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   <news:title>荷電カオンの半包接近散乱における多産率の比較（Charged Kaon multiplicities of Semi-inclusive DIS off the deuteron target）</news:title>
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   <news:title>ボトルネック・アテンション・モジュールによる特徴改良の効率化（Bottleneck Attention Module）</news:title>
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   <news:title>動的サンプリングとグラフィカルモデル（Dynamic Sampling from Graphical Models）</news:title>
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    <news:language>ja</news:language>
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   <news:title>著者スタイルを模した多言語詩生成の手法（GUESS WHO? MULTILINGUAL APPROACH FOR THE AUTOMATED GENERATION OF AUTHOR-STYLIZED POETRY）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>深層完全畳み込みネットワークによる皮膚病変セグメンテーション（Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks）</news:title>
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   <news:title>2ビット量子化ニューラルネットワークの精度ギャップを埋める手法（Bridging the Accuracy Gap for 2-bit Quantized Neural Networks）</news:title>
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   <news:title>低資源音響イベント検出におけるデータ効率的弱教師あり学習（Data-efficient Weakly Supervised Learning for Low-Resource Audio Event Detection Using Deep Learning）</news:title>
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   <news:title>皮膚病変分類におけるDense CNNアプローチ（A Dense CNN approach for skin lesion classification）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>公平学習における差別影響の検定と信頼区間（Confidence Intervals for Testing Disparate Impact in Fair Learning）</news:title>
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   <news:title>効率的な深い表現は学習可能か（Are Efficient Deep Representations Learnable?）</news:title>
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   <news:title>楽譜を聞き、読み、追従する学習（Learning to Listen, Read, and Follow: Score Following as a Reinforcement Learning Game）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>高解像度写真生成における自己点検型VAEの革新（IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis）</news:title>
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   <news:title>確率ビット列で実現する最大・最小回路の設計と解析（Design and Analysis of Efficient Maximum/Minimum Circuits for Stochastic Computing）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>SGDとランダム特徴による学習（Learning with SGD and Random Features）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>電池劣化予測の汎用モデル化（Battery health prediction under generalized conditions using a Gaussian process transition model）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>マルチテナント向けクロススライス資源オーケストレーション（Multi-Tenant Cross-Slice Resource Orchestration: A Deep Reinforcement Learning Approach）</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>Knowledge-aware Autoencodersによる説明可能なレコメンダ（Knowledge-aware Autoencoders for Explainable Recommender Sytems）</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>GeoDesc：幾何学的制約を統合した局所記述子学習（GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints）</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>ニューロンの非線形性を学習するカーネルベース深層ニューラルネットワーク（Learning Neuron Non-Linearities with Kernel-Based Deep 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>ルベーグ積分に基づく新しい求積法（On Lebesgue Integral Quadrature）</news:title>
   <news:publication_date>2026-05-27T07:53:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>撮像プロトコルの違いに強いドメイン適応（Domain Adaptation for Deviating Acquisition Protocols in CNN-based Lesion Classification on Diffusion-Weighted MR Images）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>分散アルゴリズムのスパース化と大規模グラフ処理の新境地（Sparsifying Distributed Algorithms）</news:title>
   <news:publication_date>2026-05-27T07:52:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>DeepPhase: 白内障手術動画における手術工程認識（DeepPhase: Surgical Phase Recognition in CATARACTS Videos）</news:title>
   <news:publication_date>2026-05-27T07:52:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-27T07:00:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的マルチタスク学習によるCTCベース音声認識の改善（HIERARCHICAL MULTITASK LEARNING FOR CTC-BASED SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-05-27T07:00:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694781</loc>
  <lastmod>2026-05-27T07:00:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波クラウドRANにおける多経路伝送スケジューリング（Multipath Transmission Scheduling in Millimeter Wave Cloud Radio Access Networks）</news:title>
   <news:publication_date>2026-05-27T07:00:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694779</loc>
  <lastmod>2026-05-27T06:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報源融合と最適化によるICMEの実現（Multi-Information Source Fusion and Optimization to Realize ICME: Application to Dual Phase Materials）</news:title>
   <news:publication_date>2026-05-27T06:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694777</loc>
  <lastmod>2026-05-27T06:58:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ルール行列による説明可能な機械学習の可視化（RuleMatrix: The Visual Interface）</news:title>
   <news:publication_date>2026-05-27T06:58:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694775</loc>
  <lastmod>2026-05-27T06:58:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用拡散過程を学習することによる画像復元の効率化（Learning Generic Diffusion Processes for Image Restoration）</news:title>
   <news:publication_date>2026-05-27T06:58:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694773</loc>
  <lastmod>2026-05-27T06:58:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノックオフ手法による特徴重要度の統計と偽発見率保証（Knockoffs for the Mass: New Feature Importance Statistics with False Discovery Guarantees）</news:title>
   <news:publication_date>2026-05-27T06:58:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694771</loc>
  <lastmod>2026-05-27T06:57:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲーティッド情報融合による堅牢なマルチモーダル学習（Robust Deep Multi-modal Learning Based on Gated Information Fusion Network）</news:title>
   <news:publication_date>2026-05-27T06:57:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694769</loc>
  <lastmod>2026-05-27T06:06:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Planck 2018が残した宇宙論の遺産（Planck 2018 results. I. Overview and the cosmological legacy of Planck）</news:title>
   <news:publication_date>2026-05-27T06:06:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694767</loc>
  <lastmod>2026-05-27T06:05:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能的イメージングデータのための罰則付き行列分解（Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data）</news:title>
   <news:publication_date>2026-05-27T06:05:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694765</loc>
  <lastmod>2026-05-27T06:03:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>携帯型マルチメディア翻訳による食事管理支援（A Hand-Held Multimedia Translation and Interpretation System with Application to Diet Management）</news:title>
   <news:publication_date>2026-05-27T06:03:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694763</loc>
  <lastmod>2026-05-27T06:02:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPIRIT望遠鏡イニシアティブ──教育用ウェブ対応ロボット望遠鏡の6年間の教訓（The SPIRIT Telescope Initiative: six years on）</news:title>
   <news:publication_date>2026-05-27T06:02:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694761</loc>
  <lastmod>2026-05-27T06:02:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WiFi接続ログからプライバシーを守りつつ行動パターンを識別する手法 (Privacy-preserving classifiers recognize shared mobility behaviours from WiFi network imperfect data)</news:title>
   <news:publication_date>2026-05-27T06:02:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694759</loc>
  <lastmod>2026-05-27T06:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>判別的アプローチによるベイズフィルタリングとその応用（A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding）</news:title>
   <news:publication_date>2026-05-27T06:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694757</loc>
  <lastmod>2026-05-27T06:01:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>送電系統における植生起因停電の予測手法（A Data-Driven Approach for Predicting Vegetation-Related Outages in Power Distribution Systems）</news:title>
   <news:publication_date>2026-05-27T06:01:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694755</loc>
  <lastmod>2026-05-27T05:08:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非適応条件付きサンプリングを用いた分布検定アルゴリズム（Anaconda: A Non-Adaptive Conditional Sampling Algorithm for Distribution Testing）</news:title>
   <news:publication_date>2026-05-27T05:08:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694753</loc>
  <lastmod>2026-05-27T05:08:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小問い合わせで学ぶ凸分割と均衡計算（Learning Convex Partitions and Computing Game-theoretic Equilibria from Best Response Queries）</news:title>
   <news:publication_date>2026-05-27T05:08:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694751</loc>
  <lastmod>2026-05-27T05:07:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能な推薦のための層別関連度伝播（Layer-wise Relevance Propagation for Explainable Recommendations）</news:title>
   <news:publication_date>2026-05-27T05:07:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694749</loc>
  <lastmod>2026-05-27T05:07:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Horn包のPAC学習（Probably approximately correct learning of Horn envelopes from queries）</news:title>
   <news:publication_date>2026-05-27T05:07:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694747</loc>
  <lastmod>2026-05-27T05:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続行動空間における線形計算量の離散化によるQ学習の拡張（DISCRETE LINEAR-COMPLEXITY REINFORCEMENT LEARNING IN CONTINUOUS ACTION SPACES FOR Q-LEARNING ALGORITHMS）</news:title>
   <news:publication_date>2026-05-27T05:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694745</loc>
  <lastmod>2026-05-27T05:07:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー材料の性質を機械学習で予測する（Machine Learning of Energetic Material Properties）</news:title>
   <news:publication_date>2026-05-27T05:07:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694743</loc>
  <lastmod>2026-05-27T05:06:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察のみから模倣する生成的敵対学習（Generative Adversarial Imitation from Observation）</news:title>
   <news:publication_date>2026-05-27T05:06:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694741</loc>
  <lastmod>2026-05-27T04:15:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約ベースの視覚生成（Constraint-Based Visual Generation）</news:title>
   <news:publication_date>2026-05-27T04:15:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694739</loc>
  <lastmod>2026-05-27T04:14:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列を考慮したLSTMによる放射線異常の縦断検出（Longitudinal detection of radiological abnormalities with time-modulated LSTM）</news:title>
   <news:publication_date>2026-05-27T04:14:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694737</loc>
  <lastmod>2026-05-27T04:13:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ℓpに基づく低ランク近似のPTAS登場（A PTAS for ℓp-Low Rank Approximation）</news:title>
   <news:publication_date>2026-05-27T04:13:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694735</loc>
  <lastmod>2026-05-27T04:13:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大質量比二体ブラックホール合体の大規模並列シミュレーション（Massively Parallel Simulations of Binary Black Hole Intermediate-Mass-Ratio Inspirals）</news:title>
   <news:publication_date>2026-05-27T04:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694733</loc>
  <lastmod>2026-05-27T04:12:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データの有効活用による都市景観セマンティックセグメンテーション（Effective Use of Synthetic Data for Urban Scene Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-27T04:12:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694731</loc>
  <lastmod>2026-05-27T04:12:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>否定表現を見落とすな：Twitter顧客対応会話における否定処理を組み込んだ対話行為予測（Don’t get Lost in Negation: An Effective Negation Handled Dialogue Acts Prediction Algorithm for Twitter Customer Service Conversations）</news:title>
   <news:publication_date>2026-05-27T04:12:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694729</loc>
  <lastmod>2026-05-27T04:12:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループにおける顔レベルの相互作用解析が示すもの（Computational Social Dynamics: Analyzing the Face-level Interactions in a Group）</news:title>
   <news:publication_date>2026-05-27T04:12:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694727</loc>
  <lastmod>2026-05-27T03:20:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高階確率プログラムの形式検証（Formal Verification of Higher-Order Probabilistic Programs）</news:title>
   <news:publication_date>2026-05-27T03:20:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694725</loc>
  <lastmod>2026-05-27T03:20:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的状態を用いた予後推定（Prognostics Estimations with Dynamic States）</news:title>
   <news:publication_date>2026-05-27T03:20:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694723</loc>
  <lastmod>2026-05-27T03:20:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的シールドによる安全な強化学習（Safe Reinforcement Learning via Probabilistic Shields）</news:title>
   <news:publication_date>2026-05-27T03:20:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694721</loc>
  <lastmod>2026-05-27T03:19:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習済み3D物体検出モデルを用いた高速グラウンドトゥルース生成（Leveraging Pre-Trained 3D Object Detection Models For Fast Ground Truth Generation）</news:title>
   <news:publication_date>2026-05-27T03:19:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694719</loc>
  <lastmod>2026-05-27T03:19:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>喉頭内視鏡画像データセットとCNNベースのセマンティックセグメンテーション比較研究（A Dataset of Laryngeal Endoscopic Images with Comparative Study on Convolution Neural Network Based Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-27T03:19:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694717</loc>
  <lastmod>2026-05-27T03:19:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線における弱教師あり深層学習による疾患分類と局所化（Weakly Supervised Deep Learning for Thoracic Disease Classification and Localization on Chest X-rays）</news:title>
   <news:publication_date>2026-05-27T03:19:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694715</loc>
  <lastmod>2026-05-27T03:19:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キロディグリーサーベイによる銀河のサイズ―恒星質量関係の進化（Evolution of galaxy size–stellar mass relation from the Kilo Degree Survey）</news:title>
   <news:publication_date>2026-05-27T03:19:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694713</loc>
  <lastmod>2026-05-27T02:27:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の敵対者が存在する環境下でのオンライン頑健方策学習（Online Robust Policy Learning in the Presence of Unknown Adversaries）</news:title>
   <news:publication_date>2026-05-27T02:27:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694711</loc>
  <lastmod>2026-05-27T02:27:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四次元群における極分解のアルゴリズムと四元数（Algorithms for the Polar Decomposition in Certain Groups and the Quaternions）</news:title>
   <news:publication_date>2026-05-27T02:27:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694709</loc>
  <lastmod>2026-05-27T02:27:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高校生と望遠鏡が生む市民科学の広がり（The Pulsar Search Collaboratory: Expanding Nationwide）</news:title>
   <news:publication_date>2026-05-27T02:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694707</loc>
  <lastmod>2026-05-27T02:26:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Unlimited Road-scene Synthetic Annotation（Unlimited Road-scene Synthetic Annotation (URSA) Dataset）</news:title>
   <news:publication_date>2026-05-27T02:26:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694705</loc>
  <lastmod>2026-05-27T02:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zap: オンライン行動に基づく予測パイプラインの実務的意義（Zap: Making Predictions Based on Online User Behavior）</news:title>
   <news:publication_date>2026-05-27T02:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694703</loc>
  <lastmod>2026-05-27T02:26:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論的距離測度と双方向Helmholtzマシン（On the Information Theoretic Distance Measures and Bidirectional Helmholtz Machines）</news:title>
   <news:publication_date>2026-05-27T02:26:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694701</loc>
  <lastmod>2026-05-27T02:25:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変質量系に対するニュートンの第二法則に関する考察（Remarks on Newton’s Second Law for Variable Mass Systems）</news:title>
   <news:publication_date>2026-05-27T02:25:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694699</loc>
  <lastmod>2026-05-27T01:34:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし学習で新物理を見つける道案内（Guiding New Physics Searches with Unsupervised Learning）</news:title>
   <news:publication_date>2026-05-27T01:34:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694697</loc>
  <lastmod>2026-05-27T01:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pangloss: ノイズの多いテキスト環境における高速エンティティリンク（Pangloss: Fast Entity Linking in Noisy Text Environments）</news:title>
   <news:publication_date>2026-05-27T01:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694695</loc>
