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   <news:title>SAFE: 不正検知のタイミングを早める生存分析ニューラルモデル（SAFE: A Neural Survival Analysis Model for Fraud Early Detection）</news:title>
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   <news:title>長いプログラムの自動合成と学習型ガベージコレクタ（Automatic Program Synthesis of Long Programs with a Learned Garbage Collector）</news:title>
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   <news:title>光散乱によるスピークル障害下の超冷却原子のエネルギー予測（Supervised machine learning of ultracold atoms with speckle disorder）</news:title>
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   <news:title>クリック予測のための統一バッチオンライン学習フレームワーク（A Unified Batch Online Learning Framework for Click Prediction）</news:title>
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   <news:title>基本ブロック再配置の改良—実行ファイル性能を左右するコード配置の最適化（Improved Basic Block Reordering）</news:title>
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    <news:language>ja</news:language>
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   <news:title>アテローム性心血管疾患リスク予測における公平性の構築（CREATING FAIR MODELS OF ATHEROSCLEROTIC CARDIOVASCULAR DISEASE）</news:title>
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   <news:title>推薦システムと意見形成の閉ループ（The closed loop between opinion formation and personalised recommendations）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>アンドロメダIIの運動性は大規模合併が起源（The major merger origin of the Andromeda II kinematics）</news:title>
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   <news:title>視覚品質駆動型学習による水中画像の視覚改善 (VISUAL-QUALITY-DRIVEN LEARNING FOR UNDERWATER VISION ENHANCEMENT)</news:title>
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   <news:title>確率的勾配ハミルトニアンモンテカルロの有限時間収束と加速性（Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Stochastic Optimization: Non-Asymptotic Performance Bounds and Momentum-Based Acceleration）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>異種画像ペアのマッチングを可能にする深層スペクトル対応（Deep Spectral Correspondence for Matching Disparate Image Pairs）</news:title>
   <news:publication_date>2026-06-12T23:53:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>異なるドメインの顔に対するランドマーク検出の二段階学習法（A Two-Step Learning Method for Detecting Landmarks on Faces from Different Domains）</news:title>
   <news:publication_date>2026-06-12T23:52:51Z</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>分散チェルノフ検定によるネットワーク上の最適意思決定（Distributed Chernoff Test: Optimal Decision Systems over Networks）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ベイズ的スパース再構成が切り開く画像復元と機械学習の新展望（Bayesian Sparse Reconstruction: a brute‑force approach to astronomical imaging and machine learning）</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>エンコーダの記憶力を高めるクローズドブック訓練（Closed-Book Training to Improve Summarization Encoder Memory）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-12T23:00:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>単純化が生む不平等――InterpretabilityとFairnessの緊張関係（Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>干渉トリガーアレイの設計と性能（Design and Performance of an Interferometric Trigger Array for Radio Detection of High-Energy Neutrinos）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>確率的勾配降下法のモメンタムの一般化に関する研究（On the Generalization of Stochastic Gradient Descent with Momentum）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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   <news:title>FINN-Rによる量子化ニューラルネットワークの高速探索（FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>潜在空間表現に基づく協調異種分散センシング（Coordinated Heterogeneous Distributed Perception based on Latent Space Representation）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-12T22:08:02Z</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>勾配ブースティング決定木のベンチマークと最適化（Benchmarking and Optimization of Gradient Boosting Decision Tree Algorithms）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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   <news:title>エンドツーエンドの音声・映像同時音声検出（End-to-end Audiovisual Speech Activity Detection with Bimodal Recurrent Neural Models）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>制限付き f-GAN の帰納的バイアス（The Inductive Bias of Restricted f-GANs）</news:title>
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  <news:news>
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    <news:language>ja</news:language>
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   <news:title>構造制約付きCycleGANによる非対応脳MR→CT合成（Unpaired Brain MR-to-CT Synthesis using a Structure-Constrained CycleGAN）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-12T22:06:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>テキスト分類で可解釈なルールを学ぶ新機軸（Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications）</news:title>
   <news:publication_date>2026-06-12T22:06:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-12T22:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極値探索における学習ダイナミクスの特徴（Characterizing the learning dynamics in extremum seeking: The role of gradient averaging and non-convexity）</news:title>
   <news:publication_date>2026-06-12T22:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699997</loc>
  <lastmod>2026-06-12T21:15:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Parton Branching法によるTMDパートン分布の決定と応用（Determination and application of TMD parton densities using the Parton Branching method）</news:title>
   <news:publication_date>2026-06-12T21:15:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/699995</loc>
  <lastmod>2026-06-12T21:14:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚化にまたがるEEGベース認知負荷推定の汎化性（Investigating the generalizability of EEG-based Cognitive Load Estimation Across Visualizations）</news:title>
   <news:publication_date>2026-06-12T21:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/699993</loc>
  <lastmod>2026-06-12T21:14:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wavelet領域で学ぶ部分帯別協調学習：SRCliqueNetの要点（Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution）</news:title>
   <news:publication_date>2026-06-12T21:14:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/699991</loc>
  <lastmod>2026-06-12T21:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Emo2Vecによる一般化された感情表現の学習（Emo2Vec: Learning Generalized Emotion Representation by Multi-task Training）</news:title>
   <news:publication_date>2026-06-12T21:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/699989</loc>
  <lastmod>2026-06-12T21:13:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>シナリオに応じた協調行動の自発的出現（Emergence of Scenario-Appropriate Collaborative Behaviors for Teams of Robotic Bodyguards）</news:title>
   <news:publication_date>2026-06-12T21:13:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/699987</loc>
  <lastmod>2026-06-12T21:13:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストベースのカスケードにおける話題間相互作用の発見（Discovering Topical Interactions in Text-based Cascades using Hidden Markov Hawkes Processes）</news:title>
   <news:publication_date>2026-06-12T21:13:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/699985</loc>
  <lastmod>2026-06-12T21:13:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパープライアーによる教師なし潜在表現の分離（Hyperprior Induced Unsupervised Disentanglement of Latent Representations）</news:title>
   <news:publication_date>2026-06-12T21:13:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699983</loc>
  <lastmod>2026-06-12T20:22:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数タスクに強い強化学習とPopArtの威力（Multi-task Deep Reinforcement Learning with PopArt）</news:title>
   <news:publication_date>2026-06-12T20:22:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699981</loc>
  <lastmod>2026-06-12T20:22:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動きから学ぶStructure-from-Motion（Learning structure-from-motion from motion）</news:title>
   <news:publication_date>2026-06-12T20:22:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699979</loc>
  <lastmod>2026-06-12T20:21:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム特徴量による線形SVMの理論的理解（But How Does It Work in Theory? Linear SVM with Random Features）</news:title>
   <news:publication_date>2026-06-12T20:21:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699977</loc>
  <lastmod>2026-06-12T20:21:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頭頸部放射線治療のための臨床適用可能なセグメンテーションを実現する深層学習（Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy）</news:title>
   <news:publication_date>2026-06-12T20:21:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699975</loc>
  <lastmod>2026-06-12T20:21:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フレームレベル話者埋め込みによるテキスト非依存話者認識の解析（FRAME-LEVEL SPEAKER EMBEDDINGS FOR TEXT-INDEPENDENT SPEAKER RECOGNITION AND ANALYSIS OF END-TO-END MODEL）</news:title>
   <news:publication_date>2026-06-12T20:21:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699973</loc>
  <lastmod>2026-06-12T20:20:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者方言識別のための教師なし音声表現学習（UNSUPERVISED REPRESENTATION LEARNING OF SPEECH FOR DIALECT IDENTIFICATION）</news:title>
   <news:publication_date>2026-06-12T20:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699971</loc>
  <lastmod>2026-06-12T20:20:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SU Aurの可視・近赤外での深い減光イベント（SU AUR: A DEEP FADING EVENT IN VISIBLE AND NEAR-INFRARED BANDS）</news:title>
   <news:publication_date>2026-06-12T20:20:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699969</loc>
  <lastmod>2026-06-12T19:29:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配に基づく表現類似性解析とサーチライトによるfMRI全脳解析（Gradient-based Representational Similarity Analysis with Searchlight for Analyzing fMRI Data）</news:title>
   <news:publication_date>2026-06-12T19:29:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699967</loc>
  <lastmod>2026-06-12T19:29:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の移動行動に対する位置情報プライバシーの再考（Rethinking Location Privacy for Unknown Mobility Behaviors）</news:title>
   <news:publication_date>2026-06-12T19:29:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699965</loc>
  <lastmod>2026-06-12T19:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実測データから「実在する」量子チャネルを復元する方法（Reconstruction of the Real Quantum Channel via Convex Optimization）</news:title>
   <news:publication_date>2026-06-12T19:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699963</loc>
  <lastmod>2026-06-12T19:28:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバルPDFフィットにおける機械学習ツールの活用（Machine Learning tools for global PDF fits）</news:title>
   <news:publication_date>2026-06-12T19:28:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699961</loc>
  <lastmod>2026-06-12T19:27:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模動画ラベリングで勝つための“ラベル除噪（Label Denoising）”の実務的教科書（Label Denoising with Large Ensembles of Heterogeneous Neural Networks）</news:title>
   <news:publication_date>2026-06-12T19:27:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699959</loc>
  <lastmod>2026-06-12T19:27:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>和積ネットワークで拡張する局所ガウス過程の混合モデル（Learning Deep Mixtures of Gaussian Process Experts Using Sum-Product Networks）</news:title>
   <news:publication_date>2026-06-12T19:27:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699957</loc>
  <lastmod>2026-06-12T19:27:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上のベイズ半教師あり学習（Bayesian Semi-supervised Learning with Graph Gaussian Processes）</news:title>
   <news:publication_date>2026-06-12T19:27:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699955</loc>
  <lastmod>2026-06-12T18:36:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調型マルチエージェント強化学習による反ジャミングアルゴリズム（A Collaborative Multi-agent Reinforcement Learning Anti-jamming Algorithm in Wireless Networks）</news:title>
   <news:publication_date>2026-06-12T18:36:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699953</loc>
  <lastmod>2026-06-12T18:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PAUサーベイにおけるフォトメトリック赤方偏移の早期検証（The PAU Survey: Early demonstration of photometric redshift performance in the COSMOS field）</news:title>
   <news:publication_date>2026-06-12T18:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699951</loc>
  <lastmod>2026-06-12T18:25:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期引用データから論文の将来の影響力を予測する（Predicting citation counts based on deep neural network learning techniques）</news:title>
   <news:publication_date>2026-06-12T18:25:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699949</loc>
  <lastmod>2026-06-12T18:25:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質のB因子（柔軟性）を盲検的に予測する手法（Blind prediction of protein B-factor and flexibility）</news:title>
   <news:publication_date>2026-06-12T18:25:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699947</loc>
  <lastmod>2026-06-12T18:25:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データ分類における深層学習の総覧（Deep learning for time series classification: a review）</news:title>
   <news:publication_date>2026-06-12T18:25:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699945</loc>
  <lastmod>2026-06-12T18:24:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心拍変動に基づく睡眠段階判定のためのLSTMと知識転移（LSTM knowledge transfer for HRV-based sleep staging）</news:title>
   <news:publication_date>2026-06-12T18:24:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699943</loc>
  <lastmod>2026-06-12T18:24:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なるデータセットで深層ニューラルネットワークを訓練する手法（Training Deep Neural Networks with Different Datasets In-the-wild: The Emotion Recognition Paradigm）</news:title>
   <news:publication_date>2026-06-12T18:24:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699941</loc>
  <lastmod>2026-06-12T17:33:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全身アーム操作を用いた人体移動のための位相基盤表現における強化学習（Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation）</news:title>
   <news:publication_date>2026-06-12T17:33:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699939</loc>
  <lastmod>2026-06-12T17:24:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報セキュリティ分野における深層学習の実務的意義（DEEP LEARNING IN INFORMATION SECURITY）</news:title>
   <news:publication_date>2026-06-12T17:24:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699937</loc>
  <lastmod>2026-06-12T17:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UGC 1922 の内部動力学と星形成（A Malin 1 “cousin” with counter-rotation: internal dynamics and stellar content of the giant low surface brightness galaxy UGC 1922）</news:title>
   <news:publication_date>2026-06-12T17:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699935</loc>
  <lastmod>2026-06-12T17:22:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>作業記憶モデルによる中国詩生成（Chinese Poetry Generation with a Working Memory Model）</news:title>
   <news:publication_date>2026-06-12T17:22:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699933</loc>
  <lastmod>2026-06-12T17:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌詞から自動作曲するニューラル手法（Neural Melody Composition from Lyrics）</news:title>
   <news:publication_date>2026-06-12T17:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699931</loc>
  <lastmod>2026-06-12T17:22:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期視覚追跡における回帰と検証ネットワークの統合（Learning regression and verification networks for long-term visual tracking）</news:title>
   <news:publication_date>2026-06-12T17:22:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699929</loc>
  <lastmod>2026-06-12T17:22:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異結合を持つクラモトモデルにおけるFilippov軌道とクラスタリング（FILIPPOV TRAJECTORIES AND CLUSTERING IN THE KURAMOTO MODEL WITH SINGULAR COUPLINGS）</news:title>
   <news:publication_date>2026-06-12T17:22:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699927</loc>
  <lastmod>2026-06-12T16:30:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚場面における発話を用いたマルチモーダルな呼びかけ先認識（Deep Learning Based Multi-modal Addressee Recognition in Visual Scenes with Utterances）</news:title>
