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   <news:title>実務に効くスキル管理ツールの運用知見（Practical Knowledge Management Tool Use in a Software Consulting Company）</news:title>
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   <news:title>VUDSによる高赤方偏移銀河のUV・Lyα輝度関数と星形成率密度の評価（The UV and Lyα Luminosity Functions of galaxies and the Star Formation Rate Density at the end of HI reionization from the VIMOS Ultra-Deep Survey (VUDS)）</news:title>
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   <news:title>小型銀河の未来研究と望遠鏡の発見（The Future of Dwarf Galaxy Research: What Telescopes Will Discover）</news:title>
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   <news:title>分類モデルの“写し”を作る技術（COPYING MACHINE LEARNING CLASSIFIERS）</news:title>
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    <news:language>ja</news:language>
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   <news:title>滑らかなカーネル正則化を学習する（Learning a smooth kernel regularizer for convolutional neural networks）</news:title>
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   <news:title>IoTネットワークにおけるエッジ計算の資源配分を強化学習で解く（Resource Allocation for Edge Computing in IoT Networks via Reinforcement Learning）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>歩行者軌跡予測のための確率的サンプリングシミュレーション（Stochastic Sampling Simulation for Pedestrian Trajectory Prediction）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>多変量時系列の未識別クラスを復元・クラスタリングする多重カーネル辞書学習（Multiple-Kernel Dictionary Learning for Reconstruction and Clustering of Unseen Multivariate Time-series）</news:title>
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   <news:title>キラル相互作用を持つLebwohl–Lasher模型における変調構造（Modulated structures in a Lebwohl-Lasher model with chiral interactions）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>非凸・非滑らか最適化のための慣性ブロック近接法（Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization）</news:title>
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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>Branch-and-Boundを機械学習で高速化する手法（Learning to Branch: Accelerating Resource Allocation in Wireless Networks）</news:title>
   <news:publication_date>2026-08-14T07:02:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-14T07:02:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>miniTimeCubeによる中性子散乱カメラ（miniTimeCube as a neutron scatter camera）</news:title>
   <news:publication_date>2026-08-14T07:02:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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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>六角格子データをそのまま扱う畳み込み（HexagDLy — Processing hexagonally sampled data with CNNs in PyTorch）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>床図を使ったロボット位置推定と部屋境界抽出ネットワーク（Robot Localization in Floor Plans Using a Room Layout Edge Extraction Network）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>多ブロックADMMにおけるランダム化の管理（Managing Randomization in the Multi-Block Alternating Direction Method of Multipliers for Quadratic Optimization）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-14T06:09:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Shape Completionを活用した3D Siameseトラッキングの実用性（Leveraging Shape Completion for 3D Siamese Tracking）</news:title>
   <news:publication_date>2026-08-14T06:09:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-14T06:09:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>中国チェッカーを理解するための探索と学習の統合（Towards Understanding Chinese Checkers with Heuristics, Monte Carlo Tree Search, and Deep Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-14T06:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>金融時系列予測のためのデータ駆動型ニューラルアーキテクチャ学習（Data-driven Neural Architecture Learning for Financial Time-series Forecasting）</news:title>
   <news:publication_date>2026-08-14T06:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-14T06:08:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Maximal Leakageによる適応的データ解析の新しい枠組み（A New Approach to Adaptive Data Analysis and Learning via Maximal Leakage）</news:title>
   <news:publication_date>2026-08-14T06:08:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-14T05:17:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>説明可能な人工知能のためのデータに基づく対話プロトコル（A Grounded Interaction Protocol for Explainable Artificial Intelligence）</news:title>
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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>SZZ Unleashed：SZZアルゴリズムの公開実装とJenkinsを用いたJITバグ予測の適用事例（SZZ Unleashed: An Open Implementation of the SZZ Algorithm）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-14T05:16:55Z</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>モデルの所有権を証明する手法（Your Model Belongs to You: A Blind-Watermark based Framework to Protect Intellectual Property of DNN）</news:title>
   <news:publication_date>2026-08-14T05:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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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>新規性検出の確率的モデリングと不正検知への応用（Probabilistic Modeling for Novelty Detection with Applications to Fraud Identification）</news:title>
   <news:publication_date>2026-08-14T05:15:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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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>OMPベースのスパース部分空間クラスタリングに対するデータ適応型の効率的アプローチ（A Novel Efficient Approach with Data-Adaptive Capability for OMP-based Sparse Subspace Clustering）</news:title>
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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>ネットワーク零和ゲームにおけるマルチエージェント学習はハミルトン系である（Multi-Agent Learning in Network Zero-Sum Games is a Hamiltonian System）</news:title>
   <news:publication_date>2026-08-14T05:15:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-14T05:14:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>病理報告の自動分類とTF‑IDFの現実適用（Automatic Classification of Pathology Reports using TF-IDF Features）</news:title>
   <news:publication_date>2026-08-14T05:14:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/722988</loc>
  <lastmod>2026-08-14T04:22:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教育におけるブロックチェーンの可能性（Blockchain and its Potential in Education）</news:title>
   <news:publication_date>2026-08-14T04:22:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/722986</loc>
  <lastmod>2026-08-14T04:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ埋め込みが与信・不正検知に与える実証的効果（Empirical effect of graph embeddings on fraud detection/ risk mitigation）</news:title>
   <news:publication_date>2026-08-14T04:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/722984</loc>
  <lastmod>2026-08-14T04:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>L1-normダブルバックプロパゲーションによる敵対的防御（L1-norm double backpropagation adversarial defense）</news:title>
   <news:publication_date>2026-08-14T04:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/722982</loc>
  <lastmod>2026-08-14T04:21:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称に緩和した分布整合によるドメイン適応（Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment）</news:title>
   <news:publication_date>2026-08-14T04:21:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-08-14T04:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>EdgeStereoによるステレオマッチングとエッジ検出の統合（EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection）</news:title>
   <news:publication_date>2026-08-14T04:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-14T04:21:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転車の時空間LSTMによる深層学習モーションプランニング（Deep Learning Based Motion Planning For Autonomous Vehicle Using Spatiotemporal LSTM Network）</news:title>
   <news:publication_date>2026-08-14T04:21:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/722976</loc>
  <lastmod>2026-08-14T04:21:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道徳性の複雑性：マルコフブランケットとグラフの道徳性の検査（The Complexity of Morality: Checking Markov Blanket Consistency with DAGs via Morality）</news:title>
   <news:publication_date>2026-08-14T04:21:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/722974</loc>
  <lastmod>2026-08-14T03:29:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種／非定常データからの因果発見と独立変化の原理（Causal Discovery from Heterogeneous/Nonstationary Data with Independent Changes）</news:title>
   <news:publication_date>2026-08-14T03:29:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722972</loc>
  <lastmod>2026-08-14T03:21:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共益特徴量の凸的クラスタリングによる分類改善（Convex Covariate Clustering for Classification）</news:title>
   <news:publication_date>2026-08-14T03:21:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722970</loc>
  <lastmod>2026-08-14T03:20:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多車線交通速度予測における二流多チャネル畳み込みニューラルネットワーク（Two‑Stream Multi‑Channel Convolutional Neural Network (TM‑CNN) for Multi‑Lane Traffic Speed Prediction Considering Traffic Volume Impact）</news:title>
   <news:publication_date>2026-08-14T03:20:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722968</loc>
  <lastmod>2026-08-14T03:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U統計量のための濃度に基づく信頼区間（Concentration-based confidence intervals for U-statistics）</news:title>
   <news:publication_date>2026-08-14T03:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722966</loc>
  <lastmod>2026-08-14T03:19:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的深層局所化（Deep Active Localization）</news:title>
   <news:publication_date>2026-08-14T03:19:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722964</loc>
  <lastmod>2026-08-14T03:19:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインデータポイズニング攻撃（Online Data Poisoning Attacks）</news:title>
   <news:publication_date>2026-08-14T03:19:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722962</loc>
  <lastmod>2026-08-14T03:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HEVC向け多フレームIn-Loopフィルタ（A DenseNet Based Approach for Multi-Frame In-Loop Filter in HEVC）</news:title>
   <news:publication_date>2026-08-14T03:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722960</loc>
  <lastmod>2026-08-14T02:27:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配降下―上昇の収束解析（Convergence of gradient descent-ascent analyzed as a Newtonian dynamical system with dissipation）</news:title>
   <news:publication_date>2026-08-14T02:27:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722958</loc>
  <lastmod>2026-08-14T02:26:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェア向けストリーミング低ランク更新法（Streaming Batch Eigenupdates for Hardware Neuromorphic Networks）</news:title>
   <news:publication_date>2026-08-14T02:26:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722956</loc>
  <lastmod>2026-08-14T02:26:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NVDLAをRISC-V SoCに統合しFireSimで評価する意義（Integrating NVIDIA Deep Learning Accelerator (NVDLA) with RISC-V SoC on FireSim）</news:title>
   <news:publication_date>2026-08-14T02:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722954</loc>
  <lastmod>2026-08-14T02:26:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習初期の「再ウィンド（rewinding）」で当たりくじを安定化する方法（Stabilizing the Lottery Ticket Hypothesis）</news:title>
   <news:publication_date>2026-08-14T02:26:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722952</loc>
  <lastmod>2026-08-14T02:25:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェブ規模最近傍検索を用いた敵対的画像に対する防御（Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search）</news:title>
   <news:publication_date>2026-08-14T02:25:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722950</loc>
  <lastmod>2026-08-14T02:25:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初代星（Population III）の対崩壊（Pair-Instability）超新星探索の展望（Searches for Population III pair-instability supernovae: Predictions for ULTIMATE-Subaru and WFIRST）</news:title>
   <news:publication_date>2026-08-14T02:25:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722948</loc>
  <lastmod>2026-08-14T02:25:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損特徴を伴うロジスティック回帰の期待予測と埋め込み手法（What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features）</news:title>
   <news:publication_date>2026-08-14T02:25:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722946</loc>
  <lastmod>2026-08-14T01:34:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在拡散過程を用いる生成モデルの理論的保証（Theoretical guarantees for sampling and inference in generative models with latent diffusions）</news:title>
   <news:publication_date>2026-08-14T01:34:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722944</loc>
  <lastmod>2026-08-14T01:33:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフデータに対する敵対的事例の攻防（Adversarial Examples on Graph Data: Deep Insights into Attack and Defense）</news:title>
   <news:publication_date>2026-08-14T01:33:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722942</loc>
  <lastmod>2026-08-14T01:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超高エネルギー中性ニュートリノの探索を目指すARIANNA実験（Targeting ultra-high energy neutrinos with the ARIANNA experiment）</news:title>
   <news:publication_date>2026-08-14T01:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722940</loc>
  <lastmod>2026-08-14T01:33:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>後悔するエージェント：進捗推定を用いたヒューリスティック支援ナビゲーション（The Regretful Agent: Heuristic-Aided Navigation through Progress Estimation）</news:title>
   <news:publication_date>2026-08-14T01:33:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722938</loc>
  <lastmod>2026-08-14T01:32:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期的未来を取り入れた強化学習における動力学モデル学習（LEARNING DYNAMICS MODEL IN REINFORCEMENT LEARNING BY INCORPORATING THE LONG TERM FUTURE）</news:title>
   <news:publication_date>2026-08-14T01:32:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722936</loc>
  <lastmod>2026-08-14T01:32:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PRIDEを用いた金星探査機の電波掩蔽観測（Venus Express radio occultation observed by PRIDE）</news:title>
   <news:publication_date>2026-08-14T01:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722934</loc>
  <lastmod>2026-08-14T01:32:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かなロボットシステムのための制御ラプノフ関数を用いたエピソディック学習（Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems）</news:title>
   <news:publication_date>2026-08-14T01:32:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722932</loc>
  <lastmod>2026-08-14T00:41:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群体フォトメトリック赤方偏移（Ensemble Photometric Redshifts）</news:title>
   <news:publication_date>2026-08-14T00:41:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722930</loc>
  <lastmod>2026-08-14T00:41:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>V2X向けハイブリッドGaussian Processベース通信アーキテクチャ（V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structures）</news:title>
   <news:publication_date>2026-08-14T00:41:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722928</loc>
  <lastmod>2026-08-14T00:41:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QickStopによる誤情報の最速検出（QuickStop: A Markov Optimal Stopping Approach for Quickest Misinformation Detection）</news:title>
   <news:publication_date>2026-08-14T00:41:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722926</loc>
  <lastmod>2026-08-14T00:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルプリミティブ階層的ライフロング強化学習（Model Primitive Hierarchical Lifelong Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-14T00:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722924</loc>
  <lastmod>2026-08-14T00:40:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模画像検索のための教師なしランク保存ハッシング（Unsupervised Rank-Preserving Hashing for Large-Scale Image Retrieval）</news:title>
   <news:publication_date>2026-08-14T00:40:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722922</loc>
  <lastmod>2026-08-14T00:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的トラストリージョン法による非凸最適化の効率化（A Stochastic Trust Region Method for Non-convex Minimization）</news:title>