  <lastmod>2026-05-27T01:34:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックホールのアルファビットを学ぶ（Learning the Alpha-bits of Black Holes）</news:title>
   <news:publication_date>2026-05-27T01:34:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694693</loc>
  <lastmod>2026-05-27T01:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学校における企業型ソーシャルネットワークの学習手法と安全性（Methods, Forms and Safety of Learning in Corporate Social Networks）</news:title>
   <news:publication_date>2026-05-27T01:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694691</loc>
  <lastmod>2026-05-27T01:33:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子ソーシャルネットワークにおける生徒の教授法の進化（The Evolution of Teaching Methods of Students in Electronic Social Networks）</news:title>
   <news:publication_date>2026-05-27T01:33:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694689</loc>
  <lastmod>2026-05-27T01:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低表面輝度銀河のHST撮像が示したこと（The Dragonfly Nearby Galaxies Survey. V. HST Imaging）</news:title>
   <news:publication_date>2026-05-27T01:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694687</loc>
  <lastmod>2026-05-27T01:32:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジを意識した点群統合の新展開（EC-Net: an Edge-aware Point set Consolidation Network）</news:title>
   <news:publication_date>2026-05-27T01:32:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694685</loc>
  <lastmod>2026-05-27T00:41:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非正規教育におけるクラウドサービスを用いた教員の専門能力開発（Professional Development of Teachers Using Cloud Services During Non-formal Education）</news:title>
   <news:publication_date>2026-05-27T00:41:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694683</loc>
  <lastmod>2026-05-27T00:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一段階・単一フェーズで行う肺結節検出の新展開（Towards Single-phase Single-stage Detection of Pulmonary Nodules in Chest CT Imaging）</news:title>
   <news:publication_date>2026-05-27T00:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694681</loc>
  <lastmod>2026-05-27T00:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空撮画像での複数ラベル式歩行者検出の実用化可能性（Convolutional Neural Networks for Aerial Multi-Label Pedestrian Detection）</news:title>
   <news:publication_date>2026-05-27T00:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694679</loc>
  <lastmod>2026-05-27T00:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ空間からの解放：Latent Embedding Optimization（Latent Embedding Optimization）</news:title>
   <news:publication_date>2026-05-27T00:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694677</loc>
  <lastmod>2026-05-27T00:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Manycore CPU上での計算グラフ実行スケジューリング（Scheduling Computation Graphs of Deep Learning Models on Manycore CPUs）</news:title>
   <news:publication_date>2026-05-27T00:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694675</loc>
  <lastmod>2026-05-27T00:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子QCD観測量のための機械学習推定器（Machine learning estimators for lattice QCD observables）</news:title>
   <news:publication_date>2026-05-27T00:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694673</loc>
  <lastmod>2026-05-27T00:36:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動ステレオ用エンドツーエンド自己教師あり学習（ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems）</news:title>
   <news:publication_date>2026-05-27T00:36:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694671</loc>
  <lastmod>2026-05-26T23:43:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二足歩行ロボットの強化学習による自律歩行（Bipedal Walking Robot using Deep Deterministic Policy Gradient）</news:title>
   <news:publication_date>2026-05-26T23:43:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694669</loc>
  <lastmod>2026-05-26T23:35:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ATLAS ITk向け CMOSピクセルセンサー試作の実性能評価（Performance of CMOS pixel sensor prototypes in ams H35 and aH18 technology for the ATLAS ITk upgrade）</news:title>
   <news:publication_date>2026-05-26T23:35:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694667</loc>
  <lastmod>2026-05-26T23:35:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競合リスクを伴うシアミーズ生存解析（Siamese Survival Analysis with Competing Risks）</news:title>
   <news:publication_date>2026-05-26T23:35:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694665</loc>
  <lastmod>2026-05-26T23:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分可能な遺伝子制御ネットワークの進化（Evolving Differentiable Gene Regulatory Networks）</news:title>
   <news:publication_date>2026-05-26T23:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694663</loc>
  <lastmod>2026-05-26T23:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分推論による生成モデルの統一的枠組み（Variational Inference: A Unified Framework of Generative Models and Some Revelations）</news:title>
   <news:publication_date>2026-05-26T23:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694661</loc>
  <lastmod>2026-05-26T23:33:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロパネルデータの特徴量ベースクラスタリング手法の要点（Novel Feature-Based Clustering of Micro-Panel Data (CluMP))</news:title>
   <news:publication_date>2026-05-26T23:33:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694659</loc>
  <lastmod>2026-05-26T23:33:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IFUデータキューブからの高速自動スペクトル抽出ソフト AutoSpec（AutoSpec: Fast Automated Spectral Extraction Software for IFU Datacubes）</news:title>
   <news:publication_date>2026-05-26T23:33:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694657</loc>
  <lastmod>2026-05-26T22:42:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポリープ分割におけるCNNの不確実性モデル化と解釈可能性（UNCERTAINTY MODELING AND INTERPRETABILITY IN CONVOLUTIONAL NEURAL NETWORKS FOR POLYP SEGMENTATION）</news:title>
   <news:publication_date>2026-05-26T22:42:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694655</loc>
  <lastmod>2026-05-26T22:42:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データへのドメインランダム化適用による物体カテゴリ検出（Applying Domain Randomization to Synthetic Data for Object Category Detection）</news:title>
   <news:publication_date>2026-05-26T22:42:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694653</loc>
  <lastmod>2026-05-26T22:42:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の「驚き」の知覚を測る──計算モデルは人を驚かせられるか（Human Perception of Surprise: A User Study）</news:title>
   <news:publication_date>2026-05-26T22:42:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694651</loc>
  <lastmod>2026-05-26T22:42:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッドな音楽推薦の機械学習アプローチ（Machine Learning Approaches to Hybrid Music Recommender Systems）</news:title>
   <news:publication_date>2026-05-26T22:42:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694649</loc>
  <lastmod>2026-05-26T22:42:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な深層強化学習への道（Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees）</news:title>
   <news:publication_date>2026-05-26T22:42:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694647</loc>
  <lastmod>2026-05-26T22:41:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンショット学習に基づく物体関係検出（Object Relation Detection Based on One-shot Learning）</news:title>
   <news:publication_date>2026-05-26T22:41:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694645</loc>
  <lastmod>2026-05-26T22:41:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メンバーシッププライバシーを守る対抗的正則化（Machine Learning with Membership Privacy using Adversarial Regularization）</news:title>
   <news:publication_date>2026-05-26T22:41:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694643</loc>
  <lastmod>2026-05-26T21:50:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布の「場」を守る敵対的学習の提案（Manifold Adversarial Learning）</news:title>
   <news:publication_date>2026-05-26T21:50:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694641</loc>
  <lastmod>2026-05-26T21:50:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験を記憶し忘れることで経験再生を改善する（Remember and Forget for Experience Replay）</news:title>
   <news:publication_date>2026-05-26T21:50:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/694639</loc>
  <lastmod>2026-05-26T21:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中動画から魚の個体数を自動推定する技術の意義（Assessing fish abundance from underwater video using deep neural networks）</news:title>
   <news:publication_date>2026-05-26T21:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694637</loc>
  <lastmod>2026-05-26T21:49:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を考慮したニューラルネットワークと雑音除去オートエンコーダの組合せによる文字列類似度測定 (Combining a Context Aware Neural Network with a Denoising Autoencoder for Measuring String Similarities)</news:title>
   <news:publication_date>2026-05-26T21:49:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694635</loc>
  <lastmod>2026-05-26T21:49:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い準障壁での軽核融合反応における天体物理学的S因子（Astrophysical S-factor for the deep sub-barrier fusion reactions of light nuclei）</news:title>
   <news:publication_date>2026-05-26T21:49:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694633</loc>
  <lastmod>2026-05-26T21:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動音響鳥類検出と深層学習の実証（Automatic acoustic detection of birds through deep learning）</news:title>
   <news:publication_date>2026-05-26T21:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694631</loc>
  <lastmod>2026-05-26T21:48:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種複雑性を持つデータに強い無正則化スコアによる異常検知（Deep Generative Model using Unregularized Score for Anomaly Detection with Heterogeneous Complexity）</news:title>
   <news:publication_date>2026-05-26T21:48:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694629</loc>
  <lastmod>2026-05-26T20:57:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分光イメージングによる顔認証の現状と課題（An Extensive Review on Spectral Imaging in Biometric Systems: Challenges &amp;amp; Advancements）</news:title>
   <news:publication_date>2026-05-26T20:57:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694627</loc>
  <lastmod>2026-05-26T20:57:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間時系列相乗残差学習によるビデオ人物再識別（Spatial-Temporal Synergic Residual Learning for Video Person Re-Identification）</news:title>
   <news:publication_date>2026-05-26T20:57:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694625</loc>
  <lastmod>2026-05-26T20:57:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1550nm帯におけるPAM‑4伝送とフォトニック・リザバーコンピューティングによる後処理（PAM-4 Transmission at 1550nm using Photonic Reservoir Computing Post-processing）</news:title>
   <news:publication_date>2026-05-26T20:57:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694623</loc>
  <lastmod>2026-05-26T20:56:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報流を手がかりにCNNを大幅圧縮するBRIEF（Backward Reduction of CNNs with Information Flow Analysis）</news:title>
   <news:publication_date>2026-05-26T20:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694621</loc>
  <lastmod>2026-05-26T20:56:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の相対論的流体力学への応用（Applications of deep learning to relativistic hydrodynamics）</news:title>
   <news:publication_date>2026-05-26T20:56:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694619</loc>
  <lastmod>2026-05-26T20:56:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程を用いた確率微分方程式の学習（Learning Stochastic Differential Equations with Gaussian Processes without Gradient Matching）</news:title>
   <news:publication_date>2026-05-26T20:56:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694617</loc>
  <lastmod>2026-05-26T20:56:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トップN推薦のための集合的変分オートエンコーダ（A Collective Variational Autoencoder for Top-N Recommendation with Side Information）</news:title>
   <news:publication_date>2026-05-26T20:56:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694615</loc>
  <lastmod>2026-05-26T20:05:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復的結合デモザイキングとノイズ除去：Residual Denoising Networkによる画像復元（Iterative Joint Image Demosaicking and Denoising using a Residual Denoising Network）</news:title>
   <news:publication_date>2026-05-26T20:05:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694613</loc>
  <lastmod>2026-05-26T20:04:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転車の統治——安全・責任・プライバシー・サイバーセキュリティと産業リスクへの新たな対応（Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks）</news:title>
   <news:publication_date>2026-05-26T20:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694611</loc>
  <lastmod>2026-05-26T20:04:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載エッジコンピューティングにおけるタスク複製と学習による遅延最小化（Task Replication for Vehicular Edge Computing: A Combinatorial Multi-Armed Bandit based Approach）</news:title>
   <news:publication_date>2026-05-26T20:04:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694609</loc>
  <lastmod>2026-05-26T20:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度リモートセンシング画像の土地被覆分類と転移可能な深層モデルの適用 (Land-Cover Classification with High-Resolution Remote Sensing Images Using Transferable Deep Models)</news:title>
   <news:publication_date>2026-05-26T20:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694607</loc>
  <lastmod>2026-05-26T20:04:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>End-to-end Neural Geometryによる頑健な深度・姿勢推定（End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs）</news:title>
   <news:publication_date>2026-05-26T20:04:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694605</loc>
  <lastmod>2026-05-26T20:03:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RESCAN: 単一画像の雨除去に向けた再帰的SE文脈集約ネットワーク（Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining）</news:title>
   <news:publication_date>2026-05-26T20:03:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694603</loc>
  <lastmod>2026-05-26T20:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResNet50で抽出した特徴をDeepForestで分類する皮膚病変判定手法（Disease Classification within Dermascopic Images Using features extracted by ResNet50 and classification through DeepForest）</news:title>
   <news:publication_date>2026-05-26T20:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694601</loc>
  <lastmod>2026-05-26T19:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーン学習による風力発電予測の革新（Scene Learning: Deep Convolutional Networks For Wind Power Prediction by Embedding Turbines into Grid Space）</news:title>
   <news:publication_date>2026-05-26T19:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694599</loc>
  <lastmod>2026-05-26T19:12:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオ人物再識別のための自己・協調注意ネットワーク（SCAN: Self-and-Collaborative Attention Network for Video Person Re-identification）</news:title>
   <news:publication_date>2026-05-26T19:12:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694597</loc>
  <lastmod>2026-05-26T19:11:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で可視化する銀河形態の隠れた特徴（Visualizing the Hidden Features of Galaxy Morphology with Machine Learning）</news:title>
   <news:publication_date>2026-05-26T19:11:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694595</loc>
  <lastmod>2026-05-26T19:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー記述子による点群の整合化を高める手法（Learning and Matching Multi-View Descriptors for Registration of Point Clouds）</news:title>
   <news:publication_date>2026-05-26T19:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694593</loc>
  <lastmod>2026-05-26T19:11:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNSトラフィックの時系列デインターリービング（Time Series Deinterleaving of DNS Traffic）</news:title>
   <news:publication_date>2026-05-26T19:11:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694591</loc>
  <lastmod>2026-05-26T19:11:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みスパースカーネルネットワーク（Convolutional Sparse Kernel Network for Unsupervised Medical Image Analysis）</news:title>
   <news:publication_date>2026-05-26T19:11:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694589</loc>
  <lastmod>2026-05-26T19:10:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル間フロー類似度による自己教師あり学習（Cross Pixel Optical Flow Similarity for Self-Supervised Learning）</news:title>
   <news:publication_date>2026-05-26T19:10:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694587</loc>
  <lastmod>2026-05-26T18:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラム平滑化による効率的なファジング（NEUZZ: Efficient Fuzzing with Neural Program Smoothing）</news:title>
   <news:publication_date>2026-05-26T18:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694585</loc>
  <lastmod>2026-05-26T18:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索とレコメンデーションの共同最適化が変える現場（Joint Modeling and Optimization of Search and Recommendation）</news:title>
   <news:publication_date>2026-05-26T18:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694583</loc>
  <lastmod>2026-05-26T18:19:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顕著性とセマンティックパーシングを併用した人物再識別の改良（Improved Person Re-Identification Based on Saliency and Semantic Parsing with Deep Neural Network Models）</news:title>
