Noise-Sensitivity-Analysis-Based Test Prioritization Technique for Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-22T17:58:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714752</loc>
  <lastmod>2026-07-22T17:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像説明の重要語を重視する学習（Video-specific Information Loss for Video Captioning）</news:title>
   <news:publication_date>2026-07-22T17:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714750</loc>
  <lastmod>2026-07-22T17:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェアに優しいメモリスティブニューラルネットの重み共有機構（A Hardware Friendly Unsupervised Memristive Neural Network with Weight Sharing Mechanism）</news:title>
   <news:publication_date>2026-07-22T17:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714748</loc>
  <lastmod>2026-07-22T17:06:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散周期格子上のクラスタ同定を機械学習で行う（Identifying Clusters on a Discrete Periodic Lattice via Machine Learning）</news:title>
   <news:publication_date>2026-07-22T17:06:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714746</loc>
  <lastmod>2026-07-22T16:56:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子スケールの知見を「そのまま」上位モデルに橋渡しする手法（Integrable Deep Neural Networks enable scale bridging by learning free energy functions）</news:title>
   <news:publication_date>2026-07-22T16:56:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714744</loc>
  <lastmod>2026-07-22T16:55:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形スケール双曲線タンジェント活性化関数 LiSHT（Linearly Scaled Hyperbolic Tangent, LiSHT）</news:title>
   <news:publication_date>2026-07-22T16:55:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714742</loc>
  <lastmod>2026-07-22T16:54:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データセンターにおける機器障害の実測と分析（Measurement and Analysis of Data Center Device Failures）</news:title>
   <news:publication_date>2026-07-22T16:54:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714740</loc>
  <lastmod>2026-07-22T16:54:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトロ・テンポラル特徴を巡る探索（EXPLORING SPECTRO-TEMPORAL FEATURES IN END-TO-END CONVOLUTIONAL NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-07-22T16:54:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714738</loc>
  <lastmod>2026-07-22T16:54:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列予測のためのリカレントニューラルネットワーク（Recurrent Neural Networks for Time Series Forecasting）</news:title>
   <news:publication_date>2026-07-22T16:54:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714736</loc>
  <lastmod>2026-07-22T16:02:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクターボソンと重いフレーバー測定（Vector Boson production with heavy flavor quarks from CMS）</news:title>
   <news:publication_date>2026-07-22T16:02:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714734</loc>
  <lastmod>2026-07-22T16:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tree-LSTMの改良と木構造注意機構（Improving Tree-LSTM with Tree Attention）</news:title>
   <news:publication_date>2026-07-22T16:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714732</loc>
  <lastmod>2026-07-22T15:59:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Figure 1とFigure 2が語る遺伝子発現の定量的対話（Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression）</news:title>
   <news:publication_date>2026-07-22T15:59:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714730</loc>
  <lastmod>2026-07-22T15:58:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍量子コンピュータにおける効率的なキュービットルーティング方策の発見に強化学習を用いる（Using Reinforcement Learning to find Efficient Qubit Routing Policies for Deployment in Near-term Quantum Computers）</news:title>
   <news:publication_date>2026-07-22T15:58:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714728</loc>
  <lastmod>2026-07-22T15:58:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>家庭内IoTの「グループ所有」攻撃と防御の提案（The Device War: The War Between IOT Brands In A Household）</news:title>
   <news:publication_date>2026-07-22T15:58:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714726</loc>
  <lastmod>2026-07-22T15:58:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Code Wizardによる共同定性コーディングの可視化と効率化（Ease on Down the Code: Complex Collaborative Qualitative Coding Simplified with &amp;#039;Code Wizard&amp;#039;）</news:title>
   <news:publication_date>2026-07-22T15:58:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714724</loc>
  <lastmod>2026-07-22T15:57:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多精度環境における高精度モデルの資源配分戦略（Allocation strategies for high fidelity models in the multifidelity regime）</news:title>
   <news:publication_date>2026-07-22T15:57:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714722</loc>
  <lastmod>2026-07-22T15:06:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hebbian励起とAnti-Hebbian抑制を用いる非線形ネットワークの教師なし学習（Unsupervised learning by a nonlinear network with Hebbian excitatory and anti-Hebbian inhibitory neurons）</news:title>
   <news:publication_date>2026-07-22T15:06:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714720</loc>
  <lastmod>2026-07-22T15:00:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューローネットワークによるCANデータフィールド予測で異常を検知する（Towards a CAN IDS based on a neural-network data field predictor）</news:title>
   <news:publication_date>2026-07-22T15:00:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714718</loc>
  <lastmod>2026-07-22T15:00:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次の自動微分を幾何学で整理する（A Geometric Theory of Higher-Order Automatic Differentiation）</news:title>
   <news:publication_date>2026-07-22T15:00:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714716</loc>
  <lastmod>2026-07-22T14:59:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限定付き逆最適制御とヒューマン操作課題への応用（Constrained Inverse Optimal Control with Application to a Human Manipulation Task）</news:title>
   <news:publication_date>2026-07-22T14:59:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714714</loc>
  <lastmod>2026-07-22T14:59:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リーシュマニア原虫の分割と分類のための深層学習（Leishmaniasis Parasite Segmentation and Classification using Deep Learning）</news:title>
   <news:publication_date>2026-07-22T14:59:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714712</loc>
  <lastmod>2026-07-22T14:59:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ROIマスクを用いたカスケード型V-Netによる脳腫瘍セグメンテーション（Cascaded V-Net using ROI masks for brain tumor segmentation）</news:title>
   <news:publication_date>2026-07-22T14:59:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714710</loc>
  <lastmod>2026-07-22T14:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローマンウルドゥ語による自動車レビューの感情分類（SENTIMENT CLASSIFICATION of Customer’s Reviews about Automobiles in Roman Urdu）</news:title>
   <news:publication_date>2026-07-22T14:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714708</loc>
  <lastmod>2026-07-22T14:07:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度病理画像分類におけるモンテカルロ・パッチサンプリングの提案（Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification）</news:title>
   <news:publication_date>2026-07-22T14:07:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714706</loc>
  <lastmod>2026-07-22T14:07:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分自己注意による文表現の構築（Variational Self-attention Model for Sentence Representation）</news:title>
   <news:publication_date>2026-07-22T14:07:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714704</loc>