   <news:publication_date>2026-08-14T00:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722920</loc>
  <lastmod>2026-08-14T00:39:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期宇宙の“最初の爆発”をELTで追う意義（ELT Contributions to The First Explosions）</news:title>
   <news:publication_date>2026-08-14T00:39:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722918</loc>
  <lastmod>2026-08-13T23:48:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択的センサフュージョンによるニューラル視覚慣性測位（Selective Sensor Fusion for Neural Visual-Inertial Odometry）</news:title>
   <news:publication_date>2026-08-13T23:48:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722916</loc>
  <lastmod>2026-08-13T23:48:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転車の希少事象サンプリングに対する行動駆動アプローチ（A behavior driven approach for sampling rare event situations for autonomous vehicles）</news:title>
   <news:publication_date>2026-08-13T23:48:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722914</loc>
  <lastmod>2026-08-13T23:48:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群体認知と多主体対話の計算モデル（MGPI: A Computational Model of Multiagent Group Perception and Interaction）</news:title>
   <news:publication_date>2026-08-13T23:48:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722912</loc>
  <lastmod>2026-08-13T23:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きな横方向運動量の半包摂的深陽電子散乱における2次摂動の再検証（Large Transverse Momentum in Semi-Inclusive Deeply Inelastic Scattering Beyond Lowest Order）</news:title>
   <news:publication_date>2026-08-13T23:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722910</loc>
  <lastmod>2026-08-13T23:46:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列知識蒸留による能動的知覚の効率化（TKD: Temporal Knowledge Distillation for Active Perception）</news:title>
   <news:publication_date>2026-08-13T23:46:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722908</loc>
  <lastmod>2026-08-13T23:46:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像のデヘイジングをセグメンテーション向けに学習する意義（Learning of Image Dehazing Models for Segmentation Tasks）</news:title>
   <news:publication_date>2026-08-13T23:46:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722906</loc>
  <lastmod>2026-08-13T23:46:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約の厳しいIoT向け三値ハイブリッドニューラル・ツリーネットワーク（Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications）</news:title>
   <news:publication_date>2026-08-13T23:46:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722904</loc>
  <lastmod>2026-08-13T22:54:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットで導く強線酸素同位体較正（A Machine Learning Artificial Neural Network Calibration of the Strong-Line Oxygen Abundance）</news:title>
   <news:publication_date>2026-08-13T22:54:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722902</loc>
  <lastmod>2026-08-13T22:53:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルCPU向けWinograd／Cook‑Toom畳み込みの高効率実装（Efficient Winograd or Cook‑Toom Convolution Kernel Implementation on Widely Used Mobile CPUs）</news:title>
   <news:publication_date>2026-08-13T22:53:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722900</loc>
  <lastmod>2026-08-13T22:53:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再イオン化期の銀河で大量のLyman連続放射（LyC）漏洩を見つける方法（Identifying reionization-epoch galaxies with extreme levels of Lyman continuum leakage in James Webb Space Telescope surveys）</news:title>
   <news:publication_date>2026-08-13T22:53:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722898</loc>
  <lastmod>2026-08-13T22:52:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習と量子物理の融合（Machine Learning meets Quantum Physics）</news:title>
   <news:publication_date>2026-08-13T22:52:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722896</loc>
  <lastmod>2026-08-13T22:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OPT-AMSGradによる非凸最適化の楽観的加速（An Optimistic Acceleration of AMSGrad for Nonconvex Optimization）</news:title>
   <news:publication_date>2026-08-13T22:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722894</loc>
  <lastmod>2026-08-13T22:51:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズに強いデータ圧縮で尤度フリー推論を高速化する手法（Nuisance hardened data compression for fast likelihood-free inference）</news:title>
   <news:publication_date>2026-08-13T22:51:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722892</loc>
  <lastmod>2026-08-13T22:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きフローに基づく確率的動画生成（VIDEOFLOW: A CONDITIONAL FLOW-BASED MODEL FOR STOCHASTIC VIDEO GENERATION）</news:title>
   <news:publication_date>2026-08-13T22:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722890</loc>
  <lastmod>2026-08-13T22:00:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ増幅による性質推定の最適化（Data Amplification: Instance-Optimal Property Estimation）</news:title>
   <news:publication_date>2026-08-13T22:00:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722888</loc>
  <lastmod>2026-08-13T21:59:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球状混合pスピンモデルにおける平均場ガラス動力学の再考（Rethinking mean-field glassy dynamics and its relation with the energy landscape: the awkward case of the spherical mixed p-spin model）</news:title>
   <news:publication_date>2026-08-13T21:59:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722886</loc>
  <lastmod>2026-08-13T21:58:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス特徴を用いたデータベース整合（Database Alignment with Gaussian Features）</news:title>
   <news:publication_date>2026-08-13T21:58:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722884</loc>
  <lastmod>2026-08-13T21:58:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドラム音源の転写に効くデータ拡張の実践（Data Augmentation for Drum Transcription with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-13T21:58:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722882</loc>
  <lastmod>2026-08-13T21:58:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量等高回帰とHardy-Krause変動の拡張（Multivariate extensions of isotonic regression and total variation denoising via entire monotonicity and Hardy-Krause variation）</news:title>
   <news:publication_date>2026-08-13T21:58:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722880</loc>
  <lastmod>2026-08-13T21:57:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep U-NetとWave-U-Netによる歌声分離の改善（Improving singing voice separation using Deep U-Net and Wave-U-Net with data augmentation）</news:title>
   <news:publication_date>2026-08-13T21:57:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722878</loc>
  <lastmod>2026-08-13T21:57:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二足歩行のシミュレーションから現実世界への転送（Sim-to-Real Transfer for Biped Locomotion）</news:title>
   <news:publication_date>2026-08-13T21:57:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722876</loc>
  <lastmod>2026-08-13T21:05:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚と制御を推論として統合する（Joint Perception and Control as Inference with an Object-Based Implementation）</news:title>
   <news:publication_date>2026-08-13T21:05:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722874</loc>
  <lastmod>2026-08-13T21:05:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフィカル計算による積と畳み込み（Graphical Calculus for products and convolutions）</news:title>
   <news:publication_date>2026-08-13T21:05:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722872</loc>
  <lastmod>2026-08-13T21:05:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市規模ITSにおける効率的なミリ波インフラ配置（Efficient Millimeter-Wave Infrastructure Placement for City-Scale ITS）</news:title>
   <news:publication_date>2026-08-13T21:05:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722870</loc>
  <lastmod>2026-08-13T21:04:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調型マルチエージェント深層強化学習による微視的交通シミュレーション (Microscopic Traffic Simulation by Cooperative Multi-agent Deep Reinforcement Learning)</news:title>
   <news:publication_date>2026-08-13T21:04:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722868</loc>
  <lastmod>2026-08-13T21:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>置換なし確率的勾配降下法の収束改善（SGD Without Replacement: Sharper Rates for General Smooth Convex Functions）</news:title>
   <news:publication_date>2026-08-13T21:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722866</loc>
  <lastmod>2026-08-13T21:04:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機会的ビューのマテリアライゼーションを深層強化学習で学ぶ（Opportunistic View Materialization with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-13T21:04:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722864</loc>
  <lastmod>2026-08-13T21:03:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デモンストレーションから学ぶ感覚–運動連合の自律化（Learning Sensory-Motor Associations from Demonstration）</news:title>
   <news:publication_date>2026-08-13T21:03:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722862</loc>
  <lastmod>2026-08-13T20:12:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反転授業と視線計測を用いたHCIデザイン教育（Teaching HCI Design in a Flipped Learning M.Sc. Course Using Eye-Tracking Peer Evaluation Data）</news:title>
   <news:publication_date>2026-08-13T20:12:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722860</loc>
  <lastmod>2026-08-13T20:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲルマニウム検出器のパルス形状識別に基づく深層学習（Deep learning based pulse shape discrimination for germanium detectors）</news:title>
   <news:publication_date>2026-08-13T20:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722858</loc>
  <lastmod>2026-08-13T20:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ化アクション空間におけるハイブリッドActor–Critic（Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Space）</news:title>
   <news:publication_date>2026-08-13T20:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722856</loc>
  <lastmod>2026-08-13T20:10:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StreetLearn：Google Street Viewを用いた学習環境とデータセット（The StreetLearn Environment and Dataset）</news:title>
   <news:publication_date>2026-08-13T20:10:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722854</loc>
  <lastmod>2026-08-13T20:10:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜血管の動脈／静脈同時分割と分類（Joint Segmentation and Classification of Retinal Arteries/Veins from Fundus Images）</news:title>
   <news:publication_date>2026-08-13T20:10:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722852</loc>
  <lastmod>2026-08-13T20:10:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファジーROCと不確実性領域の可視化（The Fuzzy ROC）</news:title>
   <news:publication_date>2026-08-13T20:10:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722850</loc>
  <lastmod>2026-08-13T20:09:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア工学倫理を教えるシリアスゲームの実践と検証（A Serious Game for Introducing Software Engineering Ethics to University Students）</news:title>
   <news:publication_date>2026-08-13T20:09:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722848</loc>
  <lastmod>2026-08-13T19:18:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常性下での最適化とヘッジ（Learning to Optimize under Non-Stationarity）</news:title>
   <news:publication_date>2026-08-13T19:18:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722846</loc>
  <lastmod>2026-08-13T19:18:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列のブラインドソース分離を動的モード分解で実現する（Time Series Source Separation using Dynamic Mode Decomposition）</news:title>
   <news:publication_date>2026-08-13T19:18:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722844</loc>
  <lastmod>2026-08-13T19:18:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロングテール関係抽出に知識グラフ埋め込みとグラフ畳み込みネットワークを組み合わせる方法（Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks）</news:title>
   <news:publication_date>2026-08-13T19:18:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722842</loc>
  <lastmod>2026-08-13T19:17:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの安全性検証とロバストネス解析（Safety Verification and Robustness Analysis of Neural Networks via Quadratic Constraints and Semidefinite Programming）</news:title>
   <news:publication_date>2026-08-13T19:17:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722840</loc>
  <lastmod>2026-08-13T19:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>秋季における亜熱帯カナリア海盆の深海散乱層の観測（Autumnal deep scattering layer from moored acoustic sensing in the subtropical Canary Basin）</news:title>
   <news:publication_date>2026-08-13T19:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722838</loc>
  <lastmod>2026-08-13T19:16:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ可変再帰によるGCNNの一般化（Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs）</news:title>
   <news:publication_date>2026-08-13T19:16:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722836</loc>
  <lastmod>2026-08-13T19:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>従来型機械学習によるピッチ検出の実務インパクト（Traditional Machine Learning for Pitch Detection）</news:title>
   <news:publication_date>2026-08-13T19:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722834</loc>
  <lastmod>2026-08-13T18:24:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知神経科学のための深層学習（Deep Learning for Cognitive Neuroscience）</news:title>
   <news:publication_date>2026-08-13T18:24:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722832</loc>
  <lastmod>2026-08-13T18:24:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デモから仕様を学ぶ因果分析（Using Causal Analysis to Learn Specifications from Task Demonstrations）</news:title>
   <news:publication_date>2026-08-13T18:24:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722830</loc>
  <lastmod>2026-08-13T18:24:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラグエール過程と分割上の動的関係を結ぶゲートウェイ（ON A GATEWAY BETWEEN THE LAGUERRE PROCESS AND DYNAMICS ON PARTITIONS）</news:title>
   <news:publication_date>2026-08-13T18:24:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722828</loc>
  <lastmod>2026-08-13T18:23:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交通参加者の相互作用をグラフで捉える（Graph Neural Networks for Modelling Traffic Participant Interaction）</news:title>
   <news:publication_date>2026-08-13T18:23:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722826</loc>
  <lastmod>2026-08-13T18:23:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デジタル人文学領域におけるロシア語コーパスと単語埋め込みの評価（Russian Language Datasets in the Digital Humanities Domain and Their Evaluation with Word Embeddings）</news:title>
   <news:publication_date>2026-08-13T18:23:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722824</loc>
  <lastmod>2026-08-13T18:22:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習監視機構の体系的評価枠組み（Towards Structured Evaluation of Deep Neural Network Supervisors）</news:title>
   <news:publication_date>2026-08-13T18:22:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722822</loc>
  <lastmod>2026-08-13T18:22:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり学習を用いた脳病変セグメンテーションの実用性（Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher Model）</news:title>
   <news:publication_date>2026-08-13T18:22:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722820</loc>
  <lastmod>2026-08-13T17:31:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を用いた車線変更予測（Attention-based Lane Change Prediction）</news:title>
   <news:publication_date>2026-08-13T17:31:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722818</loc>
  <lastmod>2026-08-13T17:31:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスクパラメータ化された動作学習の一般化を高める枠組み重み付き軌道生成（Improving Task-Parameterised Movement Learning Generalisation with Frame-Weighted Trajectory Generation）</news:title>
   <news:publication_date>2026-08-13T17:31:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722816</loc>
  <lastmod>2026-08-13T17:30:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病理組織画像における病変検出の深層学習フレームワークの機構理解（Understanding the Mechanism of Deep Learning Framework for Lesion Detection in Pathological Images with Breast Cancer）</news:title>
   <news:publication_date>2026-08-13T17:30:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722814</loc>