   <news:publication_date>2026-05-26T18:19:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694581</loc>
  <lastmod>2026-05-26T18:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非圧縮乱流におけるモデル由来の不確かさの特徴付け（CHARACTERIZATION OF MODEL-BASED UNCERTAINTIES IN INCOMPRESSIBLE TURBULENT FLOWS BY MACHINE LEARNING）</news:title>
   <news:publication_date>2026-05-26T18:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694579</loc>
  <lastmod>2026-05-26T18:18:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小限ハードウェアでの意味的セグメンテーションの深層学習（Deep Learning for Semantic Segmentation on Minimal Hardware）</news:title>
   <news:publication_date>2026-05-26T18:18:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694577</loc>
  <lastmod>2026-05-26T18:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノスケール導波路におけるフォノン‐ポラリトンとBrillouin誘起透過・不透過（Phonon-Polaritons in Nanoscale Waveguides）</news:title>
   <news:publication_date>2026-05-26T18:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694575</loc>
  <lastmod>2026-05-26T18:17:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク神経科学による脳–コンピュータ・インターフェース最適化（Network neuroscience for optimizing brain-computer interfaces）</news:title>
   <news:publication_date>2026-05-26T18:17:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694573</loc>
  <lastmod>2026-05-26T17:27:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離辞書学習の大域最適化と拡散MRIへの応用（GLOBAL OPTIMALITY IN SEPARABLE DICTIONARY LEARNING WITH APPLICATIONS TO THE ANALYSIS OF DIFFUSION MRI）</news:title>
   <news:publication_date>2026-05-26T17:27:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694571</loc>
  <lastmod>2026-05-26T17:26:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化された低消費電力IoTネットワーク：分散学習アプローチ（Self-organized Low-power IoT Networks: A Distributed Learning Approach）</news:title>
   <news:publication_date>2026-05-26T17:26:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694569</loc>
  <lastmod>2026-05-26T17:26:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし視覚特徴のためのディープクラスタリング（Deep Clustering for Unsupervised Learning of Visual Features）</news:title>
   <news:publication_date>2026-05-26T17:26:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694567</loc>
  <lastmod>2026-05-26T17:25:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で組合せ問題のモデリングを強化する（Boosting Combinatorial Problem Modeling with Machine Learning）</news:title>
   <news:publication_date>2026-05-26T17:25:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694565</loc>
  <lastmod>2026-05-26T17:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepInfによるソーシャル影響予測の革新（DeepInf: Social Influence Prediction with Deep Learning）</news:title>
   <news:publication_date>2026-05-26T17:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694563</loc>
  <lastmod>2026-05-26T17:25:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続値を含む確率的論理プログラムの学習（Learning Probabilistic Logic Programs in Continuous Domains）</news:title>
   <news:publication_date>2026-05-26T17:25:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694561</loc>
  <lastmod>2026-05-26T16:34:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングによる物体検出の総説（Object Detection with Deep Learning: A Review）</news:title>
   <news:publication_date>2026-05-26T16:34:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694559</loc>
  <lastmod>2026-05-26T16:34:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模推薦で振れ幅を個別制御する手法（Magnitude Bounded Matrix Factorisation for Recommender Systems）</news:title>
   <news:publication_date>2026-05-26T16:34:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694557</loc>
  <lastmod>2026-05-26T16:34:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ttH（トップクォーク対付随Higgs）探索の要点と経営判断への示唆（Searches for ttH production at CMS）</news:title>
   <news:publication_date>2026-05-26T16:34:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694555</loc>
  <lastmod>2026-05-26T16:33:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド領域における効率的な問合せと学習（Tractable Querying and Learning in Hybrid Domains via Sum-Product Networks）</news:title>
   <news:publication_date>2026-05-26T16:33:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694553</loc>
  <lastmod>2026-05-26T16:33:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ拡張とバギングによる深層ニューラルネットワークアンサンブルによる皮膚病変分類 (Deep neural network ensemble by data augmentation and bagging for skin lesion classification)</news:title>
   <news:publication_date>2026-05-26T16:33:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694551</loc>
  <lastmod>2026-05-26T16:32:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり特徴学習による筆跡識別の改善（Semi-supervised Feature Learning For Improving Writer Identification）</news:title>
   <news:publication_date>2026-05-26T16:32:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694549</loc>
  <lastmod>2026-05-26T16:32:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近リアルタイム海馬領域セグメンテーション（Near Real-time Hippocampus Segmentation Using Patch-based Canonical Neural Network）</news:title>
   <news:publication_date>2026-05-26T16:32:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694547</loc>
  <lastmod>2026-05-26T15:41:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタイムホライズンの太陽光予測を統一的に行う手法（Multi-time-horizon Solar Forecasting Using Recurrent Neural Network）</news:title>
   <news:publication_date>2026-05-26T15:41:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694545</loc>
  <lastmod>2026-05-26T15:41:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層強化学習によるマルチエージェント航行（Hierarchical Reinforcement Learning Framework towards Multi-agent Navigation）</news:title>
   <news:publication_date>2026-05-26T15:41:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694543</loc>
  <lastmod>2026-05-26T15:40:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>北天における極度逆転スペクトル外部銀河電波源の探索（Towards building a first northern-sky sample of ‘Extremely Inverted Spectrum Extragalactic Radio Sources (EISERS)’）</news:title>
   <news:publication_date>2026-05-26T15:40:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694541</loc>
  <lastmod>2026-05-26T15:40:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度マップからの3D人体姿勢推定――深度を用いたプロトタイプ線形結合によるアプローチ（3D human pose estimation from depth maps using a deep combination of poses）</news:title>
   <news:publication_date>2026-05-26T15:40:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694539</loc>
  <lastmod>2026-05-26T15:40:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース緩和正則化回帰の統一フレームワーク（A Unified Framework for Sparse Relaxed Regularized Regression: SR3）</news:title>
   <news:publication_date>2026-05-26T15:40:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694537</loc>
  <lastmod>2026-05-26T15:40:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションと部分的教師あり学習による3次元ハンドポーズ推定（3D Hand Pose Estimation using Simulation and Partial-Supervision with a Shared Latent Space）</news:title>
   <news:publication_date>2026-05-26T15:40:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694535</loc>
  <lastmod>2026-05-26T15:39:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SageMath用フィルタの開発とMoodle統合（Development of SageMath filter for Moodle）</news:title>
   <news:publication_date>2026-05-26T15:39:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694533</loc>
  <lastmod>2026-05-26T14:48:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バックキャストを使った中継協力で公平性を改善する手法（Backscatter-assisted Relaying in Wireless Powered Communications Network）</news:title>
   <news:publication_date>2026-05-26T14:48:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694531</loc>
  <lastmod>2026-05-26T14:48:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ML-Schemaが示す機械学習の意味論（ML-Schema: Exposing the Semantics of Machine Learning with Schemas and Ontologies）</news:title>
   <news:publication_date>2026-05-26T14:48:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694529</loc>
  <lastmod>2026-05-26T14:48:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNNの並列化を一歩進めるFlexFlow（Beyond Data and Model Parallelism for Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-26T14:48:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694527</loc>
  <lastmod>2026-05-26T14:47:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>準周期環境における一般化の理解（Generalization in quasi-periodic environments）</news:title>
   <news:publication_date>2026-05-26T14:47:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694525</loc>
  <lastmod>2026-05-26T14:47:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド変分オートエンコーダによる推薦の革新（A Hybrid Variational Autoencoder for Collaborative Filtering）</news:title>
   <news:publication_date>2026-05-26T14:47:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694523</loc>
  <lastmod>2026-05-26T14:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚環境における運動不変性（Motion Invariance in Visual Environments）</news:title>
   <news:publication_date>2026-05-26T14:47:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694521</loc>
  <lastmod>2026-05-26T14:47:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的に学習する混合モデル（Adversarially Learned Mixture Model）</news:title>
   <news:publication_date>2026-05-26T14:47:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694519</loc>
  <lastmod>2026-05-26T13:55:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M33の衛星銀河数をΛCDMで予測する（ΛCDM Predictions for the Satellite Population of M33）</news:title>
   <news:publication_date>2026-05-26T13:55:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694517</loc>
  <lastmod>2026-05-26T13:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔のランドマークのリアルタイム形状追跡（Real-Time Shape Tracking of Facial Landmarks）</news:title>
   <news:publication_date>2026-05-26T13:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694515</loc>
  <lastmod>2026-05-26T13:55:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的バッチで安定化したL-BFGSの加速手法（On the Acceleration of L-BFGS with Second-Order Information and Stochastic Batches）</news:title>
   <news:publication_date>2026-05-26T13:55:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694513</loc>
  <lastmod>2026-05-26T13:54:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現学習に基づくニューラルネットワークの正則化（Neural Networks Regularization Through Representation Learning）</news:title>
   <news:publication_date>2026-05-26T13:54:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694511</loc>
  <lastmod>2026-05-26T13:54:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的敵対的プライバシー（Generative Adversarial Privacy）</news:title>
   <news:publication_date>2026-05-26T13:54:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694509</loc>
  <lastmod>2026-05-26T13:54:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類器が個人の努力配分を変える仕組み（How Do Classifiers Induce Agents to Invest Effort Strategically?）</news:title>
   <news:publication_date>2026-05-26T13:54:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694507</loc>
  <lastmod>2026-05-26T13:54:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LeFlowによるTensorFlowからFPGAへの高位合成の実現（LeFlow: Enabling Flexible FPGA High-Level Synthesis of TensorFlow Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-26T13:54:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694504</loc>
  <lastmod>2026-05-26T13:02:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>L1適応制御と反復学習による高精度軌道追従の転移学習（Transfer Learning for High-Precision Trajectory Tracking Through L1 Adaptive Feedback and Iterative Learning）</news:title>
   <news:publication_date>2026-05-26T13:02:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694502</loc>
  <lastmod>2026-05-26T13:02:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人再識別（Person Re-Identification）に関する深層学習技術の総覧（Survey on Deep Learning Techniques for Person Re-Identification Task）</news:title>
   <news:publication_date>2026-05-26T13:02:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694500</loc>
  <lastmod>2026-05-26T13:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JWST北天の長期時変観測フィールドの選定（The James Webb Space Telescope North Ecliptic Pole Time-Domain Field – I: Field Selection of a JWST Community Field for Time-Domain Studies）</news:title>
   <news:publication_date>2026-05-26T13:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694498</loc>
  <lastmod>2026-05-26T13:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核子のスピン構造の理解を前進させた点（The Spin Structure of the Nucleon）</news:title>
   <news:publication_date>2026-05-26T13:00:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694496</loc>
  <lastmod>2026-05-26T13:00:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMを用いたゼロ速度検出による頑健な慣性航法（LSTM-Based Zero-Velocity Detection for Robust Inertial Navigation）</news:title>
   <news:publication_date>2026-05-26T13:00:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694494</loc>
  <lastmod>2026-05-26T13:00:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線環境の地図作成による位置把握の新枠組み（Channel Charting: Locating Users within the Radio Environment using Channel State Information）</news:title>
   <news:publication_date>2026-05-26T13:00:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694492</loc>
  <lastmod>2026-05-26T12:59:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>irbasis：虚時間グリーン関数の中間表現（irbasis: Open-source database and software for intermediate-representation basis functions of imaginary-time Green’s function）</news:title>
   <news:publication_date>2026-05-26T12:59:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694490</loc>
  <lastmod>2026-05-26T12:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース環境におけるテキスト分類とドメイン逆学習（Low-Resource Text Classification using Domain-Adversarial Learning）</news:title>
   <news:publication_date>2026-05-26T12:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694488</loc>
  <lastmod>2026-05-26T12:08:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レイアウトパターンサンプリングとホットスポット検出をつなぐバッチ型アクティブラーニング（Bridging the Gap Between Layout Pattern Sampling and Hotspot Detection via Batch Active Learning）</news:title>
   <news:publication_date>2026-05-26T12:08:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694486</loc>
  <lastmod>2026-05-26T12:07:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き地質モデルのパラメトリック生成（Parametric generation of conditional geological realizations using generative neural networks）</news:title>
   <news:publication_date>2026-05-26T12:07:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694484</loc>
  <lastmod>2026-05-26T12:06:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的談話関係認識のための深層強化表現（Deep Enhanced Representation for Implicit Discourse Relation Recognition）</news:title>
   <news:publication_date>2026-05-26T12:06:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694482</loc>
  <lastmod>2026-05-26T12:06:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市場状態の予測（Forecasting market states）</news:title>
   <news:publication_date>2026-05-26T12:06:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694480</loc>
  <lastmod>2026-05-26T12:06:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル説明からのモデル復元（Model Reconstruction from Model Explanations）</news:title>
   <news:publication_date>2026-05-26T12:06:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694478</loc>
  <lastmod>2026-05-26T12:05:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模視覚音声認識が切り開く現場応用の地平（LARGE-SCALE VISUAL SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-05-26T12:05:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694476</loc>
  <lastmod>2026-05-26T11:13:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール・スタック畳み込みによる白質高信号（WMH）セグメンテーションの堅牢化（Multi-Scale Convolutional-Stack Aggregation for Robust White Matter Hyperintensities Segmentation）</news:title>
   <news:publication_date>2026-05-26T11:13:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694474</loc>
  <lastmod>2026-05-26T11:13:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型ロバスト最適化によるシナリオベース確率的モデル予測制御（A Data-Driven Robust Optimization Approach to Scenario-Based Stochastic Model Predictive Control）</news:title>
   <news:publication_date>2026-05-26T11:13:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694472</loc>
  <lastmod>2026-05-26T11:12:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DLA: ニューラルネットワーク推論を加速するコンパイラとFPGAオーバーレイ（DLA: Compiler and FPGA Overlay for Neural Network Inference Acceleration）</news:title>
   <news:publication_date>2026-05-26T11:12:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694470</loc>
  <lastmod>2026-05-26T11:11:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境下のハイパーパラメータ探索基盤 Tune（Tune: A Research Platform for Distributed Model Selection and Training）</news:title>
   <news:publication_date>2026-05-26T11:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694468</loc>
  <lastmod>2026-05-26T11:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メムリスタ素子を用いたニューロモルフィック・インメモリ計算の実践（A neuromorphic systems approach to in-memory computing with non-ideal memristive devices: From mitigation to exploitation）</news:title>
   <news:publication_date>2026-05-26T11:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694466</loc>
