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   <news:title>Soft分類器からHard決定へ：公正性はどこまで達成できるか（From Soft Classifiers to Hard Decisions: How fair can we be?）</news:title>
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   <news:title>四点置換検定による潜在ブロック構造の検出（The Four Point Permutation Test for Latent Block Structure in Incidence Matrices）</news:title>
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   <news:title>強化学習とHybrid Zero Dynamicsの融合──RABBIT事例から学ぶ二足歩行制御（Reinforcement Learning Meets Hybrid Zero Dynamics: A Case Study for RABBIT）</news:title>
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    <news:language>ja</news:language>
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   <news:title>画像と符号化テキストの融合によるマルチモーダル分類（Image and Encoded Text Fusion for Multi-Modal Classification）</news:title>
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   <news:title>小規模シストリック配列上のスパースWinograd畳み込み（Sparse Winograd Convolutional neural networks on small-scale systolic arrays）</news:title>
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   <news:title>地震信号検出のための深層残差ネットワーク CRED（CRED: A Deep Residual Network of Convolutional and Recurrent Units for Earthquake Signal Detection）</news:title>
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    <news:language>ja</news:language>
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   <news:title>Hidden Markovモデルに対するアルゴリズミックな分極化（Algorithmic Polarization for Hidden Markov Models）</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>Transfer Learning via Unsupervised Task Discovery for Visual Question Answering（Transfer Learning via Unsupervised Task Discovery for Visual Question Answering）</news:title>
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   <news:title>カートポール問題に対する強化学習アルゴリズムの比較（Comparison of Reinforcement Learning Algorithms applied to the Cart-Pole Problem）</news:title>
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    <news:language>ja</news:language>
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   <news:title>MAWILabトレースから生成するラベル付きフローデータ（Generating Labeled Flow Data from MAWILab Traces for Network Intrusion Detection）</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>データ処理クラスタのスケジューリングを学習する（Learning Scheduling Algorithms for Data Processing Clusters）</news:title>
   <news:publication_date>2026-06-19T22:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T21:19:57Z</lastmod>
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    <news:language>ja</news:language>
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   <news:title>回折型光ニューラルネットワークの解析と電子ニューラルネットワークとの統合（Analysis of Diffractive Optical Neural Networks and Their Integration with Electronic Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news: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>バンディット学習が示す競争下の安定性（BANDIT LEARNING IN CONCAVE N-PERSON GAMES）</news:title>
   <news:publication_date>2026-06-19T21:19:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>オンライン学習による一般化逆最適化 (Generalized Inverse Optimization through Online Learning)</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T21:17:42Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>患者質問票によるパーキンソン病の早期検出（Early Detection of Parkinson&amp;#039;s Disease through Patient Questionnaire and Predictive Modelling）</news:title>
   <news:publication_date>2026-06-19T21:17:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T21:17:34Z</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>高解像度で学ぶ単眼深度推定の革新（SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T21:17:15Z</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>法務文書向け感情判定を迅速に構築する手法（Fast Approach to Build an Automatic Sentiment Annotator for Legal Domain using Transfer Learning）</news:title>
   <news:publication_date>2026-06-19T21:17:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T20:26:00Z</lastmod>
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    <news:language>ja</news:language>
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   <news:title>作業指向の手運動リターゲティングによる巧緻な操作模倣（Task-Oriented Hand Motion Retargeting for Dexterous Manipulation Imitation）</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>事前定義した類似度に基づくkクラスタ数の最適決定（Determining Optimal Number of k-Clusters based on Predefined Level-of-Similarity）</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>重み正規化された深層ニューラルネットワークの理解（Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T20:24:51Z</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>重み付きシグモイドゲートによる活性化関数の提案（Weighted Sigmoid Gate Unit for an Activation Function of Deep Neural Network）</news:title>
   <news:publication_date>2026-06-19T20:24:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T20:24:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>重なりを扱うニューラルセグメンタルハイパーグラフ（Neural Segmental Hypergraphs for Overlapping Mention Recognition）</news:title>
   <news:publication_date>2026-06-19T20:24:38Z</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>単一画像超解像におけるチャネル再校正の威力（An Effective Single-Image Super-Resolution Model Using Squeeze-and-Excitation Networks）</news:title>
   <news:publication_date>2026-06-19T20:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T20:24:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>人間中心の自動運転システム：効果的な共有自律の原則（Human-Centered Autonomous Vehicle Systems: Principles of Effective Shared Autonomy）</news:title>
   <news:publication_date>2026-06-19T20:24:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/702580</loc>
  <lastmod>2026-06-19T19:32:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Shrinkwrapによる差分プライバシー対応の高速SQL処理（Shrinkwrap: Efficient SQL Query Processing in Differentially Private Data Federations）</news:title>
   <news:publication_date>2026-06-19T19:32:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/702578</loc>
  <lastmod>2026-06-19T19:32:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ASTに基づく深層学習による悪性PowerShell検出（AST-Based Deep Learning for Detecting Malicious PowerShell）</news:title>
   <news:publication_date>2026-06-19T19:32:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/702576</loc>
  <lastmod>2026-06-19T19:32:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルにおける「スプリアス（偽）サンプル」は欠陥か、機能か（Spurious samples in deep generative models: bug or feature?）</news:title>
   <news:publication_date>2026-06-19T19:32:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/702574</loc>
  <lastmod>2026-06-19T19:31:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一意的な森の因数分解（Unambiguous Forest Factorization）</news:title>
   <news:publication_date>2026-06-19T19:31:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/702572</loc>
  <lastmod>2026-06-19T19:31:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>McTorch：PyTorchのための多様体最適化ライブラリ（McTorch, a manifold optimization library for deep learning）</news:title>
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   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-06-19T19:31:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ネストしたメンション認識の遷移基礎モデル（A Neural Transition-based Model for Nested Mention Recognition）</news:title>
   <news:publication_date>2026-06-19T19:31:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T19:30:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声に基づくアーティスト識別の拡張（Disambiguating Music Artists at Scale with Audio Metric Learning）</news:title>
   <news:publication_date>2026-06-19T19:30:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/702566</loc>
  <lastmod>2026-06-19T18:39:51Z</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>2026-06-19T18:39:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T18:39:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工ニューラルネットワークの位相的探索（Topological exploration of artificial neuronal network dynamics）</news:title>
   <news:publication_date>2026-06-19T18:39:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>センサ運動的不変性から学ぶロボットの空間認識（Learning agent’s spatial configuration from sensorimotor invariants）</news:title>
   <news:publication_date>2026-06-19T18:38:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T18:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T18:38:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>自然勾配とヘシアンフリーの統合による系列訓練最適化（Combining Natural Gradient with Hessian Free Methods for Sequence Training）</news:title>
   <news:publication_date>2026-06-19T18:37:42Z</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>オンライン毒性検出の機械学習スイート（Machine Learning Suites for Online Toxicity Detection）</news:title>
   <news:publication_date>2026-06-19T17:46:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702550</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>高次元多標本比較の非パラメトリック手法（A Nonparametric Approach to High-dimensional k-sample Comparison Problems）</news:title>
   <news:publication_date>2026-06-19T17:46:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702548</loc>
  <lastmod>2026-06-19T17:46:35Z</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>2026-06-19T17:46:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T17:45:39Z</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>エンドエフェクタ配置空間の内部表現学習（Learning an internal representation of the end-effector configuration space）</news:title>
   <news:publication_date>2026-06-19T17:45:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新領域のNLU向けアクティブラーニング（Active Learning for New Domains in Natural Language Understanding）</news:title>
   <news:publication_date>2026-06-19T17:45:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T17:45:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アグノスティック回帰における有界サンプル圧縮の前進（Agnostic Sample Compression Schemes for Regression）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702534</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実稼働HPCクラスターにおける熱モデル同定の堅牢化とデータ選択（Robust identification of thermal models for in-production High-Performance-Computing clusters with machine learning-based data selection）</news:title>
   <news:publication_date>2026-06-19T16:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースによる完全自動の短軸心臓MRI層間動き補正法（A Comprehensive Approach for Learning-based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks）</news:title>
   <news:publication_date>2026-06-19T16:45:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Safe RuleFitによる最適スパースルール学習（Safe RuleFit: Learning Optimal Sparse Rule Model by Meta Safe Screening）</news:title>
   <news:publication_date>2026-06-19T16:44:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702528</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>扱いやすい経験的尤度を用いたABC法（An Easy-to-Use Empirical Likelihood ABC Method）</news:title>
   <news:publication_date>2026-06-19T16:44:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702526</loc>
  <lastmod>2026-06-19T16:44:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LN-CASS：スパイク・アンド・スラブの連続近似による同時推定と変数選択（Simultaneous Parameter Estimation and Variable Selection via the LN-CASS Prior）</news:title>
   <news:publication_date>2026-06-19T16:44:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702524</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>DeepImageSpam: 画像スパム検出における深層学習の実践（DeepImageSpam: Deep Learning based Image Spam Detection）</news:title>
   <news:publication_date>2026-06-19T15:52:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702522</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>スマホ向け知覚的画質向上チャレンジの総括（PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report）</news:title>
   <news:publication_date>2026-06-19T15:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702520</loc>
  <lastmod>2026-06-19T15:51:14Z</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>2026-06-19T15:51:14Z</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>Inhibited Softmaxによる不確かさ推定の実践的解説（Inhibited Softmax for Uncertainty Estimation in Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702516</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>2026-06-19T15:50:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702514</loc>
  <lastmod>2026-06-19T15:50:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KiDS0239-3211 による強重力レンズ候補の発見（KiDS0239-3211: A new gravitational quadruple lens candidate）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702512</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>2026-06-19T15:49:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702510</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>極端なデータ拡張：手作業で一例だけラベル付けした医療画像で学習できるか（Extreme Augmentation: Can deep learning based medical image segmentation be trained using a single manually delineated scan?）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702508</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>WARSHIPによる脳インスパイア型画像超解像の統合的枠組み（Towards WARSHIP: Combining Components of Brain-Inspired Computing of RSH for Image Super Resolution）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成深層学習の理論 II：正則化に基づく容量制御で経験誤差の地形を探る（Theory of Generative Deep Learning II: Probe Landscape of Empirical Error via Norm Based Capacity Control）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>階層的モジュラー表現による層状ニューラルネットワークの解釈（Interpreting Layered Neural Networks via Hierarchical Modular Representation）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>LHCで有効演算子を特定する学習法 — ttbbシグネチャの解析（Learning to pinpoint effective operators at the LHC: a study of the ttbb signature）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対応点なしで求める基本行列の深層推定（Deep Fundamental Matrix Estimation without Correspondences）</news:title>
   <news:publication_date>2026-06-19T14:04:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702492</loc>
  <lastmod>2026-06-19T14:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RF電源バックスキャッタ認知無線ネットワークにおける時間割当ての深層強化学習（Deep Reinforcement Learning for Time Scheduling in RF-Powered Backscatter Cognitive Radio Networks）</news:title>
   <news:publication_date>2026-06-19T14:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702490</loc>
  <lastmod>2026-06-19T14:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子ベースの動力学学習によるロボット操作（LEARNING PARTICLE DYNAMICS FOR MANIPULATING RIGID BODIES, DEFORMABLE OBJECTS, AND FLUIDS）</news:title>
   <news:publication_date>2026-06-19T14:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702488</loc>
  <lastmod>2026-06-19T14:03:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転車向けディープラーニングベースのキャッシング（Deep Learning Based Caching for Self-Driving Cars in Multi-access Edge Computing）</news:title>
   <news:publication_date>2026-06-19T14:03:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702486</loc>
  <lastmod>2026-06-19T14:03:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者記録の匿名化に向けた深層学習アーキテクチャ（A Deep Learning Architecture for De-identiﬁcation of Patient Notes: Implementation and Evaluation）</news:title>
   <news:publication_date>2026-06-19T14:03:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702484</loc>
  <lastmod>2026-06-19T14:02:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相対的注目度とオブジェクトのランキング（Relative Saliency and Ranking: Models, Metrics, Data and Benchmarks）</news:title>
   <news:publication_date>2026-06-19T14:02:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702482</loc>
  <lastmod>2026-06-19T13:11:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像をデータ化する：政治学のための自動視覚コンテンツ分析（Image as Data: Automated Visual Content Analysis for Political Science）</news:title>
   <news:publication_date>2026-06-19T13:11:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702480</loc>
  <lastmod>2026-06-19T13:10:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適ドメイン適応のための一般化ニーマン・ピアソン基準（A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation）</news:title>
   <news:publication_date>2026-06-19T13:10:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702478</loc>
  <lastmod>2026-06-19T13:10:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的プログラミング言語による自動化学習（Automated learning with a probabilistic programming language: Birch）</news:title>
   <news:publication_date>2026-06-19T13:10:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702476</loc>
  <lastmod>2026-06-19T13:08:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連結データで正しい推論を行う実用的アプローチ（A Practical Approach to Proper Inference with Linked Data）</news:title>
   <news:publication_date>2026-06-19T13:08:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702474</loc>
  <lastmod>2026-06-19T13:08:38Z</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決定境界を可視化する手法（Geometric Illustration of Neural Networks）</news:title>
   <news:publication_date>2026-06-19T13:08:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702472</loc>
  <lastmod>2026-06-19T13:08:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変ソケット位置での挿入作業に対する現実的アプローチ（A Practical Approach to Insertion with Variable Socket Position）</news:title>
   <news:publication_date>2026-06-19T13:08:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702470</loc>
  <lastmod>2026-06-19T13:08:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デュアルバンドシステムにおけるバンド割当の学習的アプローチ（Band Assignment in Dual Band Systems: A Learning-based Approach）</news:title>
   <news:publication_date>2026-06-19T13:08:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702468</loc>
  <lastmod>2026-06-19T12:16:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンドロメダの巨大南方ストリームに沿った距離と金属量の勾配（Distance and Metallicity Gradients Along Andromeda’s Giant Southern Stream From the Red Clump）</news:title>
   <news:publication_date>2026-06-19T12:16:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702466</loc>
  <lastmod>2026-06-19T12:15:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CINIC-10データセットの意義（CINIC-10 Is Not ImageNet or CIFAR-10）</news:title>
   <news:publication_date>2026-06-19T12:15:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702464</loc>
  <lastmod>2026-06-19T12:15:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動プレイリスト補完の競技的検討──RecSys Challenge 2018の示した実務示唆（An Analysis of Approaches Taken in the ACM RecSys Challenge 2018 for Automatic Music Playlist Continuation）</news:title>
   <news:publication_date>2026-06-19T12:15:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702462</loc>
  <lastmod>2026-06-19T12:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練を要さない簡潔な画像表現としてのDeep Decoder（Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks）</news:title>
   <news:publication_date>2026-06-19T12:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702460</loc>
  <lastmod>2026-06-19T12:14:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブモジュラー最適化のMapReduceモデル（Submodular Optimization in the MapReduce Model）</news:title>
   <news:publication_date>2026-06-19T12:14:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702458</loc>
  <lastmod>2026-06-19T12:14:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的コミュニティ検出の再帰的分割法（Hierarchical community detection by recursive partitioning）</news:title>
   <news:publication_date>2026-06-19T12:14:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702456</loc>
  <lastmod>2026-06-19T12:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果的コンテクスチュアル多腕バンディットによるマーケティング最適化（Contextual Multi-Armed Bandits for Causal Marketing）</news:title>
   <news:publication_date>2026-06-19T12:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702454</loc>
  <lastmod>2026-06-19T11:23:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepCMBによるCMB重力レンズ復元と深層学習の応用（DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-19T11:23:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702452</loc>
  <lastmod>2026-06-19T11:22:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽レコメンドの多様化手法（Diversifying Music Recommendations）</news:title>
   <news:publication_date>2026-06-19T11:22:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702450</loc>
  <lastmod>2026-06-19T11:22:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘキソース結合の生化学的知見を検証する帰納的論理プログラミングの応用（An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge）</news:title>
   <news:publication_date>2026-06-19T11:22:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702448</loc>