   <news:publication_date>2026-06-12T16:30:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699925</loc>
  <lastmod>2026-06-12T16:30:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文と意味情報を埋め込みに取り込む方法（Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-06-12T16:30:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699923</loc>
  <lastmod>2026-06-12T16:30:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠測データからの連続時間ベイジアンネットワーク構造学習におけるクラスタ変分近似（Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data）</news:title>
   <news:publication_date>2026-06-12T16:30:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699921</loc>
  <lastmod>2026-06-12T16:29:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識を取り入れた会話型テーブル意味解析 (Knowledge-Aware Conversational Semantic Parsing Over Web Tables)</news:title>
   <news:publication_date>2026-06-12T16:29:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699919</loc>
  <lastmod>2026-06-12T16:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続変数を離散的に緩和して実用的な変分推論を可能にする方法（Discretely Relaxing Continuous Variables for tractable Variational Inference）</news:title>
   <news:publication_date>2026-06-12T16:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699917</loc>
  <lastmod>2026-06-12T16:29:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜OCT画像における層分割と不確実性可視化：ベイズ深層学習による信頼度の導入（Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images using Bayesian Deep Learning）</news:title>
   <news:publication_date>2026-06-12T16:29:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699915</loc>
  <lastmod>2026-06-12T16:29:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Music Transformerによる長期構造を持つ音楽生成（MUSIC TRANSFORMER: GENERATING MUSIC WITH LONG-TERM STRUCTURE）</news:title>
   <news:publication_date>2026-06-12T16:29:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699913</loc>
  <lastmod>2026-06-12T15:37:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MotherNets による迅速なディープアンサンブル学習（MOTHERNETS: RAPID DEEP ENSEMBLE LEARNING）</news:title>
   <news:publication_date>2026-06-12T15:37:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699911</loc>
  <lastmod>2026-06-12T15:37:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wasserstein重心を高速に求めるアルゴリズム（A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters）</news:title>
   <news:publication_date>2026-06-12T15:37:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699909</loc>
  <lastmod>2026-06-12T15:37:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分文字列で単語埋め込みを一般化する（Generalizing Word Embeddings using Bag of Subwords）</news:title>
   <news:publication_date>2026-06-12T15:37:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699907</loc>
  <lastmod>2026-06-12T15:36:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波(EEG)を用いた視聴映像認識とグラフ畳み込みニューラルネットワーク（EEG-BASED VIDEO IDENTIFICATION USING GRAPH SIGNAL MODELING AND GRAPH CONVOLUTIONAL NEURAL NETWORK）</news:title>
   <news:publication_date>2026-06-12T15:36:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699905</loc>
  <lastmod>2026-06-12T15:36:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>糖尿病性網膜症と黄斑浮腫の自動診断に向けたCNNアンサンブル手法（ENSEMBLE OF CONVOLUTIONAL NEURAL NETWORKS FOR AUTOMATIC GRADING OF DIABETIC RETINOPATHY AND MACULAR EDEMA）</news:title>
   <news:publication_date>2026-06-12T15:36:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699903</loc>
  <lastmod>2026-06-12T15:36:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時変安全性を考慮した安全探索：ST-SAFEMDP（Safe Exploration in Markov Decision Processes with Time-Variant Safety using Spatio-Temporal Gaussian Process）</news:title>
   <news:publication_date>2026-06-12T15:36:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699901</loc>
  <lastmod>2026-06-12T15:36:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>洗練された対戦相手に対する効率的検出と最適応答（Towards Efficient Detection and Optimal Response against Sophisticated Opponents）</news:title>
   <news:publication_date>2026-06-12T15:36:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699899</loc>
  <lastmod>2026-06-12T14:44:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市場の共投資関係を自動で学ぶDeepCNL（Deep Co-investment Network Learning for Financial Assets）</news:title>
   <news:publication_date>2026-06-12T14:44:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699897</loc>
  <lastmod>2026-06-12T14:34:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次の関係を捉えるグラフ畳み込み（Higher-order Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-06-12T14:34:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699895</loc>
  <lastmod>2026-06-12T14:33:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意に基づく視覚解析による多指ロボットハンドの高速把持計画（Attention based visual analysis for fast grasp planning with multi-fingered robotic hand）</news:title>
   <news:publication_date>2026-06-12T14:33:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699893</loc>
  <lastmod>2026-06-12T14:32:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動・個人化・柔軟なプレイリスト生成（AUTOMATIC, PERSONALIZED, AND FLEXIBLE PLAYLIST GENERATION USING REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-06-12T14:32:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699891</loc>
  <lastmod>2026-06-12T14:32:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ連鎖上での確率的勾配法の現実的進化（On Markov Chain Gradient Descent）</news:title>
   <news:publication_date>2026-06-12T14:32:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699889</loc>
  <lastmod>2026-06-12T14:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き最適化を生態学的力学として読み解く（Constrained optimization as ecological dynamics with applications to random quadratic programming in high dimensions）</news:title>
   <news:publication_date>2026-06-12T14:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699887</loc>
  <lastmod>2026-06-12T14:32:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Routine Blood Testsで冠動脈疾患を予測する（Prediction of Coronary Heart Disease Using Routine Blood Tests）</news:title>
   <news:publication_date>2026-06-12T14:32:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699885</loc>
  <lastmod>2026-06-12T13:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル空間制約に基づくラベルノイズ浄化とランダムラベル伝播（Random Label Propagation with Spectral-Spatial Constraints）</news:title>
   <news:publication_date>2026-06-12T13:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699883</loc>
  <lastmod>2026-06-12T13:40:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGを用いた感情認識における脳結合性と空間情報の活用（CONVOLUTIONAL NEURAL NETWORK APPROACH FOR EEG-BASED EMOTION RECOGNITION USING BRAIN CONNECTIVITY AND ITS SPATIAL INFORMATION）</news:title>
   <news:publication_date>2026-06-12T13:40:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699881</loc>
  <lastmod>2026-06-12T13:40:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>飽和した測定からの高速信号復元（Fast Signal Recovery from Saturated Measurements by Linear Loss and Nonconvex Penalties）</news:title>
   <news:publication_date>2026-06-12T13:40:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699879</loc>
  <lastmod>2026-06-12T13:40:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非微分制約を持つ最適化とその応用（Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals）</news:title>
   <news:publication_date>2026-06-12T13:40:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699877</loc>
  <lastmod>2026-06-12T13:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列変数を選ぶ注意機構が切り拓く予測精度の飛躍（Temporal Pattern Attention for Multivariate Time Series Forecasting）</news:title>
   <news:publication_date>2026-06-12T13:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699875</loc>
  <lastmod>2026-06-12T13:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的概日モデルにおける変化点検出（Change-Point Detection on Hierarchical Circadian Models）</news:title>
   <news:publication_date>2026-06-12T13:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699873</loc>
  <lastmod>2026-06-12T13:39:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zoomに学ぶSSD活用ベクトル検索の実務応用（Zoom: SSD-based Vector Search for Optimizing Accuracy, Latency and Memory）</news:title>
   <news:publication_date>2026-06-12T13:39:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699871</loc>
  <lastmod>2026-06-12T12:48:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DISにおけるハドロン最終状態のNNLO QCDとパートンシャワーの統合（Hadronic Final States in DIS at NNLO QCD with Parton Showers）</news:title>
   <news:publication_date>2026-06-12T12:48:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699869</loc>
  <lastmod>2026-06-12T12:48:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度ネットワークで組込み推論を劇的に効率化する（DISCOVERING LOW-PRECISION NETWORKS CLOSE TO FULL-PRECISION NETWORKS FOR EFFICIENT EMBEDDED INFERENCE）</news:title>
   <news:publication_date>2026-06-12T12:48:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699867</loc>
  <lastmod>2026-06-12T12:47:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードディスクの健康度予測における層別摂動型敵対的訓練（Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction）</news:title>
   <news:publication_date>2026-06-12T12:47:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699865</loc>
  <lastmod>2026-06-12T12:46:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Micro-Dictionary Learning and Coding Network（Deep Micro-Dictionary Learning and Coding Network）</news:title>
   <news:publication_date>2026-06-12T12:46:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699863</loc>
  <lastmod>2026-06-12T12:46:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られた学習データからの反復的セグメンテーション（Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease）</news:title>
   <news:publication_date>2026-06-12T12:46:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699861</loc>
  <lastmod>2026-06-12T12:46:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語学とディープラーニングの相互利益（What can linguistics and deep learning contribute to each other?）</news:title>
   <news:publication_date>2026-06-12T12:46:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699859</loc>
  <lastmod>2026-06-12T12:46:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密な画像予測のための効率的なマルチスケールアーキテクチャ探索（Searching for Efficient Multi-Scale Architectures for Dense Image Prediction）</news:title>
   <news:publication_date>2026-06-12T12:46:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699857</loc>
  <lastmod>2026-06-12T11:54:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相情報を失った状態での動的サブスペース追跡（Phaseless Subspace Tracking）</news:title>
   <news:publication_date>2026-06-12T11:54:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699855</loc>
  <lastmod>2026-06-12T11:54:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Leabra7による生物学的に現実的な再帰ニューラルネット実装（Leabra7: a Python package for modeling recurrent, biologically-realistic neural networks）</news:title>
   <news:publication_date>2026-06-12T11:54:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699853</loc>
  <lastmod>2026-06-12T11:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン講座のクリックログ時系列解析が示す学習行動の見える化（Time Series Analysis of Clickstream Logs from Online Courses）</news:title>
   <news:publication_date>2026-06-12T11:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699851</loc>
  <lastmod>2026-06-12T11:54:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型再生可能電源が増えた配電網における同時確率制約の学習による改良（Joint Chance Constraints in AC Optimal Power Flow: Improving Bounds through Learning）</news:title>
   <news:publication_date>2026-06-12T11:54:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699849</loc>
  <lastmod>2026-06-12T11:53:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトマックス温度を上げることで得られる埋め込みの改善（Heated-Up Softmax Embedding）</news:title>
   <news:publication_date>2026-06-12T11:53:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699847</loc>
  <lastmod>2026-06-12T11:53:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドの画像キャプショニングは分布類似性を利用している（End-to-end Image Captioning Exploits Multimodal Distributional Similarity）</news:title>
   <news:publication_date>2026-06-12T11:53:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699845</loc>
  <lastmod>2026-06-12T11:53:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語ベクトル特化の敵対的伝播とゼロショット跨言語転移（Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization）</news:title>
   <news:publication_date>2026-06-12T11:53:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699843</loc>
  <lastmod>2026-06-12T11:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化された賭けメカニズムの設計と意義（Randomized Wagering Mechanisms）</news:title>
   <news:publication_date>2026-06-12T11:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699841</loc>
  <lastmod>2026-06-12T10:52:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>断片画像の再構成を深層学習で行うJigsawNet（JigsawNet: Shredded Image Reassembly using Convolutional Neural Network and Loop-based Composition）</news:title>
   <news:publication_date>2026-06-12T10:52:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699839</loc>
  <lastmod>2026-06-12T10:51:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的言語解釈を学ぶ再帰型モデルの可能性と限界（On Learning Interpreted Languages with Recurrent Models）</news:title>
   <news:publication_date>2026-06-12T10:51:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699837</loc>
  <lastmod>2026-06-12T10:50:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフベース推薦システムへの毒物注入攻撃（Poisoning Attacks to Graph-Based Recommender Systems）</news:title>
   <news:publication_date>2026-06-12T10:50:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699835</loc>
  <lastmod>2026-06-12T10:50:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型弾性イメージングのためのCartesian NNCM（Cartesian Neural Network Constitutive Models for Data-driven Elasticity Imaging）</news:title>
   <news:publication_date>2026-06-12T10:50:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699833</loc>
  <lastmod>2026-06-12T10:50:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間は敵対的画像を解読できる（Deciphering Adversarial Images）</news:title>
   <news:publication_date>2026-06-12T10:50:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699831</loc>
  <lastmod>2026-06-12T10:50:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>厚い星盤（スラブ）が示す外縁部の古い星形成停止の痕跡（The imprint of the thick stellar disc in the mid-plane of three early-type edge-on galaxies in the Fornax cluster）</news:title>
   <news:publication_date>2026-06-12T10:50:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699829</loc>
  <lastmod>2026-06-12T09:58:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタグラフとメタパスを同時に埋め込む手法の本質（Joint Embedding of Meta-Path and Meta-Graph for Heterogeneous Information Networks）</news:title>
   <news:publication_date>2026-06-12T09:58:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699827</loc>
  <lastmod>2026-06-12T09:58:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サービスロボットのワンショット話者識別（One-Shot Speaker Identification for a Service Robot using a CNN-based Generic Verifier）</news:title>
   <news:publication_date>2026-06-12T09:58:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699825</loc>
  <lastmod>2026-06-12T09:58:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cas Aの未衝撃放出物の温度と電離状態（The Temperature and Ionization of Unshocked Ejecta in Cas A）</news:title>
   <news:publication_date>2026-06-12T09:58:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699823</loc>
  <lastmod>2026-06-12T09:57:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列分解型3D畳み込みが変える動画・ボリュームデータ解析（Parallel Separable 3D Convolution for Video and Volumetric Data Understanding）</news:title>
   <news:publication_date>2026-06-12T09:57:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699821</loc>
  <lastmod>2026-06-12T09:57:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PUFとAESを組み合わせた新しい不正アクセス耐性（PUF-AES-PUF: a novel PUF architecture against non-invasive attacks）</news:title>