  <lastmod>2026-05-26T11:11:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホモグラフィ先行を用いた学習ベースの自然な幾何整合（Learning-based Natural Geometric Matching with Homography Prior）</news:title>
   <news:publication_date>2026-05-26T11:11:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694464</loc>
  <lastmod>2026-05-26T11:10:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的損失と新資源によるファイングレインなエンティティ型付けとリンク（Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking）</news:title>
   <news:publication_date>2026-05-26T11:10:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694462</loc>
  <lastmod>2026-05-26T10:19:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前方急速度における孤立光子生成によるプロトン–原子核衝突の解析 (Forward rapidity isolated photon production in proton-nucleus collisions)</news:title>
   <news:publication_date>2026-05-26T10:19:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694460</loc>
  <lastmod>2026-05-26T10:19:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所学習則によるニューラルネットワークの忘却軽減（Local learning rules to attenuate forgetting in neural networks）</news:title>
   <news:publication_date>2026-05-26T10:19:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694458</loc>
  <lastmod>2026-05-26T10:19:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デンドログラムによるグラフ表現の再定義（Learning Graph Representations by Dendrograms）</news:title>
   <news:publication_date>2026-05-26T10:19:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694456</loc>
  <lastmod>2026-05-26T10:18:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CascadeCNNによるCNN量子化性能の限界突破（CascadeCNN: Pushing the Performance Limits of Quantisation in Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-26T10:18:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694454</loc>
  <lastmod>2026-05-26T10:18:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模量子鎖における多体局在と非局在化（Many-body localization and delocalization in large quantum chains）</news:title>
   <news:publication_date>2026-05-26T10:18:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694452</loc>
  <lastmod>2026-05-26T10:17:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク上の影響力ある拡散ノードを見つけるためのPerturb and Combine（Perturb and Combine to Identify Influential Spreaders in Real-World Networks）</news:title>
   <news:publication_date>2026-05-26T10:17:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694450</loc>
  <lastmod>2026-05-26T10:17:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイバーフィジカルシステムによるスタジアムの省エネ化（Cyber-Physical System For Energy Efficient Stadium Operation）</news:title>
   <news:publication_date>2026-05-26T10:17:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694448</loc>
  <lastmod>2026-05-26T09:25:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間連合ニューラル表現によるマルチセンサー知覚の相互作用のモデリングに向けて (Towards Modeling the Interaction of Spatial-Associative Neural Network Representations for Multisensory Perception)</news:title>
   <news:publication_date>2026-05-26T09:25:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694446</loc>
  <lastmod>2026-05-26T09:25:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフライン署名検証における疎表現技術の包括的研究（A Comprehensive Study of Sparse Representation Techniques for Offline Signature Verification）</news:title>
   <news:publication_date>2026-05-26T09:25:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694444</loc>
  <lastmod>2026-05-26T09:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層-aware逆強化学習の探求（Exploring Hierarchy-Aware Inverse Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-26T09:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694442</loc>
  <lastmod>2026-05-26T09:24:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mastodonデータで切り拓く対話行為と感情認識の再現性（Multi-task dialog act and sentiment recognition on Mastodon）</news:title>
   <news:publication_date>2026-05-26T09:24:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694440</loc>
  <lastmod>2026-05-26T09:24:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SGDの歩幅と損失の鋭さが示す学習の本質（On the relation between the sharpest directions of DNN loss and the SGD step length）</news:title>
   <news:publication_date>2026-05-26T09:24:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694438</loc>
  <lastmod>2026-05-26T09:24:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形と学習で見えるてんかん発作の自動検出（A hybrid automated detection of epileptic seizures in EEG based on wavelet and machine learning techniques）</news:title>
   <news:publication_date>2026-05-26T09:24:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694436</loc>
  <lastmod>2026-05-26T09:24:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルは異常検知で本当に優れているのか（Are generative deep models for novelty detection truly better?）</news:title>
   <news:publication_date>2026-05-26T09:24:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694434</loc>
  <lastmod>2026-05-26T08:33:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックホールのエントロピーと情報パラドックスの再検討 (Revisiting the black hole entropy and the information paradox)</news:title>
   <news:publication_date>2026-05-26T08:33:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694432</loc>
  <lastmod>2026-05-26T08:32:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ感情資源強化注意ネットワークによる感情分類の改良（A Multi-sentiment-resource Enhanced Attention Network for Sentiment Classification）</news:title>
   <news:publication_date>2026-05-26T08:32:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694430</loc>
  <lastmod>2026-05-26T08:32:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフを意識したオートエンコーダによるレコメンデーション（Computing recommendations via a Knowledge Graph-aware Autoencoder）</news:title>
   <news:publication_date>2026-05-26T08:32:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694428</loc>
  <lastmod>2026-05-26T08:31:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zoom-Net: 深層特徴間の相互作用を掘る視覚関係認識（Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition）</news:title>
   <news:publication_date>2026-05-26T08:31:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694426</loc>
  <lastmod>2026-05-26T08:31:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超グラフのスペクトル疎化の実装的意義（Spectral Sparsification of Hypergraphs）</news:title>
   <news:publication_date>2026-05-26T08:31:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694424</loc>
  <lastmod>2026-05-26T08:31:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の環境における物体認識（Recognition in Terra Incognita）</news:title>
   <news:publication_date>2026-05-26T08:31:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694422</loc>
  <lastmod>2026-05-26T08:31:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロジェクト駆動型建設における統合情報システムの展望（Envision of an Integrated Information System for Project-Driven Production in Construction）</news:title>
   <news:publication_date>2026-05-26T08:31:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694420</loc>
  <lastmod>2026-05-26T07:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>赤外検出器に残る「残像」を可視化する指標の提案（Persistence Characterisation of Teledyne H2RG detectors）</news:title>
   <news:publication_date>2026-05-26T07:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694418</loc>
  <lastmod>2026-05-26T07:39:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Behler–Parrinelloニューラルネットワークを用いた自己学習モンテカルロ法（Self-learning Monte Carlo method with Behler–Parrinello neural networks）</news:title>
   <news:publication_date>2026-05-26T07:39:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694416</loc>
  <lastmod>2026-05-26T07:39:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現場でのディープラーニング（Deep Learning in the Wild）</news:title>
   <news:publication_date>2026-05-26T07:39:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694414</loc>
  <lastmod>2026-05-26T07:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非ガウス成分解析とエントロピー手法（Non-Gaussian Component Analysis using Entropy Methods）</news:title>
   <news:publication_date>2026-05-26T07:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694412</loc>
  <lastmod>2026-05-26T07:39:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANが作る偽物の見分け方（TequilaGAN: How to easily identify GAN samples）</news:title>
   <news:publication_date>2026-05-26T07:39:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694410</loc>
  <lastmod>2026-05-26T07:39:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次データ下のガウス過程潜在変数モデルの逐次サンプリング（Sequential sampling of Gaussian process latent variable models）</news:title>
   <news:publication_date>2026-05-26T07:39:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694408</loc>
  <lastmod>2026-05-26T07:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強結合系での大規模キャット状態の高速増幅と位相再同期（Fast amplification and rephasing of entangled cat states in a qubit-oscillator system）</news:title>
   <news:publication_date>2026-05-26T07:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694406</loc>
  <lastmod>2026-05-26T06:48:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超細粒度エンティティタイピング（Ultra-Fine Entity Typing）</news:title>
   <news:publication_date>2026-05-26T06:48:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694404</loc>
  <lastmod>2026-05-26T06:47:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化解析辞書学習（Structured Analysis Dictionary Learning: Structure for Robustness）</news:title>
   <news:publication_date>2026-05-26T06:47:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694402</loc>
  <lastmod>2026-05-26T06:47:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メムリスタで作るパーセプトロン（Perceptrons from Memristors）</news:title>
   <news:publication_date>2026-05-26T06:47:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694400</loc>
  <lastmod>2026-05-26T06:47:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的再集計アルゴリズム（Probabilistic Re-aggregation Algorithm）</news:title>
   <news:publication_date>2026-05-26T06:47:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694398</loc>
  <lastmod>2026-05-26T06:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周囲のセグメンテーション文脈によるタイトボックスの探索（Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection）</news:title>
   <news:publication_date>2026-05-26T06:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694396</loc>
  <lastmod>2026-05-26T06:46:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォンを用いた医療モニタの数値読み取り（Utilizing Smartphone-Based Machine Learning in Medical Monitor Data Collection: Seven Segment Digit Recognition）</news:title>
   <news:publication_date>2026-05-26T06:46:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694394</loc>
  <lastmod>2026-05-26T06:46:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変の自動セグメンテーション（Automatic segmentation of skin lesions using deep learning）</news:title>
   <news:publication_date>2026-05-26T06:46:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694392</loc>
  <lastmod>2026-05-26T05:55:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在変数の崩壊を避ける生成スキップモデル（Avoiding Latent Variable Collapse with Generative Skip Models）</news:title>
   <news:publication_date>2026-05-26T05:55:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694390</loc>
  <lastmod>2026-05-26T05:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コントラスト埋め込みによる距離学習アルゴリズム（Algorithms for Metric Learning via Contrastive Embeddings）</news:title>
   <news:publication_date>2026-05-26T05:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694388</loc>
  <lastmod>2026-05-26T05:46:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep LOFAR 150 MHz観測によるBoötes領域の低周波数深宇宙地図（Deep LOFAR 150 MHz imaging of the Boötes field: Unveiling the faint low-frequency sky）</news:title>
   <news:publication_date>2026-05-26T05:46:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694386</loc>
  <lastmod>2026-05-26T05:45:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可逆な一般化同期による暗黙学習のメカニズム（Invertible generalized synchronization: A putative mechanism for implicit learning in biological and artificial neural systems）</news:title>
   <news:publication_date>2026-05-26T05:45:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694384</loc>
  <lastmod>2026-05-26T05:45:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>模倣学習軌道の予測可能性（Predictability of the imitative learning trajectories）</news:title>
   <news:publication_date>2026-05-26T05:45:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694382</loc>
  <lastmod>2026-05-26T05:45:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴設計に依存しないOCTボリュームからの緑内障検出（A feature agnostic approach for glaucoma detection in OCT volumes）</news:title>
   <news:publication_date>2026-05-26T05:45:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694380</loc>
  <lastmod>2026-05-26T05:44:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>操作ビデオから接触と動きを抽出する技術（Extracting Contact and Motion from Manipulation Videos）</news:title>
   <news:publication_date>2026-05-26T05:44:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694378</loc>
  <lastmod>2026-05-26T04:53:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声と顔画像のクロスモーダル照合のための分離写像ネットワーク（Disjoint Mapping Network for Cross-modal Matching of Voices and Faces）</news:title>
   <news:publication_date>2026-05-26T04:53:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694376</loc>
  <lastmod>2026-05-26T04:53:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次世代育成：工学分野のラーニングアシスタント・プログラムの成果 (Cultivating the Next Generation: Outcomes from a Learning Assistant Program in Engineering)</news:title>
   <news:publication_date>2026-05-26T04:53:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694374</loc>
  <lastmod>2026-05-26T04:53:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変量を比較することで導く最適な照合・検索戦略（Optimal Strategies for Matching and Retrieval Problems by Comparing Covariates）</news:title>
   <news:publication_date>2026-05-26T04:53:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694372</loc>
  <lastmod>2026-05-26T04:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DP-GP-LVMで学ぶ多変量依存構造の自動発見（DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures）</news:title>
   <news:publication_date>2026-05-26T04:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694370</loc>
  <lastmod>2026-05-26T04:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>撮像段階の工夫でAIの超解像を強化する（Optimal Physical Preprocessing for Example-Based Super-Resolution）</news:title>
   <news:publication_date>2026-05-26T04:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694368</loc>
  <lastmod>2026-05-26T04:52:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体の視点合成のための潜在変換（Latent Transformations for Object View Points Synthesis）</news:title>
   <news:publication_date>2026-05-26T04:52:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694366</loc>
  <lastmod>2026-05-26T04:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TDOAを用いた位置推定と確率的勾配法の実務的示唆（TDOA-based Localization via Stochastic Gradient Descent Variants）</news:title>
   <news:publication_date>2026-05-26T04:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694364</loc>
  <lastmod>2026-05-26T04:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心筋ひずみ解析における学習ベースの正則化とドメイン適応の可能性（Learning-based Regularization for Cardiac Strain Analysis with Ability for Domain Adaptation）</news:title>
   <news:publication_date>2026-05-26T04:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694362</loc>
  <lastmod>2026-05-26T04:00:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実務で直面するアクティブラーニングの障害（Practical Obstacles to Deploying Active Learning）</news:title>
   <news:publication_date>2026-05-26T04:00:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694360</loc>
  <lastmod>2026-05-26T04:00:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生活満足度調査における特徴選択による性別分類（Feature Selection for Gender Classification in TUIK Life Satisfaction Survey）</news:title>
   <news:publication_date>2026-05-26T04:00:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694358</loc>
  <lastmod>2026-05-26T03:59:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非エルゴード拡張状態を介した効率的なポピュレーション転送（Efficient population transfer via non-ergodic extended states in quantum spin glass）</news:title>
   <news:publication_date>2026-05-26T03:59:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694356</loc>
  <lastmod>2026-05-26T03:59:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hydranetによる回帰ニューラルネットのデータ拡張（Hydranet: Data Augmentation for Regression Neural Networks）</news:title>
   <news:publication_date>2026-05-26T03:59:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694354</loc>
  <lastmod>2026-05-26T03:59:01Z</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>2026-05-26T03:59:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694352</loc>
  <lastmod>2026-05-26T03:58:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルゴリズムの説明責任評価モデル（A Model for Evaluating Algorithmic Systems Accountability）</news:title>
   <news:publication_date>2026-05-26T03:58:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694350</loc>