  <lastmod>2026-07-22T14:07:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択的転移学習による深層テキストマッチングの強化（Learning to Selectively Transfer: Reinforced Transfer Learning for Deep Text Matching）</news:title>
   <news:publication_date>2026-07-22T14:07:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714702</loc>
  <lastmod>2026-07-22T14:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置情報に頼らないスペクトラム地図作成（Location-free Spectrum Cartography）</news:title>
   <news:publication_date>2026-07-22T14:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714700</loc>
  <lastmod>2026-07-22T14:06:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース・低ランク回帰における交差検証の再考（On Cross-validation for Sparse Reduced Rank Regression）</news:title>
   <news:publication_date>2026-07-22T14:06:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714698</loc>
  <lastmod>2026-07-22T14:06:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepESNとゲート付きRNNの比較（Comparison between DeepESNs and gated RNNs on multivariate time-series prediction）</news:title>
   <news:publication_date>2026-07-22T14:06:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714696</loc>
  <lastmod>2026-07-22T14:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェット断片化と波動的タービュレンス（Jet fragmentation in a QCD medium: Universal quark/gluon ration and Wave turbulence）</news:title>
   <news:publication_date>2026-07-22T14:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714694</loc>
  <lastmod>2026-07-22T13:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新しいARIMA-ANNハイブリッド法とEMDによる時系列予測精度の向上 (Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition)</news:title>
   <news:publication_date>2026-07-22T13:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714692</loc>
  <lastmod>2026-07-22T13:15:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差予測精度を高めるための特徴選択の空間拡張（Space Expansion of Feature Selection for Designing more Accurate Error Predictors）</news:title>
   <news:publication_date>2026-07-22T13:15:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714690</loc>
  <lastmod>2026-07-22T13:14:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模リモートセンシング分類をつなぐ共通部分空間学習（CoSpace: Common Subspace Learning from Hyperspectral-Multispectral Correspondences）</news:title>
   <news:publication_date>2026-07-22T13:14:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714688</loc>
  <lastmod>2026-07-22T13:14:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフライン手書き漢字認識の高性能CNNと可視化（A High-Performance CNN Method for Offline Handwritten Chinese Character Recognition and Visualization）</news:title>
   <news:publication_date>2026-07-22T13:14:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714686</loc>
  <lastmod>2026-07-22T13:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブロードバンドアナログ集約による低遅延フェデレーテッドエッジ学習（Broadband Analog Aggregation for Low-Latency Federated Edge Learning）</news:title>
   <news:publication_date>2026-07-22T13:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714684</loc>
  <lastmod>2026-07-22T13:13:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハンガリーにおけるEコマースの現状と展望（E-commerce in Hungary: A Market Analysis）</news:title>
   <news:publication_date>2026-07-22T13:13:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714682</loc>
  <lastmod>2026-07-22T13:13:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注釈品質が意味するもの：粗いアノテーションでも交通状況セグメンテーションは実用に耐えるか（Impact of Ground Truth Annotation Quality on Performance of Semantic Image Segmentation of Traffic Conditions）</news:title>
   <news:publication_date>2026-07-22T13:13:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714680</loc>
  <lastmod>2026-07-22T12:22:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的非再帰型コントローラを備えたメモリ拡張ニューラルネットワーク（Partially Non-Recurrent Controllers for Memory-Augmented Neural Networks）</news:title>
   <news:publication_date>2026-07-22T12:22:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714678</loc>
  <lastmod>2026-07-22T12:22:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク再構築と動的学習のための汎用深層学習フレームワーク（A General Deep Learning Framework for Network Reconstruction and Dynamics Learning）</news:title>
   <news:publication_date>2026-07-22T12:22:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714676</loc>
  <lastmod>2026-07-22T12:22:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DART による教師なしドメイン適応の実用化可能性（DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification）</news:title>
   <news:publication_date>2026-07-22T12:22:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714674</loc>
  <lastmod>2026-07-22T12:21:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ORIGAMIの3D積層メモリを活用した学習アクセラレーション（ORIGAMI: A Heterogeneous Split Architecture for In-Memory Acceleration of Learning）</news:title>
   <news:publication_date>2026-07-22T12:21:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714672</loc>
  <lastmod>2026-07-22T12:21:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安静時fMRI解析における機械学習（Machine learning in resting-state fMRI analysis）</news:title>
   <news:publication_date>2026-07-22T12:21:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714670</loc>
  <lastmod>2026-07-22T12:21:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報制約下での推論 I：カイ二乗収縮に基づく下限（Inference under Information Constraints I: Lower Bounds from Chi-Square Contraction）</news:title>
   <news:publication_date>2026-07-22T12:21:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714668</loc>
  <lastmod>2026-07-22T12:20:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負ランク1のロバストPCAにおける擬似局所最小値の不存在に関する厳密保証（Exact Guarantees on the Absence of Spurious Local Minima for Non-negative Rank-1 Robust Principal Component Analysis）</news:title>
   <news:publication_date>2026-07-22T12:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714666</loc>
  <lastmod>2026-07-22T11:29:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベトナム語の単語分割・品詞付与・依存構文解析を同時に学習するニューラル結合モデル (A neural joint model for Vietnamese word segmentation, POS tagging and dependency parsing)</news:title>
   <news:publication_date>2026-07-22T11:29:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714664</loc>
  <lastmod>2026-07-22T11:29:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多面的にもつれが示す本質と応用可能性（Multi-Faced Entanglement）</news:title>
   <news:publication_date>2026-07-22T11:29:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714662</loc>
  <lastmod>2026-07-22T11:28:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込み符号の高性能復号器（High-performance Decoder for Convolutional Code with Deep Neural Network）</news:title>
   <news:publication_date>2026-07-22T11:28:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714660</loc>
  <lastmod>2026-07-22T11:28:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークから悪意あるノードを排除する最適化（Removing Malicious Nodes from Networks）</news:title>
   <news:publication_date>2026-07-22T11:28:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714658</loc>
  <lastmod>2026-07-22T11:28:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化需要予測のための多変量到着時間モデル（Multivariate Arrival Times with Recurrent Neural Networks for Personalized Demand Forecasting）</news:title>
   <news:publication_date>2026-07-22T11:28:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714656</loc>
  <lastmod>2026-07-22T11:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層逐次の貪欲学習でImageNetに拡張できる（Greedy Layerwise Learning Can Scale to ImageNet）</news:title>