   <news:publication_date>2026-06-12T09:57:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699819</loc>
  <lastmod>2026-06-12T09:57:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子アルゴリズムによる構造化予測の高速化（Quantum Algorithms for Structured Prediction）</news:title>
   <news:publication_date>2026-06-12T09:57:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699817</loc>
  <lastmod>2026-06-12T09:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みネットワークがフーリエ基底に敏感である構造的理由（On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions）</news:title>
   <news:publication_date>2026-06-12T09:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699815</loc>
  <lastmod>2026-06-12T09:05:45Z</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（z∼2）の光学的に暗いAGNを対象としたイオン化ガス星雲のイメージング分光学（IMAGING SPECTROSCOPY OF IONIZED GASEOUS NEBULAE AROUND OPTICALLY FAINT AGN AT REDSHIFT Z ∼2）</news:title>
   <news:publication_date>2026-06-12T09:05:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699813</loc>
  <lastmod>2026-06-12T09:05:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural-Augmented Static Analysis of Android Communication（Neural-Augmented Static Analysis of Android Communication）</news:title>
   <news:publication_date>2026-06-12T09:05:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699811</loc>
  <lastmod>2026-06-12T09:05:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D畳み込みを用いたアンサンブル学習で機能的コネクトーム予測を強化する（Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction）</news:title>
   <news:publication_date>2026-06-12T09:05:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699809</loc>
  <lastmod>2026-06-12T09:04:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一次元系における単粒子移動端を伴う多体局在の観測（Observation of many-body localization in a one-dimensional system with single-particle mobility edge）</news:title>
   <news:publication_date>2026-06-12T09:04:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699807</loc>
  <lastmod>2026-06-12T09:04:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称単語埋め込みによるテキスト含意の改善（AWE: Asymmetric Word Embedding for Textual Entailment）</news:title>
   <news:publication_date>2026-06-12T09:04:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699805</loc>
  <lastmod>2026-06-12T09:03:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepProteomicsによるタンパク質ファミリー分類（DeepProteomics: Protein family classification using Shallow and Deep Networks）</news:title>
   <news:publication_date>2026-06-12T09:03:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699803</loc>
  <lastmod>2026-06-12T09:03:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超距離標準光源による運動学的宇宙論の現状（Status of kinematic cosmology with SN Ia: JLA, Pantheon and future constraints with LSST）</news:title>
   <news:publication_date>2026-06-12T09:03:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699801</loc>
  <lastmod>2026-06-12T08:12:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>史料刻字（グラフィティ）認識に向けたカプセル深層ニューラルネットワークの応用（Capsule Deep Neural Network for Recognition of Historical Graffiti Handwriting）</news:title>
   <news:publication_date>2026-06-12T08:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699799</loc>
  <lastmod>2026-06-12T08:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率ビット（p-bit）による確率的スピン論理の提案（p-Bits for Probabilistic Spin Logic）</news:title>
   <news:publication_date>2026-06-12T08:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699797</loc>
  <lastmod>2026-06-12T08:12:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GitHub上の「保守されていない」プロジェクトを機械学習で見抜く方法（Identifying Unmaintained Projects in GitHub）</news:title>
   <news:publication_date>2026-06-12T08:12:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699795</loc>
  <lastmod>2026-06-12T08:11:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文の意味的合理性の評価（Evaluating Semantic Rationality of a Sentence: A Sememe-Word-Matching Neural Network based on HowNet）</news:title>
   <news:publication_date>2026-06-12T08:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699793</loc>
  <lastmod>2026-06-12T08:11:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ混入した履歴データを用いるテキスト分類の課題（Training and Prediction Data Discrepancies: Challenges of Text Classification with Noisy, Historical Data）</news:title>
   <news:publication_date>2026-06-12T08:11:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699791</loc>
  <lastmod>2026-06-12T08:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMはバスク語の一致を学べるか（Can LSTM Learn to Capture Agreement? The Case of Basque）</news:title>
   <news:publication_date>2026-06-12T08:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699789</loc>
  <lastmod>2026-06-12T08:11:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>看護記録から感染兆候を検出する自動早期敗血症アラートへの道（Toward Automated Early Sepsis Alerting: Identifying Infection Patients from Nursing Notes）</news:title>
   <news:publication_date>2026-06-12T08:11:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699787</loc>
  <lastmod>2026-06-12T07:20:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>切り取られたデータからの効率的推定（Efficient Statistics, in High Dimensions, from Truncated Samples）</news:title>
   <news:publication_date>2026-06-12T07:20:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699785</loc>
  <lastmod>2026-06-12T07:20:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路車線検出に効率化をもたらす深層学習手法（Efficient Road Lane Marking Detection with Deep Learning）</news:title>
   <news:publication_date>2026-06-12T07:20:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699783</loc>
  <lastmod>2026-06-12T07:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外部攪乱からの回復でロボットの長期自律性を高める方法（Endowing Robots with Longer-term Autonomy by Recovering from External Disturbances in Manipulation through Grounded Anomaly Classification and Recovery Policies）</news:title>
   <news:publication_date>2026-06-12T07:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699781</loc>
  <lastmod>2026-06-12T07:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抽象化学習（Abstraction Learning）</news:title>
   <news:publication_date>2026-06-12T07:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699779</loc>
  <lastmod>2026-06-12T07:19:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子位置に依存しない記述子による材料物性の機械学習（Atomic positions independent descriptor for machine learning of material properties）</news:title>
   <news:publication_date>2026-06-12T07:19:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699777</loc>
  <lastmod>2026-06-12T07:19:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空気汚染予測のための深層推論時空間ネットワーク（Deep Inferential Spatial-Temporal Network for Forecasting Air Pollution Concentrations）</news:title>
   <news:publication_date>2026-06-12T07:19:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699775</loc>
  <lastmod>2026-06-12T07:18:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さな神経回路でロボット制御を再発明する（Can a Compact Neuronal Circuit Policy be Re-purposed to Learn Simple Robotic Control?）</news:title>
   <news:publication_date>2026-06-12T07:18:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699773</loc>
  <lastmod>2026-06-12T06:27:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ガウス過程を用いた効率的全域最適化（EFFICIENT GLOBAL OPTIMIZATION USING DEEP GAUSSIAN PROCESSES）</news:title>
   <news:publication_date>2026-06-12T06:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699771</loc>
  <lastmod>2026-06-12T06:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感覚的人工知能が囲碁に示した新しい方針（SAI, a Sensible Artificial Intelligence that plays Go）</news:title>
   <news:publication_date>2026-06-12T06:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699769</loc>
  <lastmod>2026-06-12T06:18:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定量的手法に関する二相研究が示す課題と示唆（A two-phase study examining perspectives and use of quantitative methods in PER）</news:title>
   <news:publication_date>2026-06-12T06:18:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699767</loc>
  <lastmod>2026-06-12T06:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMセルの応答特性による可視化と監査（Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks）</news:title>
   <news:publication_date>2026-06-12T06:18:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699765</loc>
  <lastmod>2026-06-12T06:18:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脆弱な道路利用者の意図検出と協調知能（Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence）</news:title>
   <news:publication_date>2026-06-12T06:18:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699763</loc>
  <lastmod>2026-06-12T06:17:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EXS: ローカルでモデル非依存な解釈性を用いた説明可能な検索（EXS: Explainable Search Using Local Model Agnostic Interpretability）</news:title>
   <news:publication_date>2026-06-12T06:17:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699761</loc>
  <lastmod>2026-06-12T06:17:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンハラ語の算数問題をニューラルネットワークで解く（Solving Sinhala Language Arithmetic Problems using Neural Networks）</news:title>
   <news:publication_date>2026-06-12T06:17:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699759</loc>
  <lastmod>2026-06-12T05:26:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変分類のためのCNN可視化による診断支援の強化（Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification）</news:title>
   <news:publication_date>2026-06-12T05:26:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699757</loc>
  <lastmod>2026-06-12T05:26:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>危険度を見て切り替える自己航行用DRLエージェントの統合手法（Danger-aware Adaptive Composition of DRL Agents for Self-navigation）</news:title>
   <news:publication_date>2026-06-12T05:26:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699755</loc>
  <lastmod>2026-06-12T05:25:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソース誘導差異に基づく教師なしドメイン適応（Unsupervised Domain Adaptation Based on Source-guided Discrepancy）</news:title>
   <news:publication_date>2026-06-12T05:25:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699753</loc>
  <lastmod>2026-06-12T05:25:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習率適応法によるフェデレーテッド／差分プライバシー学習の改善（Learning Rate Adaptation for Federated and Differentially Private Learning）</news:title>
   <news:publication_date>2026-06-12T05:25:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699751</loc>
  <lastmod>2026-06-12T05:24:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シリーズ弾性アクチュエータを用いたBWSのリアルタイム力制御と2-DOF制御構造（Real-Time Force Control of an SEA-based Body Weight Support Unit with the 2-DOF Control Structure）</news:title>
   <news:publication_date>2026-06-12T05:24:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699749</loc>
  <lastmod>2026-06-12T05:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMとBi-LSTMを用いた血糖値予測の実務的意義（Predicting Blood Glucose with an LSTM and Bi-LSTM Based Deep Neural Network）</news:title>
   <news:publication_date>2026-06-12T05:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699747</loc>
  <lastmod>2026-06-12T05:24:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野球ではなくクリケットの「審判ジェスチャー」検出データセットと予備結果（A Dataset and Preliminary Results for Umpire Pose Detection）</news:title>
   <news:publication_date>2026-06-12T05:24:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699745</loc>
  <lastmod>2026-06-12T04:33:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NGC 4388におけるラム圧剥離の詳細解析（The uneven sisters I: NGC 4388 – a strongly constrained ram pressure stripping event）</news:title>
   <news:publication_date>2026-06-12T04:33:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699743</loc>
  <lastmod>2026-06-12T04:33:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークにおけるマルチタスク学習（Multitask Learning on Graph Neural Networks）</news:title>
   <news:publication_date>2026-06-12T04:33:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699741</loc>
  <lastmod>2026-06-12T04:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホログラフィックにおけるエンタングルメントとQNECの数値検証（Holographic Entanglement Entropy and QNEC Numerical Studies）</news:title>
   <news:publication_date>2026-06-12T04:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699739</loc>
  <lastmod>2026-06-12T04:32:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マンモグラフィにおける微小石灰化のセグメンテーションのための畳み込みニューラルネットワーク（Convolutional Neural Networks for the segmentation of microcalcification in Mammography Imaging）</news:title>
   <news:publication_date>2026-06-12T04:32:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699737</loc>
  <lastmod>2026-06-12T04:32:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互作用ネットワークで模倣する複雑な転位ダイナミクス（Mimicking complex dislocation dynamics by Interaction Networks）</news:title>
   <news:publication_date>2026-06-12T04:32:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699735</loc>
  <lastmod>2026-06-12T04:31:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタイルを持つ画像説明を教師なしで生成する仕組み（Unsupervised Stylish Image Description Generation via Domain Layer Norm）</news:title>
   <news:publication_date>2026-06-12T04:31:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699733</loc>
  <lastmod>2026-06-12T04:31:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一機械スケジューリングにおける時間依存処理時間と学習効果を同時扱いする新しい正確アルゴリズム（A new exact algorithm for solving single machine scheduling problems with learning effects and deteriorating jobs）</news:title>
   <news:publication_date>2026-06-12T04:31:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699731</loc>
  <lastmod>2026-06-12T03:40:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期占有グリッド予測と再帰型ニューラルネットワーク（Long-Term Occupancy Grid Prediction Using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-12T03:40:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699729</loc>
  <lastmod>2026-06-12T03:40:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U-Net学習における正規化が2D生体医用セグメンテーションにもたらす変化（Normalization in Training U-Net for 2D Biomedical Semantic Segmentation）</news:title>
   <news:publication_date>2026-06-12T03:40:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699727</loc>
  <lastmod>2026-06-12T03:39:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られた投影データでのCT再構成に対する確率的アプローチ（Probabilistic approach to limited-data computed tomography reconstruction）</news:title>
   <news:publication_date>2026-06-12T03:39:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699725</loc>
  <lastmod>2026-06-12T03:39:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模マルチエージェントの因子化Q学習（Factorized Q-Learning for Large-Scale Multi-Agent Systems）</news:title>
   <news:publication_date>2026-06-12T03:39:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699723</loc>
  <lastmod>2026-06-12T03:38:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元スカラー関数の可視化と主成分パラメータ化（Visualization of High-dimensional Scalar Functions using Principal Parameterizations）</news:title>
   <news:publication_date>2026-06-12T03:38:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699721</loc>
  <lastmod>2026-06-12T03:38:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在特徴モデルの非同定性を解く（Solving Non-identiﬁable Latent Feature Models）</news:title>
   <news:publication_date>2026-06-12T03:38:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699719</loc>
  <lastmod>2026-06-12T03:38:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動詞は問われているか？深層学習QAにおける動詞の重要性の再評価（Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System）</news:title>
   <news:publication_date>2026-06-12T03:38:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699717</loc>
  <lastmod>2026-06-12T02:47:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化・非構造化外れ値の識別によるパラメータフリーなRobust PCA（Structured and Unstructured Outlier Identification for Robust PCA: A Non iterative, Parameter free Algorithm）</news:title>
   <news:publication_date>2026-06-12T02:47:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699715</loc>