  <lastmod>2026-05-26T03:07:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェット画像とN-subjettinessの比較が示す本質（Reports of My Demise Are Greatly Exaggerated: N-subjettiness Taggers Take On Jet Images）</news:title>
   <news:publication_date>2026-05-26T03:07:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694348</loc>
  <lastmod>2026-05-26T03:07:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽子線によるハイブリッドCMOS検出器の損傷実験（Proton Radiation Damage Experiment on a Hybrid CMOS Detector）</news:title>
   <news:publication_date>2026-05-26T03:07:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694346</loc>
  <lastmod>2026-05-26T03:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QA向けRNNの精度改善に効く名詞タグ付け（Improving on Q &amp;amp; A Recurrent Neural Networks Using Noun-Tagging）</news:title>
   <news:publication_date>2026-05-26T03:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694344</loc>
  <lastmod>2026-05-26T03:06:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲームダイナミクス改善のための負のモメンタム（Negative Momentum for Improved Game Dynamics）</news:title>
   <news:publication_date>2026-05-26T03:06:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694342</loc>
  <lastmod>2026-05-26T03:06:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダージェット平面（The Lund Jet Plane）</news:title>
   <news:publication_date>2026-05-26T03:06:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694340</loc>
  <lastmod>2026-05-26T03:06:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習がセキュリティに出会う時（When deep learning meets security）</news:title>
   <news:publication_date>2026-05-26T03:06:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694338</loc>
  <lastmod>2026-05-26T03:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イメージで目標を想像する視覚強化学習（Visual Reinforcement Learning with Imagined Goals）</news:title>
   <news:publication_date>2026-05-26T03:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694336</loc>
  <lastmod>2026-05-26T02:14:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボトルネックシミュレータ：モデルベース深層強化学習の手法（The Bottleneck Simulator: A Model-based Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-05-26T02:14:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694334</loc>
  <lastmod>2026-05-26T02:14:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルな畳み込み辞書学習と制約付き再帰スパースオートエンコーダ（Scalable Convolutional Dictionary Learning with Constrained Recurrent Sparse Auto-Encoders）</news:title>
   <news:publication_date>2026-05-26T02:14:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694332</loc>
  <lastmod>2026-05-26T02:14:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANにおける正則化と正規化の大規模比較（A Large-Scale Study on Regularization and Normalization in GANs）</news:title>
   <news:publication_date>2026-05-26T02:14:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694330</loc>
  <lastmod>2026-05-26T02:14:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>横断データから多次元の老化速度を推定する（Inferring Multidimensional Rates of Aging from Cross-Sectional Data）</news:title>
   <news:publication_date>2026-05-26T02:14:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694328</loc>
  <lastmod>2026-05-26T02:13:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相を保つ潜在表現による変分オートエンコーダの探究（Explorations in Homeomorphic Variational Auto-Encoding）</news:title>
   <news:publication_date>2026-05-26T02:13:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694326</loc>
  <lastmod>2026-05-26T02:13:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類における貪欲選択で高精度と高疎性を両立する手法（Orthogonal Matching Pursuit for Text Classification）</news:title>
   <news:publication_date>2026-05-26T02:13:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694324</loc>
  <lastmod>2026-05-26T02:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン専門家の時間を効率的に使う関係抽出法（Making Efficient Use of a Domain Expert’s Time in Relation Extraction）</news:title>
   <news:publication_date>2026-05-26T02:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694322</loc>
  <lastmod>2026-05-26T01:22:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実写真のノイズ除去を前進させたCBDNet（Toward Convolutional Blind Denoising of Real Photographs）</news:title>
   <news:publication_date>2026-05-26T01:22:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694320</loc>
  <lastmod>2026-05-26T01:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HyperNetsによる空間変換の学習（HyperNets: Learning to manipulate network parameters）</news:title>
   <news:publication_date>2026-05-26T01:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694318</loc>
  <lastmod>2026-05-26T01:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換に基づく非教師付き点登録による未シード低ランクグラフ写像（Unseeded low-rank graph matching by transform-based unsupervised point registration）</news:title>
   <news:publication_date>2026-05-26T01:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694316</loc>
  <lastmod>2026-05-26T01:21:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約整合学習のためのライブラリ（A Library for Constraint Consistent Learning）</news:title>
   <news:publication_date>2026-05-26T01:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694314</loc>
  <lastmod>2026-05-26T01:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スクリブルだけで医療画像のセグメンテーションを学ぶ（Learning to Segment Medical Images with Scribble-Supervision Alone）</news:title>
   <news:publication_date>2026-05-26T01:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694312</loc>
  <lastmod>2026-05-26T01:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロダクト量子化を組み込んだVQ-VAEによる画像検索向けコードブック学習（LEARNING PRODUCT CODEBOOKS USING VECTOR-QUANTIZED AUTOENCODERS FOR IMAGE RETRIEVAL）</news:title>
   <news:publication_date>2026-05-26T01:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694310</loc>
  <lastmod>2026-05-26T01:20:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーム学習をPythonで民主化した基盤—Scikit-Multiflowの意義と実務的示唆 (Scikit-Multiflow: A Multi-output Streaming Framework)</news:title>
   <news:publication_date>2026-05-26T01:20:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694308</loc>
  <lastmod>2026-05-26T00:30:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超巨星の不規則な明るさ変動が示す内部波動の手がかり（A BRITE view on the massive O-type supergiant V973 Scorpii: Hints towards internal gravity waves or subsurface convection zones）</news:title>
   <news:publication_date>2026-05-26T00:30:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694306</loc>
  <lastmod>2026-05-26T00:29:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み平均に基づく一貫性ターゲットを用いた深層半教師ありセグメンテーション（Deep semi-supervised segmentation with weight-averaged consistency targets）</news:title>
   <news:publication_date>2026-05-26T00:29:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694304</loc>
  <lastmod>2026-05-26T00:29:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘッブ則を用いた高速重みのメタラーニング (Metalearning with Hebbian Fast Weights)</news:title>
   <news:publication_date>2026-05-26T00:29:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694302</loc>
  <lastmod>2026-05-26T00:28:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現変換を組み合わせることで汎化する仕組み（Automatically Composing Representation Transformations as a Means for Generalization）</news:title>
   <news:publication_date>2026-05-26T00:28:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694300</loc>
  <lastmod>2026-05-26T00:28:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子環境のクラスタリングによる機械学習強化全域最適化（Machine learning enhanced global optimization by clustering local environments to enable bundled atomic energies）</news:title>
   <news:publication_date>2026-05-26T00:28:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694298</loc>
  <lastmod>2026-05-26T00:27:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶するアルゴリズム：モデル反転攻撃とデータ保護法（Algorithms that remember: model inversion attacks and data protection law）</news:title>
   <news:publication_date>2026-05-26T00:27:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694296</loc>
  <lastmod>2026-05-26T00:27:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能なルールベース予測手法の実務的意義（RIPE: Rule Induction Partitioning Estimator）</news:title>
   <news:publication_date>2026-05-26T00:27:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694294</loc>
  <lastmod>2026-05-25T23:36:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wold過程を用いた因果関係推定の高速化（Fast Estimation of Causal Interactions using Wold Processes）</news:title>
   <news:publication_date>2026-05-25T23:36:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694292</loc>
  <lastmod>2026-05-25T23:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分近接法の確率論的視点（THE INCREMENTAL PROXIMAL METHOD: A PROBABILISTIC PERSPECTIVE）</news:title>
   <news:publication_date>2026-05-25T23:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694290</loc>
  <lastmod>2026-05-25T23:35:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込み特徴に内在する視覚的注目（Visual Attention driven by Convolutional Features）</news:title>
   <news:publication_date>2026-05-25T23:35:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694288</loc>
  <lastmod>2026-05-25T23:34:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所ハミルトニアンの復元法（Learning a Local Hamiltonian from Local Measurements）</news:title>
   <news:publication_date>2026-05-25T23:34:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694286</loc>
  <lastmod>2026-05-25T23:34:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データ分類に強い学習設計の勘所（Deep Learning for Imbalance Data Classification using Class Expert Generative Adversarial Network）</news:title>
   <news:publication_date>2026-05-25T23:34:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694284</loc>
  <lastmod>2026-05-25T23:33:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮データ上での分散クラスタリング — クラスタ数不明でも動く手法（Decentralized Clustering on Compressed Data without Prior Knowledge of the Number of Clusters）</news:title>
   <news:publication_date>2026-05-25T23:33:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694282</loc>
  <lastmod>2026-05-25T23:33:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大不変データ摂動の最大化（Maximizing Invariant Data Perturbation with Stochastic Optimization）</news:title>
   <news:publication_date>2026-05-25T23:33:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694280</loc>
  <lastmod>2026-05-25T22:42:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付きランダム化最短経路フレームワークによる最適探索（A Constrained Randomized Shortest-Paths Framework for Optimal Exploration）</news:title>
   <news:publication_date>2026-05-25T22:42:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694278</loc>
  <lastmod>2026-05-25T22:42:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XMMPZCAT: X線源のフォトメトリック赤方偏移カタログの意義と応用（XMMPZCAT: A catalogue of photometric redshifts for X-ray sources）</news:title>
   <news:publication_date>2026-05-25T22:42:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694276</loc>
  <lastmod>2026-05-25T22:41:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における注目領域検出を3D畳み込みで捉える（Video Saliency Detection by 3D Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-25T22:41:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694274</loc>
  <lastmod>2026-05-25T22:41:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴選択がバグ数予測に与える影響（The Impact of Feature Selection on Predicting the Number of Bugs）</news:title>
   <news:publication_date>2026-05-25T22:41:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694272</loc>
  <lastmod>2026-05-25T22:41:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑モデルにおける変分推論のための高速かつ単純な自然勾配降下（Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex Models）</news:title>
   <news:publication_date>2026-05-25T22:41:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694270</loc>
  <lastmod>2026-05-25T22:41:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴のリプレイを用いたニューラルネットワーク訓練（Training Neural Networks Using Features Replay）</news:title>
   <news:publication_date>2026-05-25T22:41:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694268</loc>
  <lastmod>2026-05-25T22:40:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コード構造とCodeRankによる概念位置検索の改良（Improved Query Reformulation for Concept Location using CodeRank and Document Structures）</news:title>
   <news:publication_date>2026-05-25T22:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694266</loc>
  <lastmod>2026-05-25T21:49:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>価値関数の合成によるスキル再利用（Will it Blend? Composing Value Functions in Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-25T21:49:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694264</loc>
  <lastmod>2026-05-25T21:43:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COのRu(0001)表面での異常な付着と散乱の支配因子（Strong anisotropic interaction controls unusual sticking and scattering of CO at Ru(0001))</news:title>
   <news:publication_date>2026-05-25T21:43:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694262</loc>
  <lastmod>2026-05-25T21:43:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>劇場公開映画の予測分析：予告編の深層映像表現による解析（Analysis System for Theatrical Movie Releases Based on Movie Trailer Deep Video Representation）</news:title>
   <news:publication_date>2026-05-25T21:43:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694260</loc>
  <lastmod>2026-05-25T21:43:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2D Bridged U-netによる前立腺領域分割の進化（Prostate Segmentation using 2D Bridged U-net）</news:title>
   <news:publication_date>2026-05-25T21:43:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694258</loc>
  <lastmod>2026-05-25T21:42:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ効率の良いハードラベル・ブラックボックス攻撃（Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach）</news:title>
   <news:publication_date>2026-05-25T21:42:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694256</loc>
  <lastmod>2026-05-25T21:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語の意味変化を追跡する時間反映型テキスト表現（Tracking the Evolution of Words with Time-reflective Text Representations）</news:title>
   <news:publication_date>2026-05-25T21:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694254</loc>
  <lastmod>2026-05-25T21:41:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>円筒対称非対称薄殻ワームホールの安定性（The Stability of Asymmetric Cylindrical Thin-Shell Wormholes）</news:title>
   <news:publication_date>2026-05-25T21:41:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694252</loc>
  <lastmod>2026-05-25T20:50:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通信規格教育の実践手法（Teaching Telecommunication Standards: Bridging the Gap Between Theory and Practice）</news:title>
   <news:publication_date>2026-05-25T20:50:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694250</loc>
  <lastmod>2026-05-25T20:50:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所最適解下での統計的推論（Statistical Inference with Local Optima）</news:title>
   <news:publication_date>2026-05-25T20:50:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694248</loc>
  <lastmod>2026-05-25T20:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像における人物再識別を変える技術統合（Video-based Person Re-identification via 3D Convolutional Networks and Non-local Attention）</news:title>
   <news:publication_date>2026-05-25T20:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694246</loc>
  <lastmod>2026-05-25T20:49:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時コヒーレント構造カラーリングによる可解釈なクラスタリング（Simultaneous coherent structure coloring facilitates interpretable clustering）</news:title>
   <news:publication_date>2026-05-25T20:49:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694244</loc>
  <lastmod>2026-05-25T20:49:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブロック座標上昇法によるBurer–Monteiro法の収束率（Convergence Rate of Block-Coordinate Maximization Burer-Monteiro Method for Solving Large SDPs）</news:title>
   <news:publication_date>2026-05-25T20:49:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694242</loc>
  <lastmod>2026-05-25T20:48:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有界次数の確率的ブロックモデルに対する尤度比型検定（A Likelihood-Ratio Type Test for Stochastic Block Models with Bounded Degrees）</news:title>
   <news:publication_date>2026-05-25T20:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694240</loc>
  <lastmod>2026-05-25T20:48:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多視点ニューラルアーキテクチャによる推薦システムの進化（Multi-Perspective Neural Architecture for Recommendation System）</news:title>
   <news:publication_date>2026-05-25T20:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694238</loc>
  <lastmod>2026-05-25T19:57:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乱流歪み除去ネットワーク（Subsampled Turbulence Removal Network）</news:title>
   <news:publication_date>2026-05-25T19:57:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694236</loc>
  <lastmod>2026-05-25T19:57:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類木と隠れ半マルコフモデルによるプロセス発見（Process Discovery using Classification Tree Hidden Semi-Markov Model）</news:title>
   <news:publication_date>2026-05-25T19:57:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694234</loc>