  <lastmod>2026-06-19T11:21:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造に基づく多ラベル医療テキストタグ付け（Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding）</news:title>
   <news:publication_date>2026-06-19T11:21:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702446</loc>
  <lastmod>2026-06-19T11:21:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロシア系ツイッター操作の痕跡を無監督学習で解き明かす（Unsupervised Machine Learning of Open Source Russian Twitter Data Reveals Global Scope and Operational Characteristics）</news:title>
   <news:publication_date>2026-06-19T11:21:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702444</loc>
  <lastmod>2026-06-19T11:21:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力分割を学習するNMTが示す文字レベルの優位性（Learning to Segment Inputs for NMT）</news:title>
   <news:publication_date>2026-06-19T11:21:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702442</loc>
  <lastmod>2026-06-19T11:20:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的個別化による視覚的発見の多様化（Adaptive, Personalized Diversity for Visual Discovery）</news:title>
   <news:publication_date>2026-06-19T11:20:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702440</loc>
  <lastmod>2026-06-19T10:29:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動認識のための表現フロー（Representation Flow for Action Recognition）</news:title>
   <news:publication_date>2026-06-19T10:29:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702438</loc>
  <lastmod>2026-06-19T10:28:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き暗黙的最尤推定による超解像（Super-Resolution via Conditional Implicit Maximum Likelihood Estimation）</news:title>
   <news:publication_date>2026-06-19T10:28:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702436</loc>
  <lastmod>2026-06-19T10:28:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算的に実現可能な頑健学習は可能か（Can Adversarially Robust Learning Leverage Computational Hardness?）</news:title>
   <news:publication_date>2026-06-19T10:28:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702434</loc>
  <lastmod>2026-06-19T10:28:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GrAMME：マルチレイヤーグラフ注意モデルを用いた半教師あり学習（GrAMME: Semi-Supervised Learning using Multi-layered Graph Attention Models）</news:title>
   <news:publication_date>2026-06-19T10:28:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702432</loc>
  <lastmod>2026-06-19T10:28:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GLAD: 人間を巻き込むローカル重み付けによる異常検知の実務接続（GLAD: GLocalized Anomaly Detection via Human-in-the-Loop Learning）</news:title>
   <news:publication_date>2026-06-19T10:28:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702430</loc>
  <lastmod>2026-06-19T10:27:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適補完蒸留法（Optimal Completion Distillation）によるシーケンス学習の革新</news:title>
   <news:publication_date>2026-06-19T10:27:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702428</loc>
  <lastmod>2026-06-19T10:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在ディリクレ・カテゴリカルモデルのスケッチ手法 (Sketching for Latent Dirichlet-Categorical Models)</news:title>
   <news:publication_date>2026-06-19T10:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702426</loc>
  <lastmod>2026-06-19T09:36:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルのアンサンブルによる堅牢な異常検知（WAIC, but Why? Generative Ensembles for Robust Anomaly Detection）</news:title>
   <news:publication_date>2026-06-19T09:36:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702424</loc>
  <lastmod>2026-06-19T09:36:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習によるヒトプロモーター予測（PromID: human promoter prediction by deep learning）</news:title>
   <news:publication_date>2026-06-19T09:36:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702422</loc>
  <lastmod>2026-06-19T09:36:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散表現を用いた位相推定で音源分離の天井を押し上げる（Phasebook and Friends: Leveraging discrete representations for source separation）</news:title>
   <news:publication_date>2026-06-19T09:36:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702420</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>2026-06-19T09:34:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702418</loc>
  <lastmod>2026-06-19T09:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半密度ステレオマッチングを実現する二重CNN（Semi-dense Stereo Matching using Dual CNNs）</news:title>
   <news:publication_date>2026-06-19T09:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702416</loc>
  <lastmod>2026-06-19T09:34:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FFJORD: 自由形式の連続ダイナミクスによるスケーラブルな可逆生成モデル（FFJORD: Free-Form Continuous Dynamics for Scalable Reversible Generative Models）</news:title>
   <news:publication_date>2026-06-19T09:34:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702414</loc>
  <lastmod>2026-06-19T09:34:32Z</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>2026-06-19T09:34:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702412</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>エネルギーに基づくヒンドサイト経験優先化（Energy-Based Hindsight Experience Prioritization）</news:title>
   <news:publication_date>2026-06-19T08:43:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702410</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>自己変調がもたらすGAN性能向上（ON SELF MODULATION FOR GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-06-19T08:42:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702408</loc>
  <lastmod>2026-06-19T08:42:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T08:42:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702406</loc>
  <lastmod>2026-06-19T08:41:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現場用スペクトル吸収蛍光顕微システムによる藻類の迅速同定（Spectral Absorption-fluorescence Microscopy System for ON-site-imaging of algae）</news:title>
   <news:publication_date>2026-06-19T08:41:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702404</loc>
  <lastmod>2026-06-19T08:41:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FutureGANによる映像フレーム予測の実用性と限界（FutureGAN: Anticipating the Future Frames of Video Sequences using Spatio-Temporal 3d Convolutions in Progressively Growing GANs）</news:title>
   <news:publication_date>2026-06-19T08:41:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702402</loc>
  <lastmod>2026-06-19T08:41:11Z</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>2026-06-19T08:41:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702400</loc>
  <lastmod>2026-06-19T08:40:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>災害対応ロボットMomaroによる現場作業解決（NimbRo Rescue: Solving Disaster-Response Tasks through Mobile Manipulation Robot Momaro）</news:title>
   <news:publication_date>2026-06-19T08:40:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702398</loc>
  <lastmod>2026-06-19T07:49:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多偏波GPR体積データを用いたオートエンコーダによる地雷検出 (Landmine Detection Using Autoencoders on Multi-polarization GPR Volumetric Data)</news:title>
   <news:publication_date>2026-06-19T07:49:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702396</loc>
  <lastmod>2026-06-19T07:49:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的強化学習におけるほぼ最適な表現学習（Near-Optimal Representation Learning for Hierarchical Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-19T07:49:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702394</loc>
  <lastmod>2026-06-19T07:48:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム学習率による学習（Learning with Random Learning Rates）</news:title>
   <news:publication_date>2026-06-19T07:48:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702392</loc>
  <lastmod>2026-06-19T07:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的手法と勾配ベース手法を組み合わせた方策探索：CEM-RL（CEM-RL: Combining evolutionary and gradient-based methods for policy search）</news:title>
   <news:publication_date>2026-06-19T07:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702390</loc>
  <lastmod>2026-06-19T07:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T07:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702388</loc>
  <lastmod>2026-06-19T07:48:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海洋ロボット航法のためのスパースガウス過程Temporal Difference学習（Sparse Gaussian Process Temporal Difference Learning）</news:title>
   <news:publication_date>2026-06-19T07:48:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702386</loc>
  <lastmod>2026-06-19T07:47:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球より大きな電波干渉計：宇宙VLBIの教訓と展望（Radio Interferometers Larger than Earth: Lessons Learned and Forward Look of Space VLBI）</news:title>
   <news:publication_date>2026-06-19T07:47:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702384</loc>
  <lastmod>2026-06-19T06:56:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトニックニューラルネットにおける全光学的非線形活性化（All-optical Nonlinear Activation Function for Photonic Neural Networks）</news:title>
   <news:publication_date>2026-06-19T06:56:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702382</loc>
  <lastmod>2026-06-19T06:56:10Z</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>2026-06-19T06:56:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702380</loc>
  <lastmod>2026-06-19T06:56:03Z</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>2026-06-19T06:56:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702378</loc>
  <lastmod>2026-06-19T06:55:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的事例の全体像とその含意（Adversarial Examples - A Complete Characterisation of the Phenomenon）</news:title>
   <news:publication_date>2026-06-19T06:55:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702376</loc>
  <lastmod>2026-06-19T06:55:00Z</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>2026-06-19T06:55:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702374</loc>
  <lastmod>2026-06-19T06:54:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EMIによる探索強化（EMI: Exploration with Mutual Information）</news:title>
   <news:publication_date>2026-06-19T06:54:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702372</loc>
  <lastmod>2026-06-19T06:54:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的プログラミングによるプログラム誘導の推論（Inference Over Programs That Make Predictions）</news:title>
   <news:publication_date>2026-06-19T06:54:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702370</loc>
  <lastmod>2026-06-19T06:03:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粉末X線回折パターン解析に機械学習クラスタリングを適用して合金置換を識別する手法（Machine learning clustering technique applied to powder X-ray diffraction patterns to distinguish alloy substitutions）</news:title>
   <news:publication_date>2026-06-19T06:03:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702368</loc>
  <lastmod>2026-06-19T06:03:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド自然言語生成チャレンジの所見（Findings of the E2E NLG Challenge）</news:title>
   <news:publication_date>2026-06-19T06:03:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702366</loc>
  <lastmod>2026-06-19T06:02:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多項式サイズ回路のための量子準同型暗号（A quantum homomorphic encryption scheme for polynomial-sized circuits）</news:title>
   <news:publication_date>2026-06-19T06:02:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702364</loc>
  <lastmod>2026-06-19T06:01:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>判別器をエネルギーネットワークとして学習する敵対的学習（Learning Discriminators as Energy Networks in Adversarial Learning）</news:title>
   <news:publication_date>2026-06-19T06:01:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702362</loc>
  <lastmod>2026-06-19T06:01:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き生成敵対ネットワークを用いた半教師ありテキスト回帰（Semi-supervised Text Regression with Conditional Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-19T06:01:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702360</loc>
  <lastmod>2026-06-19T06:01:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習に基づく物理層通信によるマルチエージェント協調（Learning-based physical layer communications for multi-agent collaboration）</news:title>
   <news:publication_date>2026-06-19T06:01:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702358</loc>
  <lastmod>2026-06-19T06:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルノイズ下での深層学習におけるエントロピー的最適輸送損失（An Entropic Optimal Transport Loss for Learning Deep Neural Networks under Label Noise in Remote Sensing Images）</news:title>
   <news:publication_date>2026-06-19T06:00:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702356</loc>
  <lastmod>2026-06-19T05:09:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>循環行列を用いた動画分類モデルの圧縮（Training compact deep learning models for video classification using circulant matrices）</news:title>
   <news:publication_date>2026-06-19T05:09:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702354</loc>
  <lastmod>2026-06-19T05:09:49Z</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>2026-06-19T05:09:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702352</loc>
  <lastmod>2026-06-19T05:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TRASS: 時間反転を用いた自己教師あり学習によるロボット操作の新展開（TRASS: Time Reversal as Self-Supervision）</news:title>
   <news:publication_date>2026-06-19T05:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702350</loc>
  <lastmod>2026-06-19T05:08:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sinkhorn AutoEncoders（Sinkhorn AutoEncoders）</news:title>
   <news:publication_date>2026-06-19T05:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702348</loc>
  <lastmod>2026-06-19T05:08:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次元分光データの機械学習（Machine Learning of Two-Dimensional Spectroscopic Data）</news:title>
   <news:publication_date>2026-06-19T05:08:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702346</loc>
  <lastmod>2026-06-19T05:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインコメントに対する宛先自動判別の実用可能性（Who is Addressed in this Comment? Automatically Classifying Meta-Comments）</news:title>
   <news:publication_date>2026-06-19T05:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702344</loc>
  <lastmod>2026-06-19T05:07:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>述語学習が示す生成構造の発見（Predicate learning in neural systems: Discovering latent generative structures）</news:title>
   <news:publication_date>2026-06-19T05:07:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702342</loc>
  <lastmod>2026-06-19T04:16:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ターゲット認識型ネットワーク適応による効率的表現学習（Target Aware Network Adaptation for Efficient Representation Learning）</news:title>
   <news:publication_date>2026-06-19T04:16:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702340</loc>
  <lastmod>2026-06-19T04:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>夢見る変分オートエンコーダによる強化学習環境（The Dreaming Variational Autoencoder for Reinforcement Learning Environments）</news:title>
   <news:publication_date>2026-06-19T04:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702338</loc>
  <lastmod>2026-06-19T04:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンク予測に対する敵対的攻撃（Link Prediction Adversarial Attack）</news:title>
   <news:publication_date>2026-06-19T04:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702336</loc>
  <lastmod>2026-06-19T04:08:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像から直接学ぶ視覚的敵対的模倣学習の単射写像仮説（Injective State-Image Mapping facilitates Visual Adversarial Imitation Learning）</news:title>
   <news:publication_date>2026-06-19T04:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702334</loc>
  <lastmod>2026-06-19T04:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子化対応位相復元（Quantization-Aware Phase Retrieval）</news:title>
   <news:publication_date>2026-06-19T04:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702332</loc>
  <lastmod>2026-06-19T04:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース・インド語の効率的音響モデル改良（Semi-supervised and active-learning scenarios: Efficient acoustic model refinement for a low resource Indian language）</news:title>
   <news:publication_date>2026-06-19T04:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702330</loc>
  <lastmod>2026-06-19T04:06:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙をつなぐ次世代インターネット（The Sky is NOT the Limit Anymore: Future Architecture of the Interplanetary Internet）</news:title>
   <news:publication_date>2026-06-19T04:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702328</loc>
  <lastmod>2026-06-19T03:15:09Z</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おける暗黙的自己正則化（Implicit Self-Regularization in Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-19T03:15:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702326</loc>
  <lastmod>2026-06-19T03:15:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lipschitzかつ凸な損失関数によるロバスト統計学の前進（Robust Statistical learning with Lipschitz and convex loss functions）</news:title>
   <news:publication_date>2026-06-19T03:15:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702324</loc>
  <lastmod>2026-06-19T03:13:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマホで回る小型高精度ランドマーク認識モデル（NU-LiteNet: Mobile Landmark Recognition using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-19T03:13:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702322</loc>
  <lastmod>2026-06-19T03:13:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損値を含むデータでの特徴選択による企業生存予測の実務的示唆（Feature Selection Approach with Missing Values Conducted for Statistical Learning - A Case Study of Entrepreneurship Survival Dataset）</news:title>
   <news:publication_date>2026-06-19T03:13:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702320</loc>
  <lastmod>2026-06-19T03:13:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンセンサス最大化による文表現改善（Improving Sentence Representations with Consensus Maximisation）</news:title>
   <news:publication_date>2026-06-19T03:13:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702318</loc>
  <lastmod>2026-06-19T03:13:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超解像ブラインドチャネル・信号推定による大型MIMOの角度解像向上（Super-Resolution Blind Channel-and-Signal Estimation for Massive MIMO with One-Dimensional Antenna Array）</news:title>
   <news:publication_date>2026-06-19T03:13:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702316</loc>
  <lastmod>2026-06-19T03:13:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低演算力デバイスでのリアルタイム深層視覚処理（Cloud Chaser: Real Time Deep Learning Computer Vision on Low Computing Power Devices）</news:title>
   <news:publication_date>2026-06-19T03:13:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702314</loc>
  <lastmod>2026-06-19T02:22:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブロック単位中間表現訓練によるモデル圧縮（Block-wise Intermediate Representation Training）</news:title>
   <news:publication_date>2026-06-19T02:22:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702312</loc>
  <lastmod>2026-06-19T02:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトロボティクス向けリアルタイム微分可能物理シミュレータ（ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics）</news:title>
   <news:publication_date>2026-06-19T02:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702310</loc>
  <lastmod>2026-06-19T02:21:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報道の事実性とメディアのバイアスを予測する（Predicting Factuality of Reporting and Bias of News Media Sources）</news:title>
   <news:publication_date>2026-06-19T02:21:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702308</loc>
  <lastmod>2026-06-19T02:20:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>摂動された報酬による強化学習（Reinforcement Learning with Perturbed Rewards）</news:title>
   <news:publication_date>2026-06-19T02:20:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702306</loc>
  <lastmod>2026-06-19T02:20:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォン内の私的写真を守る仕組み（PhotoSafer: Content-Based and Context-Aware Private Photo Protection for Smartphones）</news:title>
   <news:publication_date>2026-06-19T02:20:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702304</loc>
  <lastmod>2026-06-19T02:20:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河中心の複雑な星形成を解く極めて大型望遠鏡の役割（Extremely large telescopes for complex stellar populations around the Galactic centre）</news:title>
   <news:publication_date>2026-06-19T02:20:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702302</loc>