  <lastmod>2026-06-12T02:47:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノード単位で感度を変える非対称ネットワーク（Deep Asymmetric Networks with a Set of Node-wise Variant Activation Functions）</news:title>
   <news:publication_date>2026-06-12T02:47:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699713</loc>
  <lastmod>2026-06-12T02:46:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TSARDI: トランジット光度曲線の残差ノイズを自動検出するアルゴリズム（TSARDI: a Machine Learning data rejection algorithm for transiting exoplanet light curves）</news:title>
   <news:publication_date>2026-06-12T02:46:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699711</loc>
  <lastmod>2026-06-12T02:46:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的な「もしも」質問に答える仕組み（Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions）</news:title>
   <news:publication_date>2026-06-12T02:46:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699709</loc>
  <lastmod>2026-06-12T02:45:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Visual QAにおける細部の罠（The Visual QA Devil in the Details: The Impact of Early Fusion and Batch Norm on CLEVR）</news:title>
   <news:publication_date>2026-06-12T02:45:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699707</loc>
  <lastmod>2026-06-12T02:45:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Bio-LSTM：歩行者の3D姿勢と歩容を予測する生体力学に基づくリカレントニューラルネットワーク（Bio-LSTM: A Biomechanically Inspired Recurrent Neural Network for 3D Pedestrian Pose and Gait Prediction）</news:title>
   <news:publication_date>2026-06-12T02:45:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699705</loc>
  <lastmod>2026-06-12T02:45:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AFM画像の解像度を深層学習で高める方法（General Resolution Enhancement Method in Atomic Force Microscopy (AFM) Using Deep Learning）</news:title>
   <news:publication_date>2026-06-12T02:45:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699703</loc>
  <lastmod>2026-06-12T01:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リマインドによる長期時系列のクレジット配分を実現する手法（Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding）</news:title>
   <news:publication_date>2026-06-12T01:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699701</loc>
  <lastmod>2026-06-12T01:54:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話文脈と潜在トピックの共同モデル（A Joint Model of Conversational Discourse and Latent Topics on Microblogs）</news:title>
   <news:publication_date>2026-06-12T01:54:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699699</loc>
  <lastmod>2026-06-12T01:53:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロモルフィック・スパイキングニューラルネットワークによる時間学習（Tutorial: Neuromorphic spiking neural networks for temporal learning）</news:title>
   <news:publication_date>2026-06-12T01:53:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699697</loc>
  <lastmod>2026-06-12T01:52:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンド線形システムのためのCNNベース信号検出（CNN-Based Signal Detection for Banded Linear Systems）</news:title>
   <news:publication_date>2026-06-12T01:52:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699695</loc>
  <lastmod>2026-06-12T01:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スクリプト学習を隠れマルコフモデルとして捉える（Learning Scripts as Hidden Markov Models）</news:title>
   <news:publication_date>2026-06-12T01:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699693</loc>
  <lastmod>2026-06-12T01:52:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声認識に対する敵対的攻撃検出における音声前処理とアンサンブルの有効性（Isolated and Ensemble Audio Preprocessing Methods for Detecting Adversarial Examples against Automatic Speech Recognition）</news:title>
   <news:publication_date>2026-06-12T01:52:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699691</loc>
  <lastmod>2026-06-12T01:52:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスセクショナル株式リターン予測のための視覚的注意モデルとエンドツーエンドマルチモーダル市場表現学習 (Visual Attention Model for Cross-sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning)</news:title>
   <news:publication_date>2026-06-12T01:52:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699689</loc>
  <lastmod>2026-06-12T01:00:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー興味の時間的進化を捉えるDIEN（Deep Interest Evolution Network for Click-Through Rate Prediction）</news:title>
   <news:publication_date>2026-06-12T01:00:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699687</loc>
  <lastmod>2026-06-12T01:00:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データでロボットの視覚を偏りなく強化する方法（Unbiasing Semantic Segmentation For Robot Perception using Synthetic Data）</news:title>
   <news:publication_date>2026-06-12T01:00:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699685</loc>
  <lastmod>2026-06-12T00:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間空間マッピングによる行動認識（Temporal-Spatial Mapping for Action Recognition）</news:title>
   <news:publication_date>2026-06-12T00:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699683</loc>
  <lastmod>2026-06-12T00:59:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボリックデータ解析の新しい枠組み（New models for symbolic data analysis）</news:title>
   <news:publication_date>2026-06-12T00:59:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699681</loc>
  <lastmod>2026-06-12T00:59:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈依存拡散ネットワークによる視覚関係検出（Context-Dependent Diffusion Network for Visual Relationship Detection）</news:title>
   <news:publication_date>2026-06-12T00:59:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699679</loc>
  <lastmod>2026-06-12T00:59:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間俳優映像のニューラルレンダリングと再演（Neural Rendering and Reenactment of Human Actor Videos）</news:title>
   <news:publication_date>2026-06-12T00:59:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699677</loc>
  <lastmod>2026-06-12T00:58:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマノイドロボットでの深層学習向け計算プラットフォーム比較 (Comparing Computing Platforms for Deep Learning on a Humanoid Robot)</news:title>
   <news:publication_date>2026-06-12T00:58:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699675</loc>
  <lastmod>2026-06-12T00:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸正則化サポートベクターマシンに対する効率的なADMMベースのアルゴリズム（An Efficient ADMM-Based Algorithm to Nonconvex Penalized Support Vector Machines）</news:title>
   <news:publication_date>2026-06-12T00:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699673</loc>
  <lastmod>2026-06-12T00:07:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク行列復元における構造の有効かつ効率的な活用（Exploiting the structure effectively and efficiently in low rank matrix recovery）</news:title>
   <news:publication_date>2026-06-12T00:07:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699671</loc>
  <lastmod>2026-06-12T00:06:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波で嗜好を読み取る――CNNによるマルチメディア嗜好評価の進展（Evaluation of preference of multimedia content using deep neural networks for electroencephalography）</news:title>
   <news:publication_date>2026-06-12T00:06:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699669</loc>
  <lastmod>2026-06-12T00:06:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースの効率的グラフ類似度計算（Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching）</news:title>
   <news:publication_date>2026-06-12T00:06:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699667</loc>
  <lastmod>2026-06-12T00:06:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込み空間の教師なしクロスリンガルトランスファー（Unsupervised Cross-lingual Transfer of Word Embedding Spaces）</news:title>
   <news:publication_date>2026-06-12T00:06:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699665</loc>
  <lastmod>2026-06-12T00:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ManifoldNet——多様体値データのための深層ネットワークフレームワーク（ManifoldNet: A Deep Network Framework for Manifold-valued Data）</news:title>
   <news:publication_date>2026-06-12T00:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699663</loc>
  <lastmod>2026-06-12T00:05:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ClusterGANによる潜在空間クラスタリング（ClusterGAN: Latent Space Clustering in Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-12T00:05:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699661</loc>
  <lastmod>2026-06-11T23:14:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河の固有配向が波長で変わるという発見（The dependence of intrinsic alignment of galaxies on wavelength using KiDS and GAMA）</news:title>
   <news:publication_date>2026-06-11T23:14:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699659</loc>
  <lastmod>2026-06-11T23:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全なインデックス符号化の容量領域について（On the Capacity Region for Secure Index Coding）</news:title>
   <news:publication_date>2026-06-11T23:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699657</loc>
  <lastmod>2026-06-11T23:13:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書のみで学ぶ固有表現タグ付け（Learning Named Entity Tagger using Domain-Specific Dictionary）</news:title>
   <news:publication_date>2026-06-11T23:13:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699655</loc>
  <lastmod>2026-06-11T23:12:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリックベイズ群因子解析のための効率的な崩壊変分推論（Collapsed Variational Inference for Nonparametric Bayesian Group Factor Analysis）</news:title>
   <news:publication_date>2026-06-11T23:12:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699653</loc>
  <lastmod>2026-06-11T23:12:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像公平性を組み込んだ多様性再ランキング（Using Image Fairness Representations in Diversity-Based Re-ranking for Recommendations）</news:title>
   <news:publication_date>2026-06-11T23:12:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699651</loc>
  <lastmod>2026-06-11T23:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PCGMLの根本的緊張に対処する識別学習（Addressing the Fundamental Tension of PCGML with Discriminative Learning）</news:title>
   <news:publication_date>2026-06-11T23:12:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699649</loc>
  <lastmod>2026-06-11T23:11:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GEFCom2017の確率的負荷予測における分位点回帰（Quantile Regression for Qualifying Match of GEFCom2017 Probabilistic Load Forecasting）</news:title>
   <news:publication_date>2026-06-11T23:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699647</loc>
  <lastmod>2026-06-11T22:20:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層時系列辞書学習によるエネルギー分解（Energy Disaggregation via Deep Temporal Dictionary Learning）</news:title>
   <news:publication_date>2026-06-11T22:20:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699645</loc>
  <lastmod>2026-06-11T22:11:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向け深層学習（Deep Learning Towards Mobile Applications）</news:title>
   <news:publication_date>2026-06-11T22:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699643</loc>
  <lastmod>2026-06-11T22:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ケースベース推論をベイズ的に組み立てる手法の実務的解説（Bayesian Patchworks: An Approach to Case-Based Reasoning）</news:title>
   <news:publication_date>2026-06-11T22:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699641</loc>
  <lastmod>2026-06-11T22:11:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Policy Embeddingによる転移強化学習の要点（Variational Policy Embedding for Transfer Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-11T22:11:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699639</loc>
  <lastmod>2026-06-11T21:18:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PRIMAL: 分散学習による実用的なマルチエージェント経路探索（PRIMAL: Pathfinding via Reinforcement and Imitation）</news:title>
   <news:publication_date>2026-06-11T21:18:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699637</loc>
  <lastmod>2026-06-11T21:18:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュース記事の政治的イデオロギー検出の多視点モデル（Multi-view Models for Political Ideology Detection of News Articles）</news:title>
   <news:publication_date>2026-06-11T21:18:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699635</loc>
  <lastmod>2026-06-11T21:17:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師データ不要で「形式化」を制御する文章変換（Unsupervised Controllable Text Formalization）</news:title>
   <news:publication_date>2026-06-11T21:17:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699633</loc>
  <lastmod>2026-06-11T21:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SpRRAMによる事前定義スパースメムリスタ回路で実現する低電力ニューラル推論（SpRRAM: A Predefined Sparsity Based Memristive Neuromorphic Circuit for Low Power Application）</news:title>
   <news:publication_date>2026-06-11T21:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699631</loc>
  <lastmod>2026-06-11T20:25:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理情報支援型クリギング（Physics-Information-Aided Kriging: Constructing Covariance Functions using Stochastic Simulation Models）</news:title>
   <news:publication_date>2026-06-11T20:25:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699629</loc>
  <lastmod>2026-06-11T20:25:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データベース運用の産業的手法と最適化アプローチ（A collection of database industrial techniques and optimization approaches of database operations）</news:title>
   <news:publication_date>2026-06-11T20:25:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699627</loc>
  <lastmod>2026-06-11T20:24:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エキスパート強化型アクタークリティックの実用的インパクト（Expert-augmented actor-critic for ViZDoom and Montezuma’s Revenge）</news:title>
   <news:publication_date>2026-06-11T20:24:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699625</loc>
  <lastmod>2026-06-11T20:23:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆整合性を持つ深層ネットワークによる教師なし変形画像レジストレーション（Inverse-Consistent Deep Networks for Unsupervised Deformable Image Registration）</news:title>
   <news:publication_date>2026-06-11T20:23:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699623</loc>
  <lastmod>2026-06-11T20:23:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠落する経路を補う：語彙意味関係検出のための単語対と依存パスの共起モデル化（Filling Missing Paths: Modeling Co-occurrences of Word Pairs and Dependency Paths for Recognizing Lexical Semantic Relations）</news:title>
   <news:publication_date>2026-06-11T20:23:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699621</loc>
  <lastmod>2026-06-11T20:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>裁判記録における文間関係の特定（Identifying Relationships Among Sentences in Court Case Transcripts using Discourse Relations）</news:title>
   <news:publication_date>2026-06-11T20:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699619</loc>
  <lastmod>2026-06-11T20:23:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルクラウドにおけるプライベート深層学習の性能改善（Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud）</news:title>
   <news:publication_date>2026-06-11T20:23:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699617</loc>
  <lastmod>2026-06-11T19:32:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>想像とヒューリスティックを結合して一般化可能な戦略を学ぶ（Combining imagination and heuristics to learn strategies that generalize）</news:title>
   <news:publication_date>2026-06-11T19:32:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699615</loc>
  <lastmod>2026-06-11T19:31:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見る・尋ねる・推測するを共同で学ぶ研究の本質（Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat）</news:title>
   <news:publication_date>2026-06-11T19:31:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699613</loc>
  <lastmod>2026-06-11T19:31:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タッチ操作で個人認証は可能か（Does Your Phone Know Your Touch?）</news:title>
   <news:publication_date>2026-06-11T19:31:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699611</loc>
  <lastmod>2026-06-11T19:30:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平な機械学習を道徳的に解釈する枠組み（A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity）</news:title>
   <news:publication_date>2026-06-11T19:30:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699609</loc>
