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   <news:title>柔軟な教師なし〜弱教師あり学習で行動検出を学ぶ（A flexible model for training action localization with varying levels of supervision）</news:title>
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   <news:title>高次元正式表現による概念空間の量子的性質（Quantum aspects of high dimensional formal representation of conceptual spaces）</news:title>
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   <news:title>ランキングモデルの事後解釈可能性と二次学習データの活用（Posthoc Interpretability of Learning to Rank Models using Secondary Training Data）</news:title>
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   <news:title>潜在クラス文脈異常の無監督検出と説明（Unsupervised Detection and Explanation of Latent-class Contextual Anomalies）</news:title>
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   <news:title>Twitterにおけるフェイクニュース検出（Fake News Identification on Twitter with Hybrid CNN and RNN Models）</news:title>
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   <news:title>テキストから対応する画像を生成する改良GAN-CLS手法（Generate the corresponding Image from Text Description using Modified GAN-CLS Algorithm）</news:title>
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   <news:title>意味解釈と談話構造におけるバイアスのモデル化（Bias in Semantic and Discourse Interpretation）</news:title>
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   <news:title>一変量混合分布間のトータル・バリエーションに関する決定論的境界の保証（Guaranteed Deterministic Bounds on the Total Variation Distance between Univariate Mixtures）</news:title>
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    <news:language>ja</news:language>
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   <news:title>複数生体信号からの頑健な心拍検出（Robust Heartbeat Detection from Multimodal Data via CNN-based Generalizable Information Fusion）</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>条件変化に不変な空間の発掘（Excavate Condition-invariant Space by Intrinsic Encoder）</news:title>
   <news:publication_date>2026-05-21T13:36:02Z</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>高速動的畳み込みニューラルネットワークによる視覚トラッキングの実務的意義（Fast Dynamic Convolutional Neural Networks for Visual Tracking）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>粗から細への再帰的改良による高精度セマンティックセグメンテーション（Gated Feedback Refinement Network for Coarse-to-Fine Dense Semantic Image Labeling）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>深度映像におけるマルチビュー動的画像による行動認識（Action Recognition for Depth Video using Multi-view Dynamic Images）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>観察からのワンショット学習による多段階タスク習得（One-Shot Learning of Multi-Step Tasks from Observation via Activity Localization in Auxiliary Video）</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>人間行動認識と予測に関する総説（Human Action Recognition and Prediction: A Survey）</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>集合的判断に基づくオープンセット認識の枠組み（Collective Decision for Open Set Recognition）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-21T12:43:59Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>XGBoostのGPU並列化が切り拓いた大規模学習の時短（XGBoost: Scalable GPU Accelerated Learning）</news:title>
   <news:publication_date>2026-05-21T12:43:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-21T11:52:33Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>大規模な品揃え生成のためのマルチモーダル推薦（A Multimodal Recommender System for Large-scale Assortment Generation in E-commerce）</news:title>
   <news:publication_date>2026-05-21T11:52:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>予測区間を狭める新しい損失関数：Expanded Interval Minimization（Tight Prediction Intervals Using Expanded Interval Minimization）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>Subject2Vec: 画像パッチ集合から患者レベルの表現を作る手法（Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>圧縮センシングMRI再構成の敵対的・知覚的洗練（Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction）</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>プロキシによる公平性改善の実務的提案（Proxy Fairness）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>多視点生成のための完全な表現学習（CR-GAN: Learning Complete Representations for Multi-view Generation）</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>途中停止で速くするアンサンブル評価（Quit When You Can: Efficient Evaluation of Ensembles with Ordering Optimization）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-21T10:59:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>符号付き粒子とニューラルネットワークを組み合わせた量子系シミュレーション高速化（Combining neural networks and signed particles to simulate quantum systems more efficiently, Part III）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-21T10:59:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>GenerationMania: 音楽からゲーム譜面を自動生成する手法の要点（GenerationMania: Learning to Semantically Choreograph）</news:title>
   <news:publication_date>2026-05-21T10:59:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/692651</loc>
  <lastmod>2026-05-21T10:58:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>L2正則化の新たな視点（A New Angle on L2 Regularization）</news:title>
   <news:publication_date>2026-05-21T10:58:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/692649</loc>
  <lastmod>2026-05-21T10:58:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの敵対的再プログラミング（ADVERSARIAL REPROGRAMMING OF NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-05-21T10:58:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>単一指数潜在変数モデルによるネットワークトポロジー推定（Single Index Latent Variable Models for Network Topology Inference）</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>学習管理システム（LMS）から教育用デジタルプラットフォームへ（Toward modern educational IT-ecosystems: from learning management systems to digital platforms）</news:title>
   <news:publication_date>2026-05-21T10:58:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱アノテーションで実現する3D医用画像のインスタンスセグメンテーション（Deep Learning Based Instance Segmentation in 3D Biomedical Images Using Weak Annotation）</news:title>
   <news:publication_date>2026-05-21T10:57:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-21T10:06:22Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習と画像カテゴリ発見のための確率的制約付きクラスタリング（A probabilistic constrained clustering for transfer learning and image category discovery）</news:title>
   <news:publication_date>2026-05-21T10:06:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692639</loc>
  <lastmod>2026-05-21T09:57:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習者英語のCEFRLレベル予測──メトリクスと全文から読み解く言語力の定量化（Predicting CEFRL levels in learner English on the basis of metrics and full texts）</news:title>
   <news:publication_date>2026-05-21T09:57:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692637</loc>
  <lastmod>2026-05-21T09:57:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然画像パッチの教師なし学習（Unsupervised Natural Image Patch Learning）</news:title>
   <news:publication_date>2026-05-21T09:57:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692635</loc>
  <lastmod>2026-05-21T09:57:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸クラスタリングで木構造を復元する（Recovering Trees with Convex Clustering）</news:title>
   <news:publication_date>2026-05-21T09:57:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692633</loc>
  <lastmod>2026-05-21T09:56:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習サービスにおけるメンバーシップ推測攻撃の解明（Demystifying Membership Inference Attacks in Machine Learning as a Service）</news:title>
   <news:publication_date>2026-05-21T09:56:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692631</loc>
  <lastmod>2026-05-21T09:56:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所相関分光の深層学習による高速化と定量化（Acceleration and Quantitation of Localized Correlated Spectroscopy using Deep Learning: A Pilot Simulation Study）</news:title>
   <news:publication_date>2026-05-21T09:56:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692629</loc>
  <lastmod>2026-05-21T09:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファッション性（Style Quotient）で読み解く売上の本質（Understanding Fashionability: What drives sales of a style?）</news:title>
   <news:publication_date>2026-05-21T09:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692627</loc>
  <lastmod>2026-05-21T09:04:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュートリノ質量の順序問題—振動から宇宙観測まで（Neutrino Mass Ordering from Oscillations and Beyond: 2018 Status and Future Prospects）</news:title>
   <news:publication_date>2026-05-21T09:04:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692625</loc>
  <lastmod>2026-05-21T09:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペルセウス銀河団の深いガンマ線観測による暗黒物質寿命制約（Constraining Dark Matter lifetime with a deep gamma-ray survey of the Perseus Galaxy Cluster with MAGIC）</news:title>
   <news:publication_date>2026-05-21T09:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692623</loc>
  <lastmod>2026-05-21T09:03:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SAGAの直接加速とSampled Negative Momentum（Direct Acceleration of SAGA using Sampled Negative Momentum）</news:title>
   <news:publication_date>2026-05-21T09:03:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692621</loc>
  <lastmod>2026-05-21T09:03:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド深層模倣学習によるロボットサッカーの事例研究（End-to-End Deep Imitation Learning: Robot Soccer）</news:title>
   <news:publication_date>2026-05-21T09:03:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692619</loc>
  <lastmod>2026-05-21T09:02:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Network Cognitive Engineによる自律分散型アンダーレイ周波数共有の実現（Neural Network Cognitive Engine for Autonomous and Distributed Underlay Dynamic Spectrum Access）</news:title>
   <news:publication_date>2026-05-21T09:02:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692617</loc>
  <lastmod>2026-05-21T09:02:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>湿潤対流の機械学習パラメータ化の可能性（Using machine learning to parameterize moist convection）</news:title>
   <news:publication_date>2026-05-21T09:02:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692615</loc>
  <lastmod>2026-05-21T09:02:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Web検索における日常的学習の検出と支援（Detecting, Understanding and Supporting Everyday Learning in Web Search）</news:title>
   <news:publication_date>2026-05-21T09:02:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692613</loc>
  <lastmod>2026-05-21T08:10:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>αβ T細胞受容体の起源を定量化する研究（Genesis of the αβ T-cell receptor）</news:title>
   <news:publication_date>2026-05-21T08:10:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692611</loc>
  <lastmod>2026-05-21T08:10:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化されたPD-L1腫瘍細胞スコアリングの半教師あり生成学習（Deep Semi Supervised Generative Learning for Automated PD-L1 Tumor Cell Scoring on NSCLC Tissue Needle Biopsies）</news:title>
   <news:publication_date>2026-05-21T08:10:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692609</loc>
  <lastmod>2026-05-21T08:10:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速収束を実現する単純確率的分散削減アルゴリズム（A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates）</news:title>
   <news:publication_date>2026-05-21T08:10:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692607</loc>
  <lastmod>2026-05-21T08:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外観と形状の結合モデルによる頑健な姿勢追跡（Robust pose tracking with a joint model of appearance and shape）</news:title>
   <news:publication_date>2026-05-21T08:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692605</loc>
  <lastmod>2026-05-21T08:09:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習されたモーメント法による暗黙的生成モデル学習（Learning Implicit Generative Models with the Method of Learned Moments）</news:title>
   <news:publication_date>2026-05-21T08:09:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692603</loc>
  <lastmod>2026-05-21T08:09:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PCアルゴリズムのハイパーパラメータをベイズ最適化で自動化する（Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks）</news:title>
   <news:publication_date>2026-05-21T08:09:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692601</loc>
  <lastmod>2026-05-21T08:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LiDARとマルチスペクトル画像の統合による露出および地震脆弱性推定（Integration of LiDAR and multispectral images for exposure and earthquake vulnerability estimation）</news:title>
   <news:publication_date>2026-05-21T08:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692599</loc>
  <lastmod>2026-05-21T07:17:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固体中の核スピン集合体を制御する量子ダイナミクスによる機械学習（Machine learning with controllable quantum dynamics of a nuclear spin ensemble in a solid）</news:title>
   <news:publication_date>2026-05-21T07:17:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692597</loc>
  <lastmod>2026-05-21T07:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OpenML上での機械学習実験の自動探索（Automatic Exploration of Machine Learning Experiments on OpenML）</news:title>
   <news:publication_date>2026-05-21T07:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692595</loc>
  <lastmod>2026-05-21T07:16:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像のかすみ（ヘイズ）除去における深層学習の比較と解析（Deep learning for dehazing: Comparison and analysis）</news:title>
   <news:publication_date>2026-05-21T07:16:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692593</loc>
  <lastmod>2026-05-21T07:15:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタからクエリへ：モジュラリティ景観の不確実性を活用する（From clusters to queries: exploiting uncertainty in the modularity landscape of complex networks）</news:title>
   <news:publication_date>2026-05-21T07:15:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692591</loc>
  <lastmod>2026-05-21T07:15:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超周辺（ultra-peripheral）p↑A衝突における単一スピン非対称性の新しい観察手段（Single spin asymmetries in ultra-peripheral p↑A collisions）</news:title>
   <news:publication_date>2026-05-21T07:15:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692589</loc>
  <lastmod>2026-05-21T07:15:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極端に狭いResNetが持つ表現力の再評価（ResNet with one-neuron hidden layers is a Universal Approximator）</news:title>
   <news:publication_date>2026-05-21T07:15:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692587</loc>
  <lastmod>2026-05-21T07:15:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビジネス分析とオペレーションズリサーチにおける深層学習（Deep learning in business analytics and operations research: Models, applications and managerial implications）</news:title>
   <news:publication_date>2026-05-21T07:15:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692585</loc>
  <lastmod>2026-05-21T06:23:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>救急出動需要の時空間予測とガウス過程回帰（Spatiotemporal Prediction of Ambulance Demand using Gaussian Process Regression）</news:title>
   <news:publication_date>2026-05-21T06:23:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692583</loc>
  <lastmod>2026-05-21T06:23:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴選択による教師なしドメイン適応と最適輸送（Feature Selection for Unsupervised Domain Adaptation using Optimal Transport）</news:title>
   <news:publication_date>2026-05-21T06:23:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692581</loc>
  <lastmod>2026-05-21T06:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNベースのワードスポッティング向けアーキテクチャ探索（Exploring Architectures for CNN-Based Word Spotting）</news:title>
   <news:publication_date>2026-05-21T06:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692579</loc>
  <lastmod>2026-05-21T06:22:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSDCS: Ki67染色スライドのがん増殖多様性解析（DeepSDCS: Dissecting cancer proliferation heterogeneity in Ki67 digital whole slide images）</news:title>
   <news:publication_date>2026-05-21T06:22:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692577</loc>
  <lastmod>2026-05-21T06:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Grassmannian Discriminant Maps による多様体次元削減と画像セット分類への応用（Grassmannian Discriminant Maps (GDM) for Manifold Dimensionality Reduction with Application to Image Set Classification）</news:title>
   <news:publication_date>2026-05-21T06:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692575</loc>
  <lastmod>2026-05-21T06:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模過負荷MIMO検出におけるデータ駆動型反復法の提案（Deep Learning-Aided Projected Gradient Detector for Massive Overloaded MIMO Channels）</news:title>
   <news:publication_date>2026-05-21T06:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692573</loc>
  <lastmod>2026-05-21T06:21:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルを判定モデルで評価する手法（Training Discriminative Models to Evaluate Generative Ones）</news:title>
   <news:publication_date>2026-05-21T06:21:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692571</loc>
  <lastmod>2026-05-21T05:30:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>出力ラベルを低次元に埋めることで学習が速くなる（Beyond One-hot Encoding: lower dimensional target embedding）</news:title>
   <news:publication_date>2026-05-21T05:30:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692569</loc>
  <lastmod>2026-05-21T05:30:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型強化学習と仮説的（アブダクティブ）計画の統合（Hierarchical Reinforcement Learning with Abductive Planning）</news:title>
   <news:publication_date>2026-05-21T05:30:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692567</loc>
  <lastmod>2026-05-21T05:30:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Switchable Normalization（Differentiable Learning-to-Normalize via Switchable Normalization）</news:title>