  <lastmod>2026-05-25T19:57:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔の部分情報を組み合わせる表情認識の新潮流（Multi-Region Ensemble Convolutional Neural Network for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-05-25T19:57:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694232</loc>
  <lastmod>2026-05-25T19:56:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラスベースのデノイジングオートエンコーダと混合画素拡張によるハイパースペクトル画像分類（DEEP LEARNING HYPERSPECTRAL IMAGE CLASSIFICATION USING MULTIPLE CLASS–BASED DENOISING AUTOENCODERS, MIXED PIXEL TRAINING AUGMENTATION, AND MORPHOLOGICAL OPERATIONS）</news:title>
   <news:publication_date>2026-05-25T19:56:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694230</loc>
  <lastmod>2026-05-25T19:56:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース制約付き非負値行列因子分解によるトピック拡散検出（Topic Diffusion Discovery based on Sparseness-constrained Non-negative Matrix Factorization）</news:title>
   <news:publication_date>2026-05-25T19:56:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694228</loc>
  <lastmod>2026-05-25T19:55:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MIMO DF中継路における深層学習検出ネットワーク（Deep Learning Detection Networks in MIMO Decode-Forward Relay Channels）</news:title>
   <news:publication_date>2026-05-25T19:55:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694226</loc>
  <lastmod>2026-05-25T19:55:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高齢者支援する感情応答型ロボット伴走者（An Affective Robot Companion for Assisting the Elderly in a Cognitive Game Scenario）</news:title>
   <news:publication_date>2026-05-25T19:55:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694224</loc>
  <lastmod>2026-05-25T19:04:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クライアント側差分プライバシーを実現する Draw and Discard 機械学習（Differentially-Private “Draw and Discard” Machine Learning）</news:title>
   <news:publication_date>2026-05-25T19:04:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694222</loc>
  <lastmod>2026-05-25T18:54:35Z</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における深層学習の最前線と課題（STATE–OF–THE–ART AND GAPS FOR DEEP LEARNING ON LIMITED TRAINING DATA IN REMOTE SENSING）</news:title>
   <news:publication_date>2026-05-25T18:54:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694220</loc>
  <lastmod>2026-05-25T18:54:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Landsatと全球標高データを融合した三次元都市構造マッピング（Mapping Three-dimensional Urban Structure by Fusing Landsat and Global Elevation Data）</news:title>
   <news:publication_date>2026-05-25T18:54:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694218</loc>
  <lastmod>2026-05-25T18:53:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deepwoundを用いた術後創傷評価と手術部位監視（Deepwound: Automated Postoperative Wound Assessment and Surgical Site Surveillance through Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-25T18:53:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694216</loc>
  <lastmod>2026-05-25T18:53:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTにおける情報鮮度の最適化（Joint Status Sampling and Updating for Minimizing Age of Information in the Internet of Things）</news:title>
   <news:publication_date>2026-05-25T18:53:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694214</loc>
  <lastmod>2026-05-25T18:52:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シリウスAbの探索：コロナグラフィー熱赤外高コントラストイメージングにおけるアルゴリズム的背景推定とPSF推定性能の比較 (The hunt for Sirius Ab: Comparison of algorithmic sky and PSF estimation performance in deep coronagraphic thermal-IR high contrast imaging)</news:title>
   <news:publication_date>2026-05-25T18:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694212</loc>
  <lastmod>2026-05-25T18:52:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なキーワード検出における時間遅延ニューラルネットワークの活用（Efficient keyword spotting using time delay neural networks）</news:title>
   <news:publication_date>2026-05-25T18:52:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694210</loc>
  <lastmod>2026-05-25T18:01:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像における汎用的肺領域分割の枠組み（A Generic Approach to Lung Field Segmentation from Chest Radiographs using Deep Space and Shape Learning）</news:title>
   <news:publication_date>2026-05-25T18:01:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694208</loc>
  <lastmod>2026-05-25T18:01:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUアーキテクチャ向けデータ並列ハッシュ法の概観（Data-Parallel Hashing Techniques for GPU Architectures）</news:title>
   <news:publication_date>2026-05-25T18:01:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694206</loc>
  <lastmod>2026-05-25T18:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-25T18:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694204</loc>
  <lastmod>2026-05-25T18:00:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化ベイズ型ガウス過程潜在変数モデルによる高次元逆問題の扱い（Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversion）</news:title>
   <news:publication_date>2026-05-25T18:00:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694202</loc>
  <lastmod>2026-05-25T17:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANを使った多様体正則化による半教師あり学習（Manifold regularization with GANs for semi-supervised learning）</news:title>
   <news:publication_date>2026-05-25T17:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694200</loc>
  <lastmod>2026-05-25T17:59:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的事前分布による位相復元（Phase Retrieval Under a Generative Prior）</news:title>
   <news:publication_date>2026-05-25T17:59:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694198</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694196</loc>
  <lastmod>2026-05-25T17:08:06Z</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>2026-05-25T17:08:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694194</loc>
  <lastmod>2026-05-25T17:07:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コーデッド・データシャッフリングの基礎限界（On the Fundamental Limits of Coded Data Shufﬂing for Distributed Machine Learning）</news:title>
   <news:publication_date>2026-05-25T17:07:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694192</loc>
  <lastmod>2026-05-25T17:07:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization（Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization）</news:title>
   <news:publication_date>2026-05-25T17:07:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694190</loc>
  <lastmod>2026-05-25T17:06:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業用マルチセンサー衝突回避におけるLiDARとカメラ検出の融合（LiDAR and Camera Detection Fusion in a Real-Time Industrial Multi-Sensor Collision Avoidance System）</news:title>
   <news:publication_date>2026-05-25T17:06:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694188</loc>
  <lastmod>2026-05-25T17:06:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-25T17:06:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694186</loc>
  <lastmod>2026-05-25T17:06:07Z</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>2026-05-25T17:06:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694184</loc>
  <lastmod>2026-05-25T17:05:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepMoveによる場所表現の学習（DeepMove: Learning Place Representations through Large Scale Movement Data）</news:title>
   <news:publication_date>2026-05-25T17:05:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694182</loc>
  <lastmod>2026-05-25T16:14:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モールス符号データセットと機械学習への応用（Morse Code Datasets for Machine Learning）</news:title>
   <news:publication_date>2026-05-25T16:14:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/694180</loc>
  <lastmod>2026-05-25T16:14:09Z</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>2026-05-25T16:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/694178</loc>
  <lastmod>2026-05-25T16:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークにおける抽象推論の計測（Measuring abstract reasoning in neural networks）</news:title>
   <news:publication_date>2026-05-25T16:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/694176</loc>
  <lastmod>2026-05-25T16:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-25T16:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694174</loc>
  <lastmod>2026-05-25T16:13:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-25T16:13:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694172</loc>
  <lastmod>2026-05-25T16:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の位置ベース類似度を組み込んだ協調ランキングによる店舗提案（A Collaborative Ranking Model with Multiple Location-based Similarities for Venue Suggestion）</news:title>
   <news:publication_date>2026-05-25T16:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694170</loc>
  <lastmod>2026-05-25T16:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-25T16:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694168</loc>
  <lastmod>2026-05-25T15:21:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔軟な深層学習特化のためのハードウェア・ソフトウェア設計図（A Hardware-Software Blueprint for Flexible Deep Learning Specialization）</news:title>
   <news:publication_date>2026-05-25T15:21:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694166</loc>
  <lastmod>2026-05-25T15:12:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散変分表現学習（Distributed Variational Representation Learning）</news:title>
   <news:publication_date>2026-05-25T15:12:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694164</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>2026-05-25T15:11:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694162</loc>
  <lastmod>2026-05-25T15:11:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠中の脳波イベントを一括検出する深層学習アーキテクチャ（A DEEP LEARNING ARCHITECTURE TO DETECT EVENTS IN EEG SIGNALS DURING SLEEP）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694160</loc>
  <lastmod>2026-05-25T15:11:20Z</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>2026-05-25T15:11:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694158</loc>
  <lastmod>2026-05-25T15:11:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Indy：産業施設での空間ナビゲーション技能を鍛える仮想現実ゲーム（Indy: a virtual reality multi-player game for navigation skills training）</news:title>
   <news:publication_date>2026-05-25T15:11:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694156</loc>
  <lastmod>2026-05-25T15:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測データに基づく連続・多次元意思決定の最適化（Optimization over Continuous and Multi-dimensional Decisions with Observational Data）</news:title>
   <news:publication_date>2026-05-25T15:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694154</loc>
  <lastmod>2026-05-25T14:19:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイバーバンドルを用いた現場波面補正による二光子レンズレスマイクロ内視鏡（Two-Photon Lensless Micro-endoscopy with in-situ Wavefront Correction）</news:title>
   <news:publication_date>2026-05-25T14:19:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694152</loc>
  <lastmod>2026-05-25T14:10:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>死後（ポストモーテム）虹彩画像の自動セグメンテーション（Post-mortem Iris Image Segmentation with Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-25T14:10:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694150</loc>
  <lastmod>2026-05-25T14:10:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復評価を導入したLSTMの設計思想と実装的示唆（Iterative evaluation of LSTM cells）</news:title>
   <news:publication_date>2026-05-25T14:10:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694148</loc>
  <lastmod>2026-05-25T14:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実数空間における木構造の線形表現（Trees in the Real Field）</news:title>
   <news:publication_date>2026-05-25T14:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694146</loc>
  <lastmod>2026-05-25T14:09:19Z</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>2026-05-25T14:09:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694144</loc>
  <lastmod>2026-05-25T14:08:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-25T14:08:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694142</loc>
  <lastmod>2026-05-25T14:08:21Z</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>2026-05-25T14:08:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694140</loc>
  <lastmod>2026-05-25T13:16:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/694138</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変精度LSTMをFPGAで加速するための設計とライブラリ拡張（FINN-L: Library Extensions and Design Trade-off Analysis for Variable Precision LSTM Networks on FPGAs）</news:title>
   <news:publication_date>2026-05-25T13:14:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694132</loc>
  <lastmod>2026-05-25T13:14:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブルPPGによる心臓異常の検出（Recognising Cardiac Abnormalities in Wearable Device Photoplethysmography (PPG) with Deep Learning）</news:title>
   <news:publication_date>2026-05-25T13:14:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694130</loc>
  <lastmod>2026-05-25T13:14:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一走行からキロメートル規模の実装可能なナビゲーション方策を学習する（Learning Deployable Navigation Policies at Kilometer Scale from a Single Traversal）</news:title>
   <news:publication_date>2026-05-25T13:14:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694128</loc>
  <lastmod>2026-05-25T13:13:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>従業員離職の予測と予防介入（Proactive Intervention to Downtrend Employee Attrition using Artificial Intelligence Techniques）</news:title>
   <news:publication_date>2026-05-25T13:13:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694126</loc>
  <lastmod>2026-05-25T12:21:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔軟なゲートを持つ再帰型ニューラルネットワーク（Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions）</news:title>
   <news:publication_date>2026-05-25T12:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694124</loc>
  <lastmod>2026-05-25T12:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>死後虹彩の提示攻撃検出（Presentation Attack Detection for Cadaver Iris）</news:title>
   <news:publication_date>2026-05-25T12:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694122</loc>
  <lastmod>2026-05-25T12:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胎児腹部大動脈のリアルタイム径測定に向けた時間方向畳み込みネットワーク（Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound）</news:title>
   <news:publication_date>2026-05-25T12:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694120</loc>
  <lastmod>2026-05-25T12:19:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3C 279の史上最大ガンマ線フレアの観測と理論的課題（Challenges in reconciling observations and theory of the brightest high-energy flare ever of 3C 279）</news:title>
   <news:publication_date>2026-05-25T12:19:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694118</loc>
  <lastmod>2026-05-25T12:19:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>死後虹彩認識における画像特徴の知覚（Perception of Image Features in Post-Mortem Iris Recognition: Humans vs Machines）</news:title>
   <news:publication_date>2026-05-25T12:19:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694116</loc>
  <lastmod>2026-05-25T12:19:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アパレル属性分類のための二層混合ネットワークアンサンブル（Two-Layer Mixture Network Ensemble for Apparel Attributes Classification）</news:title>
   <news:publication_date>2026-05-25T12:19:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694114</loc>
  <lastmod>2026-05-25T12:19:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeSTNetによる空間変形の解消と頑健化（DeSTNet: Densely Fused Spatial Transformer Networks）</news:title>
   <news:publication_date>2026-05-25T12:19:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694112</loc>
  <lastmod>2026-05-25T11:27:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異点回避の学習（Learning Singularity Avoidance）</news:title>
   <news:publication_date>2026-05-25T11:27:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694110</loc>
  <lastmod>2026-05-25T11:26:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負値行列分解のための改良SVD初期化と低ランク補正（Improved SVD-based Initialization for Nonnegative Matrix Factorization using Low-Rank Correction）</news:title>
   <news:publication_date>2026-05-25T11:26:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694108</loc>
  <lastmod>2026-05-25T11:26:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANにおける壊滅的忘却とモード崩壊の関係（Catastrophic forgetting and mode collapse in GANs）</news:title>
   <news:publication_date>2026-05-25T11:26:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694106</loc>
  <lastmod>2026-05-25T11:25:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠測データ下の因果探索（Causal Discovery in the Presence of Missing Data）</news:title>
   <news:publication_date>2026-05-25T11:25:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694104</loc>
  <lastmod>2026-05-25T11:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によるエンドツーエンド・クラスタリング（Learning Neural Models for End-to-End Clustering）</news:title>
   <news:publication_date>2026-05-25T11:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694102</loc>
  <lastmod>2026-05-25T11:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Medusaが示すメモリ相互接続の新しい設計（Medusa: A Scalable Interconnect for Many-Port DNN Accelerators and Wide DRAM Controller Interfaces）</news:title>