  <lastmod>2026-08-13T17:29:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしドメイン適応によるRGB-D階段認識（Unsupervised Domain Adaptation Learning Algorithm for RGB-D Staircase Recognition）</news:title>
   <news:publication_date>2026-08-13T17:29:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722812</loc>
  <lastmod>2026-08-13T17:29:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画行動認識のための協調時空間特徴学習（Collaborative Spatiotemporal Feature Learning for Video Action Recognition）</news:title>
   <news:publication_date>2026-08-13T17:29:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722810</loc>
  <lastmod>2026-08-13T17:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補完目的トレーニング（COMPLEMENT OBJECTIVE TRAINING）</news:title>
   <news:publication_date>2026-08-13T17:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722808</loc>
  <lastmod>2026-08-13T17:29:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルゴリズム判断が社会を変える長期影響（On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning）</news:title>
   <news:publication_date>2026-08-13T17:29:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722806</loc>
  <lastmod>2026-08-13T16:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的時間伸縮距離を伸縮不変にする方法（Making the Dynamic Time Warping Distance Warping-Invariant）</news:title>
   <news:publication_date>2026-08-13T16:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722804</loc>
  <lastmod>2026-08-13T16:29:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子理論に触発された二値分類器の実務的意義（Binary Classifier Inspired by Quantum Theory）</news:title>
   <news:publication_date>2026-08-13T16:29:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722802</loc>
  <lastmod>2026-08-13T16:29:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークを進化させる非線形制御問題への応用（Evolving Spiking Neural Networks for Nonlinear Control Problems）</news:title>
   <news:publication_date>2026-08-13T16:29:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722800</loc>
  <lastmod>2026-08-13T16:29:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌声合成のスペクトル包絡予測に関する深層学習手法の比較（Analysing Deep Learning–Spectral Envelope Prediction Methods for Singing Synthesis）</news:title>
   <news:publication_date>2026-08-13T16:29:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722798</loc>
  <lastmod>2026-08-13T16:27:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度距離学習と条件付き確率場を組み合わせたハイパースペクトル画像分類（Hyperspectral Image Classification with Deep Metric Learning and Conditional Random Field）</news:title>
   <news:publication_date>2026-08-13T16:27:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722796</loc>
  <lastmod>2026-08-13T16:27:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による水理データの再構築（Reconstruction of Hydraulic Data by Machine Learning）</news:title>
   <news:publication_date>2026-08-13T16:27:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722794</loc>
  <lastmod>2026-08-13T16:27:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>STRIPSアクションモデルの学習（Learning STRIPS Action Models with Classical Planning）</news:title>
   <news:publication_date>2026-08-13T16:27:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722792</loc>
  <lastmod>2026-08-13T15:35:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習データが無くてもタスクモデルを作る考え方（Zero-Shot Task Transfer）</news:title>
   <news:publication_date>2026-08-13T15:35:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722790</loc>
  <lastmod>2026-08-13T15:35:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延トレースによる微分可能な因果計算（Differentiable Causal Computations via Delayed Trace）</news:title>
   <news:publication_date>2026-08-13T15:35:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722788</loc>
  <lastmod>2026-08-13T15:35:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パ ン クロマティックモデリングから学ぶ教訓（Challenges in Panchromatic Modelling with Next Generation Facilities）</news:title>
   <news:publication_date>2026-08-13T15:35:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722786</loc>
  <lastmod>2026-08-13T15:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペアなし学習で低線量CTのノイズを除去するGAN（Unpaired image denoising using a generative adversarial network in X-ray CT）</news:title>
   <news:publication_date>2026-08-13T15:34:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722784</loc>
  <lastmod>2026-08-13T15:33:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的グラフフィードバックによる確率的オンライン学習の拡張（Stochastic Online Learning with Probabilistic Graph Feedback）</news:title>
   <news:publication_date>2026-08-13T15:33:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722782</loc>
  <lastmod>2026-08-13T15:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成学習による教師なしクロススペクトルステレオマッチング (Unsupervised Cross-spectral Stereo Matching by Learning to Synthesize)</news:title>
   <news:publication_date>2026-08-13T15:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722780</loc>
  <lastmod>2026-08-13T15:33:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層監督付き密度回帰による自動顕微鏡細胞計数（Automatic Microscopic Cell Counting by Use of Deeply-Supervised Density Regression Model）</news:title>
   <news:publication_date>2026-08-13T15:33:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722778</loc>
  <lastmod>2026-08-13T14:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習エクス・ニーヒロ（Learning Ex Nihilo）</news:title>
   <news:publication_date>2026-08-13T14:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722776</loc>
  <lastmod>2026-08-13T14:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然画像で訓練されたニューラルネットワークはゲシュタルトの閉合を示す（Neural Networks Trained on Natural Scenes Exhibit Gestalt Closure）</news:title>
   <news:publication_date>2026-08-13T14:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722774</loc>
  <lastmod>2026-08-13T14:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートブラックボックス：価値駆動の高帯域車載イベントデータレコーダ（The Smart Black Box: A Value-Driven High-Bandwidth Automotive Event Data Recorder）</news:title>
   <news:publication_date>2026-08-13T14:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722772</loc>
  <lastmod>2026-08-13T14:40:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬なしで環境に適応するメタ学習（No-Reward Meta Learning）</news:title>
   <news:publication_date>2026-08-13T14:40:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722770</loc>
  <lastmod>2026-08-13T14:40:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変インピーダンス制御器を用いた強化学習による高精度ロボット組み立て（Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly）</news:title>
   <news:publication_date>2026-08-13T14:40:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722768</loc>
  <lastmod>2026-08-13T14:40:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Straight-Through Estimatorを使わない低精度ニューラルネットワーク学習（Learning low-precision neural networks without Straight-Through Estimator (STE))</news:title>
   <news:publication_date>2026-08-13T14:40:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722766</loc>
  <lastmod>2026-08-13T14:40:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カロリトロニクスに基づくモットニューロスター（A caloritronics-based Mott neuristor）</news:title>
   <news:publication_date>2026-08-13T14:40:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722764</loc>
  <lastmod>2026-08-13T13:49:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多ブロックADMMを用いたアイソトニック回帰への応用（THE APPLICATION OF MULTI-BLOCK ADMM ON ISOTONIC REGRESSION PROBLEMS）</news:title>
   <news:publication_date>2026-08-13T13:49:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722762</loc>
  <lastmod>2026-08-13T13:48:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>米国におけるインフルエンザ流行の早期検知手法（Early Detection of Influenza outbreaks in the United States）</news:title>
   <news:publication_date>2026-08-13T13:48:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722760</loc>
  <lastmod>2026-08-13T13:48:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超大規模データに効くスペクトルクラスタリングの実用化（Ultra-Scalable Spectral Clustering and Ensemble Clustering）</news:title>
   <news:publication_date>2026-08-13T13:48:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722758</loc>
  <lastmod>2026-08-13T13:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CodeNetによる誤り耐性を持つ大規模ニューラルネットワーク訓練（CodeNet: Training Large Scale Neural Networks in Presence of Soft-Errors）</news:title>
   <news:publication_date>2026-08-13T13:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722756</loc>
  <lastmod>2026-08-13T13:47:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接続モバイル端末からの頑健な通勤者移動推定（Robust commuter movement inference from connected mobile devices）</news:title>
   <news:publication_date>2026-08-13T13:47:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722754</loc>
  <lastmod>2026-08-13T13:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床自然言語処理における埋め込み表現の総覧（SECNLP: A Survey of Embeddings in Clinical Natural Language Processing）</news:title>
   <news:publication_date>2026-08-13T13:47:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722752</loc>
  <lastmod>2026-08-13T13:47:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏心球の壁効果と機械学習による高速近似（Wall effects of eccentric spheres machine learning for convenient computation）</news:title>
   <news:publication_date>2026-08-13T13:47:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722750</loc>
  <lastmod>2026-08-13T12:54:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間ピラミッドネットワークによる動画行動認識（Spatiotemporal Pyramid Network for Video Action Recognition）</news:title>
   <news:publication_date>2026-08-13T12:54:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722748</loc>
  <lastmod>2026-08-13T12:53:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二項分類における精度と頑健性の根本的制約（A Fundamental Performance Limitation for Adversarial Classification）</news:title>
   <news:publication_date>2026-08-13T12:53:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722746</loc>
  <lastmod>2026-08-13T12:53:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダで正則化したCNNによるワン・クラス認証（Active Authentication using an Autoencoder regularized CNN-based One-Class Classifier）</news:title>
   <news:publication_date>2026-08-13T12:53:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722744</loc>
  <lastmod>2026-08-13T12:52:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMによる短期電力需要予測の実務適用可能性（Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting）</news:title>
   <news:publication_date>2026-08-13T12:52:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722742</loc>
  <lastmod>2026-08-13T12:52:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>触覚ロボットガイドに従う人の軌道予測（Prediction of Human Trajectory Following a Haptic Robotic Guide Using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-08-13T12:52:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722740</loc>
  <lastmod>2026-08-13T12:52:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己検査型ビジョンによる障害物回避（Introspective Vision for Obstacle Avoidance）</news:title>
   <news:publication_date>2026-08-13T12:52:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722738</loc>
  <lastmod>2026-08-13T12:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンディット設定におけるモジュラー安全方策学習（Learning Modular Safe Policies in the Bandit Setting with Application to Adaptive Clinical Trials）</news:title>
   <news:publication_date>2026-08-13T12:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722736</loc>
  <lastmod>2026-08-13T12:00:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートインバータの無効電力制御ルール設計（Designing Reactive Power Control Rules for Smart Inverters using Support Vector Machines）</news:title>
   <news:publication_date>2026-08-13T12:00:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722734</loc>
  <lastmod>2026-08-13T12:00:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強い漸近的最適性を示す汎用環境下のエージェント（A Strongly Asymptotically Optimal Agent in General Environments）</news:title>
   <news:publication_date>2026-08-13T12:00:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722732</loc>
  <lastmod>2026-08-13T12:00:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的摂動の影響を低減するカーネル化マニホールド写像（A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations）</news:title>
   <news:publication_date>2026-08-13T12:00:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722730</loc>
  <lastmod>2026-08-13T11:59:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続状態空間における予算付き強化学習（Budgeted Reinforcement Learning in Continuous State Space）</news:title>
   <news:publication_date>2026-08-13T11:59:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722728</loc>
  <lastmod>2026-08-13T11:59:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における顔クラスタリングのための自己教師あり顔表現学習（Self-Supervised Learning of Face Representations for Video Face Clustering）</news:title>
   <news:publication_date>2026-08-13T11:59:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722726</loc>
  <lastmod>2026-08-13T11:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Reinforcement LearningでreCAPTCHA v3を回避する手法（Hacking Google reCAPTCHA v3 using Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-13T11:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722724</loc>
  <lastmod>2026-08-13T11:58:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手部姿勢推定の総合的概説（Hand Pose Estimation: A Survey）</news:title>
   <news:publication_date>2026-08-13T11:58:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722722</loc>
  <lastmod>2026-08-13T11:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>断面厚み予測によるRGB-D融合強化（X-Section: Cross-Section Prediction for Enhanced RGB-D Fusion）</news:title>
   <news:publication_date>2026-08-13T11:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722720</loc>
  <lastmod>2026-08-13T11:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DEPAMの開発詳細と計算ベンチマーク（Development details and computational benchmarking of DEPAM）</news:title>
   <news:publication_date>2026-08-13T11:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722718</loc>
  <lastmod>2026-08-13T11:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所多様体近似による分類（Classification via local manifold approximation）</news:title>
   <news:publication_date>2026-08-13T11:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722716</loc>
  <lastmod>2026-08-13T11:05:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス混合モデルに対する一般化期待値最大化アルゴリズムの制御系的解析（Analysis of a Generalized Expectation-Maximization Algorithm for Gaussian Mixture Models: A Control Systems Perspective）</news:title>
   <news:publication_date>2026-08-13T11:05:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722714</loc>
  <lastmod>2026-08-13T11:05:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元空間における曲面と関数のサンプリング（SAMPLING OF SURFACES AND FUNCTIONS IN HIGH DIMENSIONAL SPACES）</news:title>
   <news:publication_date>2026-08-13T11:05:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722712</loc>
  <lastmod>2026-08-13T11:05:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Anytime online-to-batch変換、楽観主義、加速化（Anytime Online-to-Batch Conversions, Optimism, and Acceleration）</news:title>
   <news:publication_date>2026-08-13T11:05:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722710</loc>
  <lastmod>2026-08-13T11:05:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚的不確かさを管理する枠組みの提案（Towards a Framework to Manage Perceptual Uncertainty for Safe Automated Driving）</news:title>
   <news:publication_date>2026-08-13T11:05:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722708</loc>
  <lastmod>2026-08-13T10:13:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サーマル顔画像から可視顔画像を合成するセマンティックガイド付きGAN（Matching Thermal to Visible Face Images Using a Semantic-Guided Generative Adversarial Network）</news:title>
   <news:publication_date>2026-08-13T10:13:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722706</loc>
  <lastmod>2026-08-13T10:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DESK：外科ロボット技能データセットとシミュレーションから現実世界への知識移転（DESK: A Robotic Activity Dataset for Dexterous Surgical Skills Transfer to Medical Robots）</news:title>
   <news:publication_date>2026-08-13T10:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722704</loc>