   <news:publication_date>2026-05-21T05:30:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692565</loc>
  <lastmod>2026-05-21T05:29:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAV通信ネットワークにおけるロバスト・ファジー学習による部分重畳チャネル割り当て（Robust Fuzzy-Learning For Partially Overlapping Channels Allocation In UAV Communication Networks）</news:title>
   <news:publication_date>2026-05-21T05:29:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692563</loc>
  <lastmod>2026-05-21T05:29:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次凸近似による非凸正則化を伴うスパース信号推定アルゴリズム（Successive Convex Approximation Algorithms for Sparse Signal Estimation with Nonconvex Regularizations）</news:title>
   <news:publication_date>2026-05-21T05:29:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692561</loc>
  <lastmod>2026-05-21T05:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態認識型アンチドリフト相関追跡（State-aware Anti-drift Robust Correlation Tracking）</news:title>
   <news:publication_date>2026-05-21T05:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692559</loc>
  <lastmod>2026-05-21T05:29:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能性手法のベンチマーク（A Benchmark for Interpretability Methods in Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-21T05:29:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692557</loc>
  <lastmod>2026-05-21T04:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内視鏡画像を使った登録アルゴリズムの自動初期化に向けて（Towards automatic initialization of registration algorithms using simulated endoscopy images）</news:title>
   <news:publication_date>2026-05-21T04:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692555</loc>
  <lastmod>2026-05-21T04:38:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈付きバンディットと代替損失による境界と効率的アルゴリズム（Contextual bandits with surrogate losses: Margin bounds and efficient algorithms）</news:title>
   <news:publication_date>2026-05-21T04:38:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692553</loc>
  <lastmod>2026-05-21T04:37:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生涯学習としての意味の計算理論（A Computational Theory for Life-Long Learning of Semantics）</news:title>
   <news:publication_date>2026-05-21T04:37:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692551</loc>
  <lastmod>2026-05-21T04:37:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手続き型レベル生成による深層強化学習の汎化の解明（Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation）</news:title>
   <news:publication_date>2026-05-21T04:37:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692549</loc>
  <lastmod>2026-05-21T04:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エミュレーションシーケンス学習による堅牢なニューラルマルウェア検出モデル（Robust Neural Malware Detection Models for Emulation Sequence Learning）</news:title>
   <news:publication_date>2026-05-21T04:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692547</loc>
  <lastmod>2026-05-21T04:36:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リスク回避的推定の公理的アプローチとWallace–Freeman推定の正当化（Risk-averse estimation, an axiomatic approach to inference, and Wallace-Freeman without MML）</news:title>
   <news:publication_date>2026-05-21T04:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692545</loc>
  <lastmod>2026-05-21T04:36:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を伴う深層エコー状態ネットワークによる時空間予測（Deep Echo State Networks with Uncertainty Quantification for Spatio-Temporal Forecasting）</news:title>
   <news:publication_date>2026-05-21T04:36:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692543</loc>
  <lastmod>2026-05-21T03:44:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep CNN Denoiserと多層Neighbor Component Embeddingによる顔ハリュシネーション（Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination）</news:title>
   <news:publication_date>2026-05-21T03:44:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692541</loc>
  <lastmod>2026-05-21T03:44:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類器の位相的正則化（A Topological Regularizer for Classiﬁers via Persistent Homology）</news:title>
   <news:publication_date>2026-05-21T03:44:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692539</loc>
  <lastmod>2026-05-21T03:44:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>獣医臨床ノートから診断を推定するDeepTagの考え方（DeepTag: inferring diagnoses from clinical notes in under-resourced medical domain）</news:title>
   <news:publication_date>2026-05-21T03:44:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692537</loc>
  <lastmod>2026-05-21T03:44:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造学習の分解法が示す経営的インパクト（Decomposition of structural learning about directed acyclic graphs）</news:title>
   <news:publication_date>2026-05-21T03:44:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692535</loc>
  <lastmod>2026-05-21T03:43:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係データに対する経験的リスク最小化と確率的勾配降下法（Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data）</news:title>
   <news:publication_date>2026-05-21T03:43:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692533</loc>
  <lastmod>2026-05-21T03:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の補間スプラインがデータ解析を変える（Interpolating splines on graphs for data science applications）</news:title>
   <news:publication_date>2026-05-21T03:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692531</loc>
  <lastmod>2026-05-21T03:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gradient Similarityによる敵対的攻撃検出（Gradient Similarity: An Explainable Approach to Detect Adversarial Attacks against Deep Learning）</news:title>
   <news:publication_date>2026-05-21T03:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692529</loc>
  <lastmod>2026-05-21T02:52:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非結合アイソトニック回帰と最小ワッサースタイン復元（Uncoupled Isotonic Regression via Minimum Wasserstein Deconvolution）</news:title>
   <news:publication_date>2026-05-21T02:52:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692527</loc>
  <lastmod>2026-05-21T02:52:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚情報と地図データで自転車経路を評価する手法（Bicycle Route Attractiveness from Street View and OpenStreetMap）</news:title>
   <news:publication_date>2026-05-21T02:52:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692525</loc>
  <lastmod>2026-05-21T02:52:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sivers関数の抽出とSIDISのTMD物理信号の評価 (Assessing signals of TMD physics in SIDIS azimuthal asymmetries and in the extraction of the Sivers function)</news:title>
   <news:publication_date>2026-05-21T02:52:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692523</loc>
  <lastmod>2026-05-21T02:51:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ効率の良いリソグラフィモデリング（Data Efficient Lithography Modeling with Transfer Learning and Active Data Selection）</news:title>
   <news:publication_date>2026-05-21T02:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692521</loc>
  <lastmod>2026-05-21T02:51:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習によるモデル予測制御則の効率的表現と近似（Efficient Representation and Approximation of Model Predictive Control Laws via Deep Learning）</news:title>
   <news:publication_date>2026-05-21T02:51:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692519</loc>
  <lastmod>2026-05-21T02:51:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークプリンター攻撃の行動分析と検出の枠組み（PIDS: A Behavioral Framework for Analysis and Detection of Network Printer Attacks）</news:title>
   <news:publication_date>2026-05-21T02:51:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692517</loc>
  <lastmod>2026-05-21T02:51:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二峰性を示すCa豊富ギャップ過渡現象 iPTF 16hgs の発見と示唆（Double-peaked Ca-rich gap transient iPTF 16hgs）</news:title>
   <news:publication_date>2026-05-21T02:51:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692515</loc>
  <lastmod>2026-05-21T02:00:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別器の近似能力がGANの多様性を保証する（Approximability of Discriminators Implies Diversity in GANs）</news:title>
   <news:publication_date>2026-05-21T02:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692513</loc>
  <lastmod>2026-05-21T01:59:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルライブ配信における成人向けコンテンツの実態（Adult content in Social Live Streaming Services: Characterizing deviant users and relationships）</news:title>
   <news:publication_date>2026-05-21T01:59:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692511</loc>
  <lastmod>2026-05-21T01:59:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>この画像はあの部分に似ている、と説明するAI（This Looks Like That: Deep Learning for Interpretable Image Recognition）</news:title>
   <news:publication_date>2026-05-21T01:59:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692509</loc>
  <lastmod>2026-05-21T01:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高スループット同定を加速する能動学習による原子間ポテンシャル取得手法（Accelerating high-throughput searches for new alloys with active learning of interatomic potentials）</news:title>
   <news:publication_date>2026-05-21T01:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692507</loc>
  <lastmod>2026-05-21T01:58:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>すべての画素を活かす：ホリスティック3D運動理解による教師なし形状学習（Every Pixel Counts: Unsupervised Geometry Learning with Holistic 3D Motion Understanding）</news:title>
   <news:publication_date>2026-05-21T01:58:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692505</loc>
  <lastmod>2026-05-21T01:58:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽におけるメジャー感の知覚モデル化（Modeling Majorness as a Perceptual Property in Music from Listener Ratings）</news:title>
   <news:publication_date>2026-05-21T01:58:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692503</loc>
  <lastmod>2026-05-21T01:57:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>V4046 Sgrを巡るサブアーク秒ALMA分子線イメージング調査（A Subarcsecond ALMA Molecular Line Imaging Survey of the Circumbinary, Protoplanetary Disk Orbiting V4046 Sgr）</news:title>
   <news:publication_date>2026-05-21T01:57:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692501</loc>
  <lastmod>2026-05-21T01:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絡み合いとカオスを解きほぐす（Untangling entanglement and chaos）</news:title>
   <news:publication_date>2026-05-21T01:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692499</loc>
  <lastmod>2026-05-21T01:05:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等方性Vlasov物質の低圧静的解の一意性（UNIQUENESS OF STATIC, ISOTROPIC LOW-PRESSURE SOLUTIONS OF THE EINSTEIN-VLASOV SYSTEM）</news:title>
   <news:publication_date>2026-05-21T01:05:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692497</loc>
  <lastmod>2026-05-21T01:05:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンビット通知で最適なタスク割振りを学ぶ（ONLINE OPTIMAL TASK OFFLOADING WITH ONE-BIT FEEDBACK）</news:title>
   <news:publication_date>2026-05-21T01:05:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692495</loc>
  <lastmod>2026-05-21T01:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生波形を直接処理する音声デノイジングの革新（Speech Denoising with Deep Feature Losses）</news:title>
   <news:publication_date>2026-05-21T01:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692493</loc>
  <lastmod>2026-05-21T01:04:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線メッシュネットワークにおける機械学習の概観（An Overview of Machine Learning Approaches in Wireless Mesh Networks）</news:title>
   <news:publication_date>2026-05-21T01:04:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692491</loc>
  <lastmod>2026-05-21T01:03:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイモンの量子アルゴリズムを学習する（Learning Simon’s quantum algorithm）</news:title>
   <news:publication_date>2026-05-21T01:03:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692489</loc>
  <lastmod>2026-05-21T01:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ構築と合成のためのニューラル機械翻訳（Neural Machine Translation for Query Construction and Composition）</news:title>
   <news:publication_date>2026-05-21T01:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692487</loc>
  <lastmod>2026-05-21T00:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LPRNetによる自動ナンバープレート認識（LPRNet: License Plate Recognition via Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-21T00:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692485</loc>
  <lastmod>2026-05-21T00:11:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセルから学ぶ深層ステガノ解析（Deep Steganalysis: End-to-End Learning with Supervisory Information beyond Class Labels）</news:title>
   <news:publication_date>2026-05-21T00:11:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692483</loc>
  <lastmod>2026-05-21T00:11:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間圧縮による静的内部表象が示す認知上の時間圧縮（STATIC INTERNAL REPRESENTATION OF DYNAMIC SITUATIONS REVEALS TIME COMPACTION IN HUMAN COGNITION）</news:title>
   <news:publication_date>2026-05-21T00:11:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692481</loc>
  <lastmod>2026-05-21T00:10:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列スパイク列のオンライン学習と認識を可能にする神経模倣システム（A neuro-inspired system for online learning and recognition of parallel spike trains, based on spike latency and heterosynaptic STDP）</news:title>
   <news:publication_date>2026-05-21T00:10:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692479</loc>
  <lastmod>2026-05-21T00:10:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネステッドロジットモデル下の動的品揃え最適化（Dynamic Assortment Planning Under Nested Logit Models）</news:title>
   <news:publication_date>2026-05-21T00:10:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692477</loc>
  <lastmod>2026-05-21T00:10:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡散MRIに基づく軽度外傷性脳損傷の検出（MTBI Identification From Diffusion MR Images Using Bag of Adversarial Visual Features）</news:title>
   <news:publication_date>2026-05-21T00:10:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692475</loc>
  <lastmod>2026-05-21T00:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プレプリント分類と研究動向の整理（ArXiv Categories and Trends）</news:title>
   <news:publication_date>2026-05-21T00:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692473</loc>
  <lastmod>2026-05-20T23:19:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な原子系ニューラルネットワークから得られる量子化学的知見（Quantum-chemical insights from interpretable atomistic neural networks）</news:title>
   <news:publication_date>2026-05-20T23:19:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692471</loc>
  <lastmod>2026-05-20T23:19:16Z</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3Dシーン探索のための視点有用性予測（Learn-to-Score: Efficient 3D Scene Exploration by Predicting View Utility）</news:title>
   <news:publication_date>2026-05-20T23:19:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692469</loc>
  <lastmod>2026-05-20T23:18:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚に基づく意味学習（Learning Visually-Grounded Semantics from Contrastive Adversarial Samples）</news:title>
   <news:publication_date>2026-05-20T23:18:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692467</loc>
  <lastmod>2026-05-20T23:18:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MONAS: マルチ目的ニューラルアーキテクチャ探索の実務的意義（MONAS: Multi-Objective Neural Architecture Search）</news:title>
   <news:publication_date>2026-05-20T23:18:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692465</loc>
  <lastmod>2026-05-20T23:17:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習ベース通信の一般化データ表現と訓練性能解析（A Generalized Data Representation and Training-Performance Analysis for Deep Learning-Based Communications Systems）</news:title>
   <news:publication_date>2026-05-20T23:17:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692463</loc>
  <lastmod>2026-05-20T23:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>食事画像から栄養評価を一気通貫で行う多目的学習（A Multi-Task Learning Approach for Meal Assessment）</news:title>
   <news:publication_date>2026-05-20T23:17:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692461</loc>
  <lastmod>2026-05-20T23:17:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D RoI対応U-Netによる高精度かつ高効率な結直腸腫瘍分割（3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation）</news:title>
   <news:publication_date>2026-05-20T23:17:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692459</loc>
  <lastmod>2026-05-20T22:25:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ニューラルネットワークの事後分布を圧縮する技術（Adversarial Posterior Distillation）</news:title>
   <news:publication_date>2026-05-20T22:25:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692457</loc>
  <lastmod>2026-05-20T22:25:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepObfuscationによるCNN構造保護（DeepObfuscation: Securing the Structure of Convolutional Neural Networks via Knowledge Distillation）</news:title>
   <news:publication_date>2026-05-20T22:25:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692455</loc>
  <lastmod>2026-05-20T22:25:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続自己位置推定を自己教師ありで高精度に学習する手法（CeMNet: Self-supervised learning for accurate continuous ego-motion estimation）</news:title>
   <news:publication_date>2026-05-20T22:25:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692453</loc>
  <lastmod>2026-05-20T22:24:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的価格市場における電解槽の最適スケジューリング（Optimal Scheduling of Electrolyzer in Power Market with Dynamic Prices）</news:title>