  <lastmod>2026-06-19T02:20:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所性を失った制約付きデータのクラスタリングの統一的枠組み（A Unified Framework for Clustering Constrained Data without Locality Property）</news:title>
   <news:publication_date>2026-06-19T02:20:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702300</loc>
  <lastmod>2026-06-19T01:29:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重みと量子化器を同時最適化する三値ニューラルネットワーク（Simultaneously Optimizing Weight and Quantizer of Ternary Neural Network using Truncated Gaussian Approximation）</news:title>
   <news:publication_date>2026-06-19T01:29:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702298</loc>
  <lastmod>2026-06-19T01:28:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模バッチ学習における敵対的訓練と二次情報の活用 (Large Batch Size Training of Neural Networks with Adversarial Training and Second-Order Information)</news:title>
   <news:publication_date>2026-06-19T01:28:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702296</loc>
  <lastmod>2026-06-19T01:28:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値分類誤差率の経験的推定の収束率（Convergence Rates for Empirical Estimation of Binary Classification Bounds）</news:title>
   <news:publication_date>2026-06-19T01:28:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702294</loc>
  <lastmod>2026-06-19T01:27:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハミング距離ターゲットによるハッシュ符号学習（Learning Hash Codes via Hamming Distance Targets）</news:title>
   <news:publication_date>2026-06-19T01:27:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702292</loc>
  <lastmod>2026-06-19T01:27:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カイオンSIDISによるストレンジクォーク海の探査（Probing the Strange Sea Quarks with Kaon SIDIS）</news:title>
   <news:publication_date>2026-06-19T01:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702290</loc>
  <lastmod>2026-06-19T01:27:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>性的暴行に関するTwitter会話の意図検出に対する分散意味論アプローチ（Distributional Semantics Approach to Detect Intent in Twitter Conversations on Sexual Assaults）</news:title>
   <news:publication_date>2026-06-19T01:27:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702288</loc>
  <lastmod>2026-06-19T01:26:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル不確実性に対するベイズ方策最適化（Bayesian Policy Optimization for Model Uncertainty）</news:title>
   <news:publication_date>2026-06-19T01:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702286</loc>
  <lastmod>2026-06-19T00:35:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド並列処理における仕事配分の再考 — Heterogeneous MacroTasking (HeMT) の示唆（Heterogeneous MacroTasking for Parallel Processing in the Public Cloud）</news:title>
   <news:publication_date>2026-06-19T00:35:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702284</loc>
  <lastmod>2026-06-19T00:35:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小限の局所平滑性仮定下での単純でパラメータ不要かつ適応的な最適化手法 (A simple parameter-free and adaptive approach to optimization under a minimal local smoothness assumption)</news:title>
   <news:publication_date>2026-06-19T00:35:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702282</loc>
  <lastmod>2026-06-19T00:35:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジャイロを利用した動きブレ除去（Gyroscope-Aided Motion Deblurring with Deep Networks）</news:title>
   <news:publication_date>2026-06-19T00:35:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702280</loc>
  <lastmod>2026-06-19T00:34:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>透明性駆動型環境による信頼できる自動ジャンル分類の実践（Utilizing a Transparency-driven Environment toward Trusted Automatic Genre Classification: A Case Study in Journalism History）</news:title>
   <news:publication_date>2026-06-19T00:34:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702278</loc>
  <lastmod>2026-06-19T00:33:57Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T00:33:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T00:33:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全情報下におけるネットワーク化マイクログリッドの学習ベース電力管理（A Learning-based Power Management for Networked Microgrids Under Incomplete Information）</news:title>
   <news:publication_date>2026-06-18T23:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークによる量子暗号の誤り訂正（Error correction in quantum cryptography based on artificial neural networks）</news:title>
   <news:publication_date>2026-06-18T23:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類器を因果推論に使う際の課題と道筋（Challenges of Using Text Classifiers for Causal Inference）</news:title>
   <news:publication_date>2026-06-18T23:40:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロショット音声意味解析と強化学習対話管理の共同オンライン学習（Joint On-line Learning of a Zero-shot Spoken Semantic Parser and a Reinforcement Learning Dialogue Manager）</news:title>
   <news:publication_date>2026-06-18T23:40:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工ニューラルネットワークによる解析継続問題の解法（Artificial Neural Network Approach to the Analytic Continuation Problem）</news:title>
   <news:publication_date>2026-06-18T23:40:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702262</loc>
  <lastmod>2026-06-18T23:40:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な多変量・関数型アーキタイプ分析（Robust multivariate and functional archetypal analysis）</news:title>
   <news:publication_date>2026-06-18T23:40:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702260</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>Sr2RuO4における深いギャップ最小値と不純物が残留熱輸送に与える影響 (Effects of deep superconducting gap minima and disorder on residual thermal transport in Sr2RuO4)</news:title>
   <news:publication_date>2026-06-18T23:39:43Z</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>多方向性ジオデシック畳み込みニューラルネットワーク（Multi-directional Geodesic Neural Networks via Equivariant Convolution）</news:title>
   <news:publication_date>2026-06-18T22:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702256</loc>
  <lastmod>2026-06-18T22:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的好奇心：画像認識を学ぶために質問を学習する（Visual Curiosity: Learning to Ask Questions to Learn Visual Recognition）</news:title>
   <news:publication_date>2026-06-18T22:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>A1664クラスター中心部の高ダイナミクスの解明（REVEALING A HIGHLY-DYNAMIC CLUSTER CORE IN ABELL 1664 WITH CHANDRA）</news:title>
   <news:publication_date>2026-06-18T22:48:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702252</loc>
  <lastmod>2026-06-18T22:47:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的スパースグラフによる効率的な深層学習（Dynamic Sparse Graph for Efficient Deep Learning）</news:title>
   <news:publication_date>2026-06-18T22:47:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702250</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>2026-06-18T22:47:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702248</loc>
  <lastmod>2026-06-18T22:47:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似差分プライバシーにおけるプライバシーと有用性のトレードオフ（Privacy and Utility Tradeoff in Approximate Differential Privacy）</news:title>
   <news:publication_date>2026-06-18T22:47:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702246</loc>
  <lastmod>2026-06-18T22:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子化ニューラルネットワークのための近接演算子手法（ProxQuant: Quantized Neural Networks via Proximal Operators）</news:title>
   <news:publication_date>2026-06-18T22:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702244</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>CHET: 同型暗号でテンソル演算を動かすコンパイラとランタイム（CHET: Compiler and Runtime for Homomorphic Evaluation of Tensor Programs）</news:title>
   <news:publication_date>2026-06-18T21:55:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702242</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>2026-06-18T21:55:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702240</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>ポジティブ・アンラベルド・バイアスネガティブ学習の実務的意義（Classification from Positive, Unlabeled and Biased Negative Data）</news:title>
   <news:publication_date>2026-06-18T21:55:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702238</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702236</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>ラウンドアバウトにおける適応的ゲーム理論的意思決定（Adaptive Game-Theoretic Decision Making for Autonomous Vehicle Control at Roundabouts）</news:title>
   <news:publication_date>2026-06-18T21:54:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702234</loc>
  <lastmod>2026-06-18T21:54:41Z</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>2026-06-18T21:54:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702232</loc>
  <lastmod>2026-06-18T21:54:29Z</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>2026-06-18T21:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702230</loc>
  <lastmod>2026-06-18T21:03:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集合トランスフォーマー（Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks）</news:title>
   <news:publication_date>2026-06-18T21:03:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702228</loc>
  <lastmod>2026-06-18T21:03:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分識別器ボトルネック（VARIATIONAL DISCRIMINATOR BOTTLENECK: IMPROVING IMITATION LEARNING, INVERSE RL, AND GANS BY CONSTRAINING INFORMATION FLOW）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702226</loc>
  <lastmod>2026-06-18T21:02:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graph Neural Networksの表現力（How Powerful Are Graph Neural Networks?）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702224</loc>
  <lastmod>2026-06-18T21:02:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプリングベース探索に深い系列モデルを組み合わせる意義（Deep sequential models for sampling-based planning）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702222</loc>
  <lastmod>2026-06-18T21:02:08Z</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>
  <loc>https://aibr.jp/archives/702220</loc>
  <lastmod>2026-06-18T21:01:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散乱物中での自律把持のためのRGB-D物体検出と意味セグメンテーション（RGB-D Object Detection and Semantic Segmentation for Autonomous Manipulation in Clutter）</news:title>
   <news:publication_date>2026-06-18T21:01:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702218</loc>
  <lastmod>2026-06-18T21:01:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ拡散埋め込みネットワーク（Graph Diffusion-Embedding Networks）</news:title>
   <news:publication_date>2026-06-18T21:01:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702216</loc>
  <lastmod>2026-06-18T20:10:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BARTの理論的基盤の確立（On Theory for BART）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702214</loc>
  <lastmod>2026-06-18T20:10:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロファイリング・マシン：知識上の能動的な一般化（The Profiling Machine: Active Generalization over Knowledge）</news:title>
   <news:publication_date>2026-06-18T20:10:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702212</loc>
  <lastmod>2026-06-18T20:10:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トネッツ上の固有三和音と固有進行（Eigentriads and Eigenprogressions on the Tonnetz）</news:title>
   <news:publication_date>2026-06-18T20:10:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702210</loc>
  <lastmod>2026-06-18T20:09:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>白色矮星を巡るトランジット惑星の検出可能性（On the detectability of transiting planets orbiting white dwarfs using LSST）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-18T20:09:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光ファイバー通信における幾何学的コンステレーション整形のエンドツーエンド学習（Geometric Constellation Shaping for Fiber Optic Communication Systems via End-to-end Learning）</news:title>
   <news:publication_date>2026-06-18T20:09:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-18T20:08:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半適応型ニューラルネットワークによる人間運動予測（Human Motion Prediction using Semi-adaptable Neural Networks）</news:title>
   <news:publication_date>2026-06-18T20:08:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-18T19:17:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-18T19:17:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未来の街路風景のベイズ予測（Bayesian Prediction of Future Street Scenes Using Synthetic Likelihoods）</news:title>
   <news:publication_date>2026-06-18T19:08:56Z</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>リーマン適応最適化法（RIEMANNIAN ADAPTIVE OPTIMIZATION METHODS）</news:title>
   <news:publication_date>2026-06-18T19:08:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702196</loc>
  <lastmod>2026-06-18T19:08:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン適応による敵対的訓練の一般化改善（Improving the Generalization of Adversarial Training with Domain Adaptation）</news:title>
   <news:publication_date>2026-06-18T19:08:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702194</loc>
  <lastmod>2026-06-18T19:07:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リスク回避型確率的凸バンディット問題の解析（Risk-Averse Stochastic Convex Bandit）</news:title>
   <news:publication_date>2026-06-18T19:07:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702192</loc>
  <lastmod>2026-06-18T19:07:10Z</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>2026-06-18T19:07:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702190</loc>
  <lastmod>2026-06-18T19:06:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動で見出すサイバーフィジカルシステム（Data-driven Discovery of Cyber-Physical Systems）</news:title>
   <news:publication_date>2026-06-18T19:06:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702188</loc>
  <lastmod>2026-06-18T18:15:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部位レベルの畳み込みニューラルネットワークによる歩行者検出（Part-Level Convolutional Neural Networks for Pedestrian Detection Using Saliency and Boundary Box Alignment）</news:title>
   <news:publication_date>2026-06-18T18:15:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702186</loc>
  <lastmod>2026-06-18T18:14:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Perfect Match を用いた反実仮想推論の簡潔実装（Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks）</news:title>
   <news:publication_date>2026-06-18T18:14:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702184</loc>
  <lastmod>2026-06-18T18:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fusion Hashing：既存ハッシュ法の自己改善フレームワーク（Fusion Hashing: A General Framework for Self-improvement of Hashing）</news:title>
   <news:publication_date>2026-06-18T18:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702182</loc>
  <lastmod>2026-06-18T18:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HST STISによる原始惑星状星雲 HEN 3-1475 の紫外線分光観測（HST STIS UV Spectroscopic Observations of the Protoplanetary Nebula HEN 3-1475）</news:title>
   <news:publication_date>2026-06-18T18:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702180</loc>
  <lastmod>2026-06-18T18:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマホで計測するパーキンソン病診断の可能性（PhoneMD: Learning to Diagnose Parkinson’s Disease from Smartphone Data）</news:title>
   <news:publication_date>2026-06-18T18:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702178</loc>
  <lastmod>2026-06-18T18:13:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SmartChoicesによるプログラミングと機械学習の融合（SmartChoices: Hybridizing Programming and Machine Learning）</news:title>
   <news:publication_date>2026-06-18T18:13:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702176</loc>
  <lastmod>2026-06-18T18:13:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートネットワーク場理論（Smart Network Field Theory: The Technophysics of Blockchain and Deep Learning）</news:title>
   <news:publication_date>2026-06-18T18:13:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702174</loc>
  <lastmod>2026-06-18T17:22:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル外科デモンストレーションの教師なし軌跡分割と促進（Unsupervised Trajectory Segmentation and Promoting of Multi-Modal Surgical Demonstrations）</news:title>
   <news:publication_date>2026-06-18T17:22:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702172</loc>
  <lastmod>2026-06-18T17:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全なDNN推論を実現するPRIVADO（PRIVADO: Practical and Secure DNN Inference with Enclaves）</news:title>
   <news:publication_date>2026-06-18T17:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702170</loc>
  <lastmod>2026-06-18T17:21:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンクリック注釈と誘導付き階層的オブジェクト検出（One-Click Annotation with Guided Hierarchical Object Detection）</news:title>
   <news:publication_date>2026-06-18T17:21:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702168</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>VAEの挙動を制御する手法の提示（Taming VAEs）</news:title>
   <news:publication_date>2026-06-18T17:20:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702166</loc>
  <lastmod>2026-06-18T17:20:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュースに潜む風刺を機械学習で見抜く方法（Detecting Satire in the News with Machine Learning）</news:title>
   <news:publication_date>2026-06-18T17:20:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702164</loc>
  <lastmod>2026-06-18T17:20:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弾力的ニューラルネットワークによる分類（Elastic Neural Networks for Classification）</news:title>
   <news:publication_date>2026-06-18T17:20:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702162</loc>
  <lastmod>2026-06-18T17:20:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cherenkov望遠鏡データからのガンマ線情報抽出（Extracting gamma-ray information from images with convolutional neural network methods on simulated Cherenkov Telescope Array data）</news:title>
   <news:publication_date>2026-06-18T17:20:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702160</loc>
  <lastmod>2026-06-18T16:29:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CdZnTeSe検出器の電気輸送特性に対する深い準位の影響（Influence of deep levels on the electrical transport properties of CdZnTeSe detectors）</news:title>
   <news:publication_date>2026-06-18T16:29:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702158</loc>
  <lastmod>2026-06-18T16:28:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適適応型および加速確率的勾配下降法（Optimal Adaptive and Accelerated Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-06-18T16:28:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702156</loc>
  <lastmod>2026-06-18T16:28:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的メタ表現によるニューラルネットワークの重みモデリング（Probabilistic Meta-Representations Of Neural Networks）</news:title>
   <news:publication_date>2026-06-18T16:28:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702154</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>Adv-BNNによる堅牢化—ベイズニューラルネットを用いた対敵防御の実用化 (ADV-BNN: IMPROVED ADVERSARIAL DEFENSE THROUGH ROBUST BAYESIAN NEURAL NETWORK)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702152</loc>
  <lastmod>2026-06-18T16:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォルナクス深部サーベイによる矮小銀河カタログ（The Fornax Deep Survey (FDS) with the VST. IV. A size and magnitude limited catalog of dwarf galaxies in the area of the Fornax cluster）</news:title>
   <news:publication_date>2026-06-18T16:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702150</loc>
  <lastmod>2026-06-18T16:27:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像向け生成敵対ネットワークの実践的意義（Generative Adversarial Network for Medical Images）</news:title>
   <news:publication_date>2026-06-18T16:27:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702148</loc>
  <lastmod>2026-06-18T16:26:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Z∼4における星形成が抑制された大型銀河の休止光学サイズ（THE REST-FRAME OPTICAL SIZES OF MASSIVE GALAXIES WITH SUPPRESSED STAR FORMATION AT Z ∼4）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702146</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多階層で把持候補を統合する実用的ロボット把持検出（Densely Supervised Grasp Detector）</news:title>
   <news:publication_date>2026-06-18T15:35:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702144</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチキャリア通信における信号悪用攻撃の耐性評価（How Secure are Multicarrier Communication Systems Against Signal Exploitation Attacks?）</news:title>
   <news:publication_date>2026-06-18T15:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702142</loc>