   <news:publication_date>2026-07-22T11:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714654</loc>
  <lastmod>2026-07-22T11:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Brain MRI超解像における3D生成敵対ネットワーク（Brain MRI super-resolution using 3D generative adversarial networks）</news:title>
   <news:publication_date>2026-07-22T11:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714652</loc>
  <lastmod>2026-07-22T10:36:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EMMA：感情を読むウェルビーイング・チャットボット（EMMA: An Emotion-Aware Wellbeing Chatbot）</news:title>
   <news:publication_date>2026-07-22T10:36:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714650</loc>
  <lastmod>2026-07-22T10:36:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損が情報を帯びる場面での低ランク行列補完（Imputation and low-rank estimation with Missing Not At Random data）</news:title>
   <news:publication_date>2026-07-22T10:36:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714648</loc>
  <lastmod>2026-07-22T10:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レコメンダーにおける損失回避の活用（Loss Aversion in Recommender Systems: Utilizing Negative User Preference to Improve Recommendation Quality）</news:title>
   <news:publication_date>2026-07-22T10:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714646</loc>
  <lastmod>2026-07-22T10:35:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘッセ行列を考慮したゼロ次最適化によるブラックボックス敵対的攻撃（Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack）</news:title>
   <news:publication_date>2026-07-22T10:35:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714644</loc>
  <lastmod>2026-07-22T10:35:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘテロ接触触媒の微視的視点（A microscopic perspective on heterogeneous catalysis）</news:title>
   <news:publication_date>2026-07-22T10:35:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714642</loc>
  <lastmod>2026-07-22T10:34:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SLIM LSTMs（SLIM LSTMs）</news:title>
   <news:publication_date>2026-07-22T10:34:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714640</loc>
  <lastmod>2026-07-22T10:34:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索的分析のための集計説明（Explaining Aggregates for Exploratory Analytics）</news:title>
   <news:publication_date>2026-07-22T10:34:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714638</loc>
  <lastmod>2026-07-22T09:44:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所最適からの脱出を目指す導関数不要手法の数値検証（Escaping local minima with derivative-free methods: a numerical investigation）</news:title>
   <news:publication_date>2026-07-22T09:44:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714636</loc>
  <lastmod>2026-07-22T09:43:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークの効率化を狙う量子化付き誘導プルーニング（Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-22T09:43:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714634</loc>
  <lastmod>2026-07-22T09:43:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カプセルネットワークと動的ルーティングによる関係抽出の革新（Attention-Based Capsule Networks with Dynamic Routing for Relation Extraction）</news:title>
   <news:publication_date>2026-07-22T09:43:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714632</loc>
  <lastmod>2026-07-22T09:42:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接触不要な手のひら認証を深層学習で実現する枠組み（A Deep Learning based Framework to Detect and Recognize Humans using Contactless Palmprints in the Wild）</news:title>
   <news:publication_date>2026-07-22T09:42:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714630</loc>
  <lastmod>2026-07-22T09:42:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索パラメータ分布を進化戦略で学ぶメタ強化学習（Meta Reinforcement Learning with Distribution of Exploration Parameters Learned by Evolution Strategies）</news:title>
   <news:publication_date>2026-07-22T09:42:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714628</loc>
  <lastmod>2026-07-22T09:42:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D Hall–MHD系におけるLeray–Hopf級の非一意的弱解（NON-UNIQUE WEAK SOLUTIONS IN LERAY-HOPF CLASS FOR THE 3D HALL-MHD SYSTEM）</news:title>
   <news:publication_date>2026-07-22T09:42:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714626</loc>
  <lastmod>2026-07-22T09:41:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Support Vector Guided Softmax Loss（Support Vector Guided Softmax Loss for Face Recognition）</news:title>
   <news:publication_date>2026-07-22T09:41:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714624</loc>
  <lastmod>2026-07-22T08:50:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPI-Optimizer：積分分離型PIコントローラによる確率的最適化（SPI-Optimizer: an integral-Separated PI Controller for Stochastic Optimization）</news:title>
   <news:publication_date>2026-07-22T08:50:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714622</loc>
  <lastmod>2026-07-22T08:49:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeGroot-Friedkinモデルの変革点：意見力学を鏡像降下法として再解釈する（DeGroot-Friedkin Map in Opinion Dynamics is Mirror Descent）</news:title>
   <news:publication_date>2026-07-22T08:49:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714620</loc>
  <lastmod>2026-07-22T08:49:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドの関係抽出における深いバイアフィン注意の威力（End-to-end neural relation extraction using deep biaffine attention）</news:title>
   <news:publication_date>2026-07-22T08:49:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714618</loc>
  <lastmod>2026-07-22T08:48:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Atariエージェントの解釈を学ぶ（Learn to Interpret Atari Agents）</news:title>
   <news:publication_date>2026-07-22T08:48:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714616</loc>
  <lastmod>2026-07-22T08:48:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB-D点群に対する3D畳み込みによるモデル不要な物体姿勢推定（3D Convolution on RGB-D Point Clouds for Accurate Model-free Object Pose Estimation）</news:title>
   <news:publication_date>2026-07-22T08:48:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/714614</loc>
  <lastmod>2026-07-22T08:47:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ICF-CYに基づく子どものセルフケア分類（Classification of Functioning, Disability, and Health for Children and Youth: ICF-CY Self Care (SCADI Dataset) Using Predictive Analytics）</news:title>
   <news:publication_date>2026-07-22T08:47:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714612</loc>
  <lastmod>2026-07-22T07:57:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバスト意思決定者を伴う動的モデルの識別と推定 (Dynamic Models with Robust Decision Makers: Identification and Estimation)</news:title>
   <news:publication_date>2026-07-22T07:57:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714610</loc>
  <lastmod>2026-07-22T07:56:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり階層テキスト分類の実践的意義（Weakly-Supervised Hierarchical Text Classification）</news:title>
   <news:publication_date>2026-07-22T07:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714608</loc>
  <lastmod>2026-07-22T07:56:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Autoencoderベースの残差深層ネットワークによる頑健な回帰予測と時空間推定（Autoencoder Based Residual Deep Networks for Robust Regression Prediction and Spatiotemporal Estimation）</news:title>
   <news:publication_date>2026-07-22T07:56:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714606</loc>
  <lastmod>2026-07-22T07:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Clustering Processesの概要と実務への示唆（Neural Clustering Processes）</news:title>
