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   <news:title>階層-aware逆強化学習の探求（Exploring Hierarchy-Aware Inverse Reinforcement Learning）</news:title>
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   <news:title>Mastodonデータで切り拓く対話行為と感情認識の再現性（Multi-task dialog act and sentiment recognition on Mastodon）</news:title>
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   <news:title>SGDの歩幅と損失の鋭さが示す学習の本質（On the relation between the sharpest directions of DNN loss and the SGD step length）</news:title>
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   <news:title>波形と学習で見えるてんかん発作の自動検出（A hybrid automated detection of epileptic seizures in EEG based on wavelet and machine learning techniques）</news:title>
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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>深層生成モデルは異常検知で本当に優れているのか（Are generative deep models for novelty detection truly better?）</news:title>
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    <news:language>ja</news:language>
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   <news:title>ブラックホールのエントロピーと情報パラドックスの再検討 (Revisiting the black hole entropy and the information paradox)</news:title>
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    <news:language>ja</news:language>
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   <news:title>マルチ感情資源強化注意ネットワークによる感情分類の改良（A Multi-sentiment-resource Enhanced Attention Network for Sentiment Classification）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>知識グラフを意識したオートエンコーダによるレコメンデーション（Computing recommendations via a Knowledge Graph-aware Autoencoder）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>Zoom-Net: 深層特徴間の相互作用を掘る視覚関係認識（Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>超グラフのスペクトル疎化の実装的意義（Spectral Sparsification of Hypergraphs）</news:title>
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    <news:language>ja</news:language>
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   <news:title>未知の環境における物体認識（Recognition in Terra Incognita）</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>プロジェクト駆動型建設における統合情報システムの展望（Envision of an Integrated Information System for Project-Driven Production in Construction）</news:title>
   <news:publication_date>2026-05-26T08:31:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-26T07:40:04Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>赤外検出器に残る「残像」を可視化する指標の提案（Persistence Characterisation of Teledyne H2RG detectors）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>Behler–Parrinelloニューラルネットワークを用いた自己学習モンテカルロ法（Self-learning Monte Carlo method with Behler–Parrinello neural networks）</news:title>
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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>現場でのディープラーニング（Deep Learning in the Wild）</news:title>
   <news:publication_date>2026-05-26T07:39:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>非ガウス成分解析とエントロピー手法（Non-Gaussian Component Analysis using Entropy Methods）</news:title>
   <news:publication_date>2026-05-26T07:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>GANが作る偽物の見分け方（TequilaGAN: How to easily identify GAN samples）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-26T07:39:04Z</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>逐次データ下のガウス過程潜在変数モデルの逐次サンプリング（Sequential sampling of Gaussian process latent variable models）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-26T07:38:34Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>強結合系での大規模キャット状態の高速増幅と位相再同期（Fast amplification and rephasing of entangled cat states in a qubit-oscillator system）</news:title>
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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>超細粒度エンティティタイピング（Ultra-Fine Entity Typing）</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>構造化解析辞書学習（Structured Analysis Dictionary Learning: Structure for Robustness）</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>メムリスタで作るパーセプトロン（Perceptrons from Memristors）</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>確率的再集計アルゴリズム（Probabilistic Re-aggregation Algorithm）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-26T06:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>周囲のセグメンテーション文脈によるタイトボックスの探索（Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection）</news:title>
   <news:publication_date>2026-05-26T06:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
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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>スマートフォンを用いた医療モニタの数値読み取り（Utilizing Smartphone-Based Machine Learning in Medical Monitor Data Collection: Seven Segment Digit Recognition）</news:title>