  <lastmod>2026-06-18T15:34:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な時空間注意による動画行動認識（Interpretable Spatio-temporal Attention for Video Action Recognition）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702140</loc>
  <lastmod>2026-06-18T15:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドで挑むアルツハイマー病診断とバイオマーカー特定（End-To-End Alzheimer’s Disease Diagnosis and Biomarker Identification）</news:title>
   <news:publication_date>2026-06-18T15:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702138</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>FIRE-DES++: 動的アンサンブル選択のためのオンライン剪定強化（FIRE-DES++: Enhanced Online Pruning of Base Classifiers for Dynamic Ensemble Selection）</news:title>
   <news:publication_date>2026-06-18T15:33:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動アプローチは常識推論に足りるか（A Simple Method for Commonsense Reasoning）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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  </news: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:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-18T14:41:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702126</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-18T14:40:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-18T14:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702122</loc>
  <lastmod>2026-06-18T14:40:22Z</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>2026-06-18T14:40:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-18T14:40:14Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハドロン衝突を含むグローバル解析によるトランスヴァーシティの初抽出（First extraction of transversity from data on lepton-hadron scattering and hadronic collisions）</news:title>
   <news:publication_date>2026-06-18T14:40:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702118</loc>
  <lastmod>2026-06-18T13:48:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床データから深い潜在表現を学ぶ（Learning Deep Representations from Clinical Data for Chronic Kidney Disease）</news:title>
   <news:publication_date>2026-06-18T13:48:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702116</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>MultiWOZが示した対話AI研究の地殻変動（MultiWOZ – A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling）</news:title>
   <news:publication_date>2026-06-18T13:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702114</loc>
  <lastmod>2026-06-18T13:47:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段落ランク付けによるオープンドメインQAの想定改善（Ranking Paragraphs for Improving Answer Recall in Open-Domain Question Answering）</news:title>
   <news:publication_date>2026-06-18T13:47:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702112</loc>
  <lastmod>2026-06-18T13:47:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未分割実演からサブタスクを自動発見し階層方策を学ぶ手法（DIRECTED-INFO GAIL: LEARNING HIERARCHICAL POLICIES FROM UNSEGMENTED DEMONSTRATIONS USING DIRECTED INFORMATION）</news:title>
   <news:publication_date>2026-06-18T13:47:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702110</loc>
  <lastmod>2026-06-18T13:47:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模確率的最適化のための高速準ニュートン法（A fast quasi-Newton-type method for large-scale stochastic optimisation）</news:title>
   <news:publication_date>2026-06-18T13:47:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702108</loc>
  <lastmod>2026-06-18T13:47:11Z</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>2026-06-18T13:47:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702106</loc>
  <lastmod>2026-06-18T13:47:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移可能な敵対的例の生成（CAAD 2018: Generating Transferable Adversarial Examples）</news:title>
   <news:publication_date>2026-06-18T13:47:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702104</loc>
  <lastmod>2026-06-18T12:55:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rでの強化学習入門と実装の要点（Reinforcement Learning in R）</news:title>
   <news:publication_date>2026-06-18T12:55:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702102</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コマ銀河団コアにおける矮小銀河の構造と分類（Dwarf Galaxies in the Core of Coma Cluster）</news:title>
   <news:publication_date>2026-06-18T12:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702100</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>説明を正則化して学習する機械学習モデル（Training Machine Learning Models by Regularizing their Explanations）</news:title>
   <news:publication_date>2026-06-18T12:55:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702098</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>音色（ティンバー）を多対多で変換する新手法：Modulated Variational auto-Encoders（MODULATED VARIATIONAL AUTO-ENCODERS FOR MANY-TO-MANY MUSICAL TIMBRE TRANSFER）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702096</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>一般化マルチチャンネル変分オートエンコーダによる過未決定音源分離（GENERALIZED MULTICHANNEL VARIATIONAL AUTOENCODER FOR UNDERDETERMINED SOURCE SEPARATION）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702094</loc>
  <lastmod>2026-06-18T12:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多臓器組織像における核セグメンテーションの深層敵対的訓練（Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images）</news:title>
   <news:publication_date>2026-06-18T12:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702092</loc>
  <lastmod>2026-06-18T12:53:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dynamic Ensemble Active Learning（Dynamic Ensemble Active Learning: A Non-Stationary Bandit with Expert Advice）</news:title>
   <news:publication_date>2026-06-18T12:53:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702090</loc>
  <lastmod>2026-06-18T12:02:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PHY層鍵抽出に対する統計的推論攻撃と対策（Statistical Inference Attack Against PHY-layer Key Extraction and Countermeasures）</news:title>
   <news:publication_date>2026-06-18T12:02:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702088</loc>
  <lastmod>2026-06-18T12:01:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮して使うべきか否か：敵対的攻撃とニューラルネットワーク圧縮の相互作用を理解する (TO COMPRESS OR NOT TO COMPRESS: UNDERSTANDING THE INTERACTIONS BETWEEN ADVERSARIAL ATTACKS AND NEURAL NETWORK COMPRESSION)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702086</loc>
  <lastmod>2026-06-18T12:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈依存処理を継続的に学習するニューラルネット（Continual Learning of Context-dependent Processing in Neural Networks）</news:title>
   <news:publication_date>2026-06-18T12:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702084</loc>
  <lastmod>2026-06-18T12:01:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒトのデモ映像から学ぶロボットの眼手協調（Robot eye-hand coordination learning by watching human demonstrations: a task function approximation approach）</news:title>
   <news:publication_date>2026-06-18T12:01:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702082</loc>
  <lastmod>2026-06-18T12:01:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造学習による量化子消去（Quantifier Elimination With Structural Learning）</news:title>
   <news:publication_date>2026-06-18T12:01:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702080</loc>
  <lastmod>2026-06-18T12:00:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手作業で作った記号地上化と上位計画の自動改善（Refining Manually-Designed Symbol Grounding and High-Level Planning by Policy Gradients）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702078</loc>
  <lastmod>2026-06-18T12:00:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NICE：ノイズ注入とクランピング推定によるニューラルネットワーク量子化（NICE: Noise Injection and Clamping Estimation for Neural Network Quantization）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-18T11:09:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配降下法における方向性解析（Directional Analysis of Stochastic Gradient Descent via von Mises-Fisher Distributions in Deep Learning）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702074</loc>
  <lastmod>2026-06-18T11:09:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>労働者の「こころ」を読む管理者学習：M3RL（M3RL: Mind-aware Multi-agent Management Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702072</loc>
  <lastmod>2026-06-18T11:09:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数デモから一般化するロボット技能の学習（Auto-conditioned Recurrent Mixture Density Networks for Learning Generalizable Robot Skills）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702070</loc>
  <lastmod>2026-06-18T11:08:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ヒトの操作デモから幾何学的制約を推定する方法（Inferring geometric constraints in human demonstrations）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702068</loc>
  <lastmod>2026-06-18T11:08:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702066</loc>
  <lastmod>2026-06-18T11:07:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識指導型セマンティックコンピューティングネットワーク（Knowledge-guided Semantic Computing Network）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>AdaShiftが示した「適応学習率の再考」—Adamの非収束問題を時間ずらしで解く（ADASHIFT: DECORRELATION AND CONVERGENCE OF ADAPTIVE LEARNING RATE METHODS）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702062</loc>
  <lastmod>2026-06-18T10:16:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FusedLSTMによる動画関連性予測（FusedLSTM at ACMMM-2018 CBVRP Challenge: Fusing frame-level and video-level features for Content-based Video Relevance Prediction）</news:title>
   <news:publication_date>2026-06-18T10:16:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702060</loc>
  <lastmod>2026-06-18T10:16:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>X線透視撮影システムにおける誤差モデリングとデータ駆動型自己較正（MODELLING ERRORS IN X-RAY FLUOROSCOPIC IMAGING SYSTEMS USING PHOTOGRAMMETRIC BUNDLE ADJUSTMENT WITH A DATA-DRIVEN SELF-CALIBRATION APPROACH）</news:title>
   <news:publication_date>2026-06-18T10:16:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702058</loc>
  <lastmod>2026-06-18T10:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイドアングルレンズカメラの自動較正法（ROBOT VISION: CALIBRATION OF WIDE-ANGLE LENS CAMERAS USING COLLINEARITY CONDITION AND K-NEAREST NEIGHBOUR REGRESSION）</news:title>
   <news:publication_date>2026-06-18T10:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702056</loc>
  <lastmod>2026-06-18T10:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化が勾配降下法にもたらす定量的効果（A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent）</news:title>
   <news:publication_date>2026-06-18T10:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702054</loc>
  <lastmod>2026-06-18T10:15:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散分布上の勾配最適化改善（IMPROVED GRADIENT-BASED OPTIMIZATION OVER DISCRETE DISTRIBUTIONS）</news:title>
   <news:publication_date>2026-06-18T10:15:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702052</loc>
  <lastmod>2026-06-18T10:15:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DQNにおける汎化と正則化の考察（Generalization and Regularization in DQN）</news:title>
   <news:publication_date>2026-06-18T10:15:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702050</loc>
  <lastmod>2026-06-18T10:14:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変量情報に基づくランダム分割モデルによる相互作用の発見 (Discovering Interactions Using Covariate Informed Random Partition Models)</news:title>
   <news:publication_date>2026-06-18T10:14:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702048</loc>
  <lastmod>2026-06-18T09:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン対抗マルチタスクフレームワークによる化合物の新規治療特性予測（Domain-Adversarial Multi-Task Framework for Novel Therapeutic Property Prediction of Compounds）</news:title>
   <news:publication_date>2026-06-18T09:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702046</loc>
  <lastmod>2026-06-18T09:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マージン分布による深層ネットワークの汎化ギャップ予測 (Predicting the Generalization Gap in Deep Networks with Margin Distributions)</news:title>
   <news:publication_date>2026-06-18T09:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702044</loc>
  <lastmod>2026-06-18T09:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSSMによる原画像からの統計形状モデリング（DeepSSM: A Deep Learning Framework for Statistical Shape Modeling from Raw Images）</news:title>
   <news:publication_date>2026-06-18T09:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702042</loc>
  <lastmod>2026-06-18T09:22:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>保証付きマシンティーチングのためのバリア証明（Barrier Certificates for Assured Machine Teaching）</news:title>
   <news:publication_date>2026-06-18T09:22:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702040</loc>
  <lastmod>2026-06-18T09:22:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小児体部MRAを短時間化する深層残差ネットワークによるオフレゾナンス補正（Deep Residual Network for Off-Resonance Artifact Correction with Application to Pediatric Body Magnetic Resonance Angiography with 3D Cones）</news:title>
   <news:publication_date>2026-06-18T09:22:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702038</loc>
  <lastmod>2026-06-18T09:22:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタイルとコンテンツの切り分けで「未知の組合せ」を作る技術（Open-Ended Content-Style Recombination via Leakage Filtering）</news:title>
   <news:publication_date>2026-06-18T09:22:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702036</loc>
  <lastmod>2026-06-18T09:21:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子核パートン分布の最近の進展 (Recent progress in Nuclear Parton Distributions)</news:title>
   <news:publication_date>2026-06-18T09:21:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702034</loc>
  <lastmod>2026-06-18T08:30:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的攻撃と防御の総説（Adversarial Attacks and Defences: A Survey）</news:title>
   <news:publication_date>2026-06-18T08:30:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702032</loc>
  <lastmod>2026-06-18T08:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシー下の文脈付き線形バンディット（Differentially Private Contextual Linear Bandits）</news:title>
   <news:publication_date>2026-06-18T08:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702030</loc>
  <lastmod>2026-06-18T08:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定した脳–機械インターフェースのための敵対的ドメイン適応（Adversarial Domain Adaptation for Stable Brain-Machine Interfaces）</news:title>
   <news:publication_date>2026-06-18T08:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702028</loc>
  <lastmod>2026-06-18T08:28:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きジニ不純度最小化とk平均問題の接続（Minimization of Gini impurity via connections with the k-means problem）</news:title>
   <news:publication_date>2026-06-18T08:28:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702026</loc>
  <lastmod>2026-06-18T08:28:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的公平性――情報取得を変えることで達成するアルゴリズム公正性（Active Fairness in Algorithmic Decision Making）</news:title>
   <news:publication_date>2026-06-18T08:28:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702024</loc>
  <lastmod>2026-06-18T08:28:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生体内で動作する超音波スイッチ型蛍光イメージング（In vivo ultrasound-switchable fluorescence imaging）</news:title>
   <news:publication_date>2026-06-18T08:28:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702022</loc>
  <lastmod>2026-06-18T08:28:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>I-DLVグラウンダーとASPソルバーの効率的な連携（Efficiently Coupling the I-DLV Grounder with ASP Solvers）</news:title>
   <news:publication_date>2026-06-18T08:28:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702020</loc>
  <lastmod>2026-06-18T07:36:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOSFIREによる休止銀河のスペクトル解析が示す星形成履歴と消光メカニズム（MOSFIRE Spectroscopy of Quiescent Galaxies at 1.5 &amp;lt; z &amp;lt; 2.5: Star Formation Histories and Galaxy Quenching）</news:title>
   <news:publication_date>2026-06-18T07:36:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702018</loc>
  <lastmod>2026-06-18T07:36:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NuSTARによる外宇宙調査が暴いた埋もれたAGNの実像（THE NuSTAR EXTRAGALACTIC SURVEYS: UNVEILING RARE, BURIED AGNS AND DETECTING THE CONTRIBUTORS TO THE PEAK OF THE COSMIC X-RAY BACKGROUND）</news:title>
   <news:publication_date>2026-06-18T07:36:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702016</loc>
  <lastmod>2026-06-18T07:35:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群れの「まとまり度」から感情影響を予測する手法（Data-Driven Modeling of Group Entitativity in Virtual Environments）</news:title>
   <news:publication_date>2026-06-18T07:35:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702014</loc>
  <lastmod>2026-06-18T07:34:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配降下法の揺らぎ–散逸関係（Fluctuation-Dissipation Relations for Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-06-18T07:34:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702012</loc>
  <lastmod>2026-06-18T07:34:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPyTorchによるGPU高速化ガウス過程推論（GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration）</news:title>
   <news:publication_date>2026-06-18T07:34:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702010</loc>
  <lastmod>2026-06-18T07:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測下でのモデルベース制御のためのPropagation Networks（Propagation Networks for Model-Based Control Under Partial Observation）</news:title>
   <news:publication_date>2026-06-18T07:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702008</loc>
  <lastmod>2026-06-18T07:34:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハッブル超深度場の失われた光（The missing light of the Hubble Ultra Deep Field）</news:title>
   <news:publication_date>2026-06-18T07:34:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702006</loc>
  <lastmod>2026-06-18T06:42:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動で新物理を探す手法の実務的意義（Learning New Physics from a Machine）</news:title>
   <news:publication_date>2026-06-18T06:42:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702004</loc>
  <lastmod>2026-06-18T06:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dirichlet分布による形式的コンテキストの生成（Formal Context Generation using Dirichlet Distributions）</news:title>
   <news:publication_date>2026-06-18T06:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702002</loc>
  <lastmod>2026-06-18T06:41:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGA上でのDNN推論のスループット最適化（Throughput Optimizations for FPGA-based Deep Neural Network Inference）</news:title>
   <news:publication_date>2026-06-18T06:41:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702000</loc>
  <lastmod>2026-06-18T06:41:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノード重み付きスペクトル埋め込み（Weighted Spectral Embedding of Graphs）</news:title>
   <news:publication_date>2026-06-18T06:41:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701998</loc>
  <lastmod>2026-06-18T06:40:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャネル方向と空間特徴の変調ネットワークによる単一画像超解像（Channel-wise and Spatial Feature Modulation Network for Single Image Super-Resolution）</news:title>
   <news:publication_date>2026-06-18T06:40:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701996</loc>
  <lastmod>2026-06-18T06:40:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XXL-S電波源の多波長同定（Identifications of 2.1 GHz radio sources in the XXL-S field）</news:title>
   <news:publication_date>2026-06-18T06:40:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701994</loc>
  <lastmod>2026-06-18T06:39:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EDDIによる効率的な情報取得（Efficient Dynamic Discovery of High-Value Information with Partial VAE）</news:title>
   <news:publication_date>2026-06-18T06:39:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701992</loc>
  <lastmod>2026-06-18T05:48:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>自動運転の再考（RETHINKING SELF-DRIVING: MULTI-TASK KNOWLEDGE FOR BETTER GENERALIZATION AND ACCIDENT EXPLANATION ABILITY）</news:title>
   <news:publication_date>2026-06-18T05:48:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701990</loc>
  <lastmod>2026-06-18T05:48:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模GANトレーニングによる高忠実度自然画像合成（LARGE SCALE GAN TRAINING FOR HIGH FIDELITY NATURAL IMAGE SYNTHESIS）</news:title>
   <news:publication_date>2026-06-18T05:48:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701988</loc>
  <lastmod>2026-06-18T05:47:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子構造の解析におけるカーネルベース手法（A kernel-based approach to molecular conformation analysis）</news:title>