   <news:publication_date>2026-05-25T11:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694100</loc>
  <lastmod>2026-05-25T11:24:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マクロ経済時系列のクラスタリング手法が変える構造分析（Clustering Macroeconomic Time Series）</news:title>
   <news:publication_date>2026-05-25T11:24:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694098</loc>
  <lastmod>2026-05-25T10:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース範囲制約学習と医用画像の自動グレーディング（Sparse Range-constrained Learning and Its Application for Medical Image Grading）</news:title>
   <news:publication_date>2026-05-25T10:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694096</loc>
  <lastmod>2026-05-25T10:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ESSにおけるソフトウェア中心の中性子検出データ処理（Software-based data acquisition and processing for neutron detectors at European Spallation Source — early experience from four detector designs）</news:title>
   <news:publication_date>2026-05-25T10:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694094</loc>
  <lastmod>2026-05-25T10:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動物体解析：未来位置と軌跡予測の概観（Moving Objects Analytics: Survey on Future Location &amp;amp; Trajectory Prediction Methods）</news:title>
   <news:publication_date>2026-05-25T10:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694092</loc>
  <lastmod>2026-05-25T10:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLU深層ニューラルネットワークと線形有限要素の関係（ReLU Deep Neural Networks and Linear Finite Elements）</news:title>
   <news:publication_date>2026-05-25T10:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694090</loc>
  <lastmod>2026-05-25T10:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型深層信念ネットワークから抽出する知識によるリアルタイム決定制御（Knowledge Extracted from Recurrent Deep Belief Network for Real Time Deterministic Control）</news:title>
   <news:publication_date>2026-05-25T10:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694088</loc>
  <lastmod>2026-05-25T10:23:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データ解析のための適応学習型再帰時系列ディープビリーフネットワーク（Adaptive Learning Method of Recurrent Temporal Deep Belief Network to Analyze Time Series Data）</news:title>
   <news:publication_date>2026-05-25T10:23:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694086</loc>
  <lastmod>2026-05-25T10:23:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な深度推定を実現する注意ベース分類ネットワーク（Deep attention-based classification network for robust depth prediction）</news:title>
   <news:publication_date>2026-05-25T10:23:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694084</loc>
  <lastmod>2026-05-25T09:32:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書知識を取り込む中国語単語分割の新手法（Neural Chinese Word Segmentation with Dictionary Knowledge）</news:title>
   <news:publication_date>2026-05-25T09:32:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694082</loc>
  <lastmod>2026-05-25T09:32:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列予測のための量子リザバーコンピュータの最適化（Optimizing a quantum reservoir computer for time series prediction）</news:title>
   <news:publication_date>2026-05-25T09:32:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694080</loc>
  <lastmod>2026-05-25T09:31:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習時間を短縮するAdaptive DBNの工夫（Shortening Time Required for Adaptive Structural Learning Method of Deep Belief Network with Multi-Modal Data Arrangement）</news:title>
   <news:publication_date>2026-05-25T09:31:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694078</loc>
  <lastmod>2026-05-25T09:31:07Z</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エントロピー・ファジィSVMによる不均衡データ分類（Instance-based entropy fuzzy support vector machine for imbalanced data）</news:title>
   <news:publication_date>2026-05-25T09:31:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694076</loc>
  <lastmod>2026-05-25T09:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Decoder-Encoder出力ノイズを用いた生成的敵対ネットワーク（Generative Adversarial Networks with Decoder-Encoder Output Noise）</news:title>
   <news:publication_date>2026-05-25T09:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694074</loc>
  <lastmod>2026-05-25T09:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所特徴を持つ階層ベイズ線形回帰による確率的力学の近似 (A Hierarchical Bayesian Linear Regression Model with Local Features for Stochastic Dynamics Approximation)</news:title>
   <news:publication_date>2026-05-25T09:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694072</loc>
  <lastmod>2026-05-25T09:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前確率シフト下の定量化：比率推定器とその拡張（Quantification Under Prior Probability Shift: the Ratio Estimator and its Extensions）</news:title>
   <news:publication_date>2026-05-25T09:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694070</loc>
  <lastmod>2026-05-25T08:39:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声からの感情認識：関連する特徴選択と多数決手法の強調（Emotion Recognition from Human Speech: Emphasizing on Relevant Feature Selection and Majority Voting Technique）</news:title>
   <news:publication_date>2026-05-25T08:39:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694068</loc>
  <lastmod>2026-05-25T08:38:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生産歩留まりデータ解析における興味深いプロットの発見（Discovering Interesting Plots in Production Yield Data Analytics）</news:title>
   <news:publication_date>2026-05-25T08:38:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694066</loc>
  <lastmod>2026-05-25T08:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seq2Seqによるマルチモーダル感情分析（Multimodal Sequence to Sequence Models for Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-25T08:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694064</loc>
  <lastmod>2026-05-25T08:38:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚注意の集約による深層不均衡属性分類（Deep Imbalanced Attribute Classification using Visual Attention Aggregation）</news:title>
   <news:publication_date>2026-05-25T08:38:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694062</loc>
  <lastmod>2026-05-25T08:38:12Z</lastmod>
  <news:news>
   <news:publication>
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    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694018</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユニバーサル・トランスフォーマーの計算力と実務的意義 (Universal Transformers)</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何学的一般化に基づくゼロショット学習（Geometric Generalization Based Zero-Shot Learning）</news:title>
   <news:publication_date>2026-05-25T03:47:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693988</loc>
  <lastmod>2026-05-25T03:46:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fisher–Shannon平面で読み解くVAEの本質（Understanding VAEs in Fisher-Shannon Plane）</news:title>
   <news:publication_date>2026-05-25T03:46:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693986</loc>
  <lastmod>2026-05-25T02:56:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース音声データにおける深層学習による音声転写の実践（Deep Learning for Audio Transcription on Low-Resource Datasets）</news:title>
   <news:publication_date>2026-05-25T02:56:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693984</loc>
  <lastmod>2026-05-25T02:55:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的な状態遷移を持つ決定論的ポリシー勾配（Deterministic Policy Gradients With General State Transitions）</news:title>
   <news:publication_date>2026-05-25T02:55:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693982</loc>
  <lastmod>2026-05-25T02:55:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mask R-CNNによる病変解析と診断（Lesion Analysis and Diagnosis with Mask-RCNN）</news:title>
   <news:publication_date>2026-05-25T02:55:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693980</loc>
  <lastmod>2026-05-25T02:54:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河地図作成とSkyMapperによる内部ハローの構造解析（Galactic cartography with SkyMapper: I. Population sub-structure and the stellar number density of the inner halo）</news:title>
   <news:publication_date>2026-05-25T02:54:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693978</loc>
  <lastmod>2026-05-25T02:54:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OCT画像からのプラーク自動分類（Convolutional neural network based automatic plaque characterization from intracoronary optical coherence tomography images）</news:title>
   <news:publication_date>2026-05-25T02:54:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693976</loc>
  <lastmod>2026-05-25T02:53:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全かつ異種混在データを扱うVAEの枠組み（Handling Incomplete Heterogeneous Data using VAEs）</news:title>
   <news:publication_date>2026-05-25T02:53:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693974</loc>
  <lastmod>2026-05-25T02:53:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習によるパートン・シャワーの模倣（Deep Learning as a Parton Shower）</news:title>
   <news:publication_date>2026-05-25T02:53:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693972</loc>
  <lastmod>2026-05-25T02:01:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイド観測を持つバンディット問題：有界後悔と対数後悔の境界（Bandits with Side Observations: Bounded vs. Logarithmic Regret）</news:title>
   <news:publication_date>2026-05-25T02:01:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693970</loc>
  <lastmod>2026-05-25T01:52:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>窓開閉の行動モデルに深層学習を使う意義（Window Opening Model using Deep Learning Methods）</news:title>
   <news:publication_date>2026-05-25T01:52:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693968</loc>
  <lastmod>2026-05-25T01:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>本質テンソル学習によるマルチビュースペクトルクラスタリング（Essential Tensor Learning for Multi-view Spectral Clustering）</news:title>
   <news:publication_date>2026-05-25T01:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693966</loc>
  <lastmod>2026-05-25T01:51:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的マルチスケールLSTMの再検討（Revisiting the Hierarchical Multiscale LSTM）</news:title>
   <news:publication_date>2026-05-25T01:51:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693964</loc>
  <lastmod>2026-05-25T01:51:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルの定値性を探る実証的アプローチ（An Empirical Approach For Probing the Definiteness of Kernels）</news:title>
   <news:publication_date>2026-05-25T01:51:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693962</loc>
  <lastmod>2026-05-25T01:51:14Z</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重複確率的ブロックモデルの小分散漸近 (Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels)</news:title>
   <news:publication_date>2026-05-25T01:51:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693960</loc>
  <lastmod>2026-05-25T01:50:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲーム理論に基づく深層ニューラルネットワークの近似検証（A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees）</news:title>
   <news:publication_date>2026-05-25T01:50:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693958</loc>
  <lastmod>2026-05-25T00:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在的行動タイプを同定するための実験の最適設計 (Optimal design of experiments to identify latent behavioral types)</news:title>
   <news:publication_date>2026-05-25T00:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693956</loc>
  <lastmod>2026-05-25T00:59:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深海映像の鮮明化を目指すUWCNN（Deep Underwater Image Enhancement）</news:title>
   <news:publication_date>2026-05-25T00:59:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693954</loc>
  <lastmod>2026-05-25T00:59:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸制約付き目的関数の双対最適化と勾配リプシッツ性仮定不要の収束保証（Dual optimization for convex constrained objectives without the gradient-Lipschitz assumption）</news:title>
   <news:publication_date>2026-05-25T00:59:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693952</loc>
  <lastmod>2026-05-25T00:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形構造方程式モデルの代数的同値性（Algebraic Equivalence of Linear Structural Equation Models）</news:title>
   <news:publication_date>2026-05-25T00:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693950</loc>
  <lastmod>2026-05-25T00:58:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群処理のためのマルチ解像度木ネットワーク（Multiresolution Tree Networks for 3D Point Cloud Processing）</news:title>
   <news:publication_date>2026-05-25T00:58:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693948</loc>
  <lastmod>2026-05-25T00:58:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習のハイパーパラメータ最適化ライブラリ DLOPT（DLOPT: Deep Learning Optimization Library）</news:title>
   <news:publication_date>2026-05-25T00:58:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693946</loc>
  <lastmod>2026-05-25T00:58:17Z</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表現のプライバシーと公平性を守る敵対的訓練（Privacy and Fairness in Recommender Systems via Adversarial Training of User Representations）</news:title>
   <news:publication_date>2026-05-25T00:58:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693944</loc>
  <lastmod>2026-05-25T00:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アクティブターゲットTPCデータにおける自動軌跡認識（Automatic trajectory recognition in Active Target Time Projection Chambers data by means of hierarchical clustering）</news:title>
   <news:publication_date>2026-05-25T00:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693942</loc>
  <lastmod>2026-05-25T00:06:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>走行計画と通信を同時に最適化する強化学習アプローチ（A Reinforcement Learning Approach to Jointly Adapt Vehicular Communications and Planning for Optimized Driving）</news:title>
   <news:publication_date>2026-05-25T00:06:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693940</loc>
  <lastmod>2026-05-25T00:05:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロブログ上の自動デマ検出の総説（Automatic Rumor Detection on Microblogs: A Survey）</news:title>
   <news:publication_date>2026-05-25T00:05:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693938</loc>
  <lastmod>2026-05-25T00:04:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種情報ネットワークの包括的転写による埋め込み学習の簡素化（Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks）</news:title>
   <news:publication_date>2026-05-25T00:04:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693936</loc>
  <lastmod>2026-05-25T00:04:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Belief Networkからの知識獲得によるファインチューニング手法（Fine Tuning Method by using Knowledge Acquisition from Deep Belief Network）</news:title>
   <news:publication_date>2026-05-25T00:04:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693934</loc>
  <lastmod>2026-05-25T00:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み環境での深層学習による笑顔検出（Embedded Implementation of a Deep Learning Smile Detector）</news:title>
   <news:publication_date>2026-05-25T00:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693932</loc>
  <lastmod>2026-05-25T00:03:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層生成アルゴリズムによるDBNの適応学習法（An Adaptive Learning Method of Deep Belief Network by Layer Generation Algorithm）</news:title>
   <news:publication_date>2026-05-25T00:03:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693930</loc>
  <lastmod>2026-05-24T23:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一動画デモから未知の作業を実行するためのタスクグラフ学習（Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration）</news:title>
   <news:publication_date>2026-05-24T23:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693928</loc>
  <lastmod>2026-05-24T23:12:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>振幅スペクトログラムからの位相再構成（PHASE RECONSTRUCTION FROM AMPLITUDE SPECTROGRAMS BASED ON VON-MISES-DISTRIBUTION DEEP NEURAL NETWORK）</news:title>
   <news:publication_date>2026-05-24T23:12:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693926</loc>
  <lastmod>2026-05-24T23:11:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RBMの適応学習法 — ニューロン生成と消去アルゴリズムによる最適化 (An Adaptive Learning Method of Restricted Boltzmann Machine by Neuron Generation and Annihilation Algorithm)</news:title>
   <news:publication_date>2026-05-24T23:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693924</loc>
  <lastmod>2026-05-24T23:10:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SceneEDNetによるシーンフロー推定（SceneEDNet: A Deep Learning Approach for Scene Flow Estimation）</news:title>
   <news:publication_date>2026-05-24T23:10:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693922</loc>
  <lastmod>2026-05-24T23:10:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペアワイズ共変量調整ブロックモデルによるコミュニティ検出（Pairwise Covariates-Adjusted Block Model for Community Detection）</news:title>
   <news:publication_date>2026-05-24T23:10:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693920</loc>
  <lastmod>2026-05-24T23:10:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムポリマーと一般化されたバーン過程（Random Polymers and Generalized Urn Processes）</news:title>
   <news:publication_date>2026-05-24T23:10:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693918</loc>
  <lastmod>2026-05-24T23:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一Tucker分解ネットワークを用いた可変ビット率の損失型画像圧縮（Learning a Single Tucker Decomposition Network for Lossy Image Compression with Multiple Bits-Per-Pixel Rates）</news:title>