  <lastmod>2026-08-13T10:13:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希薄高次元線形回帰における予測のための経験的事前分布（Empirical priors for prediction in sparse high-dimensional linear regression）</news:title>
   <news:publication_date>2026-08-13T10:13:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722702</loc>
  <lastmod>2026-08-13T10:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続戦略ゲームにおける均衡の非効率性の上界（Bounding Ineﬃciency of Equilibria in Continuous Actions Games using Submodularity and Curvature）</news:title>
   <news:publication_date>2026-08-13T10:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722700</loc>
  <lastmod>2026-08-13T10:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デバイス別・時空間粒度で見る人間行動予測の実用化（Practical Prediction of Human Movements Across Device Types and Spatiotemporal Granularities）</news:title>
   <news:publication_date>2026-08-13T10:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722698</loc>
  <lastmod>2026-08-13T10:11:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークによる条件付き確率密度推定の実務指針（Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks）</news:title>
   <news:publication_date>2026-08-13T10:11:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722696</loc>
  <lastmod>2026-08-13T10:11:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>防御の期待効用を直接最大化する学習手法（End-to-End Game-Focused Learning of Adversary Behavior in Security Games）</news:title>
   <news:publication_date>2026-08-13T10:11:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722694</loc>
  <lastmod>2026-08-13T09:19:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然保護区におけるルリノドヒタキの個体数減少の謎を可視化で解く（Addressing The Mystery of Population Decline of The Rose-Crested Blue Pipit In A Nature Preserve Using Data Visualization）</news:title>
   <news:publication_date>2026-08-13T09:19:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722692</loc>
  <lastmod>2026-08-13T09:19:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Origins Space Telescopeの遠赤外分光サーベイの予測（Origins Space Telescope: predictions for far-IR spectroscopic surveys）</news:title>
   <news:publication_date>2026-08-13T09:19:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722690</loc>
  <lastmod>2026-08-13T09:18:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的教師ありによる非局所文法依存関係の学習改善（Structural Supervision Improves Learning of Non-Local Grammatical Dependencies）</news:title>
   <news:publication_date>2026-08-13T09:18:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722688</loc>
  <lastmod>2026-08-13T09:17:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タイのClassStartを用いたオンライン学習受容の要因分析（Investigating factors affecting learner&amp;#039;s perception toward online learning: Evidence from ClassStart Application in Thailand）</news:title>
   <news:publication_date>2026-08-13T09:17:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722686</loc>
  <lastmod>2026-08-13T09:17:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベルヌーイ・レース粒子フィルタ（Bernoulli Race Particle Filters）</news:title>
   <news:publication_date>2026-08-13T09:17:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722684</loc>
  <lastmod>2026-08-13T09:17:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>標準化損失による深層ニューラルネットワーク学習の高速化（Accelerating Training of Deep Neural Networks with a Standardization Loss）</news:title>
   <news:publication_date>2026-08-13T09:17:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722682</loc>
  <lastmod>2026-08-13T09:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列コーパスからの転移学習による中国語での認知症検出（Detecting Dementia in Mandarin Chinese using Transfer Learning from a Parallel Corpus）</news:title>
   <news:publication_date>2026-08-13T09:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722680</loc>
  <lastmod>2026-08-13T08:25:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D時空間グラフ畳み込みによる交通予測の新枠組み（3D Graph Convolutional Networks with Temporal Graphs: A Spatial Information Free Framework For Traffic Forecasting）</news:title>
   <news:publication_date>2026-08-13T08:25:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722678</loc>
  <lastmod>2026-08-13T08:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一枚の静止画からの双方向フローに基づく教師なし動画生成（Unsupervised Bi-directional Flow-based Video Generation from one Snapshot）</news:title>
   <news:publication_date>2026-08-13T08:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722676</loc>
  <lastmod>2026-08-13T08:25:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リカレントニューラルネットワークにおける特徴選択と特徴記憶の理解（Understanding Feature Selection and Feature Memorization in Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-08-13T08:25:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722674</loc>
  <lastmod>2026-08-13T08:24:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書きストロークの角点・接線点検出を堅牢にする深層学習手法（Robust corner and tangent point detection for strokes with deep learning approach）</news:title>
   <news:publication_date>2026-08-13T08:24:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722672</loc>
  <lastmod>2026-08-13T08:24:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MILDNet: 軽量単一スケール深層ランキングアーキテクチャ（MILDNet: A Lightweight Single Scaled Deep Ranking Architecture）</news:title>
   <news:publication_date>2026-08-13T08:24:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722670</loc>
  <lastmod>2026-08-13T08:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競争的ブリッジ入札における深層ニューラルネットワーク（Competitive Bridge Bidding with Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-13T08:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722668</loc>
  <lastmod>2026-08-13T08:23:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己対抗的変分オートエンコーダによる異常検知とガウス異常事前知識（adVAE: a Self-adversarial Variational Autoencoder with Gaussian Anomaly Prior Knowledge for Anomaly Detection）</news:title>
   <news:publication_date>2026-08-13T08:23:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722666</loc>
  <lastmod>2026-08-13T07:32:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザーレビューに基づく変更ファイルのローカライゼーション (User Review-Based Change File Localization for Mobile Applications)</news:title>
   <news:publication_date>2026-08-13T07:32:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722664</loc>
  <lastmod>2026-08-13T07:32:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈認識型深層学習によるソースコードモデリング（CodeGRU: Context-aware Deep Learning with Gated Recurrent Unit for Source Code Modeling）</news:title>
   <news:publication_date>2026-08-13T07:32:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722662</loc>
  <lastmod>2026-08-13T07:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超音波舌画像からの頑健な特徴抽出—Denoising Convolutional Autoencoderの応用（Denoising Convolutional Autoencoder Based B-Mode Ultrasound Tongue Image Feature Extraction）</news:title>
   <news:publication_date>2026-08-13T07:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722660</loc>
  <lastmod>2026-08-13T07:30:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きカーネル平均埋め込みを用いたベイズ学習による自動化された尤度フリー推論（Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference）</news:title>
   <news:publication_date>2026-08-13T07:30:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722658</loc>
  <lastmod>2026-08-13T07:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックス問題の可視化枠組み（Solving the Black Box Problem: A Normative Framework for Explainable Artificial Intelligence）</news:title>
   <news:publication_date>2026-08-13T07:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722656</loc>
  <lastmod>2026-08-13T07:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画長さで学ぶハイライト検出（Less is More: Learning Highlight Detection from Video Duration）</news:title>
   <news:publication_date>2026-08-13T07:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722654</loc>
  <lastmod>2026-08-13T07:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Meta-SR: 単一モデルで任意倍率の超解像を可能にする手法（Meta-SR: A Magnification-Arbitrary Network for Super-Resolution）</news:title>
   <news:publication_date>2026-08-13T07:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722652</loc>
  <lastmod>2026-08-13T06:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期予測可能な車両行動の推定手法：Behavior Interaction Network（Predicting Vehicle Behaviors Over An Extended Horizon Using Behavior Interaction Network）</news:title>
   <news:publication_date>2026-08-13T06:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722650</loc>
  <lastmod>2026-08-13T06:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CAD-Netによるリモートセンシング画像の文脈対応物体検出（CAD-Net: A Context-Aware Detection Network for Objects in Remote Sensing Imagery）</news:title>
   <news:publication_date>2026-08-13T06:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722648</loc>
  <lastmod>2026-08-13T06:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市環境でのオンライン車両軌跡予測の二層フレームワーク（Online Vehicle Trajectory Prediction using Policy Anticipation Network and Optimization-based Context Reasoning）</news:title>
   <news:publication_date>2026-08-13T06:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722646</loc>
  <lastmod>2026-08-13T06:27:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Texture Transferによる画像超解像（Image Super-Resolution by Neural Texture Transfer）</news:title>
   <news:publication_date>2026-08-13T06:27:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722644</loc>
  <lastmod>2026-08-13T06:27:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTの階層別セキュリティとプライバシーの概観（A survey of security and privacy issues in the Internet of Things from the layered context）</news:title>
   <news:publication_date>2026-08-13T06:27:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722642</loc>
  <lastmod>2026-08-13T06:26:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全なデータから生成モデルを学ぶための変分オートデコーダ（Variational Auto-Decoder）</news:title>
   <news:publication_date>2026-08-13T06:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722640</loc>
  <lastmod>2026-08-13T06:26:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データ回帰のためのMultiple Learning（Multiple Learning for Regression in Big Data）</news:title>
   <news:publication_date>2026-08-13T06:26:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722638</loc>
  <lastmod>2026-08-13T05:35:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膵臓セグメンテーションのためのモデル主導スタック型全畳み込みネットワーク（A Model-Driven Stack-Based Fully Convolutional Network for Pancreas Segmentation）</news:title>
   <news:publication_date>2026-08-13T05:35:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722636</loc>
  <lastmod>2026-08-13T05:34:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラミング問題のアルゴリズム分類を自動予測する試み（Predicting Algorithm Classes for Programming Word Problems）</news:title>
   <news:publication_date>2026-08-13T05:34:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722634</loc>
  <lastmod>2026-08-13T05:34:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算負荷の高い環境における連続制御のための非同期エピソディックDDPG（Asynchronous Episodic Deep Deterministic Policy Gradient）</news:title>
   <news:publication_date>2026-08-13T05:34:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722632</loc>
  <lastmod>2026-08-13T05:33:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワーク再正規化群による機械学習ホログラフィック写像（Machine Learning Holographic Mapping by Neural Network Renormalization Group）</news:title>
   <news:publication_date>2026-08-13T05:33:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722630</loc>
  <lastmod>2026-08-13T05:33:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループラッソ規範を持つベクトル値再生核バナッハ空間（Vector-valued Reproducing Kernel Banach Spaces with Group Lasso Norms）</news:title>
   <news:publication_date>2026-08-13T05:33:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722628</loc>
  <lastmod>2026-08-13T05:33:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を考慮した視覚ベース自動運転の実装手法（Visual-based Autonomous Driving Deployment from a Stochastic and Uncertainty-aware Perspective）</news:title>
   <news:publication_date>2026-08-13T05:33:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722626</loc>
  <lastmod>2026-08-13T05:32:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定木とロジスティック回帰の安定性（STABILITY OF DECISION TREES AND LOGISTIC REGRESSION）</news:title>
   <news:publication_date>2026-08-13T05:32:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722624</loc>
  <lastmod>2026-08-13T04:41:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンコーダ・デコーダ翻訳モデルの較正（CALIBRATION OF ENCODER DECODER MODELS FOR NEURAL MACHINE TRANSLATION）</news:title>
   <news:publication_date>2026-08-13T04:41:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722622</loc>
  <lastmod>2026-08-13T04:41:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共有意味表現の変換転送（Let’s Transfer Transformations of Shared Semantic Representations）</news:title>
   <news:publication_date>2026-08-13T04:41:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722620</loc>
  <lastmod>2026-08-13T04:41:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非ダウンサンプリング・クォータニオン・ウェーブレットによるスペクトル解析（Non-decimated Quaternion Wavelet Spectral Tools with Applications）</news:title>
   <news:publication_date>2026-08-13T04:41:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722618</loc>
  <lastmod>2026-08-13T04:40:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の言い換え検出を敵対的視点で再定義する（AIRD: Adversarial Learning Framework for Image Repurposing Detection）</news:title>
   <news:publication_date>2026-08-13T04:40:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722616</loc>
  <lastmod>2026-08-13T04:40:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural MMO（Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents）</news:title>
   <news:publication_date>2026-08-13T04:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/722614</loc>
  <lastmod>2026-08-13T04:40:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-13T04:40:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722612</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意に基づく選択的可塑性（Attention-Based Selective Plasticity）</news:title>
   <news:publication_date>2026-08-13T04:39:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722610</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱ラベルAudioSetに対する注意機構付き音声タグ付け（Weakly Labelled AudioSet Tagging with Attention Neural Networks）</news:title>
   <news:publication_date>2026-08-13T03:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722608</loc>
  <lastmod>2026-08-13T03:47:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的シーンのぼかし除去のための極端チャネル事前埋め込みネットワーク（Extreme Channel Prior Embedded Network for Dynamic Scene Deblurring）</news:title>
   <news:publication_date>2026-08-13T03:47:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722606</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空機衝突回避ニューラルネットの検証と線形近似による安全領域の定義（Verifying Aircraft Collision Avoidance Neural Networks Through Linear Approximations of Safe Regions）</news:title>
   <news:publication_date>2026-08-13T03:47:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722604</loc>
  <lastmod>2026-08-13T03:46:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Equilibrated Recurrent Neural Networkを読み解く：時差自己フィードバックがもたらす安定性と精度の向上（Equilibrated Recurrent Neural Network: Neuronal Time-Delayed Self-Feedback Improves Accuracy and Stability）</news:title>
   <news:publication_date>2026-08-13T03:46:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722602</loc>
  <lastmod>2026-08-13T03:46:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による予測モデル自動化（Automating Predictive Modeling Process using Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-13T03:46:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722600</loc>
  <lastmod>2026-08-13T03:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書順で優先順位をつける多目的クラスタリング（Lexicographically Ordered Multi-Objective Clustering）</news:title>
   <news:publication_date>2026-08-13T03:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722598</loc>