   <news:publication_date>2026-07-22T07:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714604</loc>
  <lastmod>2026-07-22T07:56:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的計画ネットワークが示す「計画の学習化」──Dynamic Planning Networks (Dynamic Planning Networks)</news:title>
   <news:publication_date>2026-07-22T07:56:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714602</loc>
  <lastmod>2026-07-22T07:55:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Kymatioによるスキャッタリング変換の実装と実用性（Kymatio: Scattering Transforms in Python）</news:title>
   <news:publication_date>2026-07-22T07:55:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714600</loc>
  <lastmod>2026-07-22T07:55:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CamLoc: リソース制約のあるスマートカメラでの姿勢推定に基づく歩行者位置検出（CamLoc: Pedestrian Location Detection from Pose Estimation on Resource-constrained Smart-cameras）</news:title>
   <news:publication_date>2026-07-22T07:55:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714598</loc>
  <lastmod>2026-07-22T07:04:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リカレント・カプセルネットワークによる状態表現学習（State representation learning with recurrent capsule networks）</news:title>
   <news:publication_date>2026-07-22T07:04:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714596</loc>
  <lastmod>2026-07-22T07:04:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラプラスカーネルにおける最小ノルム補間の一貫性は高次元現象である（Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon）</news:title>
   <news:publication_date>2026-07-22T07:04:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714594</loc>
  <lastmod>2026-07-22T07:04:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス認識型敵対的合成による胸部CTの肺結節合成（CLASS-AWARE ADVERSARIAL LUNG NODULE SYNTHESIS IN CT IMAGES）</news:title>
   <news:publication_date>2026-07-22T07:04:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714592</loc>
  <lastmod>2026-07-22T07:03:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知クラスから形状を復元する学習（Learning to Reconstruct Shapes from Unseen Classes）</news:title>
   <news:publication_date>2026-07-22T07:03:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714590</loc>
  <lastmod>2026-07-22T07:03:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分型Temporal Difference学習の要点と実務への示唆（Differential Temporal Difference Learning）</news:title>
   <news:publication_date>2026-07-22T07:03:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714588</loc>
  <lastmod>2026-07-22T07:03:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話に基づく会議スケジューリングの強化学習（MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling）</news:title>
   <news:publication_date>2026-07-22T07:03:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714586</loc>
  <lastmod>2026-07-22T07:02:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>芸術表現における物体認識のための教師なしスタイル適応（Artistic Object Recognition by Unsupervised Style Adaptation）</news:title>
   <news:publication_date>2026-07-22T07:02:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714584</loc>
  <lastmod>2026-07-22T06:11:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテーテル室からの循環器入院予測（Forecasting Cardiology Admissions from Catheterization Laboratory）</news:title>
   <news:publication_date>2026-07-22T06:11:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714582</loc>
  <lastmod>2026-07-22T06:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡散MRI特徴の再現性評価によるアルツハイマー病自動分類の検証（Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimer’s disease）</news:title>
   <news:publication_date>2026-07-22T06:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714580</loc>
  <lastmod>2026-07-22T06:11:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現代機械学習実践とバイアス‑バリアンスの再考（Reconciling Modern Machine Learning Practice and the Bias-Variance Trade-off）</news:title>
   <news:publication_date>2026-07-22T06:11:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714578</loc>
  <lastmod>2026-07-22T06:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロキシを用いた高次元での転移学習（Predicting with Proxies: Transfer Learning in High Dimension）</news:title>
   <news:publication_date>2026-07-22T06:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714576</loc>
  <lastmod>2026-07-22T06:10:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>塩ドームのノイズ耐性検出と追跡（Noise-robust detection and tracking of salt domes in postmigrated volumes using texture, tensors, and subspace learning）</news:title>
   <news:publication_date>2026-07-22T06:10:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714574</loc>
  <lastmod>2026-07-22T06:10:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルなスパース変分ガウス過程によるGAM（Scalable GAM using sparse variational Gaussian processes）</news:title>
   <news:publication_date>2026-07-22T06:10:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714572</loc>
  <lastmod>2026-07-22T06:10:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層手指姿勢推定を組み合わせたタッチ可能プロジェクタ深度システム（Enhanced Touchable Projector-depth System with Deep Hand Pose Estimation）</news:title>
   <news:publication_date>2026-07-22T06:10:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714570</loc>
  <lastmod>2026-07-22T05:19:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市場における「デザインギャップ」の予測（Predicting &amp;quot;Design Gaps&amp;quot; in the Market: Deep Consumer Choice Models Under Probabilistic Design Constraints）</news:title>
   <news:publication_date>2026-07-22T05:19:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714568</loc>
  <lastmod>2026-07-22T05:18:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高密度核物質中の重クォークからのグルオン放出（Gluon emission from heavy quarks in dense nuclear matter）</news:title>
   <news:publication_date>2026-07-22T05:18:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714566</loc>
  <lastmod>2026-07-22T05:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幅（Width）がもたらす最適化の転移：Basinsの消失について（On the Benefit of Width for Neural Networks: Disappearance of Basins）</news:title>
   <news:publication_date>2026-07-22T05:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714564</loc>
  <lastmod>2026-07-22T05:18:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチバリアントMRIバイオマーカーがアルツハイマー様認知機能障害をより良く予測する（Multivariate MR Biomarkers Better Predict Cognitive Dysfunction in Mouse Models of Alzheimer’s Disease）</news:title>
   <news:publication_date>2026-07-22T05:18:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714562</loc>
  <lastmod>2026-07-22T05:18:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケッチのための点群多列Point-CNN（Multi-column Point-CNN for Sketch Segmentation）</news:title>
   <news:publication_date>2026-07-22T05:18:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714560</loc>
  <lastmod>2026-07-22T05:17:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散確率的勾配法の連続時間解析（A continuous-time analysis of distributed stochastic gradient）</news:title>
   <news:publication_date>2026-07-22T05:17:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714558</loc>
  <lastmod>2026-07-22T05:17:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重みの対称性が深層ニューラルネットワークにもたらす効率化（Exploring Weight Symmetry in Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-22T05:17:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714556</loc>
  <lastmod>2026-07-22T04:26:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAVによる車両検出：Faster R-CNNとYOLOv3の比較（Car Detection using Unmanned Aerial Vehicles: Comparison between Faster R-CNN and YOLOv3）</news:title>