   <news:publication_date>2026-05-24T23:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693916</loc>
  <lastmod>2026-05-24T22:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>竜巻による物的被害を予測するゼロ膨張ニューラルネットワーク（Predicting property damage from tornadoes with zero-inflated neural networks）</news:title>
   <news:publication_date>2026-05-24T22:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693914</loc>
  <lastmod>2026-05-24T22:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングによる脳アトラスの構築（Developing Brain Atlas through Deep Learning）</news:title>
   <news:publication_date>2026-05-24T22:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693912</loc>
  <lastmod>2026-05-24T22:17:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘルムホルツ法：知覚圧縮を使って機械学習の複雑性を下げる方法（The Helmholtz Method: Using Perceptual Compression to Reduce Machine Learning Complexity）</news:title>
   <news:publication_date>2026-05-24T22:17:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693910</loc>
  <lastmod>2026-05-24T22:17:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUに最適化されたセカント法に基づく次元削減アルゴリズム（A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction）</news:title>
   <news:publication_date>2026-05-24T22:17:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693908</loc>
  <lastmod>2026-05-24T22:16:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師あり学習における二値分類の新しい変分モデル (A New Variational Model for Binary Classification in the Supervised Learning Context)</news:title>
   <news:publication_date>2026-05-24T22:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693906</loc>
  <lastmod>2026-05-24T22:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等分散仮定による因果発見の単純化（On Causal Discovery with Equal Variance Assumption）</news:title>
   <news:publication_date>2026-05-24T22:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693904</loc>
  <lastmod>2026-05-24T22:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像における心胸郭比の自動推定のための教師なしドメイン適応（Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio）</news:title>
   <news:publication_date>2026-05-24T22:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693902</loc>
  <lastmod>2026-05-24T21:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>警察による殺害は誰か〜階層型LSTMに対する教師付きアテンションの導入（Who is Killed by Police: Introducing Supervised Attention for Hierarchical LSTMs）</news:title>
   <news:publication_date>2026-05-24T21:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693900</loc>
  <lastmod>2026-05-24T21:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AudioMNISTによる音声分野の説明可能なAIの試金石（AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark）</news:title>
   <news:publication_date>2026-05-24T21:15:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693898</loc>
  <lastmod>2026-05-24T21:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群に対する高忠実度意味的形状補完（High Fidelity Semantic Shape Completion for Point Clouds using Latent Optimization）</news:title>
   <news:publication_date>2026-05-24T21:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693896</loc>
  <lastmod>2026-05-24T21:13:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>材料空間の階層的可視化（Hierarchical Visualization of Materials Space with Graph Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-24T21:13:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693894</loc>
  <lastmod>2026-05-24T21:13:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンティティとテキストを同時に埋め込む手法（Jointly Embedding Entities and Text with Distant Supervision）</news:title>
   <news:publication_date>2026-05-24T21:13:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693892</loc>
  <lastmod>2026-05-24T21:13:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IGLOO: 長い系列を効率的に扱うための新しい切り口（IGLOO: Slicing the Feature Space to Represent Sequences）</news:title>
   <news:publication_date>2026-05-24T21:13:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693890</loc>
  <lastmod>2026-05-24T21:12:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>切り詰めた時間逆伝播で再帰ネットワークを学習する（On Training Recurrent Networks with Truncated Backpropagation Through Time in Speech Recognition）</news:title>
   <news:publication_date>2026-05-24T21:12:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693888</loc>
  <lastmod>2026-05-24T20:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初年次大型実験授業の変革がもたらした初期効果（Initial impacts of the transformation of a large introductory lab course focused on developing experimental skills and expert epistemology）</news:title>
   <news:publication_date>2026-05-24T20:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693886</loc>
  <lastmod>2026-05-24T20:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様なロボット行動の進化に向けた組合せ多目的進化アルゴリズムの提案（Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm）</news:title>
   <news:publication_date>2026-05-24T20:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693884</loc>
  <lastmod>2026-05-24T20:12:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大系列発散を用いたプロセス監視（Process Monitoring Using Maximum Sequence Divergence）</news:title>
   <news:publication_date>2026-05-24T20:12:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693882</loc>
  <lastmod>2026-05-24T20:12:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリックな学習-to-ランクの探求（Towards Non-Parametric Learning to Rank）</news:title>
   <news:publication_date>2026-05-24T20:12:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693880</loc>
  <lastmod>2026-05-24T20:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延情報下のオンライン評価：凸最適化の視点（Online Scoring with Delayed Information: A Convex Optimization Viewpoint）</news:title>
   <news:publication_date>2026-05-24T20:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693878</loc>
  <lastmod>2026-05-24T20:11:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習におけるアンサンブルカルマンフィルタを用いたスパースGaussian Process回帰（Ensemble Kalman Filtering for Online Gaussian Process Regression and Learning）</news:title>
   <news:publication_date>2026-05-24T20:11:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693876</loc>
  <lastmod>2026-05-24T20:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆の感情を捉える注意機構（An Attention Model for group-level emotion recognition）</news:title>
   <news:publication_date>2026-05-24T20:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693874</loc>
  <lastmod>2026-05-24T19:19:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数グラフのための扱いやすいn-距離（Tractable n-Metrics for Multiple Graphs）</news:title>
   <news:publication_date>2026-05-24T19:19:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693872</loc>
  <lastmod>2026-05-24T19:19:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル駆動の弱教師あり学習による多モーダル変形画像レジストレーションの実用化（Label-driven weakly-supervised learning for multimodal deformable image registration）</news:title>
   <news:publication_date>2026-05-24T19:19:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693870</loc>
  <lastmod>2026-05-24T19:18:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Talk The Walk: 地図と対話で観光客を導く対話型ナビゲーション（Talk The Walk: Navigating Grids in New York City through Grounded Dialogue）</news:title>
   <news:publication_date>2026-05-24T19:18:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693868</loc>
  <lastmod>2026-05-24T19:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダの再構成画像を群最適化で改良する（Using Swarm Optimization To Enhance Autoencoder’s Images）</news:title>
   <news:publication_date>2026-05-24T19:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693866</loc>
  <lastmod>2026-05-24T19:18:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習研究の問題点と健全な再生の道（Troubling Trends in Machine Learning Scholarship）</news:title>
   <news:publication_date>2026-05-24T19:18:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693864</loc>
  <lastmod>2026-05-24T19:18:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>提案クラスタ学習による弱教師あり物体検出の新戦略（PCL: Proposal Cluster Learning for Weakly Supervised Object Detection）</news:title>
   <news:publication_date>2026-05-24T19:18:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693862</loc>
  <lastmod>2026-05-24T19:17:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素全畳み込みニューラルネットワークによるMR画像再構成（Complex Fully Convolutional Neural Networks for MR Image Reconstruction）</news:title>
   <news:publication_date>2026-05-24T19:17:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693860</loc>
  <lastmod>2026-05-24T18:26:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェットサブ構造のスペクトル解析とニューラルネットワーク（Spectral Analysis of Jet Substructure with Neural Networks: Boosted Higgs Case）</news:title>
   <news:publication_date>2026-05-24T18:26:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693858</loc>
  <lastmod>2026-05-24T18:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーンテキスト認識に対する適応的敵対的攻撃（Adaptive Adversarial Attack on Scene Text Recognition）</news:title>
   <news:publication_date>2026-05-24T18:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693856</loc>
  <lastmod>2026-05-24T18:16:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称性と多体系励起状態のニューラルネットワーク量子状態（Symmetries and many-body excited states with neural-network quantum states）</news:title>
   <news:publication_date>2026-05-24T18:16:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693854</loc>
  <lastmod>2026-05-24T18:15:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フロンティア・フィールド銀河団のレンズモデル評価（An Evaluation of 10 Lensing Models of the Frontier Fields Cluster MACSJ0416.1-2403）</news:title>
   <news:publication_date>2026-05-24T18:15:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693852</loc>
  <lastmod>2026-05-24T18:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチコアHW/SWコーデザインによるK-means高速化（Using Multi-Core HW/SW Co-design Architecture for Accelerating K-means Clustering Algorithm）</news:title>
   <news:publication_date>2026-05-24T18:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693850</loc>
  <lastmod>2026-05-24T18:15:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英語の訛りを統計的に補正する手法（Foreign English Accent Adjustment by Learning Phonetic Patterns）</news:title>
   <news:publication_date>2026-05-24T18:15:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693848</loc>
  <lastmod>2026-05-24T18:14:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限個の未知評価額を仮定した動的価格設定（Dynamic Pricing with Finitely Many Unknown Valuations）</news:title>
   <news:publication_date>2026-05-24T18:14:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693846</loc>
  <lastmod>2026-05-24T17:23:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次モンテカルロ期待値最大化における適応学習による効率的収束（Efficient convergence through adaptive learning in sequential Monte Carlo Expectation Maximization）</news:title>
   <news:publication_date>2026-05-24T17:23:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/693844</loc>
  <lastmod>2026-05-24T17:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>座標変換で暴露された畳み込みニューラルネットワークの落とし穴（An intriguing failing of convolutional neural networks and the CoordConv solution）</news:title>
   <news:publication_date>2026-05-24T17:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693842</loc>
  <lastmod>2026-05-24T17:14:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ニューラルネットワークのベンチマーク—古典NNとの比較で示された効率性（Benchmarking Neural Networks For Quantum Computations）</news:title>
   <news:publication_date>2026-05-24T17:14:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693840</loc>
  <lastmod>2026-05-24T17:12:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的進化的特徴選択による放射線画像の選別（Multi-objective Feature Selection with Modified Entropy Termination and Evidential Reasoning）</news:title>
   <news:publication_date>2026-05-24T17:12:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693838</loc>
  <lastmod>2026-05-24T17:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発達期における抑制のブレインワイド発達を深層学習で探る（Exploring Brain-wide Development of Inhibition through Deep Learning）</news:title>
   <news:publication_date>2026-05-24T17:12:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693836</loc>
  <lastmod>2026-05-24T17:12:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FHIRChainによる臨床データの安全かつスケーラブルな共有（FHIRChain: Applying Blockchain to Securely and Scalably Share Clinical Data）</news:title>
   <news:publication_date>2026-05-24T17:12:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693834</loc>
  <lastmod>2026-05-24T17:12:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>渦と磁場がつむぐ“大きさの逆転”──渦度・ヘリシティと双方向カスケードの概観（Helicity dynamics, inverse and bi-directional cascades in fluid and magnetohydrodynamic turbulence: A brief review）</news:title>
   <news:publication_date>2026-05-24T17:12:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693832</loc>
  <lastmod>2026-05-24T16:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNを用いたNIDS強化の方法（RNNIDS: Enhancing Network Intrusion Detection Systems through Deep Learning）</news:title>
   <news:publication_date>2026-05-24T16:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693830</loc>
  <lastmod>2026-05-24T16:19:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的モデル平均による効率的な分散深層学習（Efficient Decentralized Deep Learning by Dynamic Model Averaging）</news:title>
   <news:publication_date>2026-05-24T16:19:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693828</loc>
  <lastmod>2026-05-24T16:19:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーソナライズされた語彙学習チュータの設計と評価（Design and Evaluation of a Tutor Platform for Personalized Vocabulary Learning）</news:title>
   <news:publication_date>2026-05-24T16:19:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693826</loc>
  <lastmod>2026-05-24T16:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身近な材料と低コストセンサーで物理を学ぶ（Low-Cost Experiments with Everyday Objects for Homework Assignments）</news:title>
   <news:publication_date>2026-05-24T16:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693824</loc>
  <lastmod>2026-05-24T16:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延が未知のバンディット・オンライン学習（Bandit Online Learning with Unknown Delays）</news:title>
   <news:publication_date>2026-05-24T16:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693822</loc>
  <lastmod>2026-05-24T16:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Thresholded ConvNet Ensemblesによるテクニカル予測の要点（Thresholded ConvNet Ensembles: Neural Networks for Technical Forecasting）</news:title>
   <news:publication_date>2026-05-24T16:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693820</loc>
  <lastmod>2026-05-24T16:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似k空間モデルと深層学習による高速光音響再構成（Approximate k-space models and Deep Learning for fast photoacoustic reconstruction）</news:title>
   <news:publication_date>2026-05-24T16:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693818</loc>
  <lastmod>2026-05-24T15:26:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エリートアスリートにおける心肺パラメータの因果経路発見（Discovery of causal paths in cardiorespiratory parameters: a time-independent approach in elite athletes）</news:title>
   <news:publication_date>2026-05-24T15:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693816</loc>
  <lastmod>2026-05-24T15:25:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い文脈化単語埋め込み、アンサンブル、ツリーバンク連結によるUDパーシングの改善（Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank Concatenation）</news:title>
   <news:publication_date>2026-05-24T15:25:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693814</loc>
  <lastmod>2026-05-24T15:25:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースネットワークのためのBeta Neutral-to-the-Leftモデルのサンプリングと推論（Sampling and Inference for Beta Neutral-to-the-Left Models of Sparse Networks）</news:title>
   <news:publication_date>2026-05-24T15:25:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693812</loc>
  <lastmod>2026-05-24T15:24:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層マルチモーダルクラスタリングによる教師なし音声映像学習（Deep Multimodal Clustering for Unsupervised Audiovisual Learning）</news:title>
   <news:publication_date>2026-05-24T15:24:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693810</loc>
  <lastmod>2026-05-24T15:24:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形計測とニューラルネットワークによるMRPCの時間再構成法（The study of a new time reconstruction method for MRPC read out by waveform digitizer）</news:title>
   <news:publication_date>2026-05-24T15:24:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693808</loc>
  <lastmod>2026-05-24T15:23:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NMT-Keras：対話型・継続学習に注力した柔軟な機械翻訳ツールキット（NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning）</news:title>
   <news:publication_date>2026-05-24T15:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693806</loc>
  <lastmod>2026-05-24T15:23:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分実行で強化するText-to-SQL（Robust Text-to-SQL Generation with Execution-Guided Decoding）</news:title>
   <news:publication_date>2026-05-24T15:23:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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