  <lastmod>2026-08-13T03:46:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GraphViteによる大規模ノード埋め込みの高速化（GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding）</news:title>
   <news:publication_date>2026-08-13T03:46:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722596</loc>
  <lastmod>2026-08-13T02:54:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深いReLUネットワークが帯域制限関数の次元の呪いを克服する（Deep ReLU networks overcome the curse of dimensionality for generalized bandlimited functions）</news:title>
   <news:publication_date>2026-08-13T02:54:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722594</loc>
  <lastmod>2026-08-13T02:54:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発話が無い、あるいは雑音だらけの環境での音声認識（SPEECH RECOGNITION WITH NO SPEECH OR WITH NOISY SPEECH）</news:title>
   <news:publication_date>2026-08-13T02:54:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722592</loc>
  <lastmod>2026-08-13T02:53:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化によるスパース最適方策のアプローチ（A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-13T02:53:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722590</loc>
  <lastmod>2026-08-13T02:53:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠方太陽系天体の恒星掩蔽の将来展望（The future of stellar occultations by distant solar system bodies: perspectives from the Gaia astrometry and the deep sky surveys）</news:title>
   <news:publication_date>2026-08-13T02:53:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722588</loc>
  <lastmod>2026-08-13T02:53:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効用最大化二値予測におけるモデル選択（Model Selection in Utility-Maximizing Binary Prediction）</news:title>
   <news:publication_date>2026-08-13T02:53:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722586</loc>
  <lastmod>2026-08-13T02:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知語（OOV）に対する埋め込み予測と解釈（Predicting and interpreting embeddings for out of vocabulary words in downstream tasks）</news:title>
   <news:publication_date>2026-08-13T02:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722584</loc>
  <lastmod>2026-08-13T02:53:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴寄与区間による解釈可能かつ対話的なデータ探索（FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration）</news:title>
   <news:publication_date>2026-08-13T02:53:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722582</loc>
  <lastmod>2026-08-13T02:02:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑物流ネットワークにおける資源バランスのための協調型マルチエージェント強化学習フレームワーク (A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network)</news:title>
   <news:publication_date>2026-08-13T02:02:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722580</loc>
  <lastmod>2026-08-13T02:02:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PartNetによる階層的3D形状分割の革新（PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation）</news:title>
   <news:publication_date>2026-08-13T02:02:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722578</loc>
  <lastmod>2026-08-13T02:01:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル検索とランキングのためのneuralRank（neuralRank: Searching and ranking ANN-based model repositories）</news:title>
   <news:publication_date>2026-08-13T02:01:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722576</loc>
  <lastmod>2026-08-13T02:01:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>#MeTooはジェンダー規範を変えたか（USING ARTIFICIAL INTELLIGENCE TO RECAPTURE NORMS: DID #METOO CHANGE GENDER NORMS IN SWEDEN?）</news:title>
   <news:publication_date>2026-08-13T02:01:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722574</loc>
  <lastmod>2026-08-13T02:01:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スクリーンコンテンツ画像の画質評価に向けた深層最適化モデル（Deep Optimization Model for Screen Content Image Quality Assessment using Neural Networks）</news:title>
   <news:publication_date>2026-08-13T02:01:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722572</loc>
  <lastmod>2026-08-13T02:00:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸正則化による行列補完と近接勾配法の収束解析（Matrix Completion via Nonconvex Regularization: Convergence of the Proximal Gradient Algorithm）</news:title>
   <news:publication_date>2026-08-13T02:00:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722570</loc>
  <lastmod>2026-08-13T02:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モーションキャプチャの細粒度意味セグメンテーション（Fine-Grained Semantic Segmentation of Motion Capture Data using Dilated Temporal Fully-Convolutional Networks）</news:title>
   <news:publication_date>2026-08-13T02:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722568</loc>
  <lastmod>2026-08-13T01:09:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク復旧の競合的浸透戦略（Competitive percolation strategies for network recovery）</news:title>
   <news:publication_date>2026-08-13T01:09:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722566</loc>
  <lastmod>2026-08-13T01:09:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆問題と機械学習の統一的リプレゼンター定理（A unifying representer theorem for inverse problems and machine learning）</news:title>
   <news:publication_date>2026-08-13T01:09:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722564</loc>
  <lastmod>2026-08-13T01:08:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業用ロボット向け完全畳み込みワンショット物体セグメンテーション（Fully Convolutional One–Shot Object Segmentation for Industrial Robotics）</news:title>
   <news:publication_date>2026-08-13T01:08:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722562</loc>
  <lastmod>2026-08-13T01:08:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OmniDRLによる全周カメラでの歩行者検出の頑健化（OmniDRL: Robust Pedestrian Detection using Deep Reinforcement Learning on Omnidirectional Cameras）</news:title>
   <news:publication_date>2026-08-13T01:08:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722560</loc>
  <lastmod>2026-08-13T01:08:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディアにおける攻撃的発言検出の実践（Towards NLP with Deep Learning: Convolutional Neural Networks and Recurrent Neural Networks for Offensive Language Identification in Social Media）</news:title>
   <news:publication_date>2026-08-13T01:08:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722558</loc>
  <lastmod>2026-08-13T01:08:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Surrogate出力間の低ランク関係を利活用する構造化予測（Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction）</news:title>
   <news:publication_date>2026-08-13T01:08:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722556</loc>
  <lastmod>2026-08-13T01:08:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepGiniによるテスト優先化で実務的なDNN品質向上を狙う（DeepGini: Prioritizing Massive Tests to Enhance the Robustness of Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-13T01:08:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722554</loc>
  <lastmod>2026-08-13T00:16:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音の振動で注ぎの高さを推定する（Making Sense of Audio Vibration for Liquid Height Estimation in Robotic Pouring）</news:title>
   <news:publication_date>2026-08-13T00:16:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722552</loc>
  <lastmod>2026-08-13T00:16:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四元数畳み込みニューラルネットワークの要点（Quaternion Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-13T00:16:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722550</loc>
  <lastmod>2026-08-13T00:15:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wasserstein距離に基づく深層敵対的転移学習による機械故障診断（Wasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis）</news:title>
   <news:publication_date>2026-08-13T00:15:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722548</loc>
  <lastmod>2026-08-13T00:14:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンパスで大規模・欠損混在データを扱う実務的手法の提示（One-Pass Incomplete Multi-view Clustering）</news:title>
   <news:publication_date>2026-08-13T00:14:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722546</loc>
  <lastmod>2026-08-13T00:14:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実な形状補完を踏まえた堅牢な把持計画（Robust Grasp Planning Over Uncertain Shape Completions）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-13T00:14:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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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: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>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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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:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:publication_date>2026-08-12T19:37:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722470</loc>
  <lastmod>2026-08-12T18:45:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T18:45:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722468</loc>
  <lastmod>2026-08-12T18:45:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T18:45:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722466</loc>
  <lastmod>2026-08-12T18:44:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数画像の超解像に深層学習を組み合わせる手法（Deep Learning for Multiple-Image Super-Resolution）</news:title>
   <news:publication_date>2026-08-12T18:44:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722464</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>文献コーパスからエネルギー材料の性質・機能を自動抽出するための自然言語処理手法（USING NATURAL LANGUAGE PROCESSING TECHNIQUES TO EXTRACT INFORMATION ON THE PROPERTIES AND FUNCTIONALITIES OF ENERGETIC MATERIALS FROM LARGE TEXT CORPORA）</news:title>
   <news:publication_date>2026-08-12T18:44:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722462</loc>
  <lastmod>2026-08-12T18:44:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットの常識埋め込み（RoboCSE: Robot Common Sense Embedding）</news:title>
   <news:publication_date>2026-08-12T18:44:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722460</loc>
  <lastmod>2026-08-12T18:44:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>政策評価における機械学習：因果推論の新しい道（Machine learning in policy evaluation: new tools for causal inference）</news:title>
   <news:publication_date>2026-08-12T18:44:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722458</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>高自由度ハンドの把持姿勢生成（Generating Grasp Poses for a High-DOF Gripper Using Neural Networks）</news:title>
   <news:publication_date>2026-08-12T18:43:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722456</loc>
  <lastmod>2026-08-12T17:52:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>街路ビューでの指示に従う学習（Learning to Follow Directions in Street View）</news:title>
   <news:publication_date>2026-08-12T17:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722454</loc>
  <lastmod>2026-08-12T17:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像のかすみ除去における条件付きWasserstein敵対的生成ネットワーク（Single Image Haze Removal Using Conditional Wasserstein Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-12T17:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722452</loc>
  <lastmod>2026-08-12T17:51:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽系におけるハドレー循環の角幅の解析的推定（Analytical Estimation of the Width of Hadley Cells in the Solar System）</news:title>
   <news:publication_date>2026-08-12T17:51:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブル向けオフアクシス虹彩分割の低複雑性ネットワークとデータ拡張法（Deep Neural Network and Data Augmentation Methodology for off-axis iris segmentation in wearable headsets）</news:title>
   <news:publication_date>2026-08-12T17:51:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722448</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T17:50:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ネットワークにおけるMAP推定の漸近解析（Asymptotics of MAP Inference in Deep Networks）</news:title>
   <news:publication_date>2026-08-12T17:50:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線通信における敵対的回避攻撃の評価（Evaluating Adversarial Evasion Attacks in the Context of Wireless Communications）</news:title>
   <news:publication_date>2026-08-12T17:50:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T16:58:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Atariにおけるモデルベース強化学習の実践（Model Based Reinforcement Learning for Atari）</news:title>
   <news:publication_date>2026-08-12T16:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722438</loc>
  <lastmod>2026-08-12T16:56:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レベルセット法における状態とパラメータの同時推定（Combined State and Parameter Estimation in Level-Set Methods）</news:title>
   <news:publication_date>2026-08-12T16:56:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-12T16:56:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所化したサポートベクターマシンの定量的ロバスト性（Quantitative Robustness of Localized Support Vector Machines）</news:title>
   <news:publication_date>2026-08-12T16:56:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722434</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T16:56:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722432</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T16:55:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-12T16:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形成中惑星の質量推定に深層学習を用いる研究（Using Deep Neural Networks to compute the mass of forming planets）</news:title>
   <news:publication_date>2026-08-12T16:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722428</loc>
  <lastmod>2026-08-12T16:04:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T16:04:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722426</loc>
  <lastmod>2026-08-12T15:54:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T15:54:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722424</loc>
  <lastmod>2026-08-12T15:53:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽系内の星間塵と計算モデルの照合（Interstellar Dust in the Solar System: Model versus In-Situ Spacecraft Data）</news:title>
   <news:publication_date>2026-08-12T15:53:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722422</loc>
  <lastmod>2026-08-12T15:52:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Progress Regression RNNによるオンライン空間時系列行動定位（Progress Regression RNN for Online Spatial-Temporal Action Localization in Unconstrained Videos）</news:title>
   <news:publication_date>2026-08-12T15:52:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722420</loc>
  <lastmod>2026-08-12T15:52:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Machine Learningのための継続的インテグレーション ease.ml/ci（Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment）</news:title>
   <news:publication_date>2026-08-12T15:52:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/722418</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T15:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722416</loc>
  <lastmod>2026-08-12T15:52:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T15:52:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-12T14:53:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数領域トランスフォーマーネットワークによる映像予測（Frequency Domain Transformer Networks for Video Prediction）</news:title>
   <news:publication_date>2026-08-12T14:53:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722410</loc>
  <lastmod>2026-08-12T14:53:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T14:53:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-12T14:52:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-12T14:51:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ヒトのクラウディングは畳み込みニューラルネットワークとは異なる（Crowding in humans is unlike that in convolutional neural networks）</news:title>
   <news:publication_date>2026-08-12T14:51:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-12T13:58:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マスクスコアリングR-CNN（Mask Scoring R-CNN）</news:title>
   <news:publication_date>2026-08-12T13:58:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722398</loc>
  <lastmod>2026-08-12T13:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子から隠れメッセージを学習して密度汎関数理論を完成させる（Completing density functional theory by machine learning hidden messages from molecules）</news:title>
   <news:publication_date>2026-08-12T13:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722396</loc>