   <news:publication_date>2026-06-18T05:47:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701986</loc>
  <lastmod>2026-06-18T05:47:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>作業記憶を学習する方法：注意制御による保持・忘却・無視の学習（Learning to Remember, Forget, and Ignore using Attention Control in Memory）</news:title>
   <news:publication_date>2026-06-18T05:47:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701984</loc>
  <lastmod>2026-06-18T05:47:23Z</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の二値・三値重み学習（LEARNING RECURRENT BINARY/TERNARY WEIGHTS）</news:title>
   <news:publication_date>2026-06-18T05:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701982</loc>
  <lastmod>2026-06-18T05:47:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンティティ解決のための再利用と適応（Reuse and Adaptation for Entity Resolution through Transfer Learning）</news:title>
   <news:publication_date>2026-06-18T05:47:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701980</loc>
  <lastmod>2026-06-18T05:47:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シリコンの液相構造と結晶核生成の第一原理ディープメタダイナミクス（Silicon liquid structure and crystal nucleation from ab‑initio deep Metadynamics）</news:title>
   <news:publication_date>2026-06-18T05:47:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701978</loc>
  <lastmod>2026-06-18T04:55:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同期ネットワークの最適化ランドスケープ（On the Landscape of Synchronization Networks: A Perspective from Nonconvex Optimization）</news:title>
   <news:publication_date>2026-06-18T04:55:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701976</loc>
  <lastmod>2026-06-18T04:55:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習から得た知識でロボットの表現と推論を統合する（Robot Representation and Reasoning with Knowledge from Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-18T04:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701974</loc>
  <lastmod>2026-06-18T04:55:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転倒を防ぐ「一歩」を学習する技術 — Learning to Improve Capture Steps for Disturbance Rejection in Humanoid Soccer（Learning to Improve Capture Steps for Disturbance Rejection in Humanoid Soccer）</news:title>
   <news:publication_date>2026-06-18T04:55:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701972</loc>
  <lastmod>2026-06-18T04:54:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係性を学ぶ予測モデルが変えるマルチエージェント学習（Relational Forward Models for Multi-Agent Learning）</news:title>
   <news:publication_date>2026-06-18T04:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701970</loc>
  <lastmod>2026-06-18T04:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限記憶を伴う場面横断的語彙学習（Cross-situational learning of large lexicons with finite memory）</news:title>
   <news:publication_date>2026-06-18T04:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701968</loc>
  <lastmod>2026-06-18T04:54:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話し言葉パスフレーズ検証とi-vector空間の応用（Spoken Pass-Phrase Verification in the i-vector Space）</news:title>
   <news:publication_date>2026-06-18T04:54:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701966</loc>
  <lastmod>2026-06-18T04:53:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SConE: キーポイントの「隣人関係」を埋め込む新しい特徴量（SConE: Siamese Constellation Embedding Descriptor for Image Matching）</news:title>
   <news:publication_date>2026-06-18T04:53:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701964</loc>
  <lastmod>2026-06-18T04:02:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な線形バンディットと行列スケッチ（Efficient Linear Bandits through Matrix Sketching）</news:title>
   <news:publication_date>2026-06-18T04:02:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701962</loc>
  <lastmod>2026-06-18T04:02:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ApolloScapeデータセット上の注目点検出器安定性評価（Interest point detectors stability evaluation on ApolloScape dataset）</news:title>
   <news:publication_date>2026-06-18T04:02:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701960</loc>
  <lastmod>2026-06-18T04:01:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SIGUA: ラベルノイズ下の学習で「忘れる」ことが有効である理由（SIGUA: Forgetting May Make Learning with Noisy Labels More Robust）</news:title>
   <news:publication_date>2026-06-18T04:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701958</loc>
  <lastmod>2026-06-18T04:01:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空撮画像における建物検出のCNN融合（CNNs Fusion for Building Detection in Aerial Images）</news:title>
   <news:publication_date>2026-06-18T04:01:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701956</loc>
  <lastmod>2026-06-18T04:01:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>保守予測におけるコスト感度学習（Cost-Sensitive Learning for Predictive Maintenance）</news:title>
   <news:publication_date>2026-06-18T04:01:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701954</loc>
  <lastmod>2026-06-18T04:01:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移銀河におけるHeIIλ1640放射の性質と意味（Exploring Heiiλ1640 emission line properties at z = 2 −4）</news:title>
   <news:publication_date>2026-06-18T04:01:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701952</loc>
  <lastmod>2026-06-18T04:00:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>準備された実験データが示す ― カイオン断片化関数とSIDISにおける成果（Hadron Multiplicity and Fragmentation in SIDIS）</news:title>
   <news:publication_date>2026-06-18T04:00:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701950</loc>
  <lastmod>2026-06-18T03:09:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン固有集約モジュールによるドメイン一般化（Domain Generalization with Domain-Specific Aggregation Modules）</news:title>
   <news:publication_date>2026-06-18T03:09:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701948</loc>
  <lastmod>2026-06-18T03:09:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フードジャーナリングアプリの良し悪しを読み解く（The Good, The Bad &amp;amp; The Ugly Features: A Meta-analysis on User Review About Food Journaling Apps）</news:title>
   <news:publication_date>2026-06-18T03:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701946</loc>
  <lastmod>2026-06-18T03:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声・映像を統合した複数話者トラッキングの変分ベイズ推論（Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers）</news:title>
   <news:publication_date>2026-06-18T03:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701944</loc>
  <lastmod>2026-06-18T03:08:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語画像から筆者を特定する深層適応学習（Deep Adaptive Learning for Writer Identification based on Single Handwritten Word Images）</news:title>
   <news:publication_date>2026-06-18T03:08:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701942</loc>
  <lastmod>2026-06-18T03:08:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化する学習可能なダイナミカルネットワーク（Self-organizing dynamical networks able to learn autonomously）</news:title>
   <news:publication_date>2026-06-18T03:08:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701940</loc>
  <lastmod>2026-06-18T03:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>子どものオンラインプライバシー支援は十分か（Are Children Well-Supported by Their Parents Concerning Online Privacy Risks, and Who Supports the Parents?）</news:title>
   <news:publication_date>2026-06-18T03:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701938</loc>
  <lastmod>2026-06-18T03:07:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピックトロープス：映画トロープのデータセットの概要（Overview of PicTropes, a film trope dataset）</news:title>
   <news:publication_date>2026-06-18T03:07:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701936</loc>
  <lastmod>2026-06-18T02:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SeqSleepNet: シーケンス対シーケンス自動睡眠ステージ分類の階層型RNN（SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging）</news:title>
   <news:publication_date>2026-06-18T02:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701934</loc>
  <lastmod>2026-06-18T02:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑ネットワークとしての深層学習（Deep learning systems as complex networks）</news:title>
   <news:publication_date>2026-06-18T02:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701932</loc>
  <lastmod>2026-06-18T02:15:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半透明物体の深度復元技術（Depth Reconstruction of Translucent Objects from a Single Time-of-Flight Camera using Deep Residual Networks）</news:title>
   <news:publication_date>2026-06-18T02:15:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701930</loc>
  <lastmod>2026-06-18T02:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wikistat 2.0：人工知能教育のための教材群 (Wikistat 2.0: Educational Resources for Artificial Intelligence)</news:title>
   <news:publication_date>2026-06-18T02:15:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701928</loc>
  <lastmod>2026-06-18T02:14:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単発推論で信頼度を較正する手法の意義（Learning for Single-Shot Confidence Calibration in Deep Neural Networks through Stochastic Inferences）</news:title>
   <news:publication_date>2026-06-18T02:14:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701926</loc>
  <lastmod>2026-06-18T02:14:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声に対する敵対的事例の特徴付け：時間的依存性の活用 (CHARACTERIZING AUDIO ADVERSARIAL EXAMPLES USING TEMPORAL DEPENDENCY)</news:title>
   <news:publication_date>2026-06-18T02:14:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701924</loc>
  <lastmod>2026-06-18T02:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HyperST-Netによる時空間予測の新展開 (HyperST-Net: Hypernetworks for Spatio-Temporal Forecasting)</news:title>
   <news:publication_date>2026-06-18T02:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701922</loc>
  <lastmod>2026-06-18T01:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>H∞ノルム推定の最小最大下界（Minimax Lower Bounds for H∞-Norm Estimation）</news:title>
   <news:publication_date>2026-06-18T01:22:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701920</loc>
  <lastmod>2026-06-18T01:14:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-18T01:14:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-18T01:13:04Z</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>2026-06-18T01:12:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-18T01:12:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-18T00:20:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701906</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-18T00:20:34Z</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>埋め込み状態潜在条件付き確率場による系列ラベリングの改善（Embedded-State Latent Conditional Random Fields for Sequence Labeling）</news:title>
   <news:publication_date>2026-06-18T00:19:59Z</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>SVMで学ぶ信頼度セットの構築（Learning Confidence Sets using Support Vector Machines）</news:title>
   <news:publication_date>2026-06-18T00:19:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-18T00:19:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆輸送ネットワークによる物理知覚の学習（Inverse Transport Networks）</news:title>
   <news:publication_date>2026-06-18T00:19:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い検出の限界と線形スペクトル統計に基づく検定（Weak detection in the spiked Wigner model）</news:title>
   <news:publication_date>2026-06-18T00:19:17Z</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:publication_date>2026-06-18T00:19:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-17T23:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ATRIAS二足歩行ロボットにおける深層強化学習で学ぶ高次方策（Using Deep Reinforcement Learning to Learn High-Level Policies on the ATRIAS Biped）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FanStoreによる分散Deep Learning向けI/O最適化（FanStore: Enabling Efficient and Scalable I/O for Distributed Deep Learning）</news:title>
   <news:publication_date>2026-06-17T23:26:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>協働ロボットのデモからの学習：隠れマルコフモデルによる状態分布学習（Collaborative Robot Learning from Demonstrations using Hidden Markov Model State Distribution）</news:title>
   <news:publication_date>2026-06-17T23:26:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-17T22:33:55Z</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>2026-06-17T22:33:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-17T22:33:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-17T22:33:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身近な空間で学び動く：到達と把持の学習（Learning and Acting in Peripersonal Space: Moving, Reaching, and Grasping）</news:title>
   <news:publication_date>2026-06-17T22:32:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索的モデル解析のためのユーザベースの可視分析ワークフロー（A User-based Visual Analytics Workflow for Exploratory Model Analysis）</news:title>
   <news:publication_date>2026-06-17T21:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ推論のための適応型ガウス過程代理モデル（Adaptive Gaussian process surrogates for Bayesian inference）</news:title>
   <news:publication_date>2026-06-17T21:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701862</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>Morpho-MNISTによる表現学習の定量評価（Morpho‑MNIST: Quantitative Assessment and Diagnostics for Representation Learning）</news:title>
   <news:publication_date>2026-06-17T21:31:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/701860</loc>
  <lastmod>2026-06-17T21:30:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-17T21:30:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701858</loc>
  <lastmod>2026-06-17T21:30:05Z</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>2026-06-17T21:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701856</loc>
  <lastmod>2026-06-17T21:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己注意型オートエンコーダと近傍影響を用いたPOI推薦（Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence）</news:title>
   <news:publication_date>2026-06-17T21:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己符号化ノックオフ生成器によるFDR制御変数選択（Auto-Encoding Knockoff Generator for FDR Controlled Variable Selection）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701852</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>2026-06-17T20:37:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-17T20:36:53Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-17T20:36:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>荒れ地走破のための適応的テンセグリティ走行（Adaptive Tensegrity Locomotion on Rough Terrain via Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-17T20:34:55Z</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>2026-06-17T20:34:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701838</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>ディフラクティブパターンと系譜の対応（Diffractive patterns in deep-inelastic scattering and parton genealogy）</news:title>
   <news:publication_date>2026-06-17T19:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701836</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>交通カメラ画像の意味的トピック解析（Semantic Topic Analysis of Traffic Camera Images）</news:title>
   <news:publication_date>2026-06-17T19:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701834</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>高精度ロボット組立の姿勢推定をシミュレーション深度画像で学習する（Learning Pose Estimation for High-Precision Robotic Assembly Using Simulated Depth Images）</news:title>
   <news:publication_date>2026-06-17T19:42:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701832</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>2026-06-17T19:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701830</loc>
  <lastmod>2026-06-17T19:41:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバストなセンサ融合によるロボット姿勢推定（Robust Sensor Fusion for Robot Attitude Estimation）</news:title>
   <news:publication_date>2026-06-17T19:41:37Z</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>
   <news:title>近位大腿骨骨折の弱教師あり局所化と分類（Weakly-Supervised Localization and Classification of Proximal Femur Fractures）</news:title>
   <news:publication_date>2026-06-17T19:41:23Z</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>複数の強化学習エージェントを協調させる学習法（LEARNING TO COORDINATE MULTIPLE REINFORCEMENT LEARNING AGENTS FOR DIVERSE QUERY REFORMULATION）</news:title>
   <news:publication_date>2026-06-17T19:41:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-17T18:48:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701822</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701820</loc>
  <lastmod>2026-06-17T18:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的リプレイとフィードバック接続による継続学習戦略（Generative replay with feedback connections as a general strategy for continual learning）</news:title>
   <news:publication_date>2026-06-17T18:47:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701818</loc>
  <lastmod>2026-06-17T18:47:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同期位相測定器を用いたIPSO最適化ELMによる電力系統過渡安定性予測（Optimized Extreme Learning Machine for Power System Transient Stability Prediction Using Synchrophasors）</news:title>
   <news:publication_date>2026-06-17T18:47:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701816</loc>
  <lastmod>2026-06-17T18:46:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分自己回帰ネットワークによる統計力学問題の解法（Solving Statistical Mechanics Using Variational Autoregressive Networks）</news:title>
   <news:publication_date>2026-06-17T18:46:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701814</loc>
  <lastmod>2026-06-17T18:46:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類における反事実的公平性と頑健性（Counterfactual Fairness in Text Classification through Robustness）</news:title>
   <news:publication_date>2026-06-17T18:46:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701812</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>適応型ロボットセンシングの逐次除去アプローチ（A Successive-Elimination Approach to Adaptive Robotic Sensing）</news:title>
   <news:publication_date>2026-06-17T18:46:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701810</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>網膜光干渉断層撮影のノイズ除去に深層学習を用いる意義（A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head）</news:title>
   <news:publication_date>2026-06-17T17:55:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701808</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>軽量な音楽テクスチャ転送システム（A Lightweight Music Texture Transfer System）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701806</loc>
  <lastmod>2026-06-17T17:47:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルベース低ランクスパースモデルによる単一画像超解像（Kernel Based Low-Rank Sparse Model for Single Image Super-Resolution）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701804</loc>
  <lastmod>2026-06-17T17:46:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数基準を統合する能動学習の新枠組み（A novel active learning framework for classification: using weighted rank aggregation to achieve multiple query criteria）</news:title>
   <news:publication_date>2026-06-17T17:46:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701802</loc>
  <lastmod>2026-06-17T17:46:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adaptive Image Stream Classification via Convolutional Neural Network with Intrinsic Similarity Metrics（Adaptive Image Stream Classification via Convolutional Neural Network with Intrinsic Similarity Metrics）</news:title>
   <news:publication_date>2026-06-17T17:46:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701800</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>単眼カメラで実現するリアルタイム3D姿勢推定（Real-time 3D Pose Estimation with a Monocular Camera Using Deep Learning and Object Priors）</news:title>
   <news:publication_date>2026-06-17T17:46:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701798</loc>
  <lastmod>2026-06-17T17:46:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-17T17:46:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701796</loc>
  <lastmod>2026-06-17T16:54:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画ストリーミング学習におけるクロスレイヤー効果（Cross-Layer Effects on Training Neural Algorithms for Video Streaming）</news:title>
   <news:publication_date>2026-06-17T16:54:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701794</loc>