   <news:publication_date>2026-07-22T04:26:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714554</loc>
  <lastmod>2026-07-22T04:26:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カスケード拡散を扱う変分トポロジカルニューラルモデル（A Variational Topological Neural Model for Cascade-based Diffusion in Networks）</news:title>
   <news:publication_date>2026-07-22T04:26:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714552</loc>
  <lastmod>2026-07-22T04:26:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体指向の予測と計画による物理相互作用の思考（Reasoning about Physical Interactions with Object-Oriented Prediction and Planning）</news:title>
   <news:publication_date>2026-07-22T04:26:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714550</loc>
  <lastmod>2026-07-22T04:25:53Z</lastmod>
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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>2026-07-22T04:25:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-22T04:25:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
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  <lastmod>2026-07-22T04:25:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>がん薬感受性予測の深層学習的前進（tCNNS: Convolutional Neural Networks for Drug Response Prediction）</news:title>
   <news:publication_date>2026-07-22T04:25:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714544</loc>
  <lastmod>2026-07-22T04:25:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wikibook-BotによるWikipedia本の自動生成（Wikibook-Bot - Automatic Generation of a Wikipedia Book）</news:title>
   <news:publication_date>2026-07-22T04:25:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714542</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>画像ラベルのみからの粗から細への意味セグメンテーション（Coarse-to-fine Semantic Segmentation from Image-level Labels）</news:title>
   <news:publication_date>2026-07-22T03:33:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714540</loc>
  <lastmod>2026-07-22T03:24:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピアノ伴奏を伴うポップソング自動メロディ生成フレームワーク (A Framework for Automated Pop-song Melody Generation with Piano Accompaniment Arrangement)</news:title>
   <news:publication_date>2026-07-22T03:24:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714538</loc>
  <lastmod>2026-07-22T03:24:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッシブ・アグレッシブ学習と制御（Passive-Aggressive Learning and Control）</news:title>
   <news:publication_date>2026-07-22T03:24:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714536</loc>
  <lastmod>2026-07-22T03:24:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発散トライアングルによる生成器・エネルギー型・推論モデルの共同学習（Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model）</news:title>
   <news:publication_date>2026-07-22T03:24:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714534</loc>
  <lastmod>2026-07-22T03:23:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識表現学習の定量的レビュー（Knowledge Representation Learning: A Quantitative Review）</news:title>
   <news:publication_date>2026-07-22T03:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714532</loc>
  <lastmod>2026-07-22T03:23:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カリカチュアで明らかになる顔表現の構造（Deep Convolutional Neural Networks in the Face of Caricature: Identity and Image Revealed）</news:title>
   <news:publication_date>2026-07-22T03:23:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714530</loc>
  <lastmod>2026-07-22T03:23:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス意識型画像変換の実務的意義（INSTAGAN: INSTANCE-AWARE IMAGE-TO-IMAGE TRANSLATION）</news:title>
   <news:publication_date>2026-07-22T03:23:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714528</loc>
  <lastmod>2026-07-22T02:32:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフのクラスタリング：モジュラリティ最大化アプローチ（Hypergraph Clustering: A Modularity Maximization Approach）</news:title>
   <news:publication_date>2026-07-22T02:32:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714526</loc>
  <lastmod>2026-07-22T02:31:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化スパース性に基づく信号分類の新枠組み（Structured Sparsity Models for Classification）</news:title>
   <news:publication_date>2026-07-22T02:31:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714524</loc>
  <lastmod>2026-07-22T02:31:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文単位の事前学習と言語モデリングを超えて（Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling）</news:title>
   <news:publication_date>2026-07-22T02:31:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714522</loc>
  <lastmod>2026-07-22T02:31:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散版CMA-ESの提案（A discrete version of CMA-ES）</news:title>
   <news:publication_date>2026-07-22T02:31:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714520</loc>
  <lastmod>2026-07-22T02:31:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変数の離散化とコスト感度ロジスティック回帰による不均衡信用データの改善（A Descriptive Study of Variable Discretization and Cost-Sensitive Logistic Regression on Imbalanced Credit Data）</news:title>
   <news:publication_date>2026-07-22T02:31:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714518</loc>
  <lastmod>2026-07-22T02:30:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Clickbait検出チャレンジが示した実務的教訓（The Clickbait Challenge 2017: Towards a Regression Model for Clickbait Strength）</news:title>
   <news:publication_date>2026-07-22T02:30:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714516</loc>
  <lastmod>2026-07-22T02:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セミパラメトリック差の差分法と高次元制御変数（Semiparametric Difference-in-Differences with Potentially Many Control Variables）</news:title>
   <news:publication_date>2026-07-22T02:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714514</loc>
  <lastmod>2026-07-22T01:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による適応的画像サンプリングとXRF再構成への応用（Adaptive Image Sampling using Deep Learning and its Application on X-Ray Fluorescence Image Reconstruction）</news:title>
   <news:publication_date>2026-07-22T01:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714512</loc>
  <lastmod>2026-07-22T01:39:12Z</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>2026-07-22T01:39:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714510</loc>
  <lastmod>2026-07-22T01:38:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープビルボード：物理世界での自動運転テスト（DeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems）</news:title>
   <news:publication_date>2026-07-22T01:38:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714508</loc>
  <lastmod>2026-07-22T01:37:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波（mmWave）ネットワークにおけるバックホール容量制約への深層強化学習による対処（Dealing with Limited Backhaul Capacity in Millimeter Wave Systems: A Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-07-22T01:37:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714506</loc>
  <lastmod>2026-07-22T01:37:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化されたストリーム学習の適応戦略（Automated Adaptation Strategies for Stream Learning）</news:title>
   <news:publication_date>2026-07-22T01:37:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714504</loc>
  <lastmod>2026-07-22T01:37:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による量子断熱アルゴリズム設計（Quantum Adiabatic Algorithm Design using Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-22T01:37:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714502</loc>