  <lastmod>2026-08-12T13:57:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像のモーションブラー除去と6自由度カメラ運動推定（Single Image Deblurring and Camera Motion Estimation with Depth Map）</news:title>
   <news:publication_date>2026-08-12T13:57:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722394</loc>
  <lastmod>2026-08-12T13:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子チャネル記憶を持つ場合の古典情報率の評価と境界設定（Bounding and Estimating the Classical Information Rate of Quantum Channels with Memory）</news:title>
   <news:publication_date>2026-08-12T13:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722392</loc>
  <lastmod>2026-08-12T13:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>YouTubeから自動で音声データセットを作る仕組み（KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube Videos）</news:title>
   <news:publication_date>2026-08-12T13:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722390</loc>
  <lastmod>2026-08-12T13:56:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cramer–Wold に基づく非線形ICAの提案（Non-linear ICA based on Cramer-Wold metric）</news:title>
   <news:publication_date>2026-08-12T13:56:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722388</loc>
  <lastmod>2026-08-12T13:55:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ効率化された自己教師あり学習によるロボット把持の改善（Improving Data Efficiency of Self-supervised Learning for Robotic Grasping）</news:title>
   <news:publication_date>2026-08-12T13:55:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722386</loc>
  <lastmod>2026-08-12T13:04:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発症後の急性冠症候群患者のアウトカム駆動クラスタリング（Outcome-Driven Clustering of Acute Coronary Syndrome Patients using Multi-Task Neural Network with Attention）</news:title>
   <news:publication_date>2026-08-12T13:04:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722384</loc>
  <lastmod>2026-08-12T13:03:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波間（インターフリークエンシー）信号品質予測とハンドオーバー意思決定の高精度化（Inter-frequency radio signal quality prediction for handover, evaluated in 3GPP LTE）</news:title>
   <news:publication_date>2026-08-12T13:03:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722382</loc>
  <lastmod>2026-08-12T13:03:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強調付き時刻差分学習は常に有利か（Should All Temporal Difference Learning Use Emphasis?）</news:title>
   <news:publication_date>2026-08-12T13:03:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722372</loc>
  <lastmod>2026-08-12T13:02:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き合成最適化の近接アルゴリズム（Proximal algorithms for constrained composite optimization, with applications to solving low-rank SDPs）</news:title>
   <news:publication_date>2026-08-12T13:02:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722370</loc>
  <lastmod>2026-08-12T13:01:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散変分ベイズによる拡張物体追跡（Distributed Variational Bayesian Algorithms for Extended Object Tracking）</news:title>
   <news:publication_date>2026-08-12T13:01:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722368</loc>
  <lastmod>2026-08-12T13:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少量データで肺CT画像所見を識別する深層学習の実践（Lung CT Imaging Sign Classification through Deep Learning on Small Data）</news:title>
   <news:publication_date>2026-08-12T13:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722366</loc>
  <lastmod>2026-08-12T13:00:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピラミッド特徴注目ネットワークによる顕著領域検出 (Pyramid Feature Attention Network for Saliency detection)</news:title>
   <news:publication_date>2026-08-12T13:00:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722364</loc>
  <lastmod>2026-08-12T12:09:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問応答ペアからのオープン情報抽出（Open Information Extraction from Question-Answer Pairs）</news:title>
   <news:publication_date>2026-08-12T12:09:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722362</loc>
  <lastmod>2026-08-12T12:09:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習エージェントへのトロイ攻撃の実証（TrojDRL: Trojan Attacks on Deep Reinforcement Learning Agents）</news:title>
   <news:publication_date>2026-08-12T12:09:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722360</loc>
  <lastmod>2026-08-12T12:08:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep and Dark Web上の活動の特徴づけ（Characterizing Activity on the Deep and Dark Web）</news:title>
   <news:publication_date>2026-08-12T12:08:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722358</loc>
  <lastmod>2026-08-12T12:07:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可逆線形埋め込みによる映像外挿 (Video Extrapolation with an Invertible Linear Embedding)</news:title>
   <news:publication_date>2026-08-12T12:07:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722356</loc>
  <lastmod>2026-08-12T12:07:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人とロボットの対話で伸ばす言語理解（Improving Grounded Natural Language Understanding through Human-Robot Dialog）</news:title>
   <news:publication_date>2026-08-12T12:07:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722354</loc>
  <lastmod>2026-08-12T12:07:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未ラベルデータで事前学習したコピー拡張アーキテクチャによる文法誤り訂正の改善（Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data）</news:title>
   <news:publication_date>2026-08-12T12:07:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722352</loc>
  <lastmod>2026-08-12T12:07:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽器オーディオの統一ニューラルアーキテクチャ（A Unified Neural Architecture for Instrumental Audio Tasks）</news:title>
   <news:publication_date>2026-08-12T12:07:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722350</loc>
  <lastmod>2026-08-12T11:15:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ブロックモデルのレビューと応用展望（A Review of Stochastic Block Models and Extensions for Graph Clustering）</news:title>
   <news:publication_date>2026-08-12T11:15:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722348</loc>
  <lastmod>2026-08-12T11:14:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度データに基づく局所幾何インデクシングによるスパースマーカーからの顔再構成（Local Geometric Indexing of High Resolution Data for Facial Reconstruction from Sparse Markers）</news:title>
   <news:publication_date>2026-08-12T11:14:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722346</loc>
  <lastmod>2026-08-12T11:14:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からの自己教師あり深度・法線推定（Self-supervised Learning for Single View Depth and Surface Normal）</news:title>
   <news:publication_date>2026-08-12T11:14:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722344</loc>
  <lastmod>2026-08-12T11:13:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー保護のためのAutoGANに基づく次元削減（AutoGAN-based Dimension Reduction for Privacy Preservation）</news:title>
   <news:publication_date>2026-08-12T11:13:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722342</loc>
  <lastmod>2026-08-12T11:13:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習が至る所にある計算基盤の提案（Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation）</news:title>
   <news:publication_date>2026-08-12T11:13:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722340</loc>
  <lastmod>2026-08-12T11:13:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lipschitz適応と複数学習率によるオンライン学習（Lipschitz Adaptivity with Multiple Learning Rates in Online Learning）</news:title>
   <news:publication_date>2026-08-12T11:13:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722338</loc>
  <lastmod>2026-08-12T11:13:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動性スコアに基づく動画要約（Video Summarization via Actionness Ranking）</news:title>
   <news:publication_date>2026-08-12T11:13:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722336</loc>
  <lastmod>2026-08-12T10:22:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験に基づく計画ドメインにおける学習されたタスク知識と適用範囲（Learning Task Knowledge and its Scope of Applicability in Experience-Based Planning Domains）</news:title>
   <news:publication_date>2026-08-12T10:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722334</loc>
  <lastmod>2026-08-12T10:22:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像プライバシー予測の動的マルチモーダル融合（Dynamic Deep Multi-modal Fusion for Image Privacy Prediction）</news:title>
   <news:publication_date>2026-08-12T10:22:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722332</loc>
  <lastmod>2026-08-12T10:21:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像における肺水腫（肺浮腫）重症度の半教師あり定量化（Semi-supervised Learning for Quantification of Pulmonary Edema in Chest X-Ray Images）</news:title>
   <news:publication_date>2026-08-12T10:21:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722330</loc>
  <lastmod>2026-08-12T10:20:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列分類のためのLSTM-FCNの洞察（Insights into LSTM Fully Convolutional Networks for Time Series Classification）</news:title>
   <news:publication_date>2026-08-12T10:20:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722328</loc>
  <lastmod>2026-08-12T10:20:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tensor Dropoutによる頑健学習の提案（Tensor Dropout for Robust Learning）</news:title>
   <news:publication_date>2026-08-12T10:20:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722326</loc>
  <lastmod>2026-08-12T10:20:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データに対する敵対的攻撃（Adversarial Attacks on Time Series）</news:title>
   <news:publication_date>2026-08-12T10:20:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722324</loc>
  <lastmod>2026-08-12T10:20:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPS軌跡からの移動手段推定における半教師付きGANの応用（Semi-supervised Generative Adversarial Networks for Travel Mode Inference）</news:title>
   <news:publication_date>2026-08-12T10:20:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722322</loc>
  <lastmod>2026-08-12T09:28:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形マルコフ確率場を逆伝播で学習する（Nonlinear Markov Random Fields Learned via Backpropagation）</news:title>
   <news:publication_date>2026-08-12T09:28:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722320</loc>
  <lastmod>2026-08-12T09:28:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内省学習（Introspection Learning）</news:title>
   <news:publication_date>2026-08-12T09:28:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/722318</loc>
  <lastmod>2026-08-12T09:28:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T09:28:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722316</loc>
  <lastmod>2026-08-12T09:27:10Z</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>2026-08-12T09:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722314</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T09:26:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フラクチャー関数に基づく回折性DISの現象論と回折性パートン分布関数の決定（Phenomenology of diffractive DIS in the framework of fracture functions and determination of diffractive parton distribution functions）</news:title>
   <news:publication_date>2026-08-12T09:26:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T09:26:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T08:35:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722306</loc>
  <lastmod>2026-08-12T08:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライベート中心点と半空間の学習（Private Center Points and Learning of Halfspaces）</news:title>
   <news:publication_date>2026-08-12T08:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722304</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>高確率一般化境界と均一安定性の最適率への接近（High probability generalization bounds for uniformly stable algorithms with nearly optimal rate）</news:title>
   <news:publication_date>2026-08-12T08:34:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722302</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T08:33:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ベイズ最適化で低次元特徴空間を使う意義（High-dimensional Bayesian optimization using low-dimensional feature spaces）</news:title>
   <news:publication_date>2026-08-12T08:33:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722298</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T08:32:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722296</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>屋内ロボット向け物体検出器のカスタマイズ (Customizing Object Detectors for Indoor Robots)</news:title>
   <news:publication_date>2026-08-12T08:32:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722294</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T07:41:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722292</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>局所関数複雑性に基づく能動学習（Local Function Complexity for Active Learning via Mixture of Gaussian Processes）</news:title>
   <news:publication_date>2026-08-12T07:41:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722290</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>電子イオン衝突器での半包摂深部非弾性散乱と分布・フラグメンテーション関数（Semi-inclusive Deep-Inelastic Scattering, Parton Distributions and Fragmentation Functions at a Future Electron-Ion Collider）</news:title>
   <news:publication_date>2026-08-12T07:40:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722288</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>Regularity Normalization：神経科学に着想を得た無監督レイヤー間注目（Regularity Normalization: Neuroscience-Inspired Unsupervised Attention across Neural Network Layers）</news:title>
   <news:publication_date>2026-08-12T07:39:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722286</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>説明から合成へ：デモンストレーション学習のための合成的プログラム誘導（From explanation to synthesis: Compositional program induction for learning from demonstration）</news:title>
   <news:publication_date>2026-08-12T07:39:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T07:39:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722280</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>レベルセット学習による非線形次元削減（Learning nonlinear level sets for dimensionality reduction in function approximation）</news:title>
   <news:publication_date>2026-08-12T06:47:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722278</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>vitrivrの概念検出とVBS2019での総括 (Deep Learning-based Concept Detection in vitrivr at the Video Browser Showdown 2019 – Final Notes)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722276</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>Q学習のアンサンブル手法を社会選択理論で統一する（Unifying Ensemble Methods for Q-learning via Social Choice Theory）</news:title>
   <news:publication_date>2026-08-12T06:46:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722274</loc>
  <lastmod>2026-08-12T06:45:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配ベースのメタ学習に関する証明可能な保証 (Provable Guarantees for Gradient-Based Meta-Learning)</news:title>
   <news:publication_date>2026-08-12T06:45:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722272</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>逐次混合モデルの準ベイズ性（Quasi-Bayes properties of a recursive procedure for mixtures）</news:title>
   <news:publication_date>2026-08-12T06:45:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722270</loc>
  <lastmod>2026-08-12T06:45:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的目的を学習するポリシー（Learning Dynamic-Objective Policies from a Class of Optimal Trajectories）</news:title>
   <news:publication_date>2026-08-12T06:45:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722268</loc>
  <lastmod>2026-08-12T06:44:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T06:44:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722266</loc>
  <lastmod>2026-08-12T05:52:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河衝突の観測とシミュレーションにおける識別（Identifying Galaxy Mergers in Observations and Simulations with Deep Learning）</news:title>
   <news:publication_date>2026-08-12T05:52:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722264</loc>