  <lastmod>2026-06-11T19:30:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波MIMO-OFDMの動的サブアレイに対する機械学習ベースのハイブリッドプレコーディング（Machine Learning Based Hybrid Precoding for MmWave MIMO-OFDM with Dynamic Subarray）</news:title>
   <news:publication_date>2026-06-11T19:30:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699607</loc>
  <lastmod>2026-06-11T19:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心音の分節と分類におけるマルコフ・スイッチングモデルの応用（A Markov-Switching Model Approach to Heart Sound Segmentation and Classification）</news:title>
   <news:publication_date>2026-06-11T19:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699605</loc>
  <lastmod>2026-06-11T19:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPASS: 火星探査ローバー向け能動的科学探索システム（SPASS: Scientific Prominence Active Search System with Deep Image Captioning Network）</news:title>
   <news:publication_date>2026-06-11T19:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699603</loc>
  <lastmod>2026-06-11T18:38:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WUDSによる高赤方偏移銀河の近赤外サーベイが示す要点（The WIRCam Ultra Deep Survey (WUDS): survey overview and UV luminosity functions at z∼5–6）</news:title>
   <news:publication_date>2026-06-11T18:38:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699601</loc>
  <lastmod>2026-06-11T18:37:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的バイナリニューラルネットワークの実用性と経営判断への示唆（Probabilistic Binary Neural Networks）</news:title>
   <news:publication_date>2026-06-11T18:37:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699599</loc>
  <lastmod>2026-06-11T18:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Torchbearer：PyTorch向けモデルフィッティングライブラリの設計と実装（Torchbearer: A Model Fitting Library for PyTorch）</news:title>
   <news:publication_date>2026-06-11T18:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699597</loc>
  <lastmod>2026-06-11T18:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙に広がる拡散ラジオ源の深層学習による検出（Deep Learning Based Detection of Cosmological Diffuse Radio Sources）</news:title>
   <news:publication_date>2026-06-11T18:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699595</loc>
  <lastmod>2026-06-11T18:36:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化境界を機械学習で改善する：決定図と深層強化学習の出会い（Improving Optimization Bounds Using Machine Learning: Decision Diagrams Meet Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-11T18:36:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699593</loc>
  <lastmod>2026-06-11T18:36:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ズーム学習：サリエンシーに基づくサンプリング層（Learning to Zoom: a Saliency-Based Sampling Layer for Neural Networks）</news:title>
   <news:publication_date>2026-06-11T18:36:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699591</loc>
  <lastmod>2026-06-11T18:35:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>xSenseによる説明可能な単語意味表現の学習（xSense: Learning Sense-Separated Sparse Representations and Textual Definitions for Explainable Word Sense Networks）</news:title>
   <news:publication_date>2026-06-11T18:35:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699589</loc>
  <lastmod>2026-06-11T17:44:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ決定過程の到達確率検証におけるMCTS応用（Monte Carlo Tree Search for Verifying Reachability in Markov Decision Processes）</news:title>
   <news:publication_date>2026-06-11T17:44:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699587</loc>
  <lastmod>2026-06-11T17:44:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界カラー画像のノイズ除去に関する簡潔なレビュー（A Brief Review of Real-World Color Image Denoising）</news:title>
   <news:publication_date>2026-06-11T17:44:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699585</loc>
  <lastmod>2026-06-11T17:43:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>把持成功の予測と品質指標（Grasp success prediction with quality metrics）</news:title>
   <news:publication_date>2026-06-11T17:43:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699583</loc>
  <lastmod>2026-06-11T17:42:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み伝送によるプライバシー保護型深層学習（Privacy-Preserving Deep Learning via Weight Transmission）</news:title>
   <news:publication_date>2026-06-11T17:42:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699581</loc>
  <lastmod>2026-06-11T17:42:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的手法による深層畳み込みニューラルネットワークのトポロジ探索（Finding Better Topologies for Deep Convolutional Neural Networks by Evolution）</news:title>
   <news:publication_date>2026-06-11T17:42:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699579</loc>
  <lastmod>2026-06-11T17:42:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再生成による分類の原理と実践（Classification by Re-generation—Towards Classification Based on Variational Inference）</news:title>
   <news:publication_date>2026-06-11T17:42:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699577</loc>
  <lastmod>2026-06-11T17:42:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相を用いた動き表現による行動認識の再考（Using phase instead of optical flow for action recognition）</news:title>
   <news:publication_date>2026-06-11T17:42:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699575</loc>
  <lastmod>2026-06-11T16:50:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多文脈深層ネットワークによる前眼部OCTを用いた閉塞隅角緑内障スクリーニング（Multi-Context Deep Network for Angle-Closure Glaucoma Screening in Anterior Segment OCT）</news:title>
   <news:publication_date>2026-06-11T16:50:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699573</loc>
  <lastmod>2026-06-11T16:50:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光で駆動する軟らかいマイクロロボットの歩行学習（Gait learning for soft microrobots controlled by light fields）</news:title>
   <news:publication_date>2026-06-11T16:50:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699571</loc>
  <lastmod>2026-06-11T16:50:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトなセマンティック状態を用いた深層強化学習による自律走行の適応的行動生成 (Adaptive Behavior Generation for Autonomous Driving using Deep Reinforcement Learning with Compact Semantic States)</news:title>
   <news:publication_date>2026-06-11T16:50:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699569</loc>
  <lastmod>2026-06-11T16:49:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列知識グラフ補完の系列エンコーダ学習（Learning Sequence Encoders for Temporal Knowledge Graph Completion）</news:title>
   <news:publication_date>2026-06-11T16:49:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699567</loc>
  <lastmod>2026-06-11T16:49:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択バイアスを考慮したPositive-Unlabeled学習の拡張（Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled Data）</news:title>
   <news:publication_date>2026-06-11T16:49:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699565</loc>
  <lastmod>2026-06-11T16:49:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話文脈とドメイン知識を取り込む応答選択の改良（Improving Response Selection in Multi-turn Dialogue Systems by Incorporating Domain Knowledge）</news:title>
   <news:publication_date>2026-06-11T16:49:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699563</loc>
  <lastmod>2026-06-11T16:48:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語からの構造化クエリ生成を間接監督で学ぶ（Learning to Generate Structured Queries from Natural Language with Indirect Supervision）</news:title>
   <news:publication_date>2026-06-11T16:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699561</loc>
  <lastmod>2026-06-11T15:57:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインディスプレイ広告におけるインプレッション配分のマルチエージェント強化学習法（A Multi-Agent Reinforcement Learning Method for Impression Allocation in Online Display Advertising）</news:title>
   <news:publication_date>2026-06-11T15:57:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699559</loc>
  <lastmod>2026-06-11T15:49:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みニューラルネットワーク時代の物体検出研究の到達点（Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-11T15:49:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699557</loc>
  <lastmod>2026-06-11T15:49:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-11T15:49:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699555</loc>
  <lastmod>2026-06-11T15:49:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期多発性硬化症の白質病変セグメンテーションにおける浅層学習と深層学習の比較（Shallow vs deep learning architectures for white matter lesion segmentation in the early stages of multiple sclerosis）</news:title>
   <news:publication_date>2026-06-11T15:49:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699553</loc>
  <lastmod>2026-06-11T15:47:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-11T15:47:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699551</loc>
  <lastmod>2026-06-11T15:47:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>稀な語の翻訳を一度で学習する枠組み（Towards one-shot learning for rare-word translation with external experts）</news:title>
   <news:publication_date>2026-06-11T15:47:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699549</loc>
  <lastmod>2026-06-11T15:47:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間依存選択の学習（Learning Time Dependent Choice）</news:title>
   <news:publication_date>2026-06-11T15:47:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699547</loc>
  <lastmod>2026-06-11T14:54:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習でラベル順序依存を減らすシーケンス→集合モデル（A Deep Reinforced Sequence-to-Set Model for Multi-Label Text Classification）</news:title>
   <news:publication_date>2026-06-11T14:54:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699545</loc>
  <lastmod>2026-06-11T14:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による適応的ディスプレイ露出制御（Learning Adaptive Display Exposure for Real-Time Advertising）</news:title>
   <news:publication_date>2026-06-11T14:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699543</loc>
  <lastmod>2026-06-11T14:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>構造的事前情報を用いた深層MR画像超解像（DEEP MR IMAGE SUPER-RESOLUTION USING STRUCTURAL PRIORS）</news:title>
   <news:publication_date>2026-06-11T14:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/699541</loc>
  <lastmod>2026-06-11T14:46:19Z</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>2026-06-11T14:46:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/699539</loc>
  <lastmod>2026-06-11T14:45:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LensKit for Python（LensKit for Python: Next-Generation Software for Recommender Systems Experiments）</news:title>
   <news:publication_date>2026-06-11T14:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699537</loc>
  <lastmod>2026-06-11T14:45:24Z</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「断熱時間スケール」に迫る（Approaching the adiabatic timescale with machine-learning）</news:title>
   <news:publication_date>2026-06-11T14:45:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699535</loc>
  <lastmod>2026-06-11T14:44:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tracking by Animation: 動画からの教師なしマルチオブジェクト追跡の実務的解説（Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers）</news:title>
   <news:publication_date>2026-06-11T14:44:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699533</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>2026-06-11T13:53:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699531</loc>
  <lastmod>2026-06-11T13:53:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元深層学習の近似と推定（Approximation and Estimation for High-Dimensional Deep Learning Networks）</news:title>
   <news:publication_date>2026-06-11T13:53:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699529</loc>
  <lastmod>2026-06-11T13:52:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報を持つ右コングルエンスを持つ正規ω言語（Regular ω-Languages with an Informative Right Congruence）</news:title>
   <news:publication_date>2026-06-11T13:52:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699527</loc>
  <lastmod>2026-06-11T13:51:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンディットフィードバックからの効率的な反事実学習（Efficient Counterfactual Learning from Bandit Feedback）</news:title>
   <news:publication_date>2026-06-11T13:51:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699525</loc>
  <lastmod>2026-06-11T13:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次意思決定と拡張形ゲームのオンライン凸最適化（Online Convex Optimization for Sequential Decision Processes and Extensive-Form Games）</news:title>
   <news:publication_date>2026-06-11T13:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699523</loc>
  <lastmod>2026-06-11T13:51:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味論における深層学習の提言（A case for deep learning in semantics）</news:title>
   <news:publication_date>2026-06-11T13:51:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699521</loc>
  <lastmod>2026-06-11T13:51:10Z</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>2026-06-11T13:51:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699519</loc>
  <lastmod>2026-06-11T12:59:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間変化するゲームにおけるマルチエージェントオンライン学習の振る舞い（MULTI-AGENT ONLINE LEARNING IN TIME-VARYING GAMES）</news:title>
   <news:publication_date>2026-06-11T12:59:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699517</loc>
  <lastmod>2026-06-11T12:58:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集中の呪いが示す堅牢学習の限界（The Curse of Concentration in Robust Learning）</news:title>
   <news:publication_date>2026-06-11T12:58:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699515</loc>
  <lastmod>2026-06-11T12:57:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-11T12:57:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699513</loc>
  <lastmod>2026-06-11T12:57:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話と注意機構で皮肉を見抜く技術（Attentional Multi-Reading Sarcasm Detection）</news:title>
   <news:publication_date>2026-06-11T12:57:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699511</loc>
  <lastmod>2026-06-11T12:57:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベースラインを用いたモンテカルロ反事実後悔最小化における分散削減（Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games using Baselines）</news:title>
   <news:publication_date>2026-06-11T12:57:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699509</loc>
  <lastmod>2026-06-11T12:56:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多語表現（MWE）識別の汎化力を高めたニューラル手法（Neural Multiword Expression Tagging with High Generalisation）</news:title>
   <news:publication_date>2026-06-11T12:56:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699507</loc>
  <lastmod>2026-06-11T12:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配スケッチによる分散削減（SEGA: Variance Reduction via Gradient Sketching）</news:title>
   <news:publication_date>2026-06-11T12:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699505</loc>
  <lastmod>2026-06-11T12:04:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>FRB 121102のパルス検出と周期性解析（FAST RADIO BURST 121102 PULSE DETECTION AND PERIODICITY: A MACHINE LEARNING APPROACH）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699503</loc>
  <lastmod>2026-06-11T11:56:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TextContourNetによるシーン文字検出の改良（TextContourNet: a Flexible and Effective Framework for Improving Scene Text Detection Architecture with a Multi-task Cascade）</news:title>
   <news:publication_date>2026-06-11T11:56:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699501</loc>
  <lastmod>2026-06-11T11:55:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>距離保存型グラフ・ラプラシアンの次元削減とクラスター解析（Distance Preserving Model Order Reduction of Graph-Laplacians and Cluster Analysis）</news:title>
   <news:publication_date>2026-06-11T11:55:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699499</loc>
  <lastmod>2026-06-11T11:55:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化反復法によるフィッシャー判別分析の高速化（Randomized Iterative Algorithms for Fisher Discriminant Analysis）</news:title>
   <news:publication_date>2026-06-11T11:55:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699497</loc>