   <news:publication_date>2026-05-20T22:24:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692451</loc>
  <lastmod>2026-05-20T22:24:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QT-Optによる視覚基盤ロボット把持の大規模強化学習（QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation）</news:title>
   <news:publication_date>2026-05-20T22:24:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692449</loc>
  <lastmod>2026-05-20T22:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>独立深層学習行列解析による多チャンネル音源分離（Independent Deeply Learned Matrix Analysis for Multichannel Audio Source Separation）</news:title>
   <news:publication_date>2026-05-20T22:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692447</loc>
  <lastmod>2026-05-20T22:23:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非均一サンプリングからの行列補完（Matrix Completion from Non-Uniformly Sampled Entries）</news:title>
   <news:publication_date>2026-05-20T22:23:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692445</loc>
  <lastmod>2026-05-20T21:32:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限データで平均と分散の保証を与えるスケーラブルなガウス過程推論（Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees）</news:title>
   <news:publication_date>2026-05-20T21:32:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692443</loc>
  <lastmod>2026-05-20T21:24:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Auto-Kerasによる効率的なニューラルアーキテクチャ探索（Auto-Keras: An Efficient Neural Architecture Search System）</news:title>
   <news:publication_date>2026-05-20T21:24:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692441</loc>
  <lastmod>2026-05-20T21:24:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空映像における主要物体の階層的深層共分割（Hierarchical Deep Co-segmentation of Primary Objects in Aerial Videos）</news:title>
   <news:publication_date>2026-05-20T21:24:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692439</loc>
  <lastmod>2026-05-20T21:24:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的局所線形近似によるブラックボックス解釈（Optimal Piecewise Local-Linear Approximations）</news:title>
   <news:publication_date>2026-05-20T21:24:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692437</loc>
  <lastmod>2026-05-20T21:23:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ランダム自己改変計算（Quantum Random Self-Modifiable Computation）</news:title>
   <news:publication_date>2026-05-20T21:23:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692435</loc>
  <lastmod>2026-05-20T21:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人の目に合うサリエンシー評価を学習する（Learning a Saliency Evaluation Metric Using Crowdsourced Perceptual Judgments）</news:title>
   <news:publication_date>2026-05-20T21:22:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692433</loc>
  <lastmod>2026-05-20T21:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Guided evolutionary strategiesの実務的解説（Guided evolutionary strategies: Augmenting random search with surrogate gradients）</news:title>
   <news:publication_date>2026-05-20T21:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692431</loc>
  <lastmod>2026-05-20T20:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きスパースℓp回帰の実務的含意（Conditional Sparse ℓp-norm Regression With Optimal Probability）</news:title>
   <news:publication_date>2026-05-20T20:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692429</loc>
  <lastmod>2026-05-20T20:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核の短距離相関のエネルギー・運動量依存性（Energy and momentum dependence of nuclear short-range correlations - Spectral function, exclusive scattering experiments and the contact formalism）</news:title>
   <news:publication_date>2026-05-20T20:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/692427</loc>
  <lastmod>2026-05-20T20:30:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>幼児向けウェブ学習プラットフォームの採用意図要因（The Determinants For User Intention To Adopt Web Based Early Childhood Supplementary Educational Platform）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-20T20:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延付き確率的勾配降下法の収束解析（A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates）</news:title>
   <news:publication_date>2026-05-20T20:29:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692421</loc>
  <lastmod>2026-05-20T20:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Feature Factorizationによる概念発見（Deep Feature Factorization For Concept Discovery）</news:title>
   <news:publication_date>2026-05-20T20:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692419</loc>
  <lastmod>2026-05-20T20:29:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競合する隠れユニットによる教師なし学習（Unsupervised Learning by Competing Hidden Units）</news:title>
   <news:publication_date>2026-05-20T20:29:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692417</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>名前一致（Record Linkage）に基づく確率的手法による顧客名照合（Record Linkage to Match Customer Names: A Probabilistic Approach）</news:title>
   <news:publication_date>2026-05-20T19:37:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692415</loc>
  <lastmod>2026-05-20T19:37:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前計算された黄金分割探索によるBudgeted SGD-SVMの高速化（Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section Search）</news:title>
   <news:publication_date>2026-05-20T19:37:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692413</loc>
  <lastmod>2026-05-20T19:37:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチマージによる予算付きSGD-SVMの高速化（Multi-Merge Budget Maintenance for Stochastic Gradient Descent SVM Training）</news:title>
   <news:publication_date>2026-05-20T19:37:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692411</loc>
  <lastmod>2026-05-20T19:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生化学回路における確率的推論の具現化（Embodying probabilistic inference in biochemical circuits）</news:title>
   <news:publication_date>2026-05-20T19:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692409</loc>
  <lastmod>2026-05-20T19:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セプシス患者のICU死亡リスク検出を高精度化する意味的強化動的ベイジアンネットワーク（Semantically Enhanced Dynamic Bayesian Network for Detecting Sepsis Mortality Risk in ICU Patients with Infection）</news:title>
   <news:publication_date>2026-05-20T19:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692407</loc>
  <lastmod>2026-05-20T19:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ適応型圧縮センシングの学習—勾配アンローリングによる測定行列の最適化（Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling）</news:title>
   <news:publication_date>2026-05-20T19:36:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692405</loc>
  <lastmod>2026-05-20T19:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モジュール化メタラーニングの原理と実践（Modular meta-learning）</news:title>
   <news:publication_date>2026-05-20T19:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-20T18:44:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存の社会的慣習を観察データで学習する（Learning Existing Social Conventions via Observationally Augmented Self-Play）</news:title>
   <news:publication_date>2026-05-20T18:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/692395</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率データベースにおける任意時点近似の一般枠組み（A General Framework for Anytime Approximation in Probabilistic Databases）</news:title>
   <news:publication_date>2026-05-20T18:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/692393</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムシャッフルは有限エポックでSGDを上回る（Random Shuffling Beats SGD after Finite Epochs）</news:title>
   <news:publication_date>2026-05-20T18:42:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-20T18:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/692389</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep k-Meansによる表現学習とクラスタリングの同時最適化（Deep k-Means: Jointly clustering with k-Means and learning representations）</news:title>
   <news:publication_date>2026-05-20T17:51:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的シェーピングにおけるブラインド復号指標推定（Blind Decoding-Metric Estimation for Probabilistic Shaping via Expectation Maximization）</news:title>
   <news:publication_date>2026-05-20T17:50:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692385</loc>
  <lastmod>2026-05-20T17:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adaptive Blending Units（ADAPTIVE BLENDING UNITS: TRAINABLE ACTIVATION FUNCTIONS FOR DEEP NEURAL NETWORKS）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692383</loc>
  <lastmod>2026-05-20T17:49:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆カウントの密度適応ネットワーク（Crowd Counting with Density Adaption Networks）</news:title>
   <news:publication_date>2026-05-20T17:49:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692381</loc>
  <lastmod>2026-05-20T17:49:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デイアクティック・イメージ・マッピングによる姿勢不変な操作学習（Deictic Image Mapping）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692379</loc>
  <lastmod>2026-05-20T17:49:25Z</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>2026-05-20T17:49:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692377</loc>
  <lastmod>2026-05-20T17:49:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/692375</loc>
  <lastmod>2026-05-20T16:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号なしラプラシアンスペクトルで決定されるグラフの意義（Graphs determined by signless Laplacian Spectra）</news:title>
   <news:publication_date>2026-05-20T16:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692373</loc>
  <lastmod>2026-05-20T16:57:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆問題モデル学習のための敵対的能動探索（Adversarial Active Exploration for Inverse Dynamics Model Learning）</news:title>
   <news:publication_date>2026-05-20T16:57:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692371</loc>
  <lastmod>2026-05-20T16:56:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件性の原理が高次元回帰に与える示唆（The conditionality principle in high-dimensional regression）</news:title>
   <news:publication_date>2026-05-20T16:56:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692369</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によるモチーフとニューロン集団検出（LEMONADE: Learned Motif and Neuronal Assembly Detection in Calcium Imaging Videos）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692367</loc>
  <lastmod>2026-05-20T16:56:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的指数型ファミリー因子分解モデルのための分離拡張カルマンフィルタ (The Decoupled Extended Kalman Filter for Dynamic Exponential-Family Factorization Models)</news:title>
   <news:publication_date>2026-05-20T16:56:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692365</loc>
  <lastmod>2026-05-20T16:56:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-20T16:56:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692363</loc>
  <lastmod>2026-05-20T16:56:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>界面活性剤で覆われた変形滴の電気流体移動（Electrohydrodynamic migration of a surfactant-coated deformable drop in Poiseuielle flow）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692361</loc>
  <lastmod>2026-05-20T16:04:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数コントラストMRIのための連結辞書学習（Coupled Dictionary Learning for Multi-Contrast MRI Reconstruction）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692359</loc>
  <lastmod>2026-05-20T16:03:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト非依存の話者認証で嵐を呼んだ組合せ手法（Text-Independent Speaker Verification Based on Deep Neural Networks and Segmental Dynamic Time Warping）</news:title>
   <news:publication_date>2026-05-20T16:03:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックスを開く — データ駆動型の説明手法の要点（Open the Black Box: Data-Driven Explanation of Black Box Decision Systems）</news:title>
   <news:publication_date>2026-05-20T16:03:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/692355</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:title>Autograd Image Registration Laboratory（AIRLab: Autograd Image Registration Laboratory）</news:title>
   <news:publication_date>2026-05-20T16:02:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692353</loc>
  <lastmod>2026-05-20T16:02:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的VampPriorを用いた変分公平オートエンコーダ（Hierarchical VampPrior Variational Fair Auto-Encoder）</news:title>
   <news:publication_date>2026-05-20T16:02:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692351</loc>
  <lastmod>2026-05-20T16:02:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接線空間正則化による動的システムのニューラルネットワークモデル改善（Tangent-Space Regularization for Neural-Network Models of Dynamical Systems）</news:title>
   <news:publication_date>2026-05-20T16:02:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692349</loc>
  <lastmod>2026-05-20T16:02:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様体上の構造化予測（Manifold Structured Prediction）</news:title>
   <news:publication_date>2026-05-20T16:02:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692347</loc>
  <lastmod>2026-05-20T15:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化された自動音楽生成のための生波形生成モデルの条件付け（Conditioning Deep Generative Raw Audio Models for Structured Automatic Music）</news:title>
   <news:publication_date>2026-05-20T15:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692345</loc>
  <lastmod>2026-05-20T15:10:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分オートエンコーダを用いた金属結合タンパク質設計と新規フォールド創出（Design of metalloproteins and novel protein folds using variational autoencoders）</news:title>
   <news:publication_date>2026-05-20T15:10:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692343</loc>
  <lastmod>2026-05-20T15:09:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回帰問題におけるドロップアウトに基づく能動学習（Dropout-based Active Learning for Regression）</news:title>
   <news:publication_date>2026-05-20T15:09:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692341</loc>
  <lastmod>2026-05-20T15:09:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結合辞書学習に基づくマルチモーダル画像ノイズ除去（MULTIMODAL IMAGE DENOISING BASED ON COUPLED DICTIONARY LEARNING）</news:title>
   <news:publication_date>2026-05-20T15:09:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692339</loc>
  <lastmod>2026-05-20T15:09:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化経路の復元解析とDeep Convolutional Sparse Coding（Analysing recovery of activation pathways in DCNNs via Deep Convolutional Sparse Coding）</news:title>
   <news:publication_date>2026-05-20T15:09:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692337</loc>
  <lastmod>2026-05-20T15:08:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル画像処理のための結合辞書学習（MULTI-MODAL IMAGE PROCESSING BASED ON COUPLED DICTIONARY LEARNING）</news:title>
   <news:publication_date>2026-05-20T15:08:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692335</loc>
  <lastmod>2026-05-20T15:08:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運用的宇宙天気予報におけるアンサンブル手法の重要性（The importance of ensemble techniques for operational space weather forecasting）</news:title>
   <news:publication_date>2026-05-20T15:08:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692333</loc>
  <lastmod>2026-05-20T14:17:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>腹部脂肪組織の自動セグメンテーションに関する全畳み込みネットワークの応用（Fully Convolutional Networks for Automated Segmentation of Abdominal Adipose Tissue Depots in Multicenter Water-Fat MRI）</news:title>
   <news:publication_date>2026-05-20T14:17:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692331</loc>
  <lastmod>2026-05-20T14:16:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graph-to-Sequence学習とGGNNによる構造表現の活用（Graph-to-Sequence Learning using Gated Graph Neural Networks）</news:title>
   <news:publication_date>2026-05-20T14:16:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692329</loc>
  <lastmod>2026-05-20T14:16:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次分解可能サブモジュラ関数の最小化（Quadratic Decomposable Submodular Function Minimization）</news:title>
   <news:publication_date>2026-05-20T14:16:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692327</loc>
  <lastmod>2026-05-20T14:16:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文埋め込みの改良をもたらす一般化プーリング手法（Enhancing Sentence Embedding with Generalized Pooling）</news:title>
   <news:publication_date>2026-05-20T14:16:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692325</loc>
  <lastmod>2026-05-20T14:16:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SuperPCAによる超高分解能画像の領域別次元削減（SuperPCA: A Superpixelwise PCA Approach for Unsupervised Feature Extraction of Hyperspectral Imagery）</news:title>
   <news:publication_date>2026-05-20T14:16:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692323</loc>
  <lastmod>2026-05-20T14:15:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元における近似最近傍探索（Approximate Nearest Neighbor Search in High Dimensions）</news:title>
   <news:publication_date>2026-05-20T14:15:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692321</loc>
  <lastmod>2026-05-20T14:14:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段落認識型トピックモデルによる文書の意味構造の解明（Unveiling the semantic structure of text documents using paragraph-aware Topic Models）</news:title>
   <news:publication_date>2026-05-20T14:14:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692319</loc>
  <lastmod>2026-05-20T13:23:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多人数の逆強化学習が一般和ゲームに挑む（Multi-agent Inverse Reinforcement Learning for Certain General-Sum Stochastic Games）</news:title>