  <lastmod>2026-06-17T16:54:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオ分類におけるビットレートと精度のトレードオフ（Rate-Accuracy Trade-Off In Video Classification With Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-17T16:54:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701792</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>2026-06-17T16:53:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701790</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>2026-06-17T16:52:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701788</loc>
  <lastmod>2026-06-17T16:52:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転に頑健な畳み込みニューラルネットワークによる一次視覚野モデル化（A Rotation-Equivariant Convolutional Neural Network Model of Primary Visual Cortex）</news:title>
   <news:publication_date>2026-06-17T16:52:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701786</loc>
  <lastmod>2026-06-17T16:52:29Z</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>2026-06-17T16:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701784</loc>
  <lastmod>2026-06-17T16:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-17T16:00:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模低ランク・非滑らか行列最適化の高速確率的アルゴリズム（Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems）</news:title>
   <news:publication_date>2026-06-17T15:59:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701774</loc>
  <lastmod>2026-06-17T15:59:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pareto前線の中心に重点を置いた予算付き多目的最適化（Budgeted Multi-Objective Optimization with a Focus on the Central Part of the Pareto Front - Extended Version）</news:title>
   <news:publication_date>2026-06-17T15:59:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701772</loc>
  <lastmod>2026-06-17T15:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓CT血管撮影における心筋セグメンテーションの改善（Improving Myocardium Segmentation in Cardiac CT Angiography using Spectral Information）</news:title>
   <news:publication_date>2026-06-17T15:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701770</loc>
  <lastmod>2026-06-17T15:58:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイナリニューラルネットワークの学習方法（Learning to Train a Binary Neural Network）</news:title>
   <news:publication_date>2026-06-17T15:58:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701768</loc>
  <lastmod>2026-06-17T15:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデータで適応するテキスト音声合成（SAMPLE EFFICIENT ADAPTIVE TEXT-TO-SPEECH）</news:title>
   <news:publication_date>2026-06-17T15:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701766</loc>
  <lastmod>2026-06-17T15:07:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的依存性：Pearsonの相関を超えて（Statistical dependence: Beyond Pearson’s ρ*）</news:title>
   <news:publication_date>2026-06-17T15:07:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701764</loc>
  <lastmod>2026-06-17T15:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フロー形式ネットワークトラフィック生成にGANを使う意義（Flow-based Network Traffic Generation using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-17T15:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701762</loc>
  <lastmod>2026-06-17T15:06:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNN入力の圧縮を実現する一次スキャッタリング変換（Compressing the Input for CNNs with the First-Order Scattering Transform）</news:title>
   <news:publication_date>2026-06-17T15:06:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701760</loc>
  <lastmod>2026-06-17T15:06:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光場（ライトフィールド）画像を高精細化する単純で強力な枠組み（A Simple Framework to Leverage State-Of-The-Art Single-Image Super-Resolution Methods to Restore Light Fields）</news:title>
   <news:publication_date>2026-06-17T15:06:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701758</loc>
  <lastmod>2026-06-17T15:06:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電気自動車充電のモデルフリー協調制御の定義と評価（Definition and evaluation of model-free coordination of electrical vehicle charging with reinforcement learning）</news:title>
   <news:publication_date>2026-06-17T15:06:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701756</loc>
  <lastmod>2026-06-17T15:05:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球面上での疎表現学習（Learning sparse representations on the sphere）</news:title>
   <news:publication_date>2026-06-17T15:05:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701754</loc>
  <lastmod>2026-06-17T14:14:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>右心室セグメンテーションのための生成的敵対モデル（A Generative Adversarial Model for Right Ventricle Segmentation）</news:title>
   <news:publication_date>2026-06-17T14:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701752</loc>
  <lastmod>2026-06-17T14:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話で前後をつなぐNEXUS Network（NEXUS Network: Connecting the Preceding and the Following in Dialogue Generation）</news:title>
   <news:publication_date>2026-06-17T14:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701750</loc>
  <lastmod>2026-06-17T14:13:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRIセグメンテーションの信頼性向上（Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI）</news:title>
   <news:publication_date>2026-06-17T14:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701748</loc>
  <lastmod>2026-06-17T14:12:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散学習における重みへのノイズ導入の効果（Introducing Noise in Decentralized Training of Neural Networks）</news:title>
   <news:publication_date>2026-06-17T14:12:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701746</loc>
  <lastmod>2026-06-17T14:12:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化マップによる相転移検出と位相同定（Self-organizing maps as a method for detecting phase transitions and phase identification）</news:title>
   <news:publication_date>2026-06-17T14:12:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701744</loc>
  <lastmod>2026-06-17T14:12:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロゼッタ/OSIRISによる67P塵雲の位相関数モデル（Models of Rosetta/OSIRIS 67P dust coma phase function）</news:title>
   <news:publication_date>2026-06-17T14:12:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701742</loc>
  <lastmod>2026-06-17T14:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者間心電図（ECG）分類における畳み込み・再帰ニューラルネットワーク（Inter-Patient ECG Classification with Convolutional and Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-17T14:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701740</loc>
  <lastmod>2026-06-17T13:20:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙論シミュレーションと深いサブミリ波観測の比較（Comparison of cosmological simulations and deep submillimetre galaxy surveys）</news:title>
   <news:publication_date>2026-06-17T13:20:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701738</loc>
  <lastmod>2026-06-17T13:20:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による画像ノイズ除去の実務的意義（Image Reconstruction Using Deep Learning）</news:title>
   <news:publication_date>2026-06-17T13:20:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701736</loc>
  <lastmod>2026-06-17T13:19:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人格印象に基づく3D顔合成（3D Face Synthesis Driven by Personality Impression）</news:title>
   <news:publication_date>2026-06-17T13:19:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701734</loc>
  <lastmod>2026-06-17T13:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層間伝播の安定化がもたらす精度向上（Smooth Inter-layer Propagation of Stabilized Neural Networks for Classification）</news:title>
   <news:publication_date>2026-06-17T13:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701732</loc>
  <lastmod>2026-06-17T13:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習におけるキュー型リサンプリングの提案（Queue-based Resampling for Online Class Imbalance Learning）</news:title>
   <news:publication_date>2026-06-17T13:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701730</loc>
  <lastmod>2026-06-17T13:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブル機器のBluetoothによる識別（Identification of Wearable Devices with Bluetooth）</news:title>
   <news:publication_date>2026-06-17T13:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701728</loc>
  <lastmod>2026-06-17T13:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的辞書学習と勾配降下法による収束保証（Efficient Dictionary Learning with Gradient Descent）</news:title>
   <news:publication_date>2026-06-17T13:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701726</loc>
  <lastmod>2026-06-17T12:26:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予期せぬ道路危険下のDNNベース自律走行モデル（Deep Neural Network-based Driving Model for Roadway Hazards）</news:title>
   <news:publication_date>2026-06-17T12:26:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701724</loc>
  <lastmod>2026-06-17T12:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの非剛体形状予測を幾何学的に学ぶ（Geometry-Aware Network for Non-Rigid Shape Prediction from a Single View）</news:title>
   <news:publication_date>2026-06-17T12:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701722</loc>
  <lastmod>2026-06-17T12:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメイン表現のためのベクタ学習（Vector Learning for Cross Domain Representations）</news:title>
   <news:publication_date>2026-06-17T12:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701720</loc>
  <lastmod>2026-06-17T12:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向けニューラル言語モデルの適応的プルーニング（ADAPTIVE PRUNING OF NEURAL LANGUAGE MODELS FOR MOBILE DEVICES）</news:title>
   <news:publication_date>2026-06-17T12:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701718</loc>
  <lastmod>2026-06-17T12:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意姿勢での人物画像を教師なしで合成する手法（Unsupervised Person Image Synthesis in Arbitrary Poses）</news:title>
   <news:publication_date>2026-06-17T12:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701716</loc>
  <lastmod>2026-06-17T12:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的に不変なテキスト→画像生成（SEMANTICALLY INVARIANT TEXT-TO-IMAGE GENERATION）</news:title>
   <news:publication_date>2026-06-17T12:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701714</loc>
  <lastmod>2026-06-17T12:25:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化を組み込んだ再帰的ハイウェイネットワークの提案（BATCH-NORMALIZED RECURRENT HIGHWAY NETWORKS）</news:title>
   <news:publication_date>2026-06-17T12:25:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701712</loc>
  <lastmod>2026-06-17T11:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レビューの力が若い書き手を育てる—ファンフィクションに見る分散型メンタリングの効果（Reviews Matter: How Distributed Mentoring Predicts Lexical Diversity on Fanfiction.net）</news:title>
   <news:publication_date>2026-06-17T11:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701710</loc>
  <lastmod>2026-06-17T11:33:41Z</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Q&amp;amp;Aにおける回答者支援としてのフィードバック（Supporting Answerers with Feedback in Social Q&amp;amp;A）</news:title>
   <news:publication_date>2026-06-17T11:33:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701708</loc>
  <lastmod>2026-06-17T11:33:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型地震波形反転が切り拓く高速・頑健な地下像復元（Data-driven Seismic Waveform Inversion: A Study on the Robustness and Generalization）</news:title>
   <news:publication_date>2026-06-17T11:33:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701706</loc>
  <lastmod>2026-06-17T11:32:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列リー群上の前処理子による確率的勾配法の改善（PRECONDITIONER ON MATRIX LIE GROUP FOR SGD）</news:title>
   <news:publication_date>2026-06-17T11:32:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701704</loc>
  <lastmod>2026-06-17T11:32:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット運動計画のための深層情報に基づくサンプリング（Deeply Informed Neural Sampling for Robot Motion Planning）</news:title>
   <news:publication_date>2026-06-17T11:32:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701702</loc>
  <lastmod>2026-06-17T11:32:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量持続ホモロジーのためのカーネル（A Kernel for Multi-Parameter Persistent Homology）</news:title>
   <news:publication_date>2026-06-17T11:32:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701700</loc>
  <lastmod>2026-06-17T11:32:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションから実機への転移を拡大する組成可能なロボットスキルの学習（Scaling simulation-to-real transfer by learning composable robot skills）</news:title>
   <news:publication_date>2026-06-17T11:32:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701698</loc>
  <lastmod>2026-06-17T10:41:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽質量星周りの地球型惑星検出を高速化するマイクロレンズ経路の新しいパラメータ化（Microlensing path parametrization for Earth-like Exoplanet detection around solar mass stars）</news:title>
   <news:publication_date>2026-06-17T10:41:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701696</loc>
  <lastmod>2026-06-17T10:40:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動アノテーションで学ぶCNNによる指紋ポア記述（Automatic Dataset Annotation to Learn CNN Pore Description for Fingerprint Recognition）</news:title>
   <news:publication_date>2026-06-17T10:40:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701694</loc>
  <lastmod>2026-06-17T10:40:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適ノイズ付加機構と(0, δ)-差分プライバシーの実践的意義（Optimal Noise-Adding Mechanism in Additive Differential Privacy）</news:title>
   <news:publication_date>2026-06-17T10:40:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701692</loc>
  <lastmod>2026-06-17T10:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハンズフリーなクエリ最適化の可能性（Towards a Hands-Free Query Optimizer through Deep Learning）</news:title>
   <news:publication_date>2026-06-17T10:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701690</loc>
  <lastmod>2026-06-17T10:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>左心室のセグメンテーションと定量化を同時に学習する手法（Left Ventricle Segmentation and Quantification from Cardiac Cine MR Images via Multi-task Learning）</news:title>
   <news:publication_date>2026-06-17T10:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701688</loc>
  <lastmod>2026-06-17T10:39:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模集団を対象としたデータ解析パイプラインの計算再現性予測（Predicting computational reproducibility of data analysis pipelines in large population studies using collaborative filtering）</news:title>
   <news:publication_date>2026-06-17T10:39:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701686</loc>
  <lastmod>2026-06-17T10:39:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>出荷箱の機械学習による設計最適化（A Machine Learning Approach to Shipping Box Design）</news:title>
   <news:publication_date>2026-06-17T10:39:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701684</loc>
  <lastmod>2026-06-17T09:48:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AlphaSeq: 深層強化学習による配列探索の新パラダイム（AlphaSeq: Sequence Discovery with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-17T09:48:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701682</loc>
  <lastmod>2026-06-17T09:47:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AWiFS衛星画像に基づく水域・焼失地のコンテンツベース検索（Content Based Image Retrieval from AWiFS Images Repository of IRS Resourcesat-2 Satellite Based on Water Bodies and Burnt Areas）</news:title>
   <news:publication_date>2026-06-17T09:47:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701680</loc>
  <lastmod>2026-06-17T09:47:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Monge–Ampère流に基づく生成モデルの実装と示唆（MONGE-AMPÈRE FLOW FOR GENERATIVE MODELING）</news:title>
   <news:publication_date>2026-06-17T09:47:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701678</loc>
  <lastmod>2026-06-17T09:46:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ω-regular目的をモデルフリー強化学習で扱う（Omega-Regular Objectives in Model-Free Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-17T09:46:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701676</loc>
  <lastmod>2026-06-17T09:45:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強く重力レンズ化された超新星の発見と意義（Rates and Properties of Strongly Gravitationally Lensed Supernovae and their Host Galaxies in Time-Domain Imaging Surveys）</news:title>
   <news:publication_date>2026-06-17T09:45:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701674</loc>
  <lastmod>2026-06-17T09:45:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AutoRLによるエンドツーエンド航行学習（Learning Navigation Behaviors End-to-End with AutoRL）</news:title>
   <news:publication_date>2026-06-17T09:45:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701672</loc>
  <lastmod>2026-06-17T09:45:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PCAとMUSICにおける未知信号数のベイズ推定（Bayesian Inference for PCA and MUSIC Algorithms with Unknown Number of Sources）</news:title>
   <news:publication_date>2026-06-17T09:45:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701670</loc>
  <lastmod>2026-06-17T08:53:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き線形二次レギュレータを安全に学習する方法（Safely Learning to Control the Constrained Linear Quadratic Regulator）</news:title>
   <news:publication_date>2026-06-17T08:53:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701668</loc>
  <lastmod>2026-06-17T08:53:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典的ゼロショット学習から一般化ゼロショット学習へ（From Classical to Generalized Zero-Shot Learning: a Simple Adaptation Process）</news:title>
   <news:publication_date>2026-06-17T08:53:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701666</loc>
  <lastmod>2026-06-17T08:52:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画品質評価に畳み込みニューラルネットワークを適用する意義（Convolutional Neural Networks for Video Quality Assessment）</news:title>
   <news:publication_date>2026-06-17T08:52:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701664</loc>
  <lastmod>2026-06-17T08:52:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深サブ波長で生じる複数散乱による左手バンド（Left-handed Band in an Electromagnetic Metamaterial Induced by Sub-wavelength Multiple Scattering）</news:title>
   <news:publication_date>2026-06-17T08:52:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701662</loc>
  <lastmod>2026-06-17T08:52:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冗長な知覚と状態推定による信頼性の向上（Redundant Perception and State Estimation for Reliable Autonomous Racing）</news:title>
   <news:publication_date>2026-06-17T08:52:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701660</loc>
  <lastmod>2026-06-17T08:51:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトメトリック深度超解像（Photometric Depth Super-Resolution）</news:title>
   <news:publication_date>2026-06-17T08:51:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701658</loc>
  <lastmod>2026-06-17T08:51:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意せよ！タスク重視の視覚注意で深層視覚運動ポリシーを頑健化する（Pay attention! - Robustifying a Deep Visuomotor Policy through Task-Focused Visual Attention）</news:title>
   <news:publication_date>2026-06-17T08:51:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701656</loc>
  <lastmod>2026-06-17T08:00:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし敵対的不変性の誘導（Unsupervised Adversarial Invariance）</news:title>
   <news:publication_date>2026-06-17T08:00:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701654</loc>
  <lastmod>2026-06-17T07:59:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタマテリアルの結晶性による局所偏光波の伝搬（Locally Polarized Wave Propagation through Metamaterials’ Crystallinity）</news:title>
   <news:publication_date>2026-06-17T07:59:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701652</loc>
  <lastmod>2026-06-17T07:59:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限状態分布による深層ニューラルネットワークの再発見（Rediscovering Deep Neural Networks Through Finite State Distributions）</news:title>
   <news:publication_date>2026-06-17T07:59:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701650</loc>
  <lastmod>2026-06-17T07:59:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復正則化インクリメンタル部分勾配法によるバイレベル最適化（An Iterative Regularized Incremental Projected Subgradient Method for a Class of Bilevel Optimization Problems）</news:title>
   <news:publication_date>2026-06-17T07:59:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701648</loc>
  <lastmod>2026-06-17T07:59:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースの遅延意識キャッシュ制御（Learning-Based Delay-Aware Caching in Wireless D2D Caching Networks）</news:title>
   <news:publication_date>2026-06-17T07:59:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701646</loc>