   <news:publication_date>2026-05-26T06:46:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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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>皮膚病変の自動セグメンテーション（Automatic segmentation of skin lesions using deep learning）</news:title>
   <news:publication_date>2026-05-26T06:46:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>潜在変数の崩壊を避ける生成スキップモデル（Avoiding Latent Variable Collapse with Generative Skip Models）</news:title>
   <news:publication_date>2026-05-26T05:55:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/694390</loc>
  <lastmod>2026-05-26T05:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コントラスト埋め込みによる距離学習アルゴリズム（Algorithms for Metric Learning via Contrastive Embeddings）</news:title>
   <news:publication_date>2026-05-26T05:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/694388</loc>
  <lastmod>2026-05-26T05:46:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep LOFAR 150 MHz観測によるBoötes領域の低周波数深宇宙地図（Deep LOFAR 150 MHz imaging of the Boötes field: Unveiling the faint low-frequency sky）</news:title>
   <news:publication_date>2026-05-26T05:46:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/694386</loc>
  <lastmod>2026-05-26T05:45:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可逆な一般化同期による暗黙学習のメカニズム（Invertible generalized synchronization: A putative mechanism for implicit learning in biological and artificial neural systems）</news:title>
   <news:publication_date>2026-05-26T05:45:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-26T05:45:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>模倣学習軌道の予測可能性（Predictability of the imitative learning trajectories）</news:title>
   <news:publication_date>2026-05-26T05:45:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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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>特徴設計に依存しないOCTボリュームからの緑内障検出（A feature agnostic approach for glaucoma detection in OCT volumes）</news:title>
   <news:publication_date>2026-05-26T05:45:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>操作ビデオから接触と動きを抽出する技術（Extracting Contact and Motion from Manipulation Videos）</news:title>
   <news:publication_date>2026-05-26T05:44:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/694378</loc>
  <lastmod>2026-05-26T04:53:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声と顔画像のクロスモーダル照合のための分離写像ネットワーク（Disjoint Mapping Network for Cross-modal Matching of Voices and Faces）</news:title>
   <news:publication_date>2026-05-26T04:53:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694376</loc>
  <lastmod>2026-05-26T04:53:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次世代育成：工学分野のラーニングアシスタント・プログラムの成果 (Cultivating the Next Generation: Outcomes from a Learning Assistant Program in Engineering)</news:title>
   <news:publication_date>2026-05-26T04:53:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694374</loc>
  <lastmod>2026-05-26T04:53:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変量を比較することで導く最適な照合・検索戦略（Optimal Strategies for Matching and Retrieval Problems by Comparing Covariates）</news:title>
   <news:publication_date>2026-05-26T04:53:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694372</loc>
  <lastmod>2026-05-26T04:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DP-GP-LVMで学ぶ多変量依存構造の自動発見（DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures）</news:title>
   <news:publication_date>2026-05-26T04:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694370</loc>
  <lastmod>2026-05-26T04:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>撮像段階の工夫でAIの超解像を強化する（Optimal Physical Preprocessing for Example-Based Super-Resolution）</news:title>
   <news:publication_date>2026-05-26T04:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694368</loc>
  <lastmod>2026-05-26T04:52:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体の視点合成のための潜在変換（Latent Transformations for Object View Points Synthesis）</news:title>
   <news:publication_date>2026-05-26T04:52:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694366</loc>
  <lastmod>2026-05-26T04:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TDOAを用いた位置推定と確率的勾配法の実務的示唆（TDOA-based Localization via Stochastic Gradient Descent Variants）</news:title>
   <news:publication_date>2026-05-26T04:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694364</loc>
  <lastmod>2026-05-26T04:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心筋ひずみ解析における学習ベースの正則化とドメイン適応の可能性（Learning-based Regularization for Cardiac Strain Analysis with Ability for Domain Adaptation）</news:title>
   <news:publication_date>2026-05-26T04:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694362</loc>