   <news:publication_date>2026-05-20T13:23:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692317</loc>
  <lastmod>2026-05-20T13:23:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>C2C向けNoSQLベースのパーソナライズ推薦システム（A NoSQL Data-based Personalized Recommendation System for C2C e-Commerce）</news:title>
   <news:publication_date>2026-05-20T13:23:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692315</loc>
  <lastmod>2026-05-20T13:23:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療関係抽出のハイブリッド深層学習法（A Hybrid Deep Learning Approach for Medical Relation Extraction）</news:title>
   <news:publication_date>2026-05-20T13:23:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692313</loc>
  <lastmod>2026-05-20T13:22:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的アンサンブルによる協調フィルタ（Probabilistic Ensemble of Collaborative Filters）</news:title>
   <news:publication_date>2026-05-20T13:22:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692311</loc>
  <lastmod>2026-05-20T13:22:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル中国詩生成モデル（A Multi-Modal Chinese Poetry Generation Model）</news:title>
   <news:publication_date>2026-05-20T13:22:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692309</loc>
  <lastmod>2026-05-20T13:21:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>免疫系に学ぶ分散型・実体化された行動進化選択アルゴリズム（On an Immuno-inspired Distributed, Embodied Action-Evolution cum Selection Algorithm）</news:title>
   <news:publication_date>2026-05-20T13:21:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692307</loc>
  <lastmod>2026-05-20T13:21:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関したソフトウェア指標を自動緩和するAutoSpearman（AutoSpearman: Automatically Mitigating Correlated Software Metrics for Interpreting Defect Models）</news:title>
   <news:publication_date>2026-05-20T13:21:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692297</loc>
  <lastmod>2026-05-20T12:30:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dropoutを最適化トリックとして理解する（Understanding Dropout as an Optimization Trick）</news:title>
   <news:publication_date>2026-05-20T12:30:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692295</loc>
  <lastmod>2026-05-20T12:30:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関疑似周辺メトロポリス・ヘイスティングと準ニュートン提案（Correlated pseudo-marginal Metropolis-Hastings using quasi-Newton proposals）</news:title>
   <news:publication_date>2026-05-20T12:30:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692293</loc>
  <lastmod>2026-05-20T12:29:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>数値データのセマンティックラベリングを深層距離学習で解く（EmbNum: Semantic Labeling for Numerical Values with Deep Metric Learning）</news:title>
   <news:publication_date>2026-05-20T12:29:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692291</loc>
  <lastmod>2026-05-20T12:29:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習可能な知識制約を持つ深層生成モデル（Deep Generative Models with Learnable Knowledge Constraints）</news:title>
   <news:publication_date>2026-05-20T12:29:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692289</loc>
  <lastmod>2026-05-20T12:29:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Q-DeckRecによる高速デッキ推薦システム (Q-DeckRec: A Fast Deck Recommendation System for Collectible Card Games)</news:title>
   <news:publication_date>2026-05-20T12:29:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692287</loc>
  <lastmod>2026-05-20T12:29:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドロップアウトが生む暗黙的バイアス（On the Implicit Bias of Dropout）</news:title>
   <news:publication_date>2026-05-20T12:29:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692285</loc>
  <lastmod>2026-05-20T12:28:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置を跨いだ行動認識のための分層転移学習（Cross-position Activity Recognition with Stratified Transfer Learning）</news:title>
   <news:publication_date>2026-05-20T12:28:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692283</loc>
  <lastmod>2026-05-20T11:37:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ルチルTiO2における急速重イオン軌跡の微細構造（Fine structure of swift heavy ion track in rutile TiO2）</news:title>
   <news:publication_date>2026-05-20T11:37:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692281</loc>
  <lastmod>2026-05-20T11:36:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Boulevardによる正則化確率的勾配ブースティング木とその極限分布 (Boulevard: Regularized Stochastic Gradient Boosted Trees and Their Limiting Distribution)</news:title>
   <news:publication_date>2026-05-20T11:36:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692279</loc>
  <lastmod>2026-05-20T11:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希薄なエンティティ抽出のための実践的逐次学習フレームワーク (A Practical Incremental Learning Framework For Sparse Entity Extraction)</news:title>
   <news:publication_date>2026-05-20T11:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692277</loc>
  <lastmod>2026-05-20T11:36:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>REST-ler：REST API自動テストの知能化（REST-ler: Automatic Intelligent REST API Fuzzing）</news:title>
   <news:publication_date>2026-05-20T11:36:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <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>
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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:publication_date>2026-05-20T10:42:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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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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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-20T09:50:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>「Behemoth」で読み解くエルゴード性とランダム行列理論（Eigenstate Thermalization, Random Matrix Theory and Behemoths）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-20T08:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>粒子確率近似EMによる動的システム学習（Learning Dynamical Systems with Particle Stochastic Approximation EM）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-20T07:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-20T07:03:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>変形物体操作のための学習ベースフィードバックコントローラ（Learning-based Feedback Controller for Deformable Object Manipulation）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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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>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CT画像における半自動RECISTラベリング（Semi-Automatic RECIST Labeling on CT Scans with Cascaded Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-20T07:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692201</loc>
  <lastmod>2026-05-20T07:02:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変的離散化によるパス積分の構築（Building a path-integral calculus: a covariant discretization approach）</news:title>
   <news:publication_date>2026-05-20T07:02:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692199</loc>
  <lastmod>2026-05-20T06:11:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ補間は統計的最適性と矛盾するか（Does data interpolation contradict statistical optimality?）</news:title>
   <news:publication_date>2026-05-20T06:11:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692197</loc>
  <lastmod>2026-05-20T06:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習の概観：連続制御の視点（A Tour of Reinforcement Learning: The View from Continuous Control）</news:title>
   <news:publication_date>2026-05-20T06:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692195</loc>
  <lastmod>2026-05-20T06:10:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市交差点における文脈依存歩行者動作予測（Context-Aware Pedestrian Motion Prediction In Urban Intersections）</news:title>
   <news:publication_date>2026-05-20T06:10:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692193</loc>
  <lastmod>2026-05-20T06:09:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空レーザー測量データによる森林属性推定のためのガウス過程回帰（Gaussian Process Regression for Forest Attribute Estimation from Airborne Laser Scanning Data）</news:title>
   <news:publication_date>2026-05-20T06:09:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692191</loc>
  <lastmod>2026-05-20T06:09:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>tanh関数を通じた不確実性伝播とリザバーコンピューティングへの応用 (Propagating Uncertainty through the tanh Function with Application to Reservoir Computing)</news:title>
   <news:publication_date>2026-05-20T06:09:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692189</loc>
  <lastmod>2026-05-20T06:09:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型遅延耐性近接勾配アルゴリズムの実用的意味（A distributed flexible delay-tolerant proximal gradient algorithm）</news:title>
   <news:publication_date>2026-05-20T06:09:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692187</loc>
  <lastmod>2026-05-20T06:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交差点で移動する歩行者の行動を場所を超えて予測する手法（A Transferable Pedestrian Motion Prediction Model for Intersections with Different Geometries）</news:title>
   <news:publication_date>2026-05-20T06:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692185</loc>
  <lastmod>2026-05-20T05:16:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異なType II超新星iPTF14hlsの後期観測（Late-time observations of the extraordinary Type II supernova iPTF14hls）</news:title>
   <news:publication_date>2026-05-20T05:16:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692183</loc>
  <lastmod>2026-05-20T05:16:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>精度を変えるカリキュラムで学習効率を上げる方法（Accuracy-based Curriculum Learning in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-20T05:16:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692181</loc>
  <lastmod>2026-05-20T05:15:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物学的妥当な意思決定層を備えた時間的ニューラルネットワークによる物体認識（A temporal neural network model for object recognition using a biologically plausible decision making layer）</news:title>
   <news:publication_date>2026-05-20T05:15:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692179</loc>
  <lastmod>2026-05-20T05:15:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実信号上でのICA尤度最適化の高速化（Accelerating likelihood optimization for ICA on real signals）</news:title>
   <news:publication_date>2026-05-20T05:15:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692177</loc>
  <lastmod>2026-05-20T05:14:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし学習で監督あり法に迫る分類器の可能性（An Unsupervised Learning Classifier with Competitive Error Performance）</news:title>
   <news:publication_date>2026-05-20T05:14:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692175</loc>
  <lastmod>2026-05-20T05:14:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース報酬問題に対するデータ効率的な探索手法（Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards）</news:title>
   <news:publication_date>2026-05-20T05:14:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692173</loc>
  <lastmod>2026-05-20T04:23:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一チャネル音声の残響除去にGANを用いる手法（Single-channel Speech Dereverberation via Generative Adversarial Training）</news:title>
   <news:publication_date>2026-05-20T04:23:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692171</loc>
  <lastmod>2026-05-20T04:23:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線科医レベルの胸部X線自動診断システム（Towards Radiologist-Level Accurate Deep Learning System for Pulmonary Screening）</news:title>
   <news:publication_date>2026-05-20T04:23:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692169</loc>
  <lastmod>2026-05-20T04:22:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし音声活動検出のための堅牢な特徴クラスタリング（Robust Feature Clustering for Unsupervised Speech Activity Detection）</news:title>
   <news:publication_date>2026-05-20T04:22:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692167</loc>
  <lastmod>2026-05-20T04:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバル不変性を組み込んだ最適輸送（Towards Optimal Transport with Global Invariances）</news:title>
   <news:publication_date>2026-05-20T04:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692165</loc>
  <lastmod>2026-05-20T04:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道具操作のためのタスク指向把持学習（Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision）</news:title>
   <news:publication_date>2026-05-20T04:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692163</loc>
  <lastmod>2026-05-20T04:22:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>化学オートエンコーダの潜在空間と分子生成の多様性向上（Improving Chemical Autoencoder Latent Space and Molecular De-novo Generation Diversity with Heteroencoders）</news:title>
   <news:publication_date>2026-05-20T04:22:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692161</loc>
  <lastmod>2026-05-20T04:21:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車両再識別のための領域認識深層モデル（RAM: A REGION-AWARE DEEP MODEL FOR VEHICLE RE-IDENTIFICATION）</news:title>
   <news:publication_date>2026-05-20T04:21:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692159</loc>
  <lastmod>2026-05-20T03:31:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴マップの再重み付けによる色恒常性（Color Constancy by Reweighting Image Feature Maps）</news:title>
   <news:publication_date>2026-05-20T03:31:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692157</loc>
  <lastmod>2026-05-20T03:30:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Track Xplorerによるセンサーデータ分類の可視化と解析（Track Xplorer: A System for Visual Analysis of Sensor-based Motor Activity Predictions）</news:title>
   <news:publication_date>2026-05-20T03:30:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692155</loc>
  <lastmod>2026-05-20T03:30:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プレシーズン作物収量予測のためのスケーラブルな機械学習システム（A Scalable Machine Learning System for Pre-Season Agriculture Yield Forecast）</news:title>
   <news:publication_date>2026-05-20T03:30:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692153</loc>
  <lastmod>2026-05-20T03:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球面上の完全フーリエ空間クレブシュ–ゴルダンネット（Clebsch–Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-20T03:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692151</loc>
  <lastmod>2026-05-20T03:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワーク圧縮のためのDeep k-Means（Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions）</news:title>
   <news:publication_date>2026-05-20T03:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692149</loc>
  <lastmod>2026-05-20T03:29:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANの訓練挙動の理解と正則化の改善（Towards a Better Understanding and Regularization of GAN Training Dynamics）</news:title>
   <news:publication_date>2026-05-20T03:29:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692147</loc>
  <lastmod>2026-05-20T03:29:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FBI-Poseが切り拓く2D画像と3D人体姿勢推定の橋渡し（FBI-Pose: Towards Bridging the Gap between 2D Images and 3D Human Poses using Forward-or-Backward Information）</news:title>
   <news:publication_date>2026-05-20T03:29:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692145</loc>
  <lastmod>2026-05-20T02:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>監視学習における金融的影響の均衡化（Equalizing Financial Impact in Supervised Learning）</news:title>
   <news:publication_date>2026-05-20T02:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692143</loc>
  <lastmod>2026-05-20T02:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注目機構を用いた少数ショット人物再識別のメタ学習（Attention-based Few-Shot Person Re-identification Using Meta Learning）</news:title>
   <news:publication_date>2026-05-20T02:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692141</loc>
  <lastmod>2026-05-20T02:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>N-Gram Graphによる分子表現の単純化と有効性（N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules）</news:title>
   <news:publication_date>2026-05-20T02:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692139</loc>
  <lastmod>2026-05-20T02:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Power Normalizationsによる深層プーリングの再考（A Deeper Look at Power Normalizations）</news:title>
   <news:publication_date>2026-05-20T02:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692137</loc>
  <lastmod>2026-05-20T02:38:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-20T02:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692135</loc>
  <lastmod>2026-05-20T02:37:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Thompson Samplingの差分プライバシー性と実務的含意（On The Differential Privacy of Thompson Sampling With Gaussian Prior）</news:title>
   <news:publication_date>2026-05-20T02:37:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692133</loc>
  <lastmod>2026-05-20T02:37:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動作キャプチャの自動セグメンテーションを高速化する時系列畳み込み網（Dilated Temporal Fully-Convolutional Network for Semantic Segmentation of Motion Capture Data）</news:title>
   <news:publication_date>2026-05-20T02:37:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692131</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:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news: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>