  <lastmod>2026-06-17T07:58:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>積グラフ上のグラフ信号に関するサンプリング理論（Sampling Theory for Graph Signals on Product Graphs）</news:title>
   <news:publication_date>2026-06-17T07:58:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701644</loc>
  <lastmod>2026-06-17T07:58:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用宣言的帰納プログラミングによるデータワリング自動化（General-purpose Declarative Inductive Programming with Domain-Specific Background Knowledge for Data Wrangling Automation）</news:title>
   <news:publication_date>2026-06-17T07:58:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701642</loc>
  <lastmod>2026-06-17T07:07:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>励起子の巨大双極子状態の固有エネルギー（Eigenenergies of excitonic giant-dipole states in cuprous oxide）</news:title>
   <news:publication_date>2026-06-17T07:07:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701640</loc>
  <lastmod>2026-06-17T07:07:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤りを生成して誤り検出を強化する（Wronging a Right: Generating Better Errors to Improve Grammatical Error Detection）</news:title>
   <news:publication_date>2026-06-17T07:07:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701638</loc>
  <lastmod>2026-06-17T07:07:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語モデルは翻訳よりも構文を学ぶ（Language Modeling Teaches You More Syntax Than Translation Does: Lessons Learned Through Auxiliary Task Analysis）</news:title>
   <news:publication_date>2026-06-17T07:07:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701636</loc>
  <lastmod>2026-06-17T07:06:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QFlow liteデータセット：量子ドット実験の電荷状態に対する機械学習アプローチ（QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments）</news:title>
   <news:publication_date>2026-06-17T07:06:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701634</loc>
  <lastmod>2026-06-17T07:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルセンサのための情報マップ生成にニューラルネットワークを用いる（Using Neural Networks to Generate Information Maps for Mobile Sensors）</news:title>
   <news:publication_date>2026-06-17T07:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701632</loc>
  <lastmod>2026-06-17T07:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Learning through probing による協調行動の学習（Learning through probing: a decentralized reinforcement learning architecture for social dilemmas）</news:title>
   <news:publication_date>2026-06-17T07:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701630</loc>
  <lastmod>2026-06-17T07:05:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種情報ネットワークのための普遍的表現学習（Universal Network Representation for Heterogeneous Information Networks）</news:title>
   <news:publication_date>2026-06-17T07:05:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701628</loc>
  <lastmod>2026-06-17T06:14:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチラベル・データストリーム分類におけるオンライン積み重ねアンサンブルの提案（A Novel Online Stacked Ensemble for Multi-Label Stream Classification）</news:title>
   <news:publication_date>2026-06-17T06:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701626</loc>
  <lastmod>2026-06-17T06:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推定と推論のための深層ニューラルネットワーク（Deep Neural Networks for Estimation and Inference）</news:title>
   <news:publication_date>2026-06-17T06:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701624</loc>
  <lastmod>2026-06-17T06:14:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム遮蔽回復による人物再識別のデータ増強（Random Occlusion-recovery for Person Re-identification）</news:title>
   <news:publication_date>2026-06-17T06:14:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701622</loc>
  <lastmod>2026-06-17T06:13:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層ニューラルネットワークにおけるジャミング現象（Jamming in multilayer supervised learning models）</news:title>
   <news:publication_date>2026-06-17T06:13:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701620</loc>
  <lastmod>2026-06-17T06:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現定理はいつ成立するか（When is there a Representer Theorem?）</news:title>
   <news:publication_date>2026-06-17T06:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701618</loc>
  <lastmod>2026-06-17T06:13:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で読み解くBerezinskii–Kosterlitz–Thouless転移（A machine learning approach to the Berezinskii-Kosterlitz-Thouless transition in classical and quantum models）</news:title>
   <news:publication_date>2026-06-17T06:13:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701616</loc>
  <lastmod>2026-06-17T06:12:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>孤立銀河 CIG 96 の環境と微弱構造の解明（Unveiling the environment and faint features of the isolated galaxy CIG 96 with deep optical and HI observations）</news:title>
   <news:publication_date>2026-06-17T06:12:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701614</loc>
  <lastmod>2026-06-17T05:21:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層に基づく画像埋め込みによるセマンティック画像検索（Hierarchy-based Image Embeddings for Semantic Image Retrieval）</news:title>
   <news:publication_date>2026-06-17T05:21:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701612</loc>
  <lastmod>2026-06-17T05:21:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>すべてのノードが重要になる：自己蒸留型グラフ畳み込みネットワーク（Every Node Counts: Self-Ensembling Graph Convolutional Networks for Semi-Supervised Learning）</news:title>
   <news:publication_date>2026-06-17T05:21:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701610</loc>
  <lastmod>2026-06-17T05:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>hyper-RKHSによるカーネル学習の一般化特性と応用（Generalization Properties of hyper-RKHS and its Applications）</news:title>
   <news:publication_date>2026-06-17T05:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701608</loc>
  <lastmod>2026-06-17T05:20:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CSONに対する敵対的攻撃の脅威と今後の課題 (Adversarial Attacks on Cognitive Self-Organizing Networks: The Challenge and the Way Forward)</news:title>
   <news:publication_date>2026-06-17T05:20:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701606</loc>
  <lastmod>2026-06-17T05:20:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体検出における能動学習の実践的方法（Active Learning for Deep Object Detection）</news:title>
   <news:publication_date>2026-06-17T05:20:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701604</loc>
  <lastmod>2026-06-17T05:20:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何的グラフからランダム点配置を復元する手法（Learning Random Points from Geometric Graphs or Orderings）</news:title>
   <news:publication_date>2026-06-17T05:20:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701602</loc>
  <lastmod>2026-06-17T05:19:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無秩序な高次位相絶縁体の相図：機械学習による検証（Phase diagram of disordered higher-order topological insulator: A machine learning study）</news:title>
   <news:publication_date>2026-06-17T05:19:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701600</loc>
  <lastmod>2026-06-17T04:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続的感情予測における動的難易度認識学習（Dynamic Difficulty Awareness Training for Continuous Emotion Prediction）</news:title>
   <news:publication_date>2026-06-17T04:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701598</loc>
  <lastmod>2026-06-17T04:21:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地理時空重み付きニューラルネットワークによる衛星観測を用いた地上PM2.5推定（Geographically and Temporally Weighted Neural Networks for Satellite-based Mapping of Ground-level PM2.5）</news:title>
   <news:publication_date>2026-06-17T04:21:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701596</loc>
  <lastmod>2026-06-17T04:19:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可視的類似性に基づく転移学習でブラックボックスを発達的に最適化する（Developmental Bayesian Optimization of Black-Box with Visual Similarity-Based Transfer Learning）</news:title>
   <news:publication_date>2026-06-17T04:19:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701594</loc>
  <lastmod>2026-06-17T04:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメインを用いた店舗推薦の新手法（A novel approach for venue recommendation using cross-domain techniques）</news:title>
   <news:publication_date>2026-06-17T04:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701592</loc>
  <lastmod>2026-06-17T04:18:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不正確なヘッセ行列と勾配で動く確率的二次法の実用化（Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient）</news:title>
   <news:publication_date>2026-06-17T04:18:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701590</loc>
  <lastmod>2026-06-17T04:18:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DBLSTMベース音声変換における誤差低減ネットワーク（Error Reduction Network for DBLSTM-based Voice Conversion）</news:title>
   <news:publication_date>2026-06-17T04:18:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701588</loc>
  <lastmod>2026-06-17T04:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフラプラシアン正則化を組み込んだグラフ畳み込みネットワーク（Graph Laplacian Regularized Graph Convolutional Networks for Semi-supervised Learning）</news:title>
   <news:publication_date>2026-06-17T04:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701586</loc>
  <lastmod>2026-06-17T03:26:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インド・プレミアリーグ（IPL）試合結果予測の機械学習アプローチ（Predicting Outcome of Indian Premier League (IPL) Matches Using Machine Learning）</news:title>
   <news:publication_date>2026-06-17T03:26:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701584</loc>
  <lastmod>2026-06-17T03:25:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>布のピックポイントに関する深層転移学習（Deep Transfer Learning of Pick Points on Fabric for Robot Bed-Making）</news:title>
   <news:publication_date>2026-06-17T03:25:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701582</loc>
  <lastmod>2026-06-17T03:25:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>夜間→昼間画像変換による探索ベースの位置推定の改善（Night-to-Day Image Translation for Retrieval-based Localization）</news:title>
   <news:publication_date>2026-06-17T03:25:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701580</loc>
  <lastmod>2026-06-17T03:25:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習は感覚情報処理の計算モデルをどう進めるか（How can deep learning advance computational modeling of sensory information processing?）</news:title>
   <news:publication_date>2026-06-17T03:25:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701578</loc>
  <lastmod>2026-06-17T03:25:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Relay — 機械学習フレームワークの新しい中間表現（Relay: A New IR for Machine Learning Frameworks）</news:title>
   <news:publication_date>2026-06-17T03:25:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701576</loc>
  <lastmod>2026-06-17T03:25:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ステレオマッチングにおける信頼度推定（Confidence Inference for Focused Learning in Stereo Matching）</news:title>
   <news:publication_date>2026-06-17T03:25:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701574</loc>
  <lastmod>2026-06-17T02:33:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Residualネットワークを用いた模倣（Mimic）アーキテクチャによるスペクトルマッピングの探求（AN EXPLORATION OF MIMIC ARCHITECTURES FOR RESIDUAL NETWORK BASED SPECTRAL MAPPING）</news:title>
   <news:publication_date>2026-06-17T02:33:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701572</loc>
  <lastmod>2026-06-17T02:33:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地図が間違っているときのマップマッチング（Map matching when the map is wrong: Efficient on/off road vehicle tracking and map learning）</news:title>
   <news:publication_date>2026-06-17T02:33:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701570</loc>
  <lastmod>2026-06-17T02:33:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自転車のGPSデータだけで路面を見分ける（Surface Type Estimation from GPS Tracked Bicycle Activities）</news:title>
   <news:publication_date>2026-06-17T02:33:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701568</loc>
  <lastmod>2026-06-17T02:32:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zooniverseによる人間–機械協調の最適化（Optimizing the Human-Machine Partnership with Zooniverse）</news:title>
   <news:publication_date>2026-06-17T02:32:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701566</loc>
  <lastmod>2026-06-17T02:32:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期的記憶の最小表現（Minimal descriptions of cyclic memories）</news:title>
   <news:publication_date>2026-06-17T02:32:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701564</loc>
  <lastmod>2026-06-17T02:32:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>消費者と生産者の埋め込みを学習してユーザ生成コンテンツを推薦する（Learning Consumer and Producer Embeddings for User-Generated Content Recommendation）</news:title>
   <news:publication_date>2026-06-17T02:32:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701562</loc>
  <lastmod>2026-06-17T02:31:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学生のチェックイン行動を活用した注目地点予測の改善（Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction）</news:title>
   <news:publication_date>2026-06-17T02:31:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701560</loc>
  <lastmod>2026-06-17T01:40:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高精度かつ説明可能なモデルツリーの新しい分割基準（A Gradient-Based Split Criterion for Highly Accurate and Transparent Model Trees）</news:title>
   <news:publication_date>2026-06-17T01:40:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/701558</loc>
  <lastmod>2026-06-17T01:40:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BANDITSUM：文書切り出し要約を文脈的バンディットとして学習する（BANDITSUM: Extractive Summarization as a Contextual Bandit）</news:title>
   <news:publication_date>2026-06-17T01:40:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701556</loc>
  <lastmod>2026-06-17T01:39:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索的データ分析中の未来行動の学習と予測 (Learning and Anticipating Future Actions During Exploratory Data Analysis)</news:title>
   <news:publication_date>2026-06-17T01:39:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701554</loc>
  <lastmod>2026-06-17T01:38:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的軌跡から力場を学習する手法（Learning force fields from stochastic trajectories）</news:title>
   <news:publication_date>2026-06-17T01:38:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701552</loc>
  <lastmod>2026-06-17T01:38:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非ネイティブの子ども音声認識における転移学習と多言語DNNの応用（NON-NATIVE CHILDREN SPEECH RECOGNITION THROUGH TRANSFER LEARNING）</news:title>
   <news:publication_date>2026-06-17T01:38:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701550</loc>
  <lastmod>2026-06-17T01:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パターン認識のための深層ニューラルネットワーク（Deep Neural Networks for Pattern Recognition）</news:title>
   <news:publication_date>2026-06-17T01:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701548</loc>
  <lastmod>2026-06-17T01:38:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度パノラマSEM画像におけるAIによる損傷分類の新手法（High-resolution Panoramic SEM Damage Classification by AI）</news:title>
   <news:publication_date>2026-06-17T01:38:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701546</loc>
  <lastmod>2026-06-17T01:20:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形圧縮観測からのスパース復元と辞書学習（Sparse Recovery and Dictionary Learning from Nonlinear Compressive Measurements）</news:title>
   <news:publication_date>2026-06-17T01:20:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701544</loc>
  <lastmod>2026-06-17T01:20:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論に基づく最適な縮約変換（Optimal Renormalization Group Transformation from Information Theory）</news:title>
   <news:publication_date>2026-06-17T01:20:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701542</loc>
  <lastmod>2026-06-17T01:20:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>天の川銀河の衛星銀河総数と温かい暗黒物質粒子質量の制約（The Milky Way’s total satellite population and constraining the mass of the warm dark matter particle）</news:title>
   <news:publication_date>2026-06-17T01:20:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701540</loc>
  <lastmod>2026-06-17T01:19:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸最適化と低ランク行列因子分解の概要（Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview）</news:title>
   <news:publication_date>2026-06-17T01:19:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701538</loc>
  <lastmod>2026-06-17T01:19:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自由表面を持つ2次元流体における極の力学：新しい運動量保存量（Dynamics of Poles in 2D Hydrodynamics with Free Surface: New Constants of Motion）</news:title>
   <news:publication_date>2026-06-17T01:19:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701536</loc>
  <lastmod>2026-06-17T01:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の階層分類のためのCNNとRNNの統合（Combined Convolutional and Recurrent Neural Networks for Hierarchical Classification of Images）</news:title>
   <news:publication_date>2026-06-17T01:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701534</loc>
  <lastmod>2026-06-17T01:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈ごとの学習を越える—Contextual Bandits with Cross-Learning（Contextual Bandits with Cross-Learning）</news:title>
   <news:publication_date>2026-06-17T01:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701532</loc>
  <lastmod>2026-06-17T00:28:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソースコード変換による自動微分の実装技法（Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming）</news:title>
   <news:publication_date>2026-06-17T00:28:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701530</loc>
  <lastmod>2026-06-17T00:27:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠隔ロボット操作のためのヒューマンマシンインターフェース（Human-Machine Interface for Remote Training of Robot Tasks）</news:title>
   <news:publication_date>2026-06-17T00:27:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701528</loc>
  <lastmod>2026-06-17T00:27:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンワールド環境における支援ロボットのピック＆プレース（Towards Assistive Robotic Pick and Place in Open World Environments）</news:title>
   <news:publication_date>2026-06-17T00:27:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701526</loc>
  <lastmod>2026-06-17T00:26:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ事後分布近似誤差の実用的上界（PRACTICAL BOUNDS ON THE ERROR OF BAYESIAN POSTERIOR APPROXIMATIONS: A NONASYMPTOTIC APPROACH）</news:title>
   <news:publication_date>2026-06-17T00:26:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701524</loc>
  <lastmod>2026-06-17T00:26:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習におけるAnderson加速法（Anderson Acceleration for Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-17T00:26:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701522</loc>
  <lastmod>2026-06-17T00:26:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダウリング計量空間における多様性最大化（Diversity maximization in doubling metrics）</news:title>
   <news:publication_date>2026-06-17T00:26:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701520</loc>
  <lastmod>2026-06-17T00:26:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波列における周波数低下の比較研究（A Comparison of Frequency Downshift Models of Wave Trains on Deep Water）</news:title>
   <news:publication_date>2026-06-17T00:26:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701518</loc>
  <lastmod>2026-06-16T23:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテゴリレベル敵対学習によるセマンティック整合を重視したドメイン適応（Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation）</news:title>
   <news:publication_date>2026-06-16T23:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701516</loc>
  <lastmod>2026-06-16T23:34:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>横方向運動依存性が明かすスピン非対称性の解像（Role of transverse momentum dependence of unpolarised parton distribution and fragmentation functions in the analysis of azimuthal spin asymmetries）</news:title>
   <news:publication_date>2026-06-16T23:34:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701514</loc>
  <lastmod>2026-06-16T23:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速自動平滑化が変えるGAMの実務適用（Fast Automatic Smoothing for Generalized Additive Models）</news:title>
   <news:publication_date>2026-06-16T23:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701512</loc>