  <lastmod>2026-05-26T04:00:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実務で直面するアクティブラーニングの障害（Practical Obstacles to Deploying Active Learning）</news:title>
   <news:publication_date>2026-05-26T04:00:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694360</loc>
  <lastmod>2026-05-26T04:00:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生活満足度調査における特徴選択による性別分類（Feature Selection for Gender Classification in TUIK Life Satisfaction Survey）</news:title>
   <news:publication_date>2026-05-26T04:00:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694358</loc>
  <lastmod>2026-05-26T03:59:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非エルゴード拡張状態を介した効率的なポピュレーション転送（Efficient population transfer via non-ergodic extended states in quantum spin glass）</news:title>
   <news:publication_date>2026-05-26T03:59:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694356</loc>
  <lastmod>2026-05-26T03:59:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hydranetによる回帰ニューラルネットのデータ拡張（Hydranet: Data Augmentation for Regression Neural Networks）</news:title>
   <news:publication_date>2026-05-26T03:59:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694354</loc>
  <lastmod>2026-05-26T03:59:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英語過去形論争の再検討（Recurrent Neural Networks in Linguistic Theory: Revisiting Pinker and Prince and the Past Tense Debate）</news:title>
   <news:publication_date>2026-05-26T03:59:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694352</loc>
  <lastmod>2026-05-26T03:58:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルゴリズムの説明責任評価モデル（A Model for Evaluating Algorithmic Systems Accountability）</news:title>
   <news:publication_date>2026-05-26T03:58:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694350</loc>
  <lastmod>2026-05-26T03:07:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェット画像とN-subjettinessの比較が示す本質（Reports of My Demise Are Greatly Exaggerated: N-subjettiness Taggers Take On Jet Images）</news:title>
   <news:publication_date>2026-05-26T03:07:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694348</loc>
  <lastmod>2026-05-26T03:07:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽子線によるハイブリッドCMOS検出器の損傷実験（Proton Radiation Damage Experiment on a Hybrid CMOS Detector）</news:title>
   <news:publication_date>2026-05-26T03:07:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694346</loc>
  <lastmod>2026-05-26T03:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QA向けRNNの精度改善に効く名詞タグ付け（Improving on Q &amp;amp; A Recurrent Neural Networks Using Noun-Tagging）</news:title>
   <news:publication_date>2026-05-26T03:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694344</loc>
  <lastmod>2026-05-26T03:06:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲームダイナミクス改善のための負のモメンタム（Negative Momentum for Improved Game Dynamics）</news:title>
   <news:publication_date>2026-05-26T03:06:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694342</loc>
  <lastmod>2026-05-26T03:06:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-26T03:06:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694340</loc>
  <lastmod>2026-05-26T03:06:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習がセキュリティに出会う時（When deep learning meets security）</news:title>
   <news:publication_date>2026-05-26T03:06:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694338</loc>
  <lastmod>2026-05-26T03:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イメージで目標を想像する視覚強化学習（Visual Reinforcement Learning with Imagined Goals）</news:title>
   <news:publication_date>2026-05-26T03:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694336</loc>
  <lastmod>2026-05-26T02:14:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボトルネックシミュレータ：モデルベース深層強化学習の手法（The Bottleneck Simulator: A Model-based Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-05-26T02:14:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694334</loc>
  <lastmod>2026-05-26T02:14:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルな畳み込み辞書学習と制約付き再帰スパースオートエンコーダ（Scalable Convolutional Dictionary Learning with Constrained Recurrent Sparse Auto-Encoders）</news:title>
   <news:publication_date>2026-05-26T02:14:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694332</loc>
  <lastmod>2026-05-26T02:14:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANにおける正則化と正規化の大規模比較（A Large-Scale Study on Regularization and Normalization in GANs）</news:title>
   <news:publication_date>2026-05-26T02:14:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694330</loc>