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 </url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <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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    <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>企業向け脅威管理のための再帰的PLSアプローチ（A Recursive PLS based Approach for Enterprise Threat Management）</news:title>
   <news:publication_date>2026-05-19T21:13:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692057</loc>
  <lastmod>2026-05-19T21:13:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー最適化ロボットアーム経路計画（Energy Optimized Robot Arm Path Planning using Differential Evolution in Dynamic Environment）</news:title>
   <news:publication_date>2026-05-19T21:13:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692055</loc>
  <lastmod>2026-05-19T21:12:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑モデルを可視化する統一インターフェース（DALEX: Explainers for Complex Predictive Models in R）</news:title>
   <news:publication_date>2026-05-19T21:12:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692053</loc>
  <lastmod>2026-05-19T21:12:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習を用いた合成乱流入口生成器（Synthetic turbulent inflow generator using machine learning）</news:title>
   <news:publication_date>2026-05-19T21:12:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692051</loc>
  <lastmod>2026-05-19T21:11:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重なりを使ったスライス逆回帰による次元削減の改良（Overlapping Sliced Inverse Regression for Dimension Reduction）</news:title>
   <news:publication_date>2026-05-19T21:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692049</loc>
  <lastmod>2026-05-19T21:11:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索順位操作の不正の匿名解除（Search Rank Fraud De-Anonymization in Online Systems）</news:title>
   <news:publication_date>2026-05-19T21:11:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692047</loc>
  <lastmod>2026-05-19T20:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習の概説（Deep Reinforcement Learning: An Overview）</news:title>
   <news:publication_date>2026-05-19T20:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692045</loc>
  <lastmod>2026-05-19T20:20:13Z</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・マニフォールド変換の本質（The Sparse Manifold Transform）</news:title>
   <news:publication_date>2026-05-19T20:20:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692043</loc>
  <lastmod>2026-05-19T20:19:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海中自律ロボットにおける高精度ポシドニア海草群落セマンティック分割（Deep Semantic Segmentation in an AUV for Online Posidonia Oceanica Meadows Identification）</news:title>
   <news:publication_date>2026-05-19T20:19:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692041</loc>
  <lastmod>2026-05-19T20:19:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的シーンの視点合成で未来の走行可能性を読む（VUNet: Dynamic Scene View Synthesis for Traversability Estimation using an RGB Camera）</news:title>
   <news:publication_date>2026-05-19T20:19:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692039</loc>
  <lastmod>2026-05-19T20:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>xGEMsによるブラックボックス説明の新展開（xGEMs: Generating Examplars to Explain Black-Box Models）</news:title>
   <news:publication_date>2026-05-19T20:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692037</loc>
  <lastmod>2026-05-19T20:18:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep SNPによるSNPアレイデータのブレークポイント検出（Deep SNP: An End-to-end Deep Neural Network for Break-point Detection in SNP Array Genomic Data）</news:title>
   <news:publication_date>2026-05-19T20:18:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692035</loc>
  <lastmod>2026-05-19T20:18:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜層の自動分割を深層学習で完結させる一手（A deep learning framework for segmentation of retinal layers from OCT images）</news:title>
   <news:publication_date>2026-05-19T20:18:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692033</loc>
  <lastmod>2026-05-19T19:26:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の拡散スキャッタリング変換（Diffusion Scattering Transforms on Graphs）</news:title>
   <news:publication_date>2026-05-19T19:26:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692031</loc>
  <lastmod>2026-05-19T19:17:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組合せ構造のベイズ最適化が示す実務的インパクト（Bayesian Optimization of Combinatorial Structures）</news:title>
   <news:publication_date>2026-05-19T19:17:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692029</loc>
  <lastmod>2026-05-19T19:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートインバータによる系統プロービングで負荷を学習する：第II部 – プロービング注入設計 (Smart Inverter Grid Probing for Learning Loads: Part II – Probing Injection Design)</news:title>
   <news:publication_date>2026-05-19T19:17:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692027</loc>
  <lastmod>2026-05-19T19:17:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>急性呼吸器感染症予測のドメイン適応（Domain Adaptation for Acute Respiratory Infection Prediction）</news:title>
   <news:publication_date>2026-05-19T19:17:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692025</loc>
  <lastmod>2026-05-19T19:17:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的（Many-Goals）強化学習の拡張と実用性（Many-Goals Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-19T19:17:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692023</loc>
  <lastmod>2026-05-19T19:16:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内戦下における国内避難民（IDP）流動の予測手法（Forecasting Internally Displaced Population Migration Patterns in Syria and Yemen）</news:title>
   <news:publication_date>2026-05-19T19:16:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692021</loc>
  <lastmod>2026-05-19T19:16:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートインバータによるグリッドプロービングで負荷を学ぶ（Smart Inverter Grid Probing for Learning Loads: Part I – Identifiability Analysis）</news:title>
   <news:publication_date>2026-05-19T19:16:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692019</loc>
  <lastmod>2026-05-19T18:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河周縁ガスの一貫性スケール（The Coherence Scale of the Cool Circumgalactic Medium）</news:title>
   <news:publication_date>2026-05-19T18:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692017</loc>
  <lastmod>2026-05-19T18:24:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ランダムウォークのPCA解析（PCA of high dimensional random walks with comparison to neural network training）</news:title>
   <news:publication_date>2026-05-19T18:24:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692015</loc>
  <lastmod>2026-05-19T18:24:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的グラフ表現学習と微分可能なプーリング（Hierarchical Graph Representation Learning with Differentiable Pooling）</news:title>
   <news:publication_date>2026-05-19T18:24:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692013</loc>
  <lastmod>2026-05-19T18:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散逸系における量子電流（Quantum current in dissipative systems）</news:title>
   <news:publication_date>2026-05-19T18:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692011</loc>
  <lastmod>2026-05-19T18:23:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ネスト分散還元による局所最小解探索（Finding Local Minima via Stochastic Nested Variance Reduction）</news:title>
   <news:publication_date>2026-05-19T18:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692009</loc>
  <lastmod>2026-05-19T18:23:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子コードをニューラルネットワークで表現する（Quantum Codes from Neural Networks）</news:title>
   <news:publication_date>2026-05-19T18:23:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692007</loc>
  <lastmod>2026-05-19T18:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GOODS-N フィールドにおける z ∼2.5–3 のイオン化源探索の意義（z ∼2.5–3 Ionizers in the GOODS-N Field）</news:title>
   <news:publication_date>2026-05-19T18:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692005</loc>
  <lastmod>2026-05-19T17:31:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン知識と深層学習の組合せによる感情分析（Combination of Domain Knowledge and Deep Learning for Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-19T17:31:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692003</loc>
  <lastmod>2026-05-19T17:31:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム場を用いた交通流動学習（Learning Traffic Flow Dynamics using Random Fields）</news:title>
   <news:publication_date>2026-05-19T17:31:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692001</loc>
  <lastmod>2026-05-19T17:31:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dense Object Netsによるロボット操作のための密な視覚記述子学習（Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation）</news:title>
   <news:publication_date>2026-05-19T17:31:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691999</loc>
  <lastmod>2026-05-19T17:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模化したSLICアルゴリズムによる高速化と汎用化の実装（Scalable Simple Linear Iterative Clustering）</news:title>
   <news:publication_date>2026-05-19T17:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691997</loc>
  <lastmod>2026-05-19T17:29:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ESO telbib：経験から学び未来に備える（ESO telbib: learning from experience, preparing for the future）</news:title>
   <news:publication_date>2026-05-19T17:29:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691995</loc>
  <lastmod>2026-05-19T17:29:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>永続的隠れ状態と非線形変換によるLSTMの改良（Persistent Hidden States and Nonlinear Transformation for Long Short-Term Memory）</news:title>
   <news:publication_date>2026-05-19T17:29:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691993</loc>
  <lastmod>2026-05-19T17:29:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークのスペクトルバイアス（On the Spectral Bias of Neural Networks）</news:title>
   <news:publication_date>2026-05-19T17:29:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691991</loc>
  <lastmod>2026-05-19T16:38:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様で解釈可能な分類ルールの学習（Learning Qualitatively Diverse and Interpretable Rules for Classification）</news:title>
   <news:publication_date>2026-05-19T16:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691989</loc>
  <lastmod>2026-05-19T16:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽を“間隔”で予測するモデル：学習されたインターバル表現に基づく予測モデル（A predictive model for music based on learned interval representations）</news:title>
   <news:publication_date>2026-05-19T16:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691987</loc>
  <lastmod>2026-05-19T16:37:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見出しニュースで株価のトレンドを予測する（Using NLP on news headlines to predict index trends）</news:title>
   <news:publication_date>2026-05-19T16:37:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691985</loc>
  <lastmod>2026-05-19T16:37:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトな深層ニューラルネットワークによる筋電信号からのジェスチャ分類の効率化（Compact Deep Neural Networks for Computationally Efficient Gesture Classification From Electromyography Signals）</news:title>
   <news:publication_date>2026-05-19T16:37:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691983</loc>
  <lastmod>2026-05-19T16:36:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動する機能的プロソディの文脈依存的変化を写像する変分プロソディモデル（A Variational Prosody Model for Mapping the Context-Sensitive Variation of Functional Prosodic Prototypes）</news:title>
   <news:publication_date>2026-05-19T16:36:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691981</loc>
  <lastmod>2026-05-19T16:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメインをまたぐ変分学習とトリプレット情報（Variational learning across domains with triplet information）</news:title>
   <news:publication_date>2026-05-19T16:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691979</loc>
  <lastmod>2026-05-19T16:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全な深層学習への一歩（Towards safe deep learning: accurately quantifying biomarker uncertainty in neural network predictions）</news:title>
   <news:publication_date>2026-05-19T16:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691977</loc>
  <lastmod>2026-05-19T15:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>家族写真から子どもの顔を生成する技術の要点（KINSHIPGAN: SYNTHESIZING OF KINSHIP FACES FROM FAMILY PHOTOS BY REGULARIZING A DEEP FACE NETWORK）</news:title>
   <news:publication_date>2026-05-19T15:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691975</loc>
  <lastmod>2026-05-19T15:44:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tensor Monte Carlo：GPU時代の粒子法の再定義（Tensor Monte Carlo: Particle Methods for the GPU Era）</news:title>
   <news:publication_date>2026-05-19T15:44:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691973</loc>
  <lastmod>2026-05-19T15:44:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Multi-task WaveNetによる音声合成の簡潔化と高品質化（Multi-task WaveNet: A Multi-task Generative Model for Statistical Parametric Speech Synthesis without Fundamental Frequency Conditions）</news:title>
   <news:publication_date>2026-05-19T15:44:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691971</loc>
  <lastmod>2026-05-19T15:44:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一インクリメンタルタスクにおける継続学習（Continuous Learning in Single-Incremental-Task Scenarios）</news:title>
   <news:publication_date>2026-05-19T15:44:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691969</loc>
  <lastmod>2026-05-19T15:43:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FLARECAST：衛星データを用いた宇宙天気のI4.0技術（FLARECAST: an I4.0 technology for space weather using satellite data）</news:title>
   <news:publication_date>2026-05-19T15:43:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691967</loc>
  <lastmod>2026-05-19T15:43:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層スペクトル畳み込みネットワークによるハイパースペクトル混合解除（Deep Spectral Convolution Network for Hyperspectral Unmixing）</news:title>
   <news:publication_date>2026-05-19T15:43:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691965</loc>
  <lastmod>2026-05-19T15:43:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>20質問で学ぶ知識獲得法（Learning-to-Ask: Knowledge Acquisition via 20 Questions）</news:title>
   <news:publication_date>2026-05-19T15:43:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691963</loc>
  <lastmod>2026-05-19T14:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸なマルチ種ホップフィールドモデル（Non-convex Multi-Species Hopfield Models）</news:title>
   <news:publication_date>2026-05-19T14:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691961</loc>
  <lastmod>2026-05-19T14:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変数イテレーティブ・ラーニング制御の設計手順（Multivariable Iterative Learning Control Design Procedures）</news:title>
   <news:publication_date>2026-05-19T14:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691959</loc>
  <lastmod>2026-05-19T14:51:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速ドローンレースに学ぶ機敏な自律飛行（Deep Drone Racing: Learning Agile Flight in Dynamic Environments）</news:title>
   <news:publication_date>2026-05-19T14:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691957</loc>
  <lastmod>2026-05-19T14:51:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バーチャルコーデック監督再サンプリングネットワークによる画像圧縮（Virtual Codec Supervised Re-Sampling Network for Image Compression）</news:title>
   <news:publication_date>2026-05-19T14:51:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691955</loc>
  <lastmod>2026-05-19T14:51:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CTR予測における深層ニューラルネットワークの可視化と理解（Visualizing and Understanding Deep Neural Networks in CTR Prediction）</news:title>
   <news:publication_date>2026-05-19T14:51:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691953</loc>
  <lastmod>2026-05-19T14:51:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的グルーピングによる効率的なセマンティックセグメンテーション（Efficient Semantic Segmentation using Gradual Grouping）</news:title>
   <news:publication_date>2026-05-19T14:51:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691951</loc>
  <lastmod>2026-05-19T14:50:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間系列データにおける注目点の見極め（Focusing on What is Relevant: Time-Series Learning and Understanding using Attention）</news:title>
   <news:publication_date>2026-05-19T14:50:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691949</loc>
  <lastmod>2026-05-19T13:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚・慣性融合による物体検出とマッピング（Visual-Inertial Object Detection and Mapping）</news:title>
   <news:publication_date>2026-05-19T13:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691947</loc>
  <lastmod>2026-05-19T13:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバル意味的一貫性によるゼロショット学習の実装と意義（Global Semantic Consistency for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-05-19T13:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691945</loc>
  <lastmod>2026-05-19T13:59:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マスクからの3D人体形状再構築（Shape-from-Mask: A Deep Learning Based Human Body Shape Reconstruction from Binary Mask Images）</news:title>
   <news:publication_date>2026-05-19T13:59:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691943</loc>
  <lastmod>2026-05-19T13:58:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネット由来ガウス過程回帰による関数近似と偏微分方程式の解法（Neural-net-induced Gaussian process regression for function approximation and PDE solution）</news:title>