  <lastmod>2026-06-16T23:33:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成音声波形の自然化を実現するWaveCycleGAN（WAVECYCLEGAN: SYNTHETIC-TO-NATURAL SPEECH WAVEFORM CONVERSION USING CYCLE-CONSISTENT ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-06-16T23:33:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701510</loc>
  <lastmod>2026-06-16T23:33:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘッシアン・バリア法による線形制約付き最適化（Hessian Barrier Algorithms for Linearly Constrained Optimization Problems）</news:title>
   <news:publication_date>2026-06-16T23:33:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701508</loc>
  <lastmod>2026-06-16T23:32:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間関係に基づくランキングによる株価予測（Temporal Relational Ranking for Stock Prediction）</news:title>
   <news:publication_date>2026-06-16T23:32:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701506</loc>
  <lastmod>2026-06-16T23:32:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択時のネスト交差検証は実務的には過剰である（Nested cross-validation when selecting classifiers is overzealous for most practical applications）</news:title>
   <news:publication_date>2026-06-16T23:32:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701504</loc>
  <lastmod>2026-06-16T22:41:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分的敵対学習による最適経路計画（Incremental Adversarial Learning for Optimal Path Planning）</news:title>
   <news:publication_date>2026-06-16T22:41:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701502</loc>
  <lastmod>2026-06-16T22:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフニューラルネットワークの概観（Hypergraph Neural Networks）</news:title>
   <news:publication_date>2026-06-16T22:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701500</loc>
  <lastmod>2026-06-16T22:40:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープ畳み込みニューラルネットワークにおける非反復的知識融合（Non-Iterative Knowledge Fusion in Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-16T22:40:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701498</loc>
  <lastmod>2026-06-16T22:39:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分光スペクトルからの赤方偏移推定にCNNを用いる意義（Convolutional Neural Networks for Spectroscopic Redshift Estimation on Euclid Data）</news:title>
   <news:publication_date>2026-06-16T22:39:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701496</loc>
  <lastmod>2026-06-16T22:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ構造を考慮したベイズ的特徴選択と期待伝播（Sparse-Group Bayesian Feature Selection Using Expectation Propagation for Signal Recovery and Network Reconstruction）</news:title>
   <news:publication_date>2026-06-16T22:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701494</loc>
  <lastmod>2026-06-16T22:39:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習における状態表現学習のためのツールボックス（State Representation Learning for Reinforcement Learning Toolbox）</news:title>
   <news:publication_date>2026-06-16T22:39:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701492</loc>
  <lastmod>2026-06-16T22:39:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-16T22:39:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701490</loc>
  <lastmod>2026-06-16T21:48:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動学習とSVMによる効率的な地震脆弱性曲線推定（Efficient Seismic fragility curve estimation by Active Learning on Support Vector Machines）</news:title>
   <news:publication_date>2026-06-16T21:48:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701488</loc>
  <lastmod>2026-06-16T21:47:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意サンプリングに基づく加速座標降下法とミニバッチ最適化の最良率（Accelerated Coordinate Descent with Arbitrary Sampling and Best Rates for Minibatches）</news:title>
   <news:publication_date>2026-06-16T21:47:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701486</loc>
  <lastmod>2026-06-16T21:47:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全インプリシットオンライン学習（Fully Implicit Online Learning）</news:title>
   <news:publication_date>2026-06-16T21:47:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701484</loc>
  <lastmod>2026-06-16T21:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有害なソーシャルメディアアカウントの早期検出（Early Identification of Pathogenic Social Media Accounts）</news:title>
   <news:publication_date>2026-06-16T21:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701482</loc>
  <lastmod>2026-06-16T21:46:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データで学ぶ因果推論の概観（A Survey of Learning Causality with Data: Problems and Methods）</news:title>
   <news:publication_date>2026-06-16T21:46:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701480</loc>
  <lastmod>2026-06-16T21:46:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル駆動型深層学習によるMIMO検出 (A Model-Driven Deep Learning Network for MIMO Detection)</news:title>
   <news:publication_date>2026-06-16T21:46:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701478</loc>
  <lastmod>2026-06-16T21:46:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的深層マルチエージェント強化学習と時間抽象（Hierarchical Deep Multiagent Reinforcement Learning with Temporal Abstraction）</news:title>
   <news:publication_date>2026-06-16T21:46:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701476</loc>
  <lastmod>2026-06-16T20:54:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超低ビット非対称ハッシングの協調学習（Collaborative Learning for Extremely Low Bit Asymmetric Hashing）</news:title>
   <news:publication_date>2026-06-16T20:54:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701474</loc>
  <lastmod>2026-06-16T20:54:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所化解析による耐凍結タンパク質予測の堅牢化（RAFP-Pred: Robust Prediction of Antifreeze Proteins using Localized Analysis of n-Peptide Compositions）</news:title>
   <news:publication_date>2026-06-16T20:54:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701472</loc>
  <lastmod>2026-06-16T20:54:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模アップスケールのためのマルチグリッド逆投影（Multigrid Backprojection Super–Resolution and Deep Filter Visualization）</news:title>
   <news:publication_date>2026-06-16T20:54:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701470</loc>
  <lastmod>2026-06-16T20:53:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>C. elegansの逃避行動を自動で予測・解釈するモデル化（Automated, predictive, and interpretable inference of C. elegans escape dynamics）</news:title>
   <news:publication_date>2026-06-16T20:53:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701468</loc>
  <lastmod>2026-06-16T20:53:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Floyd-Warshall Reinforcement Learning が変えるマルチゴール強化学習の考え方（Floyd-Warshall Reinforcement Learning: Learning from Past Experiences to Reach New Goals）</news:title>
   <news:publication_date>2026-06-16T20:53:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701466</loc>
  <lastmod>2026-06-16T20:53:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スピーカー認識における注意機構：深いスピーカー埋め込みは何を学ぶか（ATTENTION MECHANISM IN SPEAKER RECOGNITION: WHAT DOES IT LEARN IN DEEP SPEAKER EMBEDDING?）</news:title>
   <news:publication_date>2026-06-16T20:53:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701464</loc>
  <lastmod>2026-06-16T20:53:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球内部の密度分布がDUNEでの非標準ニュートリノ相互作用検出に与える影響（Impact of Matter Density Profile Shape on NSI at DUNE）</news:title>
   <news:publication_date>2026-06-16T20:53:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701462</loc>
  <lastmod>2026-06-16T20:01:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Scenic: シナリオ記述と言語化によるシーン生成（Scenic: A Language for Scenario Specification and Scene Generation）</news:title>
   <news:publication_date>2026-06-16T20:01:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701460</loc>
  <lastmod>2026-06-16T20:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス情報を用いた表現形成がもたらす差（Utilizing Class Information for Deep Network Representation Shaping）</news:title>
   <news:publication_date>2026-06-16T20:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701458</loc>
  <lastmod>2026-06-16T20:01:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三重監督デコーダネットワークによる結合検出とセグメンテーション（Triply Supervised Decoder Networks for Joint Detection and Segmentation）</news:title>
   <news:publication_date>2026-06-16T20:01:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701456</loc>
  <lastmod>2026-06-16T20:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MedAL：医用画像解析における高精度で頑健な深層アクティブラーニング（MedAL: Accurate and Robust Deep Active Learning for Medical Image Analysis）</news:title>
   <news:publication_date>2026-06-16T20:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701454</loc>
  <lastmod>2026-06-16T20:00:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的に敵対的攻撃に耐えるニューラルネット（Neural Networks with Structural Resistance to Adversarial Attacks）</news:title>
   <news:publication_date>2026-06-16T20:00:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701452</loc>
  <lastmod>2026-06-16T20:00:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフフィルタによるデータ削減と再構成（GRAPH FILTERING FOR DATA REDUCTION AND RECONSTRUCTION）</news:title>
   <news:publication_date>2026-06-16T20:00:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701450</loc>
  <lastmod>2026-06-16T19:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スクラッチから学ぶ物体検出と深層監督（Object Detection from Scratch with Deep Supervision）</news:title>
   <news:publication_date>2026-06-16T19:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701448</loc>
  <lastmod>2026-06-16T19:08:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度ポリシーディスティレーションとニューロモルフィック応用（Low Precision Policy Distillation with Application to Low-Power, Real-time Sensation-Cognition-Action Loop with Neuromorphic Computing）</news:title>
   <news:publication_date>2026-06-16T19:08:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701446</loc>
  <lastmod>2026-06-16T19:08:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的システム上の強化学習によるレジリエント計算：ソーティングの事例研究（Resilient Computing with Reinforcement Learning on a Dynamical System: Case Study in Sorting）</news:title>
   <news:publication_date>2026-06-16T19:08:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701444</loc>
  <lastmod>2026-06-16T19:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期分散加速確率的勾配降下法（Asynchronous decentralized accelerated stochastic gradient descent）</news:title>
   <news:publication_date>2026-06-16T19:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701442</loc>
  <lastmod>2026-06-16T19:07:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約空間上の柔軟な混合モデル（FLEXIBLE MIXTURE MODELING ON CONSTRAINED SPACES）</news:title>
   <news:publication_date>2026-06-16T19:07:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701440</loc>
  <lastmod>2026-06-16T19:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乗算も浮動小数点演算も不要？省資源推論のためのネットワーク学習（No Multiplication? No Floating Point? No Problem! Training Networks for Efficient Inference）</news:title>
   <news:publication_date>2026-06-16T19:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701438</loc>
  <lastmod>2026-06-16T19:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による多系サロゲート材料予測モデル（Machine-learned multi-system surrogate models for materials prediction）</news:title>
   <news:publication_date>2026-06-16T19:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701436</loc>
  <lastmod>2026-06-16T19:06:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセットバイアス下における公平性指標の評価（Evaluating Fairness Metrics in the Presence of Dataset Bias）</news:title>
   <news:publication_date>2026-06-16T19:06:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701434</loc>
  <lastmod>2026-06-16T18:14:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震直後の点検を自動化する条件認識型モデル（Towards Automated Post-Earthquake Inspections with Deep Learning-based Condition-Aware Models）</news:title>
   <news:publication_date>2026-06-16T18:14:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701432</loc>
  <lastmod>2026-06-16T18:14:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケールでの個別化教育（Personalized Education at Scale）</news:title>
   <news:publication_date>2026-06-16T18:14:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701430</loc>
  <lastmod>2026-06-16T18:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経画像解析における再現可能なデータ解析の計算・情報学的進展（Computational and informatics advances for reproducible data analysis in neuroimaging）</news:title>
   <news:publication_date>2026-06-16T18:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701428</loc>
  <lastmod>2026-06-16T18:13:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Real-Time Monocular Object-Model Aware Sparse SLAM（Real-Time Monocular Object-Model Aware Sparse SLAM）</news:title>
   <news:publication_date>2026-06-16T18:13:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701426</loc>
  <lastmod>2026-06-16T18:13:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データから支配方程式を近似する数値的要点（Numerical Aspects for Approximating Governing Equations Using Data）</news:title>
   <news:publication_date>2026-06-16T18:13:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701424</loc>
  <lastmod>2026-06-16T18:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話なしのローカル差分プライバシー学習はなぜ困難か（Locally Private Learning without Interaction Requires Separation）</news:title>
   <news:publication_date>2026-06-16T18:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701422</loc>
  <lastmod>2026-06-16T18:12:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全志向の強化学習における証拠蓄積法（Better Safe than Sorry: Evidence Accumulation Allows for Safe Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-16T18:12:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701420</loc>
  <lastmod>2026-06-16T17:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EPIRLによるエピスタシス検出の強化学習アプローチ (EPIRL: A REINFORCEMENT LEARNING AGENT TO FACILITATE EPISTASIS DETECTION)</news:title>
   <news:publication_date>2026-06-16T17:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701418</loc>
  <lastmod>2026-06-16T17:21:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最も落ち着いたSPT選抜銀河団の詳細研究：クールコアと中心銀河の性質（A Detailed Study of the Most Relaxed SPT-Selected Galaxy Clusters: Cool Core and Central Galaxy Properties）</news:title>
   <news:publication_date>2026-06-16T17:21:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/701416</loc>
  <lastmod>2026-06-16T17:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>円筒変換による3次元腎臓セマンティックセグメンテーション（CYLINDRICAL TRANSFORM: 3D SEMANTIC SEGMENTATION OF KIDNEYS WITH LIMITED ANNOTATED IMAGES）</news:title>
   <news:publication_date>2026-06-16T17:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701414</loc>
  <lastmod>2026-06-16T17:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散逸的量子多体系における直交性カタストロフィー（Orthogonality catastrophe in dissipative quantum many body systems）</news:title>
   <news:publication_date>2026-06-16T17:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701412</loc>
  <lastmod>2026-06-16T17:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>輝度・深度・色を統合する融合型ネットワークによるセマンティックセグメンテーション（INCORPORATING LUMINANCE, DEPTH AND COLOR INFORMATION BY A FUSION-BASED NETWORK FOR SEMANTIC SEGMENTATION）</news:title>
   <news:publication_date>2026-06-16T17:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701410</loc>
  <lastmod>2026-06-16T17:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的最尤推定（Implicit Maximum Likelihood Estimation）</news:title>
   <news:publication_date>2026-06-16T17:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701408</loc>
  <lastmod>2026-06-16T17:19:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化するデータストリーム向け自己組織化ノイズ除去オートエンコーダ（Autonomous Deep Learning: Incremental Learning of Denoising Autoencoder for Evolving Data Streams）</news:title>
   <news:publication_date>2026-06-16T17:19:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701406</loc>
  <lastmod>2026-06-16T16:28:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>占有マップで深度を密にする手法（Sparse-to-Continuous: Enhancing Monocular Depth Estimation using Occupancy Maps）</news:title>
   <news:publication_date>2026-06-16T16:28:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701404</loc>
  <lastmod>2026-06-16T16:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Confidenceによる信頼区間の効率的算出（Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Errors for Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-16T16:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701402</loc>
  <lastmod>2026-06-16T16:26:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>28nm FDSOI CMOSの低温特性とモデリング（Characterization and Modeling of 28-nm FDSOI CMOS Technology down to Cryogenic Temperatures）</news:title>
   <news:publication_date>2026-06-16T16:26:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701400</loc>
  <lastmod>2026-06-16T16:26:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解剖学的ラベルを用いた弱教師ありメトリック集約による変形画像レジストレーション（Weakly-Supervised Learning of Metric Aggregations for Deformable Image Registration）</news:title>
   <news:publication_date>2026-06-16T16:26:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701398</loc>
  <lastmod>2026-06-16T16:26:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SDNにおけるフローエントリ管理を学習で最適化する手法（SDN Flow Entry Management Using Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-16T16:26:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701396</loc>
  <lastmod>2026-06-16T16:26:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一次元周期基板上の二次元液体ダスティプラズマのフォノンスペクトル（Phonon spectra of two-dimensional liquid dusty plasmas on a one-dimensional periodic substrate）</news:title>
   <news:publication_date>2026-06-16T16:26:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701394</loc>
  <lastmod>2026-06-16T16:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Bi-GAN支援遺伝的アルゴリズムによる深層ニューラルネットワークパラメータの自律同時最適化（Autonomously and Simultaneously Refining Deep Neural Network Parameters by a Bi-Generative Adversarial Network Aided Genetic Algorithm）</news:title>
   <news:publication_date>2026-06-16T16:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701392</loc>
  <lastmod>2026-06-16T15:34:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件生成に基づく相互情報量による敵対的部分空間の特徴付け（On the Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial Subspaces）</news:title>
   <news:publication_date>2026-06-16T15:34:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701390</loc>
  <lastmod>2026-06-16T15:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コミュニティ質問応答の共同マルチタスク学習（Joint Multitask Learning for Community Question Answering Using Task-Specific Embeddings）</news:title>
   <news:publication_date>2026-06-16T15:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701388</loc>
  <lastmod>2026-06-16T15:34:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な幾何学的摂動による対抗的顔画像（Fast Geometrically-Perturbed Adversarial Faces）</news:title>
   <news:publication_date>2026-06-16T15:34:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701386</loc>
  <lastmod>2026-06-16T15:33:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的半教師あり手法によるマルチタスク人間行動モデリング（A Probabilistic Semi-Supervised Approach to Multi-Task Human Activity Modeling）</news:title>
   <news:publication_date>2026-06-16T15:33:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701384</loc>
  <lastmod>2026-06-16T15:33:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速で精密なミエリン水量の定量化：DESSとカーネル学習による新手法（Fast, Precise Myelin Water Quantification using DESS MRI and Kernel Learning）</news:title>
   <news:publication_date>2026-06-16T15:33:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701382</loc>
  <lastmod>2026-06-16T15:33:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム干渉識別でIoT端末に共存認識を組み込む（Real-time Interference Identification via Supervised Learning: Embedding Coexistence Awareness in IoT Devices）</news:title>
   <news:publication_date>2026-06-16T15:33:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701380</loc>
  <lastmod>2026-06-16T15:32:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間接近下での四ロータ機の視覚制御（Vision-based Control of a Quadrotor in User Proximity: Mediated vs End-to-End Learning Approaches）</news:title>
   <news:publication_date>2026-06-16T15:32:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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