  <lastmod>2026-05-26T02:14:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-26T02:14:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694328</loc>
  <lastmod>2026-05-26T02:13:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相を保つ潜在表現による変分オートエンコーダの探究（Explorations in Homeomorphic Variational Auto-Encoding）</news:title>
   <news:publication_date>2026-05-26T02:13:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694326</loc>
  <lastmod>2026-05-26T02:13:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類における貪欲選択で高精度と高疎性を両立する手法（Orthogonal Matching Pursuit for Text Classification）</news:title>
   <news:publication_date>2026-05-26T02:13:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694324</loc>
  <lastmod>2026-05-26T02:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン専門家の時間を効率的に使う関係抽出法（Making Efficient Use of a Domain Expert’s Time in Relation Extraction）</news:title>
   <news:publication_date>2026-05-26T02:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694322</loc>
  <lastmod>2026-05-26T01:22:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実写真のノイズ除去を前進させたCBDNet（Toward Convolutional Blind Denoising of Real Photographs）</news:title>
   <news:publication_date>2026-05-26T01:22:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694320</loc>
  <lastmod>2026-05-26T01:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HyperNetsによる空間変換の学習（HyperNets: Learning to manipulate network parameters）</news:title>
   <news:publication_date>2026-05-26T01:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694318</loc>
  <lastmod>2026-05-26T01:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換に基づく非教師付き点登録による未シード低ランクグラフ写像（Unseeded low-rank graph matching by transform-based unsupervised point registration）</news:title>
   <news:publication_date>2026-05-26T01:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694316</loc>
  <lastmod>2026-05-26T01:21:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約整合学習のためのライブラリ（A Library for Constraint Consistent Learning）</news:title>
   <news:publication_date>2026-05-26T01:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694314</loc>
  <lastmod>2026-05-26T01:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スクリブルだけで医療画像のセグメンテーションを学ぶ（Learning to Segment Medical Images with Scribble-Supervision Alone）</news:title>
   <news:publication_date>2026-05-26T01:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694312</loc>
  <lastmod>2026-05-26T01:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロダクト量子化を組み込んだVQ-VAEによる画像検索向けコードブック学習（LEARNING PRODUCT CODEBOOKS USING VECTOR-QUANTIZED AUTOENCODERS FOR IMAGE RETRIEVAL）</news:title>
   <news:publication_date>2026-05-26T01:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694310</loc>
  <lastmod>2026-05-26T01:20:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーム学習をPythonで民主化した基盤—Scikit-Multiflowの意義と実務的示唆 (Scikit-Multiflow: A Multi-output Streaming Framework)</news:title>
   <news:publication_date>2026-05-26T01:20:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694308</loc>
  <lastmod>2026-05-26T00:30:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超巨星の不規則な明るさ変動が示す内部波動の手がかり（A BRITE view on the massive O-type supergiant V973 Scorpii: Hints towards internal gravity waves or subsurface convection zones）</news:title>
   <news:publication_date>2026-05-26T00:30:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694306</loc>
  <lastmod>2026-05-26T00:29:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み平均に基づく一貫性ターゲットを用いた深層半教師ありセグメンテーション（Deep semi-supervised segmentation with weight-averaged consistency targets）</news:title>
   <news:publication_date>2026-05-26T00:29:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694304</loc>
  <lastmod>2026-05-26T00:29:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘッブ則を用いた高速重みのメタラーニング (Metalearning with Hebbian Fast Weights)</news:title>
   <news:publication_date>2026-05-26T00:29:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694302</loc>
  <lastmod>2026-05-26T00:28:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現変換を組み合わせることで汎化する仕組み（Automatically Composing Representation Transformations as a Means for Generalization）</news:title>
   <news:publication_date>2026-05-26T00:28:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694300</loc>
  <lastmod>2026-05-26T00:28:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子環境のクラスタリングによる機械学習強化全域最適化（Machine learning enhanced global optimization by clustering local environments to enable bundled atomic energies）</news:title>
   <news:publication_date>2026-05-26T00:28:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694298</loc>