  <lastmod>2026-08-12T05:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因子化マルコフ決定過程における</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722262</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>LPWAネットワークにおける再送を考慮したチャネル選択の学習（Upper-Confidence Bound for Channel Selection in LPWA Networks with Retransmissions）</news:title>
   <news:publication_date>2026-08-12T05:52:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722260</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>信頼できる学習内蔵型自律システムの設計（Architecting Dependable Learning-enabled Autonomous Systems: A Survey）</news:title>
   <news:publication_date>2026-08-12T05:51:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722258</loc>
  <lastmod>2026-08-12T05:50:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツイートが実際に性差別的であるとき（When a Tweet is Actually Sexist）</news:title>
   <news:publication_date>2026-08-12T05:50:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722256</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>関連性照合のための多解像度グラフアテンションネットワーク（Multiresolution Graph Attention Networks for Relevance Matching）</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>多腕同時選択の全バンディット観測下での多腕同定の多項式時間アルゴリズム（Polynomial-time Algorithms for Multiple-arm Identification with Full-bandit Feedback）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722252</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>原子核における新しいクォークとグルーオン効果の露呈（Exposing Novel Quark and Gluon Effects in Nuclei）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T04:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ELMによるLED MIMO受信機設計――非線形とクロスLED干渉を同時に扱う（EXTREME LEARNING MACHINE-BASED RECEIVER FOR MIMO LED COMMUNICATIONS）</news:title>
   <news:publication_date>2026-08-12T04:56:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepLO: Geometry-Aware Deep LiDAR Odometry（DeepLO: Geometry-Aware Deep LiDAR Odometry）</news:title>
   <news:publication_date>2026-08-12T04:56:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722240</loc>
  <lastmod>2026-08-12T04:56:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己対戦学習の高速化――KataGoによるGo学習効率の革新（Accelerating Self-Play Learning in Go）</news:title>
   <news:publication_date>2026-08-12T04:56:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722238</loc>
  <lastmod>2026-08-12T04:04:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習済み言語モデルからの転移学習の極めて単純なアプローチ（An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models）</news:title>
   <news:publication_date>2026-08-12T04:04:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722236</loc>
  <lastmod>2026-08-12T04:04:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性支援による部分検出と精錬による人物再識別の改善（Attributes-aided Part Detection and Refinement for Person Re-identification）</news:title>
   <news:publication_date>2026-08-12T04:04:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722234</loc>
  <lastmod>2026-08-12T04:03:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Active Subspacesによる高次元不確かさ伝播の可視化と削減（DEEP ACTIVE SUBSPACES - A SCALABLE METHOD FOR HIGH-DIMENSIONAL UNCERTAINTY PROPAGATION）</news:title>
   <news:publication_date>2026-08-12T04:03:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722232</loc>
  <lastmod>2026-08-12T04:03:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子構造学習（Atomistic Structure Learning）</news:title>
   <news:publication_date>2026-08-12T04:03:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722230</loc>
  <lastmod>2026-08-12T04:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物学的に妥当な深層学習—浅いネットワークでどこまで可能か？ (Biologically plausible deep learning – but how far can we go with shallow networks?)</news:title>
   <news:publication_date>2026-08-12T04:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722228</loc>
  <lastmod>2026-08-12T04:03:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>依存構文解析をラベリングで再定式化する意義（Viable Dependency Parsing as Sequence Labeling）</news:title>
   <news:publication_date>2026-08-12T04:03:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722226</loc>
  <lastmod>2026-08-12T04:02:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈に基づく文結合の大規模データセット（DISCOFUSE: A Large-Scale Dataset for Discourse-Based Sentence Fusion）</news:title>
   <news:publication_date>2026-08-12T04:02:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722224</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抵抗ノイズ測定が解き明かす1/f過剰雑音の正体（Learning to measure resistance noise demystifies the ubiquitous 1/f excess noise）</news:title>
   <news:publication_date>2026-08-12T03:11:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722222</loc>
  <lastmod>2026-08-12T03:01:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EL EmbeddingsによるEL++論理理論のベクトル化（EL Embeddings: Geometric construction of models for the Description Logic EL++）</news:title>
   <news:publication_date>2026-08-12T03:01:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722220</loc>
  <lastmod>2026-08-12T03:01:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>窒化物半導体Ca(Mg1−xZnx)2N2による可変発光とp型導電性（Tunable light-emission through the range 1.8–3.2 eV and p-type conductivity at room temperature for nitride semiconductors, Ca(Mg1−xZnx)2N2）</news:title>
   <news:publication_date>2026-08-12T03:01:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-12T03:00:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模公開オンラインコースとクラウドコンピューティング（Massive Open Online Courses and Cloud Computing）</news:title>
   <news:publication_date>2026-08-12T03:00:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722216</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>継続学習における小さなエピソード記憶の効用 (On Tiny Episodic Memories in Continual Learning)</news:title>
   <news:publication_date>2026-08-12T03:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-12T03:00:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的ガウシアンコピュラABC（Adaptive Gaussian Copula ABC）</news:title>
   <news:publication_date>2026-08-12T03:00:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722212</loc>
  <lastmod>2026-08-12T02:59:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス表現を誘導して少数例から学ぶ方法（Induction Networks for Few-Shot Text Classification）</news:title>
   <news:publication_date>2026-08-12T02:59:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722210</loc>
  <lastmod>2026-08-12T02:08:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込み事前分布を持つゲート付きコンテキストモデルによる深層画像圧縮（Gated Context Model with Embedded Priors for Deep Image Compression）</news:title>
   <news:publication_date>2026-08-12T02:08:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722208</loc>
  <lastmod>2026-08-12T02:07:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Generative Collaborative Networksによる単一画像超解像の新展開（Generative Collaborative Networks for Single Image Super-Resolution）</news:title>
   <news:publication_date>2026-08-12T02:07:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722206</loc>
  <lastmod>2026-08-12T02:07:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MBCliqueNetによるCNNの軽量化と実用化の意義（Modulated Binary Cliquenet）</news:title>
   <news:publication_date>2026-08-12T02:07:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722204</loc>
  <lastmod>2026-08-12T02:06:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固定分類器と正多面体による判別表現の安定化（Fix Your Features: Stationary and Maximally Discriminative Embeddings using Regular Polytope (Fixed Classifier) Networks）</news:title>
   <news:publication_date>2026-08-12T02:06:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722202</loc>
  <lastmod>2026-08-12T02:06:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所内在次元に基づくデータ分割（Data segmentation based on the local intrinsic dimension）</news:title>
   <news:publication_date>2026-08-12T02:06:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722200</loc>
  <lastmod>2026-08-12T02:06:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層量子ニューラルネットワークの効率的学習（Efficient Learning for Deep Quantum Neural Networks）</news:title>
   <news:publication_date>2026-08-12T02:06:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722198</loc>
  <lastmod>2026-08-12T02:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電波干渉計キャリブレーションの統計的性能（Statistical Performance of Radio Interferometric Calibration）</news:title>
   <news:publication_date>2026-08-12T02:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722196</loc>
  <lastmod>2026-08-12T01:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-12T01:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722194</loc>
  <lastmod>2026-08-12T01:13:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延フィードバック下における適応ヘッジング（Adaptive Hedging under Delayed Feedback）</news:title>
   <news:publication_date>2026-08-12T01:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722192</loc>
  <lastmod>2026-08-12T01:13:16Z</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>2026-08-12T01:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722190</loc>
  <lastmod>2026-08-12T01:12:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等化正規化によるニューラルネットワークの再パラメータ化（EQUI-NORMALIZATION OF NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-08-12T01:12:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722188</loc>
  <lastmod>2026-08-12T01:12:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FickleNetの要点と実務的意義（FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference）</news:title>
   <news:publication_date>2026-08-12T01:12:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722186</loc>
  <lastmod>2026-08-12T01:12:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像で安定動作するCNNの単一フレーム正則化（Single-frame Regularization for Temporally Stable CNNs）</news:title>
   <news:publication_date>2026-08-12T01:12:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722184</loc>
  <lastmod>2026-08-12T01:12:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文章から自動で問いを作る技術の革新（Learning to Generate Questions by Learning What not to Generate）</news:title>
   <news:publication_date>2026-08-12T01:12:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722182</loc>
  <lastmod>2026-08-12T00:20:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付き内積による表現学習の普遍近似（Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities）</news:title>
   <news:publication_date>2026-08-12T00:20:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722180</loc>
  <lastmod>2026-08-12T00:20:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配フロー消滅による非線形固有関数の計算（Computing Nonlinear Eigenfunctions via Gradient Flow Extinction）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722178</loc>
  <lastmod>2026-08-12T00:20:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-12T00:20:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/722176</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>
  <loc>https://aibr.jp/archives/722174</loc>
  <lastmod>2026-08-12T00:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルビッグデータにおける信頼性と意味解析の展望（Social Credibility incorporating Semantic Analysis and Machine Learning）</news:title>
   <news:publication_date>2026-08-12T00:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722172</loc>
  <lastmod>2026-08-12T00:19:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーネットワークによる関数的画像表現（Hypernetwork functional image representation）</news:title>
   <news:publication_date>2026-08-12T00:19:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722170</loc>
  <lastmod>2026-08-12T00:19:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然画像のノイズ除去学習を地震データ補間に使えるか（Can learning from natural image denoising be used for seismic data interpolation?）</news:title>
   <news:publication_date>2026-08-12T00:19:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722168</loc>
  <lastmod>2026-08-11T23:26:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸ペナルティを用いるスパース線形回帰のCV高速化と安定性（Cross validation in sparse linear regression with piecewise continuous nonconvex penalties and its acceleration）</news:title>
   <news:publication_date>2026-08-11T23:26:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722166</loc>
  <lastmod>2026-08-11T23:26:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン制約付き広告キーワード生成（Domain-Constrained Advertising Keyword Generation）</news:title>
   <news:publication_date>2026-08-11T23:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722164</loc>
  <lastmod>2026-08-11T23:26:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系譜検索のランキング統合（RANKING IN GENEALOGY: SEARCH RESULTS FUSION AT ANCESTRY）</news:title>
   <news:publication_date>2026-08-11T23:26:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722162</loc>
  <lastmod>2026-08-11T23:25:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布的頑健性に基づく多重カーネル学習の最適化手法（A Distributionally Robust Optimization Method for Adversarial Multiple Kernel Learning）</news:title>
   <news:publication_date>2026-08-11T23:25:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722160</loc>
  <lastmod>2026-08-11T23:25:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ損失認識に基づくチャネルプルーニング（MULTI-LOSS-AWARE CHANNEL PRUNING OF DEEP NETWORKS）</news:title>
   <news:publication_date>2026-08-11T23:25:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722158</loc>
  <lastmod>2026-08-11T23:25:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モチーフを利用した拡散ネットワークの時間的ダイナミクスモデル（Leveraging Motifs to Model the Temporal Dynamics of Diffusion Networks）</news:title>
   <news:publication_date>2026-08-11T23:25:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722156</loc>
  <lastmod>2026-08-11T23:25:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスター正則化量子化による深層ネットワーク圧縮（Cluster Regularized Quantization for Deep Networks Compression）</news:title>
   <news:publication_date>2026-08-11T23:25:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722154</loc>
  <lastmod>2026-08-11T22:33:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コメントの毒性分類における機械学習手法（A Machine Learning Approach to Comment Toxicity Classification）</news:title>
   <news:publication_date>2026-08-11T22:33:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722152</loc>
  <lastmod>2026-08-11T22:22:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット視覚におけるメトリック学習の重要性（The Importance of Metric Learning for Robotic Vision: Open Set Recognition and Active Learning）</news:title>
   <news:publication_date>2026-08-11T22:22:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722150</loc>
  <lastmod>2026-08-11T22:22:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN画像フォレンジクスの一般化に関する研究（On the Generalization of GAN Image Forensics）</news:title>
   <news:publication_date>2026-08-11T22:22:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722148</loc>
  <lastmod>2026-08-11T22:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>加齢性黄斑変性の進行予測に向けた深層学習アプローチ（A Deep-learning Approach for Prognosis of Age-Related Macular Degeneration Disease using SD-OCT Imaging Biomarkers）</news:title>
   <news:publication_date>2026-08-11T22:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722146</loc>
  <lastmod>2026-08-11T22:22:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予算制約下での因果構造探索を効率化する実験設計（ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery）</news:title>
   <news:publication_date>2026-08-11T22:22:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722144</loc>
  <lastmod>2026-08-11T22:21:34Z</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とガウス過程の深い結びつきが能動学習を加速する（Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning）</news:title>
   <news:publication_date>2026-08-11T22:21:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722142</loc>
  <lastmod>2026-08-11T22:21:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類に必要な語彙サイズの見積り手法（How Large a Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary Selection）</news:title>
   <news:publication_date>2026-08-11T22:21:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722140</loc>
  <lastmod>2026-08-11T21:30:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>治療効果下のサブグループ探索のための機械学習（Machine learning for subgroup discovery under treatment effect）</news:title>
   <news:publication_date>2026-08-11T21:30:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722138</loc>