   <news:publication_date>2026-05-19T13:58:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691941</loc>
  <lastmod>2026-05-19T13:58:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と対話しながら学ぶサブゴール監督による効率的な逆強化学習（Human-Interactive Subgoal Supervision for Efficient Inverse Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-19T13:58:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691939</loc>
  <lastmod>2026-05-19T13:58:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間構造と空間詳細を同時学習する動画インペインティング（Video Inpainting by Jointly Learning Temporal Structure and Spatial Details）</news:title>
   <news:publication_date>2026-05-19T13:58:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691937</loc>
  <lastmod>2026-05-19T13:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるDB型白色矮星のスペクトル特徴抽出（Spectral Feature Extraction for DB White Dwarfs through Machine Learning）</news:title>
   <news:publication_date>2026-05-19T13:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691935</loc>
  <lastmod>2026-05-19T13:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度かつ姿勢不変な高忠実度顔正面化モデル（Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization）</news:title>
   <news:publication_date>2026-05-19T13:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691933</loc>
  <lastmod>2026-05-19T13:06:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ECOCとデータ複雑度で切り拓く多クラス・マイクロアレイ分類（A New ECOC Algorithm for Multiclass Microarray Data Classification）</news:title>
   <news:publication_date>2026-05-19T13:06:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691931</loc>
  <lastmod>2026-05-19T13:06:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOOCディスカッションフォーラムの個人化スレッド推薦（Personalized Thread Recommendation for MOOC Discussion Forums）</news:title>
   <news:publication_date>2026-05-19T13:06:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691929</loc>
  <lastmod>2026-05-19T13:05:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固定サイズニューラルネットワークの表現力と位相特性（Topological properties of the set of functions generated by neural networks of fixed size）</news:title>
   <news:publication_date>2026-05-19T13:05:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691927</loc>
  <lastmod>2026-05-19T13:05:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TriResNetによる病理組織画像のタイル単位判定の高精度化（TriResNet: A Deep Triple-stream Residual Network for Histopathology Grading）</news:title>
   <news:publication_date>2026-05-19T13:05:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691925</loc>
  <lastmod>2026-05-19T13:05:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的文生成のための確率的ワッサースタインオートエンコーダ (Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation)</news:title>
   <news:publication_date>2026-05-19T13:05:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691923</loc>
  <lastmod>2026-05-19T13:05:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疾患関連SNPの同定のためのモデルベースクラスタリング（Model-based clustering for identifying disease-associated SNPs in case-control genome-wide association studies）</news:title>
   <news:publication_date>2026-05-19T13:05:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691921</loc>
  <lastmod>2026-05-19T12:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コレスポンデンス分析の一般化と機械学習応用（Generalizing Correspondence Analysis for Applications in Machine Learning）</news:title>
   <news:publication_date>2026-05-19T12:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691919</loc>
  <lastmod>2026-05-19T12:13:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変セグメンテーションにおける星形（Star）形状事前情報の導入（Star Shape Prior in Fully Convolutional Networks for Skin Lesion Segmentation）</news:title>
   <news:publication_date>2026-05-19T12:13:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691917</loc>
  <lastmod>2026-05-19T12:12:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ia型超新星2017ejbの前駆体に対するX線上限（X-ray Limits on the Progenitor System of the Type Ia Supernova 2017ejb）</news:title>
   <news:publication_date>2026-05-19T12:12:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691915</loc>
  <lastmod>2026-05-19T12:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画像に対応した音声映像シーン応答のエンドツーエンドモデル（End-to-End Audio Visual Scene-Aware Dialog using Multimodal Attention-Based Video Features）</news:title>
   <news:publication_date>2026-05-19T12:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691913</loc>
  <lastmod>2026-05-19T12:12:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトな離散符号による埋め込み表現の学習（Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations）</news:title>
   <news:publication_date>2026-05-19T12:12:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691911</loc>
  <lastmod>2026-05-19T12:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短時間客観的可解度と短時間スペクトル振幅二乗平均誤差の関係（On the Relationship Between Short-Time Objective Intelligibility and Short-Time Spectral-Amplitude Mean-Square Error for Speech Enhancement）</news:title>
   <news:publication_date>2026-05-19T12:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691909</loc>
  <lastmod>2026-05-19T12:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサー数・配置・システム次元性が流体のスパース再構成に与える影響（Interplay of Sensor Quantity, Placement and System Dimensionality on Energy Sparse Reconstruction of Fluid Flows）</news:title>
   <news:publication_date>2026-05-19T12:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691907</loc>
  <lastmod>2026-05-19T11:20:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークの量子化による効率的推論（Quantizing deep convolutional networks for efficient inference: A whitepaper）</news:title>
   <news:publication_date>2026-05-19T11:20:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691905</loc>
  <lastmod>2026-05-19T11:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバストな判別分析の理論と実践（Target Robust Discriminant Analysis）</news:title>
   <news:publication_date>2026-05-19T11:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691903</loc>
  <lastmod>2026-05-19T11:11:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光パルス位置変調（PPM）リンクの距離依存性と背景雑音下での情報効率（Range Dependence of an Optical Pulse Position Modulation Link in the Presence of Background Noise）</news:title>
   <news:publication_date>2026-05-19T11:11:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691901</loc>
  <lastmod>2026-05-19T11:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コマ・ベレニケス矮小銀河における初期質量関数の深層近赤外観測による解析（THE INITIAL MASS FUNCTION IN THE COMA BERENICES DWARF GALAXY FROM DEEP NEAR-INFRARED HST OBSERVATIONS）</news:title>
   <news:publication_date>2026-05-19T11:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691899</loc>
  <lastmod>2026-05-19T11:10:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震波データから深層学習で地下水貯留量を推定する（Estimation of groundwater storage from seismic data using deep learning）</news:title>
   <news:publication_date>2026-05-19T11:10:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691897</loc>
  <lastmod>2026-05-19T11:10:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模画像データ群における解釈可能な発見検出（Interpretable Discovery in Large Image Data Sets）</news:title>
   <news:publication_date>2026-05-19T11:10:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691895</loc>
  <lastmod>2026-05-19T11:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互作用により学習するインスタンスセグメンテーション（Learning Instance Segmentation by Interaction）</news:title>
   <news:publication_date>2026-05-19T11:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691893</loc>
  <lastmod>2026-05-19T10:18:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェア小型化と画像再構成のトレードオフを覆す試み（Can Deep Learning Relax Endomicroscopy Hardware Miniaturization Requirements?）</news:title>
   <news:publication_date>2026-05-19T10:18:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691891</loc>
  <lastmod>2026-05-19T10:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子キッチンシンク：近接期量子コンピュータ向け機械学習アルゴリズム（Quantum Kitchen Sinks: An algorithm for machine learning on near-term quantum computers）</news:title>
   <news:publication_date>2026-05-19T10:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691889</loc>
  <lastmod>2026-05-19T10:08:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Countdown Regressionによる生存予測の鋭さと較正性の向上（Countdown Regression: Sharp and Calibrated Survival Predictions）</news:title>
   <news:publication_date>2026-05-19T10:08:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691887</loc>
  <lastmod>2026-05-19T10:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Par4Sim – 適応型パラフレーズによる文章簡易化（Par4Sim – Adaptive Paraphrasing for Text Simplification）</news:title>
   <news:publication_date>2026-05-19T10:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691885</loc>
  <lastmod>2026-05-19T10:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン鞍点問題とナップザック付きオンライン凸最適化の解法（The Online Saddle Point Problem and Online Convex Optimization with Knapsacks）</news:title>
   <news:publication_date>2026-05-19T10:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691883</loc>
  <lastmod>2026-05-19T10:06:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>図に対するグラフ重み付きモデルの学習（Learning Graph Weighted Models on Pictures）</news:title>
   <news:publication_date>2026-05-19T10:06:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691881</loc>
  <lastmod>2026-05-19T10:06:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fashion-Gen: Generative Fashion Datasetとチャレンジ（Fashion-Gen: The Generative Fashion Dataset and Challenge）</news:title>
   <news:publication_date>2026-05-19T10:06:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691879</loc>
  <lastmod>2026-05-19T09:15:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>良い局所最小値はスパース復元で幅があるのか（Are good local minima wide in sparse recovery?）</news:title>
   <news:publication_date>2026-05-19T09:15:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691877</loc>
  <lastmod>2026-05-19T09:15:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムシードの数はどれだけ必要か（How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments）</news:title>
   <news:publication_date>2026-05-19T09:15:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691875</loc>
  <lastmod>2026-05-19T09:14:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パノラマ画像からの室内レイアウト復元（Layouts from Panoramic Images with Geometry and Deep Learning）</news:title>
   <news:publication_date>2026-05-19T09:14:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691873</loc>
  <lastmod>2026-05-19T09:14:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HD 163296の高コントラストイメージング（High-contrast imaging of HD 163296 with the Keck/NIRC2 L&amp;#039;-band vortex coronograph）</news:title>
   <news:publication_date>2026-05-19T09:14:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691871</loc>
  <lastmod>2026-05-19T09:14:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素数を取り入れたゲート付き再帰ニューラルネットワーク（Complex Gated Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-19T09:14:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691869</loc>
  <lastmod>2026-05-19T09:13:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子コトンネリング間の待ち時間分布（Distribution of waiting times between electron cotunnelings）</news:title>
   <news:publication_date>2026-05-19T09:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691867</loc>
  <lastmod>2026-05-19T09:13:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付きノードの動的状態を目に見える形で復元する方法（Transparent Recovery of Dynamic States on Constrained Nodes through Deep Packet Inspection）</news:title>
   <news:publication_date>2026-05-19T09:13:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691865</loc>
  <lastmod>2026-05-19T08:22:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インターネットアーカイブの画像データから人物関係を抽出する手法（Finding Person Relations in Image Data of the Internet Archive）</news:title>
   <news:publication_date>2026-05-19T08:22:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691863</loc>
  <lastmod>2026-05-19T08:14:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の活動のためのマルチモーダル表現学習（Learning Multimodal Representations for Unseen Activities）</news:title>
   <news:publication_date>2026-05-19T08:14:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691861</loc>
  <lastmod>2026-05-19T08:14:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>X線回折分光で読み解く新星SMC 2016の教訓（WHAT WE LEARN FROM THE X-RAY GRATING SPECTRA OF NOVA SMC 2016）</news:title>
   <news:publication_date>2026-05-19T08:14:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691859</loc>
  <lastmod>2026-05-19T08:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移調不変な音程特徴量の学習（Learning transposition-invariant interval features from symbolic music and audio）</news:title>
   <news:publication_date>2026-05-19T08:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691857</loc>
  <lastmod>2026-05-19T08:13:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ削減に基づく線形時間分割クラスタリングの実務的意義（Reductive Clustering: An Efficient Linear-time Graph-based Divisive Cluster Analysis Approach）</news:title>
   <news:publication_date>2026-05-19T08:13:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691855</loc>
  <lastmod>2026-05-19T08:12:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点注釈からのシナプス結合予測（Synaptic partner prediction from point annotations in insect brains）</news:title>
   <news:publication_date>2026-05-19T08:12:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691853</loc>
  <lastmod>2026-05-19T08:12:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CMS 5.02 TeV ジェット測定が示すグルオンPDFへの影響（Impact of CMS 5.02 TeV dijet measurements on gluon PDFs – a preliminary view）</news:title>
   <news:publication_date>2026-05-19T08:12:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691851</loc>
  <lastmod>2026-05-19T07:21:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デバイス意識型のニューラルアーキテクチャ探索が変える現場（DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures）</news:title>
   <news:publication_date>2026-05-19T07:21:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691849</loc>
  <lastmod>2026-05-19T07:11:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多分野デジタルライブラリのメタデータ拡充（Metadata Enrichment of Multi-Disciplinary Digital Library: A Semantic-based Approach）</news:title>
   <news:publication_date>2026-05-19T07:11:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691847</loc>
  <lastmod>2026-05-19T07:11:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的PARAFAC2の実務的意義（Probabilistic PARAFAC2）</news:title>
   <news:publication_date>2026-05-19T07:11:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691845</loc>
  <lastmod>2026-05-19T07:10:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ単位の分類のための凸解法（A convex method for classification of groups of examples）</news:title>
   <news:publication_date>2026-05-19T07:10:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691843</loc>
  <lastmod>2026-05-19T07:10:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>血流中の赤血球形状を自動分類する手法（Classification of red blood cell shapes in flow using outlier tolerant machine learning）</news:title>
   <news:publication_date>2026-05-19T07:10:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691841</loc>
  <lastmod>2026-05-19T07:10:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイジー値・比較モデルにおけるインスタンス最適性（Instance-Optimality in the Noisy Value-and Comparison-Model）</news:title>
   <news:publication_date>2026-05-19T07:10:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691839</loc>
  <lastmod>2026-05-19T07:09:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数インスタンスデータセットの特徴付け（Characterizing Multiple Instance Datasets）</news:title>
   <news:publication_date>2026-05-19T07:09:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691837</loc>
  <lastmod>2026-05-19T06:18:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等分散誤差を仮定したガウス構造方程式モデルの識別性（Identifiability of Gaussian Structural Equation Models with Dependent Errors Having Equal Variances）</news:title>
   <news:publication_date>2026-05-19T06:18:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691835</loc>
  <lastmod>2026-05-19T06:18:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CaloriNet: プライベート環境でのシルエットを用いた消費カロリー推定（CaloriNet: From silhouettes to calorie estimation in private environments）</news:title>
   <news:publication_date>2026-05-19T06:18:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691833</loc>
  <lastmod>2026-05-19T06:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル不確実性に強いブースティング手法（Robust and Efficient Boosting Method using the Conditional Risk）</news:title>
   <news:publication_date>2026-05-19T06:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691831</loc>
  <lastmod>2026-05-19T06:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スライス・ワッサースタインフロー（Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions）</news:title>
   <news:publication_date>2026-05-19T06:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691829</loc>
  <lastmod>2026-05-19T06:17:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム多孔質媒質を通るストークス流のデータ駆動型次元削減（A data-driven model order reduction approach for Stokes flow through random porous media）</news:title>
   <news:publication_date>2026-05-19T06:17:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691827</loc>