  <lastmod>2026-07-22T01:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドラウプナー波の早期検出に向けた深層学習の適用（Early Detection of the Draupner Wave Using Deep Learning）</news:title>
   <news:publication_date>2026-07-22T01:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714500</loc>
  <lastmod>2026-07-22T00:45:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きな時間変動を持つタイムラプス動画の未来フレーム意味セグメンテーション（Future frame semantic segmentation of time-lapsed videos with large temporal displacement）</news:title>
   <news:publication_date>2026-07-22T00:45:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714498</loc>
  <lastmod>2026-07-22T00:45:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相制約に基づくホームオモルフィック自己符号化の限界と指針（Topological Constraints on Homeomorphic Auto-Encoding）</news:title>
   <news:publication_date>2026-07-22T00:45:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714496</loc>
  <lastmod>2026-07-22T00:45:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的にパラメータ化された分布でGANを評価する意味（Evaluating Generative Adversarial Networks on Explicitly Parameterized Distributions）</news:title>
   <news:publication_date>2026-07-22T00:45:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714494</loc>
  <lastmod>2026-07-22T00:44:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dポイントカプセルネットワーク（3D Point Capsule Networks）</news:title>
   <news:publication_date>2026-07-22T00:44:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714492</loc>
  <lastmod>2026-07-22T00:44:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結合隠れ因子を用いたニューラルネットワークによる終端間話者認識（Tied Hidden Factors in Neural Networks for End-to-End Speaker Recognition）</news:title>
   <news:publication_date>2026-07-22T00:44:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714490</loc>
  <lastmod>2026-07-22T00:44:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者負荷のマルチタスク予測（Multi-task Prediction of Patient Workload）</news:title>
   <news:publication_date>2026-07-22T00:44:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714488</loc>
  <lastmod>2026-07-22T00:43:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バグ修正から学ぶソースコードの変異生成（Learning How to Mutate Source Code from Bug-Fixes）</news:title>
   <news:publication_date>2026-07-22T00:43:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714486</loc>
  <lastmod>2026-07-21T23:53:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SMPLRによる3D人体姿勢と形状復元（SMPLR: Deep SMPL reverse for 3D human pose and shape recovery）</news:title>
   <news:publication_date>2026-07-21T23:53:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714484</loc>
  <lastmod>2026-07-21T23:52:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マージン分布でニューラルネットの汎化を制御する（Improving Generalization of Deep Neural Networks by Leveraging Margin Distribution）</news:title>
   <news:publication_date>2026-07-21T23:52:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714482</loc>
  <lastmod>2026-07-21T23:52:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフ・ザ・グリッドモデルに基づく深層学習（OFF-THE-GRID MODEL BASED DEEP LEARNING (O-MODL)）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-07-21T23:52:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis（Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-07-21T23:52:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3次元幾何整合性で学ぶ半教師ありセマンティックセグメンテーション（S4-Net: Geometry-Consistent Semi-Supervised Semantic Segmentation）</news:title>
   <news:publication_date>2026-07-21T23:52:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714476</loc>
  <lastmod>2026-07-21T23:51:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表面ネットワークと一般被覆（Surface Networks via General Covers）</news:title>
   <news:publication_date>2026-07-21T23:51:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714474</loc>
  <lastmod>2026-07-21T23:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>F4R上のスキュー巡回符号（Skew Cyclic Codes over F4R）</news:title>
   <news:publication_date>2026-07-21T23:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714472</loc>
  <lastmod>2026-07-21T23:00:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載エッジコンピューティングと深層強化学習（Vehicular Edge Computing via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-21T23:00:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714470</loc>
  <lastmod>2026-07-21T23:00:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク認識型生成的不確実性による分布外入力への堅牢性（Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty）</news:title>
   <news:publication_date>2026-07-21T23:00:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714468</loc>
  <lastmod>2026-07-21T23:00:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ探索空間によるニューラルアーキテクチャ探索の拡張（Neural Architecture Search Over a Graph Search Space）</news:title>
   <news:publication_date>2026-07-21T23:00:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714466</loc>
  <lastmod>2026-07-21T22:59:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層分離で高速化する分散深層学習（Stanza: Layer Separation for Distributed Training in Deep Learning）</news:title>
   <news:publication_date>2026-07-21T22:59:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714464</loc>
  <lastmod>2026-07-21T22:59:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低遅延でプライバシーを守る推論の実現（Low Latency Privacy Preserving Inference）</news:title>
   <news:publication_date>2026-07-21T22:59:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714462</loc>
  <lastmod>2026-07-21T22:59:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークを用いたグレースケール画像の自動色付け（Sampling using Neural Networks for colorizing the grayscale images）</news:title>
   <news:publication_date>2026-07-21T22:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714460</loc>
  <lastmod>2026-07-21T22:59:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース非負CANDECOMP/PARAFAC分解の比較研究（Sparse Nonnegative CANDECOMP/PARAFAC Decomposition in Block Coordinate Descent Framework: A Comparison Study）</news:title>
   <news:publication_date>2026-07-21T22:59:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714458</loc>
  <lastmod>2026-07-21T22:07:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低コスト自動医療診断デバイスの試作（Low-Cost Device Prototype for Automatic Medical Diagnosis Using Deep Learning Methods）</news:title>
   <news:publication_date>2026-07-21T22:07:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714456</loc>
  <lastmod>2026-07-21T21:49:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳領域とディスレクシアの相関・分類のための特徴量と機械学習（Features and Machine Learning for Correlating and Classifying between Brain Areas and Dyslexia）</news:title>
   <news:publication_date>2026-07-21T21:49:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714454</loc>
  <lastmod>2026-07-21T21:49:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データマニフォールドの双線形モデリングによる動的MRI復元（Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery）</news:title>
   <news:publication_date>2026-07-21T21:49:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714452</loc>
  <lastmod>2026-07-21T21:49:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フロンティア市場における修正版Black‑Scholesと機械学習による株価予測（Predicting the Stock Price of Frontier Markets Using Modified Black‑Scholes Option Pricing Model and Machine Learning）</news:title>
   <news:publication_date>2026-07-21T21:49:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714450</loc>
  <lastmod>2026-07-21T21:48:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的敵対的ユーザモデルによる強化学習推薦（Generative Adversarial User Model for Reinforcement Learning Based Recommendation System）</news:title>