  <lastmod>2026-06-11T11:54:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値データの反復分類法が切り拓く現場活用（An iterative method for classification of binary data）</news:title>
   <news:publication_date>2026-06-11T11:54:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699495</loc>
  <lastmod>2026-06-11T11:54:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路のひび割れとポットホール検出の自律手法（Crack-pot: Autonomous Road Crack and Pothole Detection）</news:title>
   <news:publication_date>2026-06-11T11:54:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699493</loc>
  <lastmod>2026-06-11T11:54:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>FiLMモデルの理解度と限界（How clever is the FiLM model, and how clever can it be?）</news:title>
   <news:publication_date>2026-06-11T11:54:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/699491</loc>
  <lastmod>2026-06-11T11:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配降下法が非線形活性化を持つ状態方程式を学習する（Stochastic Gradient Descent Learns State Equations with Nonlinear Activations）</news:title>
   <news:publication_date>2026-06-11T11:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-11T11:02:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>銀ナノ粒子密度で極性が切り替わるβ-ガリウム酸化物の自己駆動型ソーラーブラインド光検出器（Silver plasmonic density tuned polarity switching and anomalous behaviour of high performance self-powered β-gallium oxide solar-blind photodetector）</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>弾力的需要を活用した需要予測の精度改善（Leveraging Elastic Demand for Forecasting）</news:title>
   <news:publication_date>2026-06-11T11:01:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699485</loc>
  <lastmod>2026-06-11T11:00:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検証を早くするための訓練法（TRAINING FOR FASTER ADVERSARIAL ROBUSTNESS VERIFICATION VIA INDUCING RELU STABILITY）</news:title>
   <news:publication_date>2026-06-11T11:00:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699483</loc>
  <lastmod>2026-06-11T11:00:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置情報を用いたミリ波ビーム訓練のオンライン学習（Online Learning for Position-Aided Millimeter Wave Beam Training）</news:title>
   <news:publication_date>2026-06-11T11:00:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699481</loc>
  <lastmod>2026-06-11T11:00:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習の誤差指標の体系化と実務的意義（Performance Metrics (Error Measures) in Machine Learning Regression, Forecasting and Prognostics: Properties and Typology）</news:title>
   <news:publication_date>2026-06-11T11:00:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699479</loc>
  <lastmod>2026-06-11T11:00:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話生成モデルは文の構成と談話構造を学べるか（Can Neural Generators for Dialogue Learn Sentence Planning and Discourse Structuring?）</news:title>
   <news:publication_date>2026-06-11T11:00:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699477</loc>
  <lastmod>2026-06-11T10:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔形状を考慮した顔画像の補完と編集（Geometry-Aware Face Completion and Editing）</news:title>
   <news:publication_date>2026-06-11T10:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699475</loc>
  <lastmod>2026-06-11T10:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像から透水性を読む：畳み込みニューラルネットワークによる高速予測（Seeing Permeability From Images: Fast Prediction with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-11T10:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699473</loc>
  <lastmod>2026-06-11T10:08:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LS-Netが切り拓く非線形最小二乗の学習的最適化（LS-Net: Learning to Solve Nonlinear Least Squares for Monocular Stereo）</news:title>
   <news:publication_date>2026-06-11T10:08:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699471</loc>
  <lastmod>2026-06-11T10:07:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Approximation Error in Non-negative Matrix Factorization（Variational Approximation Error in Non-negative Matrix Factorization）</news:title>
   <news:publication_date>2026-06-11T10:07:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699469</loc>
  <lastmod>2026-06-11T10:07:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セルラー環境下のUAV軌道設計に強化学習を使う意義（Reinforcement Learning for Decentralized Trajectory Design in Cellular UAV Networks with Sense-and-Send Protocol）</news:title>
   <news:publication_date>2026-06-11T10:07:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699467</loc>
  <lastmod>2026-06-11T10:06:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セル・オートマトンを畳み込みニューラルネットワークとして表現する（Cellular automata as convolutional neural networks）</news:title>
   <news:publication_date>2026-06-11T10:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699465</loc>
  <lastmod>2026-06-11T10:06:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠隔医療向け自動斜視検出（Automated Strabismus Detection for Telemedicine Applications）</news:title>
   <news:publication_date>2026-06-11T10:06:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699463</loc>
  <lastmod>2026-06-11T09:14:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮想から現実へ──確率的相互状況認識と予測（Generic Probabilistic Interactive Situation Recognition and Prediction: From Virtual to Real）</news:title>
   <news:publication_date>2026-06-11T09:14:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699461</loc>
  <lastmod>2026-06-11T09:14:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的逆強化学習による相互運転行動の確率的予測 (Probabilistic Prediction of Interactive Driving Behavior via Hierarchical Inverse Reinforcement Learning)</news:title>
   <news:publication_date>2026-06-11T09:14:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699459</loc>
  <lastmod>2026-06-11T09:14:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプル効率と報酬バイアスを同時に解決する方法（Discriminator-Actor-Critic）</news:title>
   <news:publication_date>2026-06-11T09:14:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699457</loc>
  <lastmod>2026-06-11T09:12:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問応答データセットを推論データに変換する手法（Transforming Question Answering Datasets Into Natural Language Inference Datasets）</news:title>
   <news:publication_date>2026-06-11T09:12:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699455</loc>
  <lastmod>2026-06-11T09:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルツハイマー病の二値分類におけるsMRIと深層学習（Binary Classification of Alzheimer’s Disease using sMRI Imaging modality and Deep Learning）</news:title>
   <news:publication_date>2026-06-11T09:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699453</loc>
  <lastmod>2026-06-11T09:12:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ効率の高いブラックボックス攻撃：入力フリーの視点（Towards Query Efficient Black-box Attacks: An Input-free Perspective）</news:title>
   <news:publication_date>2026-06-11T09:12:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699451</loc>
  <lastmod>2026-06-11T09:12:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>食品画像の状態識別を小データで可能にした転移学習の実践（Fine-Tuning VGG Neural Network For Fine-grained State Recognition of Food Images）</news:title>
   <news:publication_date>2026-06-11T09:12:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699449</loc>
  <lastmod>2026-06-11T08:20:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震位相の結びつけを深層学習で行うPhaseLink（PhaseLink: A Deep Learning Approach to Seismic Phase Association）</news:title>
   <news:publication_date>2026-06-11T08:20:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699447</loc>
  <lastmod>2026-06-11T08:19:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コスト感度を取り入れた能動学習による頭部CT出血検出（Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection）</news:title>
   <news:publication_date>2026-06-11T08:19:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699445</loc>
  <lastmod>2026-06-11T08:19:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム偽装顔認識のための教師あり学習手法（A Supervised Learning Methodology for Real-Time Disguised Face Recognition in the Wild）</news:title>
   <news:publication_date>2026-06-11T08:19:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699443</loc>
  <lastmod>2026-06-11T08:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トラッケルト協調による教師なし人物再識別（Unsupervised Person Re-identification by Deep Learning Tracklet Association）</news:title>
   <news:publication_date>2026-06-11T08:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699441</loc>
  <lastmod>2026-06-11T08:18:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>攻撃が“転移”する理由 ― 侵入と毒殺攻撃の伝播性の解明（Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks）</news:title>
   <news:publication_date>2026-06-11T08:18:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699439</loc>
  <lastmod>2026-06-11T08:18:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的逐次学習者の機械教授（Machine Teaching of Active Sequential Learners）</news:title>
   <news:publication_date>2026-06-11T08:18:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699437</loc>
  <lastmod>2026-06-11T08:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン適応法、普遍性と加速（Online Adaptive Methods, Universality and Acceleration）</news:title>
   <news:publication_date>2026-06-11T08:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699435</loc>
  <lastmod>2026-06-11T07:26:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的に相互作用するElastic Netによる最も情報量の多い特徴抽出（Identifying The Most Informative Features Using A Structurally Interacting Elastic Net）</news:title>
   <news:publication_date>2026-06-11T07:26:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699433</loc>
  <lastmod>2026-06-11T07:26:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PMUデータを用いたリアルタイム過渡安定性評価へのEOS-ELMとBinary Jaya特徴選択の適用（Application of EOS-ELM with Binary Jaya-Based Feature Selection to Real-Time Transient Stability Assessment Using PMU Data）</news:title>
   <news:publication_date>2026-06-11T07:26:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699431</loc>
  <lastmod>2026-06-11T07:25:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ELMと改良アントマイナーによる過渡安定性評価のルール抽出（Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment）</news:title>
   <news:publication_date>2026-06-11T07:25:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699429</loc>
  <lastmod>2026-06-11T07:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路品質情報を組み込む動的経路計画（iDriveSense: Dynamic Route Planning Involving Roads Quality Information）</news:title>
   <news:publication_date>2026-06-11T07:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699427</loc>
  <lastmod>2026-06-11T07:24:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍法で解釈するニューラルネットワーク（Interpreting Neural Networks With Nearest Neighbors）</news:title>
   <news:publication_date>2026-06-11T07:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699425</loc>
  <lastmod>2026-06-11T07:24:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計測率可変型ニューラルネットワークによる空間マルチプレクサ（Rate-Adaptive Neural Networks for Spatial Multiplexers）</news:title>
   <news:publication_date>2026-06-11T07:24:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699423</loc>
  <lastmod>2026-06-11T07:23:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インターネット動画から学ぶスポーツ用カメラ選択（Learning Sports Camera Selection from Internet Videos）</news:title>
   <news:publication_date>2026-06-11T07:23:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699421</loc>
  <lastmod>2026-06-11T06:32:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチGPU環境におけるモデル並列化による効率的かつ頑健なDNN訓練（Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform）</news:title>
   <news:publication_date>2026-06-11T06:32:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699419</loc>
  <lastmod>2026-06-11T06:32:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タイプIIケフェイドにおける多様な力学現象（Diversity of dynamical phenomena in type II Cepheids of the OGLE collection）</news:title>
   <news:publication_date>2026-06-11T06:32:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699417</loc>
  <lastmod>2026-06-11T06:31:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル誘導制約論理プログラミングによるプログラム合成（Neural Guided Constraint Logic Programming for Program Synthesis）</news:title>
   <news:publication_date>2026-06-11T06:31:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699415</loc>
  <lastmod>2026-06-11T06:31:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインニュースにおける利用者反応のマルチラベル分類（Multi-label Classification of User Reactions in Online News）</news:title>
   <news:publication_date>2026-06-11T06:31:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699413</loc>
  <lastmod>2026-06-11T06:31:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリック変分推論とグラフ畳み込みによるガウス過程（Non-Parametric Variational Inference with Graph Convolutional Networks for Gaussian Processes）</news:title>
   <news:publication_date>2026-06-11T06:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699411</loc>
  <lastmod>2026-06-11T06:31:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュース記事から都市間の意味的関連性を抽出する方法（Extracting and Analyzing Semantic Relatedness between Cities Using News Articles）</news:title>
   <news:publication_date>2026-06-11T06:31:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699409</loc>
  <lastmod>2026-06-11T06:31:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Context-Free Transductions with Neural Stacks（Context-Free Transductions with Neural Stacks）</news:title>
   <news:publication_date>2026-06-11T06:31:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699407</loc>
  <lastmod>2026-06-11T05:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビルクホフダイヤモンドの二重役割（The Birkhoff Diamond as Double Agent）</news:title>
   <news:publication_date>2026-06-11T05:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699405</loc>
  <lastmod>2026-06-11T05:39:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像に映る煙を深層顕著性で検出する（Video Smoke Detection Based on Deep Saliency Network）</news:title>
   <news:publication_date>2026-06-11T05:39:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699403</loc>
  <lastmod>2026-06-11T05:39:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル再利用による概念ドリフトの扱い（Handling Concept Drift via Model Reuse）</news:title>
   <news:publication_date>2026-06-11T05:39:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699401</loc>
  <lastmod>2026-06-11T05:38:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界指標を用いた注目型意味役割付与（Attentive Semantic Role Labeling with Boundary Indicator）</news:title>
   <news:publication_date>2026-06-11T05:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699399</loc>
  <lastmod>2026-06-11T05:38:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト理解のための明示的文脈セマンティクス（Explicit Contextual Semantics for Text Comprehension）</news:title>
   <news:publication_date>2026-06-11T05:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699397</loc>
  <lastmod>2026-06-11T05:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAVによる地形モニタリング向け情報指向経路計画フレームワーク（An informative path planning framework for UAV-based terrain monitoring）</news:title>
   <news:publication_date>2026-06-11T05:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699395</loc>
  <lastmod>2026-06-11T05:37:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク埋め込みに対する高速勾配攻撃（Fast Gradient Attack on Network Embedding）</news:title>
   <news:publication_date>2026-06-11T05:37:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699393</loc>
  <lastmod>2026-06-11T04:46:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造を保つ変換による多様で転送可能な敵対的例の生成（Structure-Preserving Transformation: Generating Diverse and Transferable Adversarial Examples）</news:title>
   <news:publication_date>2026-06-11T04:46:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699391</loc>
  <lastmod>2026-06-11T04:46:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像鑑識のための敵対的学習とAtrous畳み込みを用いた深度マッチング（Adversarial Learning for Image Forensics Deep Matching with Atrous Convolution）</news:title>