  <lastmod>2026-05-19T06:17:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変品質サンプルからのランキング学習（Learning to Rank from Samples of Variable Quality）</news:title>
   <news:publication_date>2026-05-19T06:17:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691825</loc>
  <lastmod>2026-05-19T06:17:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習による資源スケジューリング新手法（A New Approach for Resource Scheduling with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-19T06:17:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691823</loc>
  <lastmod>2026-05-19T05:26:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の動作生成におけるRNNと敵対的学習の統合（Combining Recurrent Neural Networks and Adversarial Training for Human Motion Modelling, Synthesis and Control）</news:title>
   <news:publication_date>2026-05-19T05:26:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691821</loc>
  <lastmod>2026-05-19T05:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業制御システムにおけるサイバー攻撃検知と畳み込みニューラルネットワーク（Detecting Cyberattacks in Industrial Control Systems Using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-19T05:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691819</loc>
  <lastmod>2026-05-19T05:26:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ensemble p-Laplacian正則化によるリモートセンシング画像認識（Ensemble p-Laplacian Regularization for Remote Sensing Image Recognition）</news:title>
   <news:publication_date>2026-05-19T05:26:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691817</loc>
  <lastmod>2026-05-19T05:25:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外科手技の動作分割と認識に深層強化学習を適用する（Deep Reinforcement Learning for Surgical Gesture Segmentation and Classification）</news:title>
   <news:publication_date>2026-05-19T05:25:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691815</loc>
  <lastmod>2026-05-19T05:25:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型アプリケーション保守が変える現場運用（Data-Driven Application Maintenance: Views from the Trenches）</news:title>
   <news:publication_date>2026-05-19T05:25:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691813</loc>
  <lastmod>2026-05-19T05:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラマルキアン進化による畳み込みニューラルネットワークの最適化（Lamarckian Evolution of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-19T05:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691811</loc>
  <lastmod>2026-05-19T05:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフ p-ラプラシアン正則化によるリモートセンシング画像認識（Hypergraph p-Laplacian Regularization for Remote Sensing Image Recognition）</news:title>
   <news:publication_date>2026-05-19T05:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691809</loc>
  <lastmod>2026-05-19T04:34:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行為―認知ループにおける能動推論の拡張（Expanding the Active Inference Landscape: More Intrinsic Motivations in the Perception-Action Loop）</news:title>
   <news:publication_date>2026-05-19T04:34:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691807</loc>
  <lastmod>2026-05-19T04:34:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然な力学の頑健性を量る—基底境界を越えて（Beyond Basins of Attraction: Quantifying Robustness of Natural Dynamics）</news:title>
   <news:publication_date>2026-05-19T04:34:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691805</loc>
  <lastmod>2026-05-19T04:33:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GrCAN：Gradient Boost Convolutional Autoencoder with Neural Decision Forest（GrCAN: Gradient Boost Convolutional Autoencoder with Neural Decision Forest）</news:title>
   <news:publication_date>2026-05-19T04:33:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691803</loc>
  <lastmod>2026-05-19T04:33:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ガウス過程を用いたベイズ推論による汚染源局在化（Deep Gaussian Process-Based Bayesian Inference for Contaminant Source Localization）</news:title>
   <news:publication_date>2026-05-19T04:33:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691801</loc>
  <lastmod>2026-05-19T04:33:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ステガノ解析の視点から見た敵対的例の検出（Detection based Defense against Adversarial Examples from the Steganalysis Point of View）</news:title>
   <news:publication_date>2026-05-19T04:33:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691799</loc>
  <lastmod>2026-05-19T04:32:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書誘導型編集ネットワークによるパラフレーズ生成（Dictionary-Guided Editing Networks for Paraphrase Generation）</news:title>
   <news:publication_date>2026-05-19T04:32:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691797</loc>
  <lastmod>2026-05-19T04:32:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットを用いた認知モデル学習（Learning Cognitive Models using Neural Networks）</news:title>
   <news:publication_date>2026-05-19T04:32:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691795</loc>
  <lastmod>2026-05-19T03:41:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔軟な物理予測のためのニューラル表現（Flexible Neural Representation for Physics Prediction）</news:title>
   <news:publication_date>2026-05-19T03:41:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691793</loc>
  <lastmod>2026-05-19T03:41:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈手法の頑健性について（On the Robustness of Interpretability Methods）</news:title>
   <news:publication_date>2026-05-19T03:41:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691791</loc>
  <lastmod>2026-05-19T03:41:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差補償付き量子化SGDと大規模分散最適化への応用（Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization）</news:title>
   <news:publication_date>2026-05-19T03:41:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691789</loc>
  <lastmod>2026-05-19T03:41:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズのある手書きバングラ文字の画素レベル再構成と分類（Pixel-level Reconstruction and Classification for Noisy Handwritten Bangla Characters）</news:title>
   <news:publication_date>2026-05-19T03:41:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691787</loc>
  <lastmod>2026-05-19T03:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話のためのコヒーレンスモデル（Coherence Models for Dialogue）</news:title>
   <news:publication_date>2026-05-19T03:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691785</loc>
  <lastmod>2026-05-19T03:40:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配敵対的訓練がもたらす変化（Gradient Adversarial Training of Neural Networks）</news:title>
   <news:publication_date>2026-05-19T03:40:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691783</loc>
  <lastmod>2026-05-19T03:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>21世紀の理科教育（Science Education in the 21st Century）</news:title>
   <news:publication_date>2026-05-19T03:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691781</loc>
  <lastmod>2026-05-19T02:49:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予約ありキューの均衡と学習（Equilibrium and Learning in Queues with Advance Reservations）</news:title>
   <news:publication_date>2026-05-19T02:49:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691779</loc>
  <lastmod>2026-05-19T02:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識ベースの埋め込みモデルを解釈する教育的アプローチ（Interpreting Embedding Models of Knowledge Bases: A Pedagogical Approach）</news:title>
   <news:publication_date>2026-05-19T02:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691777</loc>
  <lastmod>2026-05-19T02:38:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散乱復元に強い学習モデルの安定性（Stability of Scattering Decoder for Nonlinear Diffractive Imaging）</news:title>
   <news:publication_date>2026-05-19T02:38:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691775</loc>
  <lastmod>2026-05-19T02:38:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地平線を使った単眼障害物検出の新視点（Learning What’s Above and What’s Below: Horizon Approach to Monocular Obstacle Detection）</news:title>
   <news:publication_date>2026-05-19T02:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691773</loc>
  <lastmod>2026-05-19T02:38:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人口統計情報なしでの繰返し損失最小化における公平性（Fairness Without Demographics in Repeated Loss Minimization）</news:title>
   <news:publication_date>2026-05-19T02:38:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691771</loc>
  <lastmod>2026-05-19T02:38:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>南極深層氷コアに記録された気候エントロピー生成（Climate entropy production recorded in a deep Antarctic ice core）</news:title>
   <news:publication_date>2026-05-19T02:38:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691769</loc>
  <lastmod>2026-05-19T02:37:44Z</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>2026-05-19T02:37:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-19T01:46:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エピソード記憶の意味的圧縮（Semantic Compression of Episodic Memories）</news:title>
   <news:publication_date>2026-05-19T01:46:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信号灯と道路標識の同時検出を可能にする階層的深層構造とミニバッチ選択法（A Hierarchical Deep Architecture and Mini-Batch Selection Method For Joint Traffic Sign and Light Detection）</news:title>
   <news:publication_date>2026-05-19T01:46:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-19T01:46:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コーパス複製タスクが示す意味抽出の本質（The Corpus Replication Task）</news:title>
   <news:publication_date>2026-05-19T01:46:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-19T01:45:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続値強化学習における過学習と汎化の解剖（A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-19T01:45:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691757</loc>
  <lastmod>2026-05-19T01:45:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディア上の論争を立場要約で説明する（Explaining Controversy on Social Media via Stance Summarization）</news:title>
   <news:publication_date>2026-05-19T01:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691755</loc>
  <lastmod>2026-05-19T01:45:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>課題指向の畳み込み再帰モデルによる視覚システムの理解（Task-Driven Convolutional Recurrent Models of the Visual System）</news:title>
   <news:publication_date>2026-05-19T01:45:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691753</loc>
  <lastmod>2026-05-19T00:54:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の仕組みと実務への示唆（How Deep Learning Works）</news:title>
   <news:publication_date>2026-05-19T00:54:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691751</loc>
  <lastmod>2026-05-19T00:53:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハッブル・フロンティア・フィールドにおける遠方銀河の拡大バイアス：波動（ウェーブ）対粒子ダークマターの検証（MAGNIFICATION BIAS OF DISTANT GALAXIES IN THE HUBBLE FRONTIER FIELDS: TESTING WAVE VS. PARTICLE DARK MATTER PREDICTIONS）</news:title>
   <news:publication_date>2026-05-19T00:53:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-19T00:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホットジュピター大気における乱流駆動熱・運動エネルギーフラックス（Turbulence-driven thermal and kinetic energy fluxes in the atmospheres of hot Jupiters）</news:title>
   <news:publication_date>2026-05-19T00:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-19T00:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hybrid Bayesian Eigenobjects（Hybrid Bayesian Eigenobjects: Combining Linear Subspace and Deep Network Methods for 3D Robot Vision）</news:title>
   <news:publication_date>2026-05-19T00:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-19T00:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ガウス型グラフィカルモデルにおける逐次変化点検出（Sequential change-point detection in high-dimensional Gaussian graphical models）</news:title>
   <news:publication_date>2026-05-19T00:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T00:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691741</loc>
  <lastmod>2026-05-19T00:51:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交互最小化によるReLUネットワーク学習（Learning ReLU Networks via Alternating Minimization）</news:title>
   <news:publication_date>2026-05-19T00:51:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-19T00:00:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸関数と対数対数凸関数を近似するニューラルネットワークとポシノミアルモデル（Log-sum-exp neural networks and posynomial models for convex and log-log-convex data）</news:title>
   <news:publication_date>2026-05-19T00:00:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691737</loc>
  <lastmod>2026-05-19T00:00:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションから現実へ――布など変形物体操作の強化学習による移転学習（Sim-to-Real Reinforcement Learning for Deformable Object Manipulation）</news:title>
   <news:publication_date>2026-05-19T00:00:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-19T00:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-19T00:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジデバイス向け機械学習の開発と展開の再考 (Rethinking Machine Learning Development and Deployment for Edge Devices)</news:title>
   <news:publication_date>2026-05-18T23:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691731</loc>
  <lastmod>2026-05-18T23:58:50Z</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>2026-05-18T23:58:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691729</loc>
  <lastmod>2026-05-18T23:58:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均質対象の散乱係数と波イメージングにおけ別と識別への応用（Scattering Coefficients of Inhomogeneous Objects and Their Application in Target Classification in Wave Imaging）</news:title>
   <news:publication_date>2026-05-18T23:58:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691727</loc>
  <lastmod>2026-05-18T23:58:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジインテリジェンス：デバイスとエッジの協調によるオンデマンドDNN共推論（Edge Intelligence: On-Demand Deep Learning Model Co-Inference with Device-Edge Synergy）</news:title>
   <news:publication_date>2026-05-18T23:58:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691725</loc>
  <lastmod>2026-05-18T23:06:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語デカスロン：マルチタスク学習を質問応答として統一する（The Natural Language Decathlon: Multitask Learning as Question Answering）</news:title>
   <news:publication_date>2026-05-18T23:06:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691723</loc>
  <lastmod>2026-05-18T23:06:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InfoCatVAEによるカテゴリ型変分オートエンコーダを用いた表現学習（InfoCatVAE: Representation Learning with Categorical Variational Autoencoders）</news:title>
   <news:publication_date>2026-05-18T23:06:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691721</loc>
  <lastmod>2026-05-18T23:06:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズだらけでも十分か ― 医療器具の姿勢推定における注釈ノイズの影響（How Bad is Good enough: Noisy annotations for instrument pose estimation）</news:title>
   <news:publication_date>2026-05-18T23:06:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691719</loc>
  <lastmod>2026-05-18T23:05:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重ラジオレリック銀河団Abell 3376のX線解析と衝撃波の解明（X-ray study of the double radio relic Abell 3376 with Suzaku）</news:title>
   <news:publication_date>2026-05-18T23:05:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691717</loc>
  <lastmod>2026-05-18T23:04:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定論的微分可能模倣学習によるニューラルパーサ学習（Learning Neural Parsers with Deterministic Differentiable Imitation Learning）</news:title>
   <news:publication_date>2026-05-18T23:04:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691715</loc>
  <lastmod>2026-05-18T23:04:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き画像生成による物体ランドマークの教師なし学習 (Unsupervised Learning of Object Landmarks through Conditional Image Generation)</news:title>
   <news:publication_date>2026-05-18T23:04:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691713</loc>
  <lastmod>2026-05-18T23:04:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化潜在変数を用いた半教師付き意味解析（STRUCTVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing）</news:title>
   <news:publication_date>2026-05-18T23:04:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691711</loc>
  <lastmod>2026-05-18T22:12:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対応関係の重み付けを用いたメトリック駆動の2-D/3-Dレジストレーション学習 (Metric-Driven Learning of Correspondence Weighting for 2-D/3-D Registration)</news:title>
   <news:publication_date>2026-05-18T22:12:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691709</loc>
  <lastmod>2026-05-18T22:12:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的入れ子分散削減法による非凸最適化の加速（Stochastic Nested Variance Reduction for Nonconvex Optimization）</news:title>
   <news:publication_date>2026-05-18T22:12:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691707</loc>
  <lastmod>2026-05-18T22:11:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタゲノムデータからウイルスを見つける深層学習（Identifying viruses from metagenomic data by deep learning）</news:title>
   <news:publication_date>2026-05-18T22:11:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691705</loc>
  <lastmod>2026-05-18T22:10:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトニック・ハイパークリスタルの非線形光学：光リミッティングとハイパーコンピューティング（Nonlinear optics of photonic hyper-crystals: optical limiting and hyper-computing）</news:title>
   <news:publication_date>2026-05-18T22:10:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691703</loc>
  <lastmod>2026-05-18T22:10:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1層ReLUネットワークの学習と勾配降下法による収束保証（Learning One-hidden-layer ReLU Networks via Gradient Descent）</news:title>