   <news:publication_date>2026-07-21T21:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714448</loc>
  <lastmod>2026-07-21T21:48:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制御語彙の埋め込みで捉えるトランスレーショナル科学（Identifying translational science through embeddings of controlled vocabularies）</news:title>
   <news:publication_date>2026-07-21T21:48:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714446</loc>
  <lastmod>2026-07-21T21:48:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重ニューラル・カウンターファクチュアル後悔最小化（Double Neural Counterfactual Regret Minimization）</news:title>
   <news:publication_date>2026-07-21T21:48:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714444</loc>
  <lastmod>2026-07-21T20:56:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠隔教師あり学習におけるクロスリレーション・クロスバッグ注意機構（Cross-relation Cross-bag Attention for Distantly-supervised Relation Extraction）</news:title>
   <news:publication_date>2026-07-21T20:56:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714442</loc>
  <lastmod>2026-07-21T20:56:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜画像を用いた糖尿病性網膜症の早期検出と重症度評価（Deep Learning based Early Detection and Grading of Diabetic Retinopathy Using Retinal Fundus Images）</news:title>
   <news:publication_date>2026-07-21T20:56:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714440</loc>
  <lastmod>2026-07-21T20:55:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-21T20:55:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714438</loc>
  <lastmod>2026-07-21T20:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>システムレベル熱流体シミュレーションにおける誤差推定とメッシュ・モデル最適化のデータ駆動フレームワーク（A Data-driven Framework for Error Estimation and Mesh-Model Optimization in System-level Thermal-Hydraulic Simulation）</news:title>
   <news:publication_date>2026-07-21T20:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714436</loc>
  <lastmod>2026-07-21T20:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速データ駆動型MPCを実現する線形化ガウス過程（Linearized Gaussian Processes for Fast Data-driven Model Predictive Control）</news:title>
   <news:publication_date>2026-07-21T20:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714434</loc>
  <lastmod>2026-07-21T20:55:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習可能な動的生成モデルと交互時系列逆伝播（Learning Dynamic Generator Model by Alternating Back-Propagation Through Time）</news:title>
   <news:publication_date>2026-07-21T20:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714432</loc>
  <lastmod>2026-07-21T20:55:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユークリッド空間データの階層クラスタリング改良（Hierarchical Clustering for Euclidean Data）</news:title>
   <news:publication_date>2026-07-21T20:55:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714430</loc>
  <lastmod>2026-07-21T20:04:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察データ下での交絡除去強化学習（Deconfounding Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-21T20:04:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714428</loc>
  <lastmod>2026-07-21T20:03:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QuickSelによる迅速な選択性学習（QuickSel: Quick Selectivity Learning with Mixture Models）</news:title>
   <news:publication_date>2026-07-21T20:03:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714426</loc>
  <lastmod>2026-07-21T20:03:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間ライトシートの自己修復（Self-healing of space-time light sheets）</news:title>
   <news:publication_date>2026-07-21T20:03:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714424</loc>
  <lastmod>2026-07-21T20:02:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BlinkMLによる高速かつ確率的保証付きの学習（BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees）</news:title>
   <news:publication_date>2026-07-21T20:02:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714422</loc>
  <lastmod>2026-07-21T20:02:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画からの2D→3D顔復元による虚偽検出（Deception Detection by 2D-to-3D Face Reconstruction from Videos）</news:title>
   <news:publication_date>2026-07-21T20:02:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714420</loc>
  <lastmod>2026-07-21T20:02:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負データのための一般化スコアマッチング（Generalized Score Matching for Non-Negative Data）</news:title>
   <news:publication_date>2026-07-21T20:02:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714418</loc>
  <lastmod>2026-07-21T20:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新しい骨格ベース表現による3D人体動作認識（Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-21T20:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714416</loc>
  <lastmod>2026-07-21T19:10:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ℓ0,∞に基づく畳み込みスパースコーディングへの貪欲法（A Greedy Approach to ℓ0,∞Based Convolutional Sparse Coding）</news:title>
   <news:publication_date>2026-07-21T19:10:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714414</loc>
  <lastmod>2026-07-21T19:10:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性オートエンコーダによる圧縮表現学習（Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization）</news:title>
   <news:publication_date>2026-07-21T19:10:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714412</loc>
  <lastmod>2026-07-21T19:10:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースな暗黙的フィードバックに対する深層アイテムベース協調フィルタリング（Deep Item-based Collaborative Filtering for Sparse Implicit Feedback）</news:title>
   <news:publication_date>2026-07-21T19:10:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714410</loc>
  <lastmod>2026-07-21T19:09:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号化投影からのライトフィールド再構築を統一的に扱う学習フレームワーク（A Unified Learning Based Framework for Light Field Reconstruction from Coded Projections）</news:title>
   <news:publication_date>2026-07-21T19:09:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714408</loc>
  <lastmod>2026-07-21T19:09:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己学習型スマートコントラクトの可能性（Toward a self-learned Smart Contracts）</news:title>
   <news:publication_date>2026-07-21T19:09:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-07-21T19:08:49Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>グラフデータに対する敵対的攻撃と防御の概観（Adversarial Attack and Defense on Graph Data）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業プロセスのパラメータ予測に関する機械学習の実用化（Prediction of Industrial Process Parameters using Artificial Intelligence Algorithms）</news:title>
   <news:publication_date>2026-07-21T19:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模多言語文センテンス埋め込みによるゼロショット転移の実現（Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond）</news:title>
   <news:publication_date>2026-07-21T18:17:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在変数モデリングによる生成概念表現（Latent Variable Modeling for Generative Concept Representations and Deep Generative Models）</news:title>
   <news:publication_date>2026-07-21T18:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生涯事実学習（Exploring the Challenges towards Lifelong Fact Learning）</news:title>
   <news:publication_date>2026-07-21T18:11:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-21T18:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤観測ネットワークにおける最尤推定とグラフマッチング（Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks）</news:title>
   <news:publication_date>2026-07-21T18:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/714394</loc>