   <news:publication_date>2026-06-11T04:46:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699389</loc>
  <lastmod>2026-06-11T04:45:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンスベースの深層転移学習（Instance-based Deep Transfer Learning）</news:title>
   <news:publication_date>2026-06-11T04:45:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699387</loc>
  <lastmod>2026-06-11T04:44:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマン・イン・ザ・ループにおける“弱い制御”の提案（“Weak” Control for Human-in-the-loop Systems）</news:title>
   <news:publication_date>2026-06-11T04:44:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699385</loc>
  <lastmod>2026-06-11T04:44:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アキレス腱断裂のリハビリ予後を同時に補完と予測する確率的手法（Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation）</news:title>
   <news:publication_date>2026-06-11T04:44:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699383</loc>
  <lastmod>2026-06-11T04:44:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像で説明できる単語表現の探求（Exploration on Grounded Word Embedding: Matching Words and Images with Image-Enhanced Skip-Gram Model）</news:title>
   <news:publication_date>2026-06-11T04:44:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699381</loc>
  <lastmod>2026-06-11T04:43:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合統計推定法による相互情報量推定と情報流の解析（Hybrid Statistical Estimation of Mutual Information and its Application to Information Flow）</news:title>
   <news:publication_date>2026-06-11T04:43:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699379</loc>
  <lastmod>2026-06-11T03:52:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超高輝度超新星 SN 2015bn のX線非検出が示す「失われたエネルギー」問題（Where is the engine hiding its missing energy?）</news:title>
   <news:publication_date>2026-06-11T03:52:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699377</loc>
  <lastmod>2026-06-11T03:52:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響反響を取り除き音声認証を強化する二重ラベル深層LSTM（Dual-label Deep LSTM Dereverberation for Speaker Verification）</news:title>
   <news:publication_date>2026-06-11T03:52:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699375</loc>
  <lastmod>2026-06-11T03:51:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>千日間のSN 2015bnが示すマグネター駆動の兆候（One thousand days of SN 2015bn: HST imaging shows a light curve flattening consistent with magnetar predictions）</news:title>
   <news:publication_date>2026-06-11T03:51:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699373</loc>
  <lastmod>2026-06-11T03:50:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子ハイパーグラフ文法による分子最適化（Molecular Hypergraph Grammar with Its Application to Molecular Optimization）</news:title>
   <news:publication_date>2026-06-11T03:50:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699371</loc>
  <lastmod>2026-06-11T03:50:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネステッド・ダイコトミーの較正が大規模多クラスで果たす役割（On the Calibration of Nested Dichotomies for Large Multiclass Tasks）</news:title>
   <news:publication_date>2026-06-11T03:50:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699369</loc>
  <lastmod>2026-06-11T03:50:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの実世界点群生成（RealPoint3D: Point Cloud Generation from a Single Image with Complex Background）</news:title>
   <news:publication_date>2026-06-11T03:50:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699367</loc>
  <lastmod>2026-06-11T03:49:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RF駆動アンビエントバックキャッターの動的スペクトラム利用とオンライン強化学習（Optimal and Low-Complexity Dynamic Spectrum Access for RF-Powered Ambient Backscatter System with Online Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-11T03:49:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699365</loc>
  <lastmod>2026-06-11T02:58:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入れ子二分法アンサンブルの複数部分集合評価（Ensembles of Nested Dichotomies with Multiple Subset Evaluation）</news:title>
   <news:publication_date>2026-06-11T02:58:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699363</loc>
  <lastmod>2026-06-11T02:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習型画像圧縮における自己回帰と階層的事前分布の併用による飛躍的改善（Joint Autoregressive and Hierarchical Priors for Learned Image Compression）</news:title>
   <news:publication_date>2026-06-11T02:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699361</loc>
  <lastmod>2026-06-11T02:57:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可逆（Invertible）なデコーダを利用した教師なし文表現学習（Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning）</news:title>
   <news:publication_date>2026-06-11T02:57:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699359</loc>
  <lastmod>2026-06-11T02:57:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークによる電子密度とエネルギーの高速予測（Deep Neural Network Computes Electron Densities and Energies of a Large Set of Organic Molecules Faster than Density Functional Theory）</news:title>
   <news:publication_date>2026-06-11T02:57:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699357</loc>
  <lastmod>2026-06-11T02:56:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習でNP完全問題を解く：決定版TSPのためのグラフニューラルネットワーク (Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP)</news:title>
   <news:publication_date>2026-06-11T02:56:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699355</loc>
  <lastmod>2026-06-11T02:56:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境での差分プライバシー付き置換なし確率的勾配降下法（Decentralized Differentially Private Without-Replacement Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-06-11T02:56:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699353</loc>
  <lastmod>2026-06-11T02:55:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Coupled IGMM-GANsによる深層多峰性異常検知（Coupled IGMM-GANs for deep multimodal anomaly detection in human mobility data）</news:title>
   <news:publication_date>2026-06-11T02:55:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699351</loc>
  <lastmod>2026-06-11T02:05:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DensSiamが変えたトラッキングの常識 — 密結合と自己注意で精度と速度を両立する （DensSiam: End-to-End Densely-Siamese Network with Self-Attention Model for Object Tracking）</news:title>
   <news:publication_date>2026-06-11T02:05:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699349</loc>
  <lastmod>2026-06-11T02:04:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模行動集合グラフ上のバンディット（BLAG: Bandit on Large Action Set Graph）</news:title>
   <news:publication_date>2026-06-11T02:04:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699347</loc>
  <lastmod>2026-06-11T02:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークにおける辺特徴の活用（Exploiting Edge Features in Graph Neural Networks）</news:title>
   <news:publication_date>2026-06-11T02:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699345</loc>
  <lastmod>2026-06-11T02:03:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的に発火するアームを伴う組合せ多腕バンディットに対するThompson Samplingの解析（Thompson Sampling for Combinatorial Multi-armed Bandit with Probabilistically Triggered Arms）</news:title>
   <news:publication_date>2026-06-11T02:03:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699343</loc>
  <lastmod>2026-06-11T02:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移住をサブモジュラー最適化として扱う（Migration as Submodular Optimization）</news:title>
   <news:publication_date>2026-06-11T02:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699341</loc>
  <lastmod>2026-06-11T02:03:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム学習者成績予測とドメイン適応（GritNet 2: Real-Time Student Performance Prediction with Domain Adaptation）</news:title>
   <news:publication_date>2026-06-11T02:03:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699339</loc>
  <lastmod>2026-06-11T02:02:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック一貫性を訓練目標に組み込む手法（Coherence-Aware Neural Topic Modeling）</news:title>
   <news:publication_date>2026-06-11T02:02:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699337</loc>
  <lastmod>2026-06-11T01:11:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ類似度評価を変える手法：Return Probabilityに基づくGraph Kernel（RetGK: Graph Kernels based on Return Probabilities of Random Walks）</news:title>
   <news:publication_date>2026-06-11T01:11:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699335</loc>
  <lastmod>2026-06-11T01:11:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的グラフ埋め込みでネットワークの時間変化をつかむ（dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning）</news:title>
   <news:publication_date>2026-06-11T01:11:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699333</loc>
  <lastmod>2026-06-11T01:11:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知資源の動的モデルが示すテスト中のパフォーマンス変化（Model of Cognitive Dynamics Predicts Performance on Standardized Tests）</news:title>
   <news:publication_date>2026-06-11T01:11:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699331</loc>
  <lastmod>2026-06-11T01:10:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし文章圧縮：ノイズ除去オートエンコーダによるアプローチ (Unsupervised Sentence Compression using Denoising Auto-Encoders)</news:title>
   <news:publication_date>2026-06-11T01:10:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699329</loc>
  <lastmod>2026-06-11T01:10:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照画像による検証を伴う分類（Are You Sure You Want To Do That? Classification with Verification）</news:title>
   <news:publication_date>2026-06-11T01:10:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699327</loc>
  <lastmod>2026-06-11T01:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習可能なデータベース向け自然言語インタフェース（A Transfer-Learnable Natural Language Interface for Databases）</news:title>
   <news:publication_date>2026-06-11T01:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699325</loc>
  <lastmod>2026-06-11T01:09:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様な質問のニューラル生成（Neural Generation of Diverse Questions using Answer Focus, Contextual and Linguistic Features）</news:title>
   <news:publication_date>2026-06-11T01:09:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699323</loc>
  <lastmod>2026-06-11T00:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Unityを用いた汎用的知能エージェントプラットフォーム（Unity: A General Platform for Intelligent Agents）</news:title>
   <news:publication_date>2026-06-11T00:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699321</loc>
  <lastmod>2026-06-11T00:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的に妥当なグラフの制約付き生成を実現する正則化VAE（Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders）</news:title>
   <news:publication_date>2026-06-11T00:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699319</loc>
  <lastmod>2026-06-11T00:18:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同次線形偏微分方程式のための量子アルゴリズム（Quantum algorithm for non-homogeneous linear partial differential equations）</news:title>
   <news:publication_date>2026-06-11T00:18:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699317</loc>
  <lastmod>2026-06-11T00:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データに対する変分オーバーサンプリング（VOS: a Method for Variational Oversampling of Imbalanced Data）</news:title>
   <news:publication_date>2026-06-11T00:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699315</loc>
  <lastmod>2026-06-11T00:17:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SECS: 環境に応じたクラススキューで効率化する深層ストリーム処理（SECS: Efficient Deep Stream Processing via Class Skew Dichotomy）</news:title>
   <news:publication_date>2026-06-11T00:17:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699313</loc>
  <lastmod>2026-06-11T00:17:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練セット中心点の原理的構成と確率的サンプリングによる最近傍分類精度の向上 (Improving the accuracy of nearest-neighbor classification using principled construction and stochastic sampling of training-set centroids)</news:title>
   <news:publication_date>2026-06-11T00:17:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699311</loc>
  <lastmod>2026-06-11T00:16:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間ボトルネックによる畳み込み高速化（Accelerating Deep Neural Networks with Spatial Bottleneck Modules）</news:title>
   <news:publication_date>2026-06-11T00:16:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699309</loc>
  <lastmod>2026-06-10T23:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表意文字のサブワードモデル（LOGOGRAPHIC SUBWORD MODEL FOR NEURAL MACHINE TRANSLATION）</news:title>
   <news:publication_date>2026-06-10T23:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699307</loc>
  <lastmod>2026-06-10T23:25:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>方策の不変量学習による汎化（Learning Invariances for Policy Generalization）</news:title>
   <news:publication_date>2026-06-10T23:25:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699305</loc>
  <lastmod>2026-06-10T23:24:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HyperGCN：ハイパーグラフ上でのGCN学習手法（HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs）</news:title>
   <news:publication_date>2026-06-10T23:24:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699303</loc>
  <lastmod>2026-06-10T23:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>360度映像のための自己教師あり空間音声生成（Self-Supervised Generation of Spatial Audio for 360◦Video）</news:title>
   <news:publication_date>2026-06-10T23:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699301</loc>
  <lastmod>2026-06-10T23:24:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SENetと半教師あり学習のアンサンブルによる皮膚病変分類（Skin lesion classification with ensemble of squeeze-and-excitation networks and semi-supervised learning）</news:title>
   <news:publication_date>2026-06-10T23:24:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699299</loc>
  <lastmod>2026-06-10T23:23:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NV中心を用いたnano-NMRと深層学習による雑音克服（NV center based nano-NMR enhanced by deep learning）</news:title>
   <news:publication_date>2026-06-10T23:23:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699297</loc>
  <lastmod>2026-06-10T23:23:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D形状分類器の深掘り（A Deeper Look at 3D Shape Classifiers）</news:title>
   <news:publication_date>2026-06-10T23:23:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699295</loc>
  <lastmod>2026-06-10T22:32:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層仮説検定による異種ネットワーク母集団の比較（Multi-level hypothesis testing for populations of heterogeneous networks）</news:title>
   <news:publication_date>2026-06-10T22:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699293</loc>
  <lastmod>2026-06-10T22:24:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トーリック多様体上の射影束コホモロジーを機械学習で解析する（Machine Learning Line Bundle Cohomologies of Hypersurfaces in Toric Varieties）</news:title>
   <news:publication_date>2026-06-10T22:24:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699291</loc>
  <lastmod>2026-06-10T22:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列平均化の誤差を再考する（Revisiting Inaccuracies of Time Series Averaging under Dynamic Time Warping）</news:title>
   <news:publication_date>2026-06-10T22:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699289</loc>
  <lastmod>2026-06-10T22:24:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の概念知識を模倣する疎（スパース）マルチモーダル埋め込み（Using sparse semantic embeddings learned from multimodal text and image data to model human conceptual knowledge）</news:title>
   <news:publication_date>2026-06-10T22:24:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699287</loc>
  <lastmod>2026-06-10T22:23:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推薦システムにおける行動条件付き系列モデリング（Action-conditional Sequence Modeling for Recommendation）</news:title>
   <news:publication_date>2026-06-10T22:23:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699285</loc>
  <lastmod>2026-06-10T22:23:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果的公平性モデルによるバイアスデータの学習（Fairness through Causal Awareness: Learning Causal Latent-Variable Models for Biased Data）</news:title>