   <news:publication_date>2026-05-18T22:10:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691701</loc>
  <lastmod>2026-05-18T22:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四元数畳み込みニューラルネットワークによるエンドツーエンド自動音声認識（Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition）</news:title>
   <news:publication_date>2026-05-18T22:10:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691697</loc>
  <lastmod>2026-05-18T21:18:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映画レビューの意見動態を捉える潜在状態モデル（Opinion Dynamics Modeling for Movie Review Transcripts Classification with Hidden Conditional Random Fields）</news:title>
   <news:publication_date>2026-05-18T21:18:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691695</loc>
  <lastmod>2026-05-18T21:17:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療用MR画像の画像間変換におけるGAN比較（GENERATIVE ADVERSARIAL NETWORKS FOR IMAGE-TO-IMAGE TRANSLATION ON MULTI-CONTRAST MR IMAGES - A COMPARISON OF CYCLEGAN AND UNIT）</news:title>
   <news:publication_date>2026-05-18T21:17:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691693</loc>
  <lastmod>2026-05-18T21:17:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絵文字の共起ネットワークを用いた埋め込み学習（Learning Emoji Embeddings using Emoji Co-occurrence Network Graph）</news:title>
   <news:publication_date>2026-05-18T21:17:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691691</loc>
  <lastmod>2026-05-18T21:16:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多数サンプルから最良を選ぶ系列サンプリング（Accurate and Diverse Sampling of Sequences based on a “Best of Many” Sample Objective）</news:title>
   <news:publication_date>2026-05-18T21:16:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691689</loc>
  <lastmod>2026-05-18T21:16:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EDGES High-Bandによる初期銀河パラメータの制約（Constraints on Parameters of Early Galaxies from EDGES High-Band）</news:title>
   <news:publication_date>2026-05-18T21:16:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691687</loc>
  <lastmod>2026-05-18T21:16:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フーリエ変換サロゲートによるクラス不均衡への対処（Addressing Class Imbalance in Classification Problems of Noisy Signals by using Fourier Transform Surrogates）</news:title>
   <news:publication_date>2026-05-18T21:16:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691685</loc>
  <lastmod>2026-05-18T21:16:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>802.11acエッジネットワークでの低遅延・高スループット実現（Quick &amp;amp; Plenty: Achieving Low Delay &amp;amp; High Rate in 802.11ac Edge Networks）</news:title>
   <news:publication_date>2026-05-18T21:16:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691683</loc>
  <lastmod>2026-05-18T20:24:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロン活性時系列からのネットワーク推定手法のレビュー (A Review of Network Inference Techniques for Neural Activation Time Series)</news:title>
   <news:publication_date>2026-05-18T20:24:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691681</loc>
  <lastmod>2026-05-18T20:23:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習システムの組合せテスト（Combinatorial Testing for Deep Learning Systems）</news:title>
   <news:publication_date>2026-05-18T20:23:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691679</loc>
  <lastmod>2026-05-18T20:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインニュースのクリックベイト検出にニューラルネットを使う（Using Neural Network for Identifying Clickbaits in Online News Media）</news:title>
   <news:publication_date>2026-05-18T20:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691677</loc>
  <lastmod>2026-05-18T20:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DEFRAG: 深層ユークリッド特徴表現の適応による整備（DEFRAG: DEEP EUCLIDEAN FEATURE REPRESENTATIONS THROUGH ADAPTATION ON THE GRASSMANN MANIFOLD）</news:title>
   <news:publication_date>2026-05-18T20:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691675</loc>
  <lastmod>2026-05-18T20:22:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張ニューラルネットワークを用いた強化学習（Reinforcement Learning using Augmented Neural Networks）</news:title>
   <news:publication_date>2026-05-18T20:22:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691673</loc>
  <lastmod>2026-05-18T20:21:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率回帰の非パラメトリック較正（Non-Parametric Calibration of Probabilistic Regression）</news:title>
   <news:publication_date>2026-05-18T20:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691671</loc>
  <lastmod>2026-05-18T20:21:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己重み付けマルチカーネル学習によるグラフベースクラスタリングと半教師あり分類（Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification）</news:title>
   <news:publication_date>2026-05-18T20:21:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691669</loc>
  <lastmod>2026-05-18T19:29:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー学習における動的投票と放射線オミクス応用（Dynamic voting in multi-view learning for radiomics applications）</news:title>
   <news:publication_date>2026-05-18T19:29:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691667</loc>
  <lastmod>2026-05-18T19:29:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化されたファクトチェックの展望（Automated Fact Checking: Task formulations, methods and future directions）</news:title>
   <news:publication_date>2026-05-18T19:29:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691665</loc>
  <lastmod>2026-05-18T19:28:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカルグループ矮小銀河の初期進化：星形成と超新星フィードバック（On the early evolution of Local Group dwarf galaxy types: star formation and supernova feedback）</news:title>
   <news:publication_date>2026-05-18T19:28:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691663</loc>
  <lastmod>2026-05-18T19:28:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なるパラダイム間での畳み込みネットワーク事前学習が脳内EEGデコーディングを改善する（Cross-paradigm pretraining of convolutional networks improves intracranial EEG decoding）</news:title>
   <news:publication_date>2026-05-18T19:28:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691661</loc>
  <lastmod>2026-05-18T19:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ΛΛ−ΞN混合がもたらす非メゾニック崩壊の変化（Eﬀects of ΛΛ −ΞN mixing in the decay of S = −2 hypernuclei）</news:title>
   <news:publication_date>2026-05-18T19:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691659</loc>
  <lastmod>2026-05-18T19:27:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダークエネルギー方程式の遅延変化の制約（Constraining late-time transitions in the dark energy equation of state）</news:title>
   <news:publication_date>2026-05-18T19:27:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691657</loc>
  <lastmod>2026-05-18T19:27:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀行の実運用に耐える顔照合の越境対応（Cross-Domain Deep Face Matching for Real Banking Security Systems）</news:title>
   <news:publication_date>2026-05-18T19:27:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691655</loc>
  <lastmod>2026-05-18T18:36:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スキル経験カタログ（Skilled Experience Catalogue: A Skill-Balancing Mechanism for Non-Player Characters using Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-18T18:36:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691653</loc>
  <lastmod>2026-05-18T18:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次自動運転車両の動的リスク評価を深層学習で実現する（Dynamic Risk Assessment for Vehicles of Higher Automation Levels by Deep Learning）</news:title>
   <news:publication_date>2026-05-18T18:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691651</loc>
  <lastmod>2026-05-18T18:35:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏極深部非弾性散乱における包摂的重フレーバー生成への NLO QCD 補正 (Next-to-Leading Order QCD Corrections to Inclusive Heavy-Flavor Production in Polarized Deep-Inelastic Scattering)</news:title>
   <news:publication_date>2026-05-18T18:35:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691649</loc>
  <lastmod>2026-05-18T18:35:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり学習と敵対的生成ネットワークによる発作予測（Semi-supervised Seizure Prediction with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-18T18:35:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691647</loc>
  <lastmod>2026-05-18T18:35:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実時間歩行者追跡のための深い類似度メトリック学習（Deep Similarity Metric Learning for Real-Time Pedestrian Tracking）</news:title>
   <news:publication_date>2026-05-18T18:35:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691645</loc>
  <lastmod>2026-05-18T18:34:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽子の形状ゆらぎと深層散乱の関係（Proton shape fluctuations and its relation to DIS）</news:title>
   <news:publication_date>2026-05-18T18:34:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691643</loc>
  <lastmod>2026-05-18T18:34:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リーマン最適量子化と航空交通解析への応用（Optimal Riemannian quantization with an application to air traffic analysis）</news:title>
   <news:publication_date>2026-05-18T18:34:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691641</loc>
  <lastmod>2026-05-18T17:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロブログからのニュースイベント抽出（Extracting News Events from Microblogs）</news:title>
   <news:publication_date>2026-05-18T17:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691639</loc>
  <lastmod>2026-05-18T17:43:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳動脈瘤の壁応力推定におけるZernike畳み込みニューラルネットワーク（Wall Stress Estimation of Cerebral Aneurysm based on Zernike Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-18T17:43:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691637</loc>
  <lastmod>2026-05-18T17:42:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルタンジェントカーネルが示す学習の姿（Neural Tangent Kernel: Convergence and Generalization in Neural Networks）</news:title>
   <news:publication_date>2026-05-18T17:42:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691635</loc>
  <lastmod>2026-05-18T17:42:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的安全ベイズ最適化の実務的解説（Stagewise Safe Bayesian Optimization with Gaussian Processes）</news:title>
   <news:publication_date>2026-05-18T17:42:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691633</loc>
  <lastmod>2026-05-18T17:42:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できる分散二次最適化アルゴリズム（A Distributed Second-Order Algorithm You Can Trust）</news:title>
   <news:publication_date>2026-05-18T17:42:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691631</loc>
  <lastmod>2026-05-18T17:42:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Doubly Nested Networkによるリソース効率化推論（Doubly Nested Network for Resource-Efficient Inference）</news:title>
   <news:publication_date>2026-05-18T17:42:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691629</loc>
  <lastmod>2026-05-18T17:41:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル付き確率的ブロックモデルにおける効率的推論（Efficient inference in stochastic block models with vertex labels）</news:title>
   <news:publication_date>2026-05-18T17:41:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691627</loc>
  <lastmod>2026-05-18T16:50:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>流体流のエンドツーエンドと逐次データ駆動学習の評価 (Assessment of End-to-End and Sequential Data-driven Learning of Fluid Flows)</news:title>
   <news:publication_date>2026-05-18T16:50:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691625</loc>
  <lastmod>2026-05-18T16:50:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誰にとって解釈可能かを問う役割モデル（Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems）</news:title>
   <news:publication_date>2026-05-18T16:50:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691623</loc>
  <lastmod>2026-05-18T16:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビット当たりネットワークか、ネットワーク当たりビットか（Binary Ensemble Neural Network: More Bits per Network or More Networks per Bit?）</news:title>
   <news:publication_date>2026-05-18T16:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691621</loc>
  <lastmod>2026-05-18T16:49:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データのための非同期分散期待値最大化アルゴリズム（An Asynchronous Distributed Expectation Maximization Algorithm For Massive Data: The DEM Algorithm）</news:title>
   <news:publication_date>2026-05-18T16:49:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691619</loc>
  <lastmod>2026-05-18T16:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重散乱媒体のイメージングを終端学習型ニューラルネットで（Multiple Scattering Media Imaging via End-to-End Neural Network）</news:title>
   <news:publication_date>2026-05-18T16:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691617</loc>
  <lastmod>2026-05-18T16:49:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>配列だけで化合物－タンパク質親和性を読む（DeepAffinity: Interpretable Deep Learning of Compound–Protein Affinity）</news:title>
   <news:publication_date>2026-05-18T16:49:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691615</loc>
  <lastmod>2026-05-18T16:48:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己説明型ニューラルネットワークによる頑健な解釈性の追求 (Towards Robust Interpretability with Self-Explaining Neural Networks)</news:title>
   <news:publication_date>2026-05-18T16:48:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691613</loc>
  <lastmod>2026-05-18T15:56:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像全体の注釈を人機協調で効率化するインターフェース（Fluid Annotation: A Human-Machine Collaboration Interface for Full Image Annotation）</news:title>
   <news:publication_date>2026-05-18T15:56:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691611</loc>
  <lastmod>2026-05-18T15:56:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多課題転移学習における不確実性（Uncertainty in Multitask Transfer Learning）</news:title>
   <news:publication_date>2026-05-18T15:56:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691609</loc>
  <lastmod>2026-05-18T15:56:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械読解の統合フレームワーク（Jack the Reader – A Machine Reading Framework）</news:title>
   <news:publication_date>2026-05-18T15:56:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691607</loc>
  <lastmod>2026-05-18T15:55:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定性的および定量的因子を扱うガウス過程モデリングへの潜在変数アプローチ (A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors)</news:title>
   <news:publication_date>2026-05-18T15:55:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691605</loc>
  <lastmod>2026-05-18T15:55:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習と浅層学習の簡易融合による音響シーン分類（A SIMPLE FUSION OF DEEP AND SHALLOW LEARNING FOR ACOUSTIC SCENE CLASSIFICATION）</news:title>
   <news:publication_date>2026-05-18T15:55:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691603</loc>
  <lastmod>2026-05-18T15:54:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>植え込み型スパース構造問題の還元と計算下界（Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure）</news:title>
   <news:publication_date>2026-05-18T15:54:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691601</loc>
  <lastmod>2026-05-18T15:54:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的サロゲートモデルにおける「局所性」の定義（Defining Locality for Surrogates in Post-hoc Interpretability）</news:title>
   <news:publication_date>2026-05-18T15:54:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691599</loc>
  <lastmod>2026-05-18T15:03:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所深層特徴学習による堅牢な顔スプーフィング検出（On the Learning of Deep Local Features for Robust Face Spoofing Detection）</news:title>
   <news:publication_date>2026-05-18T15:03:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691597</loc>
  <lastmod>2026-05-18T15:02:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Global-Connected Net と Generalized Multi-Piecewise ReLU の要点解説（Deep Global-Connected Net With The Generalized Multi-Piecewise ReLU Activation in Deep Learning）</news:title>
   <news:publication_date>2026-05-18T15:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691595</loc>
  <lastmod>2026-05-18T15:02:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D超音波から標準断面を自動検出する反復変換ネットワーク（Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network）</news:title>
   <news:publication_date>2026-05-18T15:02:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691593</loc>
  <lastmod>2026-05-18T15:01:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HairNetによる単一視点からの3Dヘア再構築（HairNet: Single-View Hair Reconstruction using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-18T15:01:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691591</loc>
  <lastmod>2026-05-18T15:01:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>薄い弾性シート上の水面に浮かぶハイドロエラスティック波紋（Hydroelastic wake on a thin elastic sheet floating on water）</news:title>
   <news:publication_date>2026-05-18T15:01:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691589</loc>
  <lastmod>2026-05-18T15:01:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしグラフ埋め込みの意味内容の探索（Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study）</news:title>
   <news:publication_date>2026-05-18T15:01:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/691587</loc>
  <lastmod>2026-05-18T15:00:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子スケール画像から相図を再構築する方法（Learning from imperfections: constructing phase diagrams from atomic imaging of fluctuations）</news:title>
   <news:publication_date>2026-05-18T15:00:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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