  <lastmod>2026-05-26T00:27:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶するアルゴリズム：モデル反転攻撃とデータ保護法（Algorithms that remember: model inversion attacks and data protection law）</news:title>
   <news:publication_date>2026-05-26T00:27:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694296</loc>
  <lastmod>2026-05-26T00:27:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能なルールベース予測手法の実務的意義（RIPE: Rule Induction Partitioning Estimator）</news:title>
   <news:publication_date>2026-05-26T00:27:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694294</loc>
  <lastmod>2026-05-25T23:36:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wold過程を用いた因果関係推定の高速化（Fast Estimation of Causal Interactions using Wold Processes）</news:title>
   <news:publication_date>2026-05-25T23:36:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694292</loc>
  <lastmod>2026-05-25T23:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分近接法の確率論的視点（THE INCREMENTAL PROXIMAL METHOD: A PROBABILISTIC PERSPECTIVE）</news:title>
   <news:publication_date>2026-05-25T23:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694290</loc>
  <lastmod>2026-05-25T23:35:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込み特徴に内在する視覚的注目（Visual Attention driven by Convolutional Features）</news:title>
   <news:publication_date>2026-05-25T23:35:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694288</loc>
  <lastmod>2026-05-25T23:34:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所ハミルトニアンの復元法（Learning a Local Hamiltonian from Local Measurements）</news:title>
   <news:publication_date>2026-05-25T23:34:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694286</loc>
  <lastmod>2026-05-25T23:34:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データ分類に強い学習設計の勘所（Deep Learning for Imbalance Data Classification using Class Expert Generative Adversarial Network）</news:title>
   <news:publication_date>2026-05-25T23:34:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694284</loc>
  <lastmod>2026-05-25T23:33:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮データ上での分散クラスタリング — クラスタ数不明でも動く手法（Decentralized Clustering on Compressed Data without Prior Knowledge of the Number of Clusters）</news:title>
   <news:publication_date>2026-05-25T23:33:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694282</loc>
  <lastmod>2026-05-25T23:33:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大不変データ摂動の最大化（Maximizing Invariant Data Perturbation with Stochastic Optimization）</news:title>
   <news:publication_date>2026-05-25T23:33:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694280</loc>
  <lastmod>2026-05-25T22:42:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付きランダム化最短経路フレームワークによる最適探索（A Constrained Randomized Shortest-Paths Framework for Optimal Exploration）</news:title>
   <news:publication_date>2026-05-25T22:42:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694278</loc>
  <lastmod>2026-05-25T22:42:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XMMPZCAT: X線源のフォトメトリック赤方偏移カタログの意義と応用（XMMPZCAT: A catalogue of photometric redshifts for X-ray sources）</news:title>
   <news:publication_date>2026-05-25T22:42:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694276</loc>
  <lastmod>2026-05-25T22:41:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における注目領域検出を3D畳み込みで捉える（Video Saliency Detection by 3D Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-25T22:41:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694274</loc>
  <lastmod>2026-05-25T22:41:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴選択がバグ数予測に与える影響（The Impact of Feature Selection on Predicting the Number of Bugs）</news:title>
   <news:publication_date>2026-05-25T22:41:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694272</loc>
  <lastmod>2026-05-25T22:41:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑モデルにおける変分推論のための高速かつ単純な自然勾配降下（Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex Models）</news:title>
   <news:publication_date>2026-05-25T22:41:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694270</loc>
  <lastmod>2026-05-25T22:41:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴のリプレイを用いたニューラルネットワーク訓練（Training Neural Networks Using Features Replay）</news:title>
   <news:publication_date>2026-05-25T22:41:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694268</loc>
  <lastmod>2026-05-25T22:40:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コード構造とCodeRankによる概念位置検索の改良（Improved Query Reformulation for Concept Location using CodeRank and Document Structures）</news:title>
   <news:publication_date>2026-05-25T22:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694266</loc>