   <news:publication_date>2026-06-10T22:23:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699283</loc>
  <lastmod>2026-06-10T22:22:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MixUpの外部マニフェールド局所線形正則化としての解釈 (MixUp as Locally Linear Out-Of-Manifold Regularization)</news:title>
   <news:publication_date>2026-06-10T22:22:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699281</loc>
  <lastmod>2026-06-10T21:31:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースカーネルPCAによる外れ値検知（Sparse Kernel PCA for Outlier Detection）</news:title>
   <news:publication_date>2026-06-10T21:31:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699279</loc>
  <lastmod>2026-06-10T21:30:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FI-GRL: 投影コスト保存による高速帰納的グラフ表現学習（FI-GRL: Fast Inductive Graph Representation Learning via Projection-Cost Preservation）</news:title>
   <news:publication_date>2026-06-10T21:30:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699277</loc>
  <lastmod>2026-06-10T21:30:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様体として読む都市データの解像度（Manifold Cities: Social variables of urban areas in the UK）</news:title>
   <news:publication_date>2026-06-10T21:30:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699275</loc>
  <lastmod>2026-06-10T21:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StackNetによる継続学習の設計（StackNet: Stacking feature maps for Continual learning）</news:title>
   <news:publication_date>2026-06-10T21:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699273</loc>
  <lastmod>2026-06-10T21:30:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BiasedWalkによるグラフ表現学習の新展開（BiasedWalk: Biased Sampling for Representation Learning on Graphs）</news:title>
   <news:publication_date>2026-06-10T21:30:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699271</loc>
  <lastmod>2026-06-10T21:29:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタモルフィック関係に基づく敵対的攻撃と微分可能ニューラルコンピュータ（Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer）</news:title>
   <news:publication_date>2026-06-10T21:29:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699269</loc>
  <lastmod>2026-06-10T21:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークによるテキスト分類とオープンドメイン質問応答への応用（Convolutional Neural Network: Text Classification Model for Open Domain Question Answering System）</news:title>
   <news:publication_date>2026-06-10T21:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699267</loc>
  <lastmod>2026-06-10T20:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳活動と一致する深層ビデオ表現の最適化 (Optimizing deep video representation to match brain activity)</news:title>
   <news:publication_date>2026-06-10T20:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699265</loc>
  <lastmod>2026-06-10T20:38:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号付きソーシャルネットワークにおけるノード分類と拡散界面法（Node Classification for Signed Social Networks Using Diffuse Interface Methods）</news:title>
   <news:publication_date>2026-06-10T20:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699263</loc>
  <lastmod>2026-06-10T20:37:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果推論の入門—データサイエンスにおける因果の道筋（A Primer on Causality in Data Science）</news:title>
   <news:publication_date>2026-06-10T20:37:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699261</loc>
  <lastmod>2026-06-10T20:37:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別時系列予測に挑むDeep Recurrent Survival Analysis（Deep Recurrent Survival Analysis）</news:title>
   <news:publication_date>2026-06-10T20:37:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699259</loc>
  <lastmod>2026-06-10T20:36:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的な敵対的入力の検出と人間可解釈な防御（Detecting Potential Local Adversarial Examples for Human-Interpretable Defense）</news:title>
   <news:publication_date>2026-06-10T20:36:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699257</loc>
  <lastmod>2026-06-10T20:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチネットワークトポロジーの深層特徴学習（Deep Feature Learning of Multi-Network Topology for Node Classification）</news:title>
   <news:publication_date>2026-06-10T20:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699255</loc>
  <lastmod>2026-06-10T20:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回答分離によるニューラル質問生成の改善（Improving Neural Question Generation using Answer Separation）</news:title>
   <news:publication_date>2026-06-10T20:36:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699253</loc>
  <lastmod>2026-06-10T19:45:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点を切り替えて学ぶ直観的物理予測（Neural Allocentric Intuitive Physics Prediction from Real Videos）</news:title>
   <news:publication_date>2026-06-10T19:45:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699251</loc>
  <lastmod>2026-06-10T19:44:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練されたフィードバックネットワークにおける大域的安定性の幾何学的解析（A geometrical analysis of global stability in trained feedback networks）</news:title>
   <news:publication_date>2026-06-10T19:44:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699249</loc>
  <lastmod>2026-06-10T19:44:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過去報酬統計を活用したオンポリシー学習の改善（Improving On-policy Learning with Statistical Reward Accumulation）</news:title>
   <news:publication_date>2026-06-10T19:44:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699247</loc>
  <lastmod>2026-06-10T19:43:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続稼働タスク向けにシミュレーション期間を可変化したモンテカルロ木探索（Monte Carlo Tree Search with Scalable Simulation Periods for Continuously Running Tasks）</news:title>
   <news:publication_date>2026-06-10T19:43:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699245</loc>
  <lastmod>2026-06-10T19:43:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列変量の歪んだ混合ビリニア因子解析（Mixtures of Skewed Matrix Variate Bilinear Factor Analyzers）</news:title>
   <news:publication_date>2026-06-10T19:43:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699243</loc>
  <lastmod>2026-06-10T19:42:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群ベースの分離表現学習と新規コンテンツへの一般化（Group-based Learning of Disentangled Representations with Generalizability for Novel Contents）</news:title>
   <news:publication_date>2026-06-10T19:42:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699241</loc>
  <lastmod>2026-06-10T19:42:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>On2Vecによるオントロジー充填の新展開（On2Vec: Embedding-based Relation Prediction for Ontology Population）</news:title>
   <news:publication_date>2026-06-10T19:42:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699239</loc>
  <lastmod>2026-06-10T18:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WCE画像における胃潰瘍検出のための無限カリキュラム学習（Infinite Curriculum Learning for Efficiently Detecting Gastric Ulcers in WCE Images）</news:title>
   <news:publication_date>2026-06-10T18:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699237</loc>
  <lastmod>2026-06-10T18:51:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AIがブラック・ショールズ方程式数値解法の次元の呪いを克服する証明（A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations）</news:title>
   <news:publication_date>2026-06-10T18:51:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699235</loc>
  <lastmod>2026-06-10T18:51:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタパス埋め込みによる知識グラフの特徴学習（Feature Learning for Meta-Paths in Knowledge Graphs）</news:title>
   <news:publication_date>2026-06-10T18:51:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699233</loc>
  <lastmod>2026-06-10T18:50:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論に基づく能動学習で効率的に画像検索を改善する（Information-Theoretic Active Learning for Content-Based Image Retrieval）</news:title>
   <news:publication_date>2026-06-10T18:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699231</loc>
  <lastmod>2026-06-10T18:50:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形最適化向けの高速アンダーソン・チェビシェフ加速（A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization）</news:title>
   <news:publication_date>2026-06-10T18:50:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699229</loc>
  <lastmod>2026-06-10T18:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチターゲット予測の統一的視点（Multi-target prediction: A unifying view on problems and methods）</news:title>
   <news:publication_date>2026-06-10T18:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699227</loc>
  <lastmod>2026-06-10T18:49:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNと手作り特徴の融合で肺結節の悪性度を予測する手法（Predicting Lung Nodule Malignancies by Combining Deep Convolutional Neural Network and Handcrafted Features）</news:title>
   <news:publication_date>2026-06-10T18:49:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699225</loc>
  <lastmod>2026-06-10T17:58:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模閉ループ産業プロセスの分散動的モデリングとモニタリング（Distributed dynamic modeling and monitoring for large-scale industrial processes under closed-loop control）</news:title>
   <news:publication_date>2026-06-10T17:58:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699223</loc>
  <lastmod>2026-06-10T17:57:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速グリーディ法による辞書選択と一般化スパース制約（Fast greedy algorithms for dictionary selection with generalized sparsity constraints）</news:title>
   <news:publication_date>2026-06-10T17:57:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699221</loc>
  <lastmod>2026-06-10T17:57:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>掘進機の運転データから地質を予測する手法の実用性（Geology prediction based on operation data of TBM: comparison between deep neural network and statistical learning methods）</news:title>
   <news:publication_date>2026-06-10T17:57:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699219</loc>
  <lastmod>2026-06-10T17:56:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均分散最適化のためのブロック座標上昇アルゴリズム（A Block Coordinate Ascent Algorithm for Mean-Variance Optimization）</news:title>
   <news:publication_date>2026-06-10T17:56:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699217</loc>
  <lastmod>2026-06-10T17:56:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語ニューラル言語モデルによる教師なしクロスリンガル単語埋め込み（Unsupervised Cross-lingual Word Embedding by Multilingual Neural Language Models）</news:title>
   <news:publication_date>2026-06-10T17:56:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699215</loc>
  <lastmod>2026-06-10T17:56:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間でのランク最小化によるテンソルリング補完（Tensor Ring Decomposition with Rank Minimization on Latent Space）</news:title>
   <news:publication_date>2026-06-10T17:56:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699213</loc>
  <lastmod>2026-06-10T17:55:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロン統合層による漸進的冗長性削減（Neurons Merging Layer: Towards Progressive Redundancy Reduction for Deep Supervised Hashing）</news:title>
   <news:publication_date>2026-06-10T17:55:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699211</loc>
  <lastmod>2026-06-10T17:04:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係的プログラム合成（Relational Program Synthesis）</news:title>
   <news:publication_date>2026-06-10T17:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699209</loc>
  <lastmod>2026-06-10T17:04:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的クラスタリングの近似アルゴリズム（Approximation algorithms for stochastic clustering）</news:title>
   <news:publication_date>2026-06-10T17:04:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699207</loc>
  <lastmod>2026-06-10T17:03:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト付き有向ネットワークの埋め込み学習（Learning Embeddings of Directed Networks with Text-Associated Nodes—with Application in Software Package Dependency Networks）</news:title>
   <news:publication_date>2026-06-10T17:03:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699205</loc>
  <lastmod>2026-06-10T17:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BubGANによる気泡流画像合成（BubGAN: Bubble Generative Adversarial Networks for Synthesizing Realistic Bubbly Flow Images）</news:title>
   <news:publication_date>2026-06-10T17:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699203</loc>
  <lastmod>2026-06-10T17:02:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジスティック回帰で背景ノードを除外するネットワークのコミュニティ検出（Logistic Regression Augmented Community Detection for Network Data）</news:title>
   <news:publication_date>2026-06-10T17:02:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699201</loc>
  <lastmod>2026-06-10T17:02:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動優性多発性嚢胞腎のCT画像から腎臓総量を算出する多目的3D畳み込みニューラルネットワーク（Computation of Total Kidney Volume from CT images in Autosomal Dominant Polycystic Kidney Disease using Multi-Task 3D Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-10T17:02:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:title>エッジ意味を考慮した表現学習が変えるバイオ医療知識発見（edge2vec: Representation learning using edge semantics for biomedical knowledge discovery）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>マルチソースからのドメイン適応を重み付き専門家で行う考え方（Multi-Source Domain Adaptation with Mixture of Experts）</news:title>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:title>超小型矮小銀河候補の本質（On the Nature of Ultra-faint Dwarf Galaxy Candidates. III. Horologium I, Pictor I, Grus I, and Phoenix II）</news:title>
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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>フォーラム間で学ぶ重複質問検出の実用性（Adversarial Domain Adaptation for Duplicate Question Detection）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>共有入力を持つ合成関数に対する量子アルゴリズムと近似多項式（Quantum algorithms and approximating polynomials for composed functions with shared inputs）</news:title>
   <news:publication_date>2026-06-10T16:08:49Z</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>サイクル一貫性を用いた音声強調（Cycle-Consistent Speech Enhancement）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:title>敵対的特徴変換による音声強調（Adversarial Feature-Mapping for Speech Enhancement）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な公平政策の学習（Learning Optimal Fair Policies）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>重要インフラに対する適応型戦略的サイバー防御（Adaptive Strategic Cyber Defense for Advanced Persistent Threats in Critical Infrastructure Networks）</news:title>
   <news:publication_date>2026-06-10T15:16:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-10T15:09:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>多腕バンディット的アプローチによる多重検定と偽発見率制御（A Bandit Approach to Multiple Testing with False Discovery Control）</news:title>
   <news:publication_date>2026-06-10T15:09:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-10T15:09:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>2段階フィルタ剪定によるCNN圧縮（Two-Phase Filter Pruning Based on Conditional Entropy）</news:title>
   <news:publication_date>2026-06-10T15:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-06-10T15:08:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プレイヤー経験をゲーム映像から抽出する方法（Player Experience Extraction from Gameplay Video）</news:title>
   <news:publication_date>2026-06-10T15:08:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-06-10T15:08:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ディープラーニングによるデリバティブ評価の革新（Deeply Learning Derivatives）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-10T15:07:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>マルチチャネル・マルチタッチ帰属に対する注意機構付き深層ニューラルネット（Deep Neural Net with Attention for Multi-channel Multi-touch Attribution）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-10T15:06:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>パターン化画像におけるユーザーマーキングの内容に基づく伝播（Content-based Propagation of User Markings for Interactive Segmentation of Patterned Images）</news:title>
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   <news:genres>Blog</news:genres>
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