  <lastmod>2026-07-21T18:10:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSSTによるキロノヴァの偶発的検出がもたらす変化（Serendipitous Discoveries of Kilonovae in the LSST Main Survey: Maximising Detections of Sub-Threshold Gravitational Wave Events）</news:title>
   <news:publication_date>2026-07-21T18:10:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/714392</loc>
  <lastmod>2026-07-21T18:10:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓移植患者の詳細な心機能解析を可能にする計算モデルの応用（Deep phenotyping of cardiac function in heart transplant patients using cardiovascular systems models）</news:title>
   <news:publication_date>2026-07-21T18:10:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/714390</loc>
  <lastmod>2026-07-21T18:09:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分画像解析に機械学習を適用する比較研究（Machine Learning on Difference Image Analysis: A comparison of methods for transient detection）</news:title>
   <news:publication_date>2026-07-21T18:09:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/714388</loc>
  <lastmod>2026-07-21T17:18:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数アクセスネットワーク上の疎なGGMの構造学習（Structure Learning of Sparse GGMs over Multiple Access Networks）</news:title>
   <news:publication_date>2026-07-21T17:18:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/714386</loc>
  <lastmod>2026-07-21T17:17:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助ニューラルネットワークで週末・祝日を扱う隣接（アジョイント）ネットワーク（Using an Ancillary Neural Network to Capture Weekends and Holidays in an Adjoint Neural Network Architecture for Intelligent Building Management）</news:title>
   <news:publication_date>2026-07-21T17:17:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/714384</loc>
  <lastmod>2026-07-21T17:17:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>製造業の大規模マルチストリーム監視と診断の統合手法（Large Multistream Data Analytics for Monitoring and Diagnostics in Manufacturing Systems）</news:title>
   <news:publication_date>2026-07-21T17:17:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/714382</loc>
  <lastmod>2026-07-21T17:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模機械学習のための確率的信頼領域不完全ニュートン法（Stochastic Trust Region Inexact Newton Method for Large-scale Machine Learning）</news:title>
   <news:publication_date>2026-07-21T17:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/714380</loc>
  <lastmod>2026-07-21T17:16:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>心電図（ECG）セグメンテーションと誤り訂正の実践的示唆（ECG Segmentation by Neural Networks: Errors and Correction）</news:title>
   <news:publication_date>2026-07-21T17:16:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/714378</loc>
  <lastmod>2026-07-21T17:16:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Androidマルウェア検出における深層学習の応用レビュー（A Review on The Use of Deep Learning in Android Malware Detection）</news:title>
   <news:publication_date>2026-07-21T17:16:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/714376</loc>
  <lastmod>2026-07-21T17:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実顕微鏡画像のノイズ特性に合わせたデータセットとその示唆（A Poisson-Gaussian Denoising Dataset with Real Fluorescence Microscopy Images）</news:title>
   <news:publication_date>2026-07-21T17:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/714374</loc>
  <lastmod>2026-07-21T16:24:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報量に基づく物体アノテーション選択（INFORMATIVE OBJECT ANNOTATIONS）</news:title>
   <news:publication_date>2026-07-21T16:24:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/714372</loc>
  <lastmod>2026-07-21T16:24:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏ったデータで「学ばせない」ための訓練法（Learning Not to Learn: Training Deep Neural Networks with Biased Data）</news:title>
   <news:publication_date>2026-07-21T16:24:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714370</loc>
  <lastmod>2026-07-21T16:23:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子化対話言語モデルが変えたもの（Quantized-Dialog Language Model for Goal-Oriented Conversational Systems）</news:title>
   <news:publication_date>2026-07-21T16:23:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714368</loc>
  <lastmod>2026-07-21T16:23:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地下鉄到着表示が乗客数に与える影響（The Impact of Countdown Clocks on Subway Ridership in New York City）</news:title>
   <news:publication_date>2026-07-21T16:23:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714366</loc>
  <lastmod>2026-07-21T16:23:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>医用画像における文脈選択的注意を用いた領域提案ネットワーク（Region Proposal Networks with Contextual Selective Attention for Real-Time Organ Detection）</news:title>
   <news:publication_date>2026-07-21T16:23:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/714364</loc>
  <lastmod>2026-07-21T16:22:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるアンテナ選択が変える無信頼リレーネットワーク（Machine Learning-Based Antenna Selection in Untrusted Relay Networks）</news:title>
   <news:publication_date>2026-07-21T16:22:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714362</loc>
  <lastmod>2026-07-21T16:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的解析レポートをそのまま使うマルウェア検出の実務フレームワーク（MalDy: Portable, Data-Driven Malware Detection using Natural Language Processing and Machine Learning Techniques on Behavioral Analysis Reports）</news:title>
   <news:publication_date>2026-07-21T16:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714360</loc>
  <lastmod>2026-07-21T15:31:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数の大きな地震イメージから地層境界を追跡する手法（Multi-resolution neural networks for tracking seismic horizons from few training images）</news:title>
   <news:publication_date>2026-07-21T15:31:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714358</loc>
  <lastmod>2026-07-21T15:13:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現実世界でロボットに歩かせる学習（Learning to Walk via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-21T15:13:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714356</loc>
  <lastmod>2026-07-21T15:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短いヒングリッシュ文の筆者帰属における教師あり学習法の考察（An Investigation of Supervised Learning Methods for Authorship Attribution in Short Hinglish Texts using Char &amp;amp; Word N-grams）</news:title>
   <news:publication_date>2026-07-21T15:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714354</loc>
  <lastmod>2026-07-21T15:12:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DUNEでの非標準ニュートリノ相互作用（NSI）と可変ビームによるパラメータ相関の可視化（Correlations and degeneracies among the NSI parameters with tunable beams at DUNE）</news:title>
   <news:publication_date>2026-07-21T15:12:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714352</loc>
  <lastmod>2026-07-21T15:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未教師付ドメイン適応のためのCORAL+（THE CORAL+ ALGORITHM FOR UNSUPERVISED DOMAIN ADAPTATION OF PLDA）</news:title>
   <news:publication_date>2026-07-21T15:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714350</loc>
  <lastmod>2026-07-21T15:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチエージェント強化学習によるマーケットメイクの最適化（Optimizing Market Making using Multi-Agent Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-21T15:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714348</loc>
  <lastmod>2026-07-21T15:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層顔属性解析の総覧（A Survey of Deep Facial Attribute Analysis）</news:title>
   <news:publication_date>2026-07-21T15:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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