  <lastmod>2026-05-25T21:49:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>価値関数の合成によるスキル再利用（Will it Blend? Composing Value Functions in Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-25T21:49:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694264</loc>
  <lastmod>2026-05-25T21:43:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COのRu(0001)表面での異常な付着と散乱の支配因子（Strong anisotropic interaction controls unusual sticking and scattering of CO at Ru(0001))</news:title>
   <news:publication_date>2026-05-25T21:43:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694262</loc>
  <lastmod>2026-05-25T21:43:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>劇場公開映画の予測分析：予告編の深層映像表現による解析（Analysis System for Theatrical Movie Releases Based on Movie Trailer Deep Video Representation）</news:title>
   <news:publication_date>2026-05-25T21:43:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694260</loc>
  <lastmod>2026-05-25T21:43:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2D Bridged U-netによる前立腺領域分割の進化（Prostate Segmentation using 2D Bridged U-net）</news:title>
   <news:publication_date>2026-05-25T21:43:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694258</loc>
  <lastmod>2026-05-25T21:42:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ効率の良いハードラベル・ブラックボックス攻撃（Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach）</news:title>
   <news:publication_date>2026-05-25T21:42:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694256</loc>
  <lastmod>2026-05-25T21:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語の意味変化を追跡する時間反映型テキスト表現（Tracking the Evolution of Words with Time-reflective Text Representations）</news:title>
   <news:publication_date>2026-05-25T21:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694254</loc>
  <lastmod>2026-05-25T21:41:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>円筒対称非対称薄殻ワームホールの安定性（The Stability of Asymmetric Cylindrical Thin-Shell Wormholes）</news:title>
   <news:publication_date>2026-05-25T21:41:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694252</loc>
  <lastmod>2026-05-25T20:50:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通信規格教育の実践手法（Teaching Telecommunication Standards: Bridging the Gap Between Theory and Practice）</news:title>
   <news:publication_date>2026-05-25T20:50:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694250</loc>
  <lastmod>2026-05-25T20:50:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所最適解下での統計的推論（Statistical Inference with Local Optima）</news:title>
   <news:publication_date>2026-05-25T20:50:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694248</loc>
  <lastmod>2026-05-25T20:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像における人物再識別を変える技術統合（Video-based Person Re-identification via 3D Convolutional Networks and Non-local Attention）</news:title>
   <news:publication_date>2026-05-25T20:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694246</loc>
  <lastmod>2026-05-25T20:49:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時コヒーレント構造カラーリングによる可解釈なクラスタリング（Simultaneous coherent structure coloring facilitates interpretable clustering）</news:title>
   <news:publication_date>2026-05-25T20:49:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694244</loc>
  <lastmod>2026-05-25T20:49:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブロック座標上昇法によるBurer–Monteiro法の収束率（Convergence Rate of Block-Coordinate Maximization Burer-Monteiro Method for Solving Large SDPs）</news:title>
   <news:publication_date>2026-05-25T20:49:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694242</loc>
  <lastmod>2026-05-25T20:48:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有界次数の確率的ブロックモデルに対する尤度比型検定（A Likelihood-Ratio Type Test for Stochastic Block Models with Bounded Degrees）</news:title>
   <news:publication_date>2026-05-25T20:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694240</loc>
  <lastmod>2026-05-25T20:48:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多視点ニューラルアーキテクチャによる推薦システムの進化（Multi-Perspective Neural Architecture for Recommendation System）</news:title>
   <news:publication_date>2026-05-25T20:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694238</loc>
  <lastmod>2026-05-25T19:57:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乱流歪み除去ネットワーク（Subsampled Turbulence Removal Network）</news:title>
   <news:publication_date>2026-05-25T19:57:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694236</loc>
  <lastmod>2026-05-25T19:57:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類木と隠れ半マルコフモデルによるプロセス発見（Process Discovery using Classification Tree Hidden Semi-Markov Model）</news:title>
   <news:publication_date>2026-05-25T19:57:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694234</loc>