  <lastmod>2026-08-11T21:30:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境におけるビザンチン耐性確率的勾配降下法（Distributed Byzantine Tolerant Stochastic Gradient Descent in the Era of Big Data）</news:title>
   <news:publication_date>2026-08-11T21:30:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722136</loc>
  <lastmod>2026-08-11T21:30:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分 disentangled 表現による自動エンコーディング正則化がもたらす頑健な画像分類（Disentangled Deep Autoencoding Regularization for Robust Image Classification）</news:title>
   <news:publication_date>2026-08-11T21:30:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722134</loc>
  <lastmod>2026-08-11T21:29:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知力学系の安全環境と制御器を決める新しいシミュレーション指標（A New Simulation Metric to Determine Safe Environments and Controllers for Systems with Unknown Dynamics）</news:title>
   <news:publication_date>2026-08-11T21:29:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722132</loc>
  <lastmod>2026-08-11T21:29:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TensorFlow Eagerが変えたプロトタイピングの常識（TensorFlow Eager: A multi-stage, Python-embedded DSL for machine learning）</news:title>
   <news:publication_date>2026-08-11T21:29:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722130</loc>
  <lastmod>2026-08-11T21:28:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルによるパケット分類の学習（Neural Packet Classification）</news:title>
   <news:publication_date>2026-08-11T21:28:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722128</loc>
  <lastmod>2026-08-11T21:28:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像特徴を時間と意味で豊かにする視覚エンコーディング（Spatio-Temporal Dynamics and Semantic Attribute Enriched Visual Encoding for Video Captioning）</news:title>
   <news:publication_date>2026-08-11T21:28:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722126</loc>
  <lastmod>2026-08-11T20:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FixyNNによるモバイル向け効率的画像認識ハードウェア（FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning）</news:title>
   <news:publication_date>2026-08-11T20:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722124</loc>
  <lastmod>2026-08-11T20:36:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>先端ナノ空洞による単一量子エミッタのチップ強化強結合（Tip-enhanced strong coupling spectroscopy, imaging, and control of a single quantum emitter）</news:title>
   <news:publication_date>2026-08-11T20:36:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722122</loc>
  <lastmod>2026-08-11T20:36:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ埋め込みを敵対的に整合する手法の要点と経営判断への示唆（Deep Adversarial Network Alignment）</news:title>
   <news:publication_date>2026-08-11T20:36:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722120</loc>
  <lastmod>2026-08-11T20:35:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型コンテンツ配信ネットワークにおける適応キャッシュのための深層強化学習 (Deep Reinforcement Learning for Adaptive Caching in Hierarchical Content Delivery Networks)</news:title>
   <news:publication_date>2026-08-11T20:35:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722118</loc>
  <lastmod>2026-08-11T20:35:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形式言語の表現：有限オートマタと再帰型ニューラルネットワークの比較（Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-08-11T20:35:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722116</loc>
  <lastmod>2026-08-11T20:35:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ANODE：無条件に正確なメモリ効率の良いニューラルODEの勾配（ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs）</news:title>
   <news:publication_date>2026-08-11T20:35:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722114</loc>
  <lastmod>2026-08-11T20:35:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッファード確率的変分推論によるVAEの訓練改善（Training Variational Autoencoders with Buffered Stochastic Variational Inference）</news:title>
   <news:publication_date>2026-08-11T20:35:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722112</loc>
  <lastmod>2026-08-11T19:42:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多原因因果推論における未観測交絡の限界と代替手段（On Multi-Cause Causal Inference with Unobserved Confounding: Counterexamples, Impossibility, and Alternatives）</news:title>
   <news:publication_date>2026-08-11T19:42:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722110</loc>
  <lastmod>2026-08-11T19:42:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序付き距離計量学習とMDSによる画像ランキング（Ordinal Distance Metric Learning with MDS）</news:title>
   <news:publication_date>2026-08-11T19:42:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722108</loc>
  <lastmod>2026-08-11T19:42:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データの価値を定量化する効率的手法（Towards Efficient Data Valuation Based on the Shapley Value）</news:title>
   <news:publication_date>2026-08-11T19:42:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722106</loc>
  <lastmod>2026-08-11T19:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層Q学習アルゴリズムのボトルネック診断（Diagnosing Bottlenecks in Deep Q-learning Algorithms）</news:title>
   <news:publication_date>2026-08-11T19:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722104</loc>
  <lastmod>2026-08-11T19:41:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ逆問題の「整定性」を緩やかに捉える新視点（On the well-posedness of Bayesian inverse problems）</news:title>
   <news:publication_date>2026-08-11T19:41:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722102</loc>
  <lastmod>2026-08-11T19:41:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的談話構造学習によるフェイクニュース検出の深化（Learning Hierarchical Discourse-level Structure for Fake News Detection）</news:title>
   <news:publication_date>2026-08-11T19:41:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722100</loc>
  <lastmod>2026-08-11T19:40:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群オブジェクトのゼロショット学習（Zero-shot Learning of 3D Point Cloud Objects）</news:title>
   <news:publication_date>2026-08-11T19:40:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722098</loc>
  <lastmod>2026-08-11T18:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lidarデータを圧縮して現場で使える地図と位置特定を両立する技術（TENSORMAP: LIDAR-BASED TOPOLOGICAL MAPPING AND LOCALIZATION VIA TENSOR DECOMPOSITIONS）</news:title>
   <news:publication_date>2026-08-11T18:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722096</loc>
  <lastmod>2026-08-11T18:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形力学系の線形埋め込みによる制御（Data-driven approximations of dynamical systems operators for control）</news:title>
   <news:publication_date>2026-08-11T18:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722094</loc>
  <lastmod>2026-08-11T18:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ターゲット指向ハイパースペクトル分離と一般化Robust PCA（Target–Based Hyperspectral Demixing via Generalized Robust PCA）</news:title>
   <news:publication_date>2026-08-11T18:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722092</loc>
  <lastmod>2026-08-11T18:47:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入院患者の電子カルテからの継続的AKI予測（Continual Prediction from EHR Data for Inpatient Acute Kidney Injury）</news:title>
   <news:publication_date>2026-08-11T18:47:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722090</loc>
  <lastmod>2026-08-11T18:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書に基づく一般化されたロバストPCAによるハイパースペクトル分離（A Dictionary-Based Generalization of Robust PCA Part II: Applications to Hyperspectral Demixing）</news:title>
   <news:publication_date>2026-08-11T18:47:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722088</loc>
  <lastmod>2026-08-11T18:47:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回答しない判断を学習する仕組み（Learning When Not to Answer: A Ternary Reward Structure for Reinforcement Learning based Question Answering）</news:title>
   <news:publication_date>2026-08-11T18:47:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722086</loc>
  <lastmod>2026-08-11T18:46:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑ネットワークにおける疾病制御可能性の予測（Prediction of the disease controllability in a complex network using machine learning algorithms）</news:title>
   <news:publication_date>2026-08-11T18:46:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722084</loc>
  <lastmod>2026-08-11T17:54:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インプリシット・カーネル学習が切り拓く新しいカーネル設計（Implicit Kernel Learning）</news:title>
   <news:publication_date>2026-08-11T17:54:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722082</loc>
  <lastmod>2026-08-11T17:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重精度データから学ぶ複合ニューラルネットワーク（A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems）</news:title>
   <news:publication_date>2026-08-11T17:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722080</loc>
  <lastmod>2026-08-11T17:53:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転座標系の理解を深める映像教材の効果（Improving students’ understanding of rotating frames of reference using videos from different perspectives）</news:title>
   <news:publication_date>2026-08-11T17:53:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722078</loc>
  <lastmod>2026-08-11T17:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できる深層成績予測と不確実性推定（Reliable Deep Grade Prediction with Uncertainty Estimation）</news:title>
   <news:publication_date>2026-08-11T17:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722076</loc>
  <lastmod>2026-08-11T17:53:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RotatEによる知識グラフ埋め込みと実務的示唆（RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space）</news:title>
   <news:publication_date>2026-08-11T17:53:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722074</loc>
  <lastmod>2026-08-11T17:53:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全結合的低ランク・総変動正則化を用いたDeep MR Fingerprinting（Deep MR Fingerprinting with total-variation and low-rank subspace priors）</news:title>
   <news:publication_date>2026-08-11T17:53:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722072</loc>
  <lastmod>2026-08-11T17:52:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市の水・電力需要ネクサスの統合解析（Integrated analysis of the urban water-electricity demand nexus in the Midwestern United States）</news:title>
   <news:publication_date>2026-08-11T17:52:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722070</loc>
  <lastmod>2026-08-11T17:01:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>森林と都市での深層レーザーローカリゼーション（Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU）</news:title>
   <news:publication_date>2026-08-11T17:01:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722068</loc>
  <lastmod>2026-08-11T17:01:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化するグラフ畳み込みネットワーク（EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs）</news:title>
   <news:publication_date>2026-08-11T17:01:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722066</loc>
  <lastmod>2026-08-11T17:00:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Clever Hansを見抜く方法と機械が本当に学んでいることの評価（Unmasking Clever Hans Predictors and Assessing What Machines Really Learn）</news:title>
   <news:publication_date>2026-08-11T17:00:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722064</loc>
  <lastmod>2026-08-11T17:00:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークにおけるモデル不確実性の測定のための変分推論（Variational Inference to Measure Model Uncertainty in Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-11T17:00:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722062</loc>
  <lastmod>2026-08-11T17:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attentionは説明にならない（Attention is not Explanation）</news:title>
   <news:publication_date>2026-08-11T17:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722060</loc>
  <lastmod>2026-08-11T16:59:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かさを持つ線形システムの収束性（Convergence in uncertain linear systems）</news:title>
   <news:publication_date>2026-08-11T16:59:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722058</loc>
  <lastmod>2026-08-11T16:59:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な部分集合最適化を高速化するメモ化フレームワーク（A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems）</news:title>
   <news:publication_date>2026-08-11T16:59:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722056</loc>
  <lastmod>2026-08-11T16:08:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成による非線形近似（NONLINEAR APPROXIMATION VIA COMPOSITIONS）</news:title>
   <news:publication_date>2026-08-11T16:08:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722054</loc>
  <lastmod>2026-08-11T16:08:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>割引協調コストを伴う難しい部分モジュラ問題に対する近似アルゴリズム（Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs）</news:title>
   <news:publication_date>2026-08-11T16:08:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722052</loc>
  <lastmod>2026-08-11T16:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的予測を逐次学習で統合する手法（Online Learning with Continuous Ranked Probability Score）</news:title>
   <news:publication_date>2026-08-11T16:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722050</loc>
  <lastmod>2026-08-11T16:06:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次の十年における機械学習の役割（The Role of Machine Learning in the Next Decade of Cosmology）</news:title>
   <news:publication_date>2026-08-11T16:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722048</loc>
  <lastmod>2026-08-11T16:06:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常過渡現象の起源を探るHI観測の示唆（On the nature of the unusual transient AT 2018cow from Hi observations of its host galaxy）</news:title>
   <news:publication_date>2026-08-11T16:06:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722046</loc>
  <lastmod>2026-08-11T16:06:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頻出k-merの高速近似とメタゲノミクスへの応用（Fast Approximation of Frequent k-mers and Applications to Metagenomics）</news:title>
   <news:publication_date>2026-08-11T16:06:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722044</loc>
  <lastmod>2026-08-11T16:06:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模グラフの彩色をAlphaGoZeroで学ぶ（Coloring Big Graphs With AlphaGoZero）</news:title>
   <news:publication_date>2026-08-11T16:06:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722042</loc>
  <lastmod>2026-08-11T15:14:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテキスト化単語表現を用いたマルチタスク学習による拡張固有表現認識（Multi-Task Learning with Contextualized Word Representations for Extended Named Entity Recognition）</news:title>
   <news:publication_date>2026-08-11T15:14:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722040</loc>
  <lastmod>2026-08-11T15:14:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移でガス分率が高い主系列銀河の観測結果（High Gas Fraction in a CO-Selected Main-Sequence Galaxy at z &amp;gt; 3）</news:title>
   <news:publication_date>2026-08-11T15:14:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722038</loc>
  <lastmod>2026-08-11T15:14:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークに基づく病気遺伝子予測（Network-based methods for disease-gene prediction）</news:title>
   <news:publication_date>2026-08-11T15:14:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722036</loc>
  <lastmod>2026-08-11T15:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発話レベル集約による野外環境での話者認識（UTTERANCE-LEVEL AGGREGATION FOR SPEAKER RECOGNITION IN THE WILD）</news:title>
   <news:publication_date>2026-08-11T15:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722034</loc>
  <lastmod>2026-08-11T15:12:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>伝送系の故障を想定したオンライン適応学習による電圧安定性評価（Adaptive Online Learning with Momentum for Contingency-based Voltage Stability Assessment）</news:title>
   <news:publication_date>2026-08-11T15:12:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/722032</loc>
  <lastmod>2026-08-11T15:12:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>摂動履歴による探索（Perturbed-History Exploration in Stochastic Multi-Armed Bandits）</news:title>
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 </url>
 <url>
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 </url>
</urlset>