  <lastmod>2026-05-25T19:57:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔の部分情報を組み合わせる表情認識の新潮流（Multi-Region Ensemble Convolutional Neural Network for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-05-25T19:57:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694232</loc>
  <lastmod>2026-05-25T19:56:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-25T19:56:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694230</loc>
  <lastmod>2026-05-25T19:56:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース制約付き非負値行列因子分解によるトピック拡散検出（Topic Diffusion Discovery based on Sparseness-constrained Non-negative Matrix Factorization）</news:title>
   <news:publication_date>2026-05-25T19:56:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694228</loc>
  <lastmod>2026-05-25T19:55:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MIMO DF中継路における深層学習検出ネットワーク（Deep Learning Detection Networks in MIMO Decode-Forward Relay Channels）</news:title>
   <news:publication_date>2026-05-25T19:55:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694226</loc>
  <lastmod>2026-05-25T19:55:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高齢者支援する感情応答型ロボット伴走者（An Affective Robot Companion for Assisting the Elderly in a Cognitive Game Scenario）</news:title>
   <news:publication_date>2026-05-25T19:55:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694224</loc>
  <lastmod>2026-05-25T19:04:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クライアント側差分プライバシーを実現する Draw and Discard 機械学習（Differentially-Private “Draw and Discard” Machine Learning）</news:title>
   <news:publication_date>2026-05-25T19:04:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694222</loc>
  <lastmod>2026-05-25T18:54:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られた学習データにおける深層学習の最前線と課題（STATE–OF–THE–ART AND GAPS FOR DEEP LEARNING ON LIMITED TRAINING DATA IN REMOTE SENSING）</news:title>
   <news:publication_date>2026-05-25T18:54:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694220</loc>
  <lastmod>2026-05-25T18:54:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Landsatと全球標高データを融合した三次元都市構造マッピング（Mapping Three-dimensional Urban Structure by Fusing Landsat and Global Elevation Data）</news:title>
   <news:publication_date>2026-05-25T18:54:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694218</loc>
  <lastmod>2026-05-25T18:53:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deepwoundを用いた術後創傷評価と手術部位監視（Deepwound: Automated Postoperative Wound Assessment and Surgical Site Surveillance through Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-25T18:53:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694216</loc>
  <lastmod>2026-05-25T18:53:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTにおける情報鮮度の最適化（Joint Status Sampling and Updating for Minimizing Age of Information in the Internet of Things）</news:title>
   <news:publication_date>2026-05-25T18:53:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694214</loc>
  <lastmod>2026-05-25T18:52:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シリウスAbの探索：コロナグラフィー熱赤外高コントラストイメージングにおけるアルゴリズム的背景推定とPSF推定性能の比較 (The hunt for Sirius Ab: Comparison of algorithmic sky and PSF estimation performance in deep coronagraphic thermal-IR high contrast imaging)</news:title>
   <news:publication_date>2026-05-25T18:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694212</loc>
  <lastmod>2026-05-25T18:52:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なキーワード検出における時間遅延ニューラルネットワークの活用（Efficient keyword spotting using time delay neural networks）</news:title>
   <news:publication_date>2026-05-25T18:52:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694210</loc>
  <lastmod>2026-05-25T18:01:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像における汎用的肺領域分割の枠組み（A Generic Approach to Lung Field Segmentation from Chest Radiographs using Deep Space and Shape Learning）</news:title>
   <news:publication_date>2026-05-25T18:01:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694208</loc>
  <lastmod>2026-05-25T18:01:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUアーキテクチャ向けデータ並列ハッシュ法の概観（Data-Parallel Hashing Techniques for GPU Architectures）</news:title>
   <news:publication_date>2026-05-25T18:01:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694206</loc>
  <lastmod>2026-05-25T18:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソースコードにおける自動脆弱性検出の深層表現学習（Automated Vulnerability Detection in Source Code Using Deep Representation Learning）</news:title>
   <news:publication_date>2026-05-25T18:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694204</loc>
  <lastmod>2026-05-25T18:00:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化ベイズ型ガウス過程潜在変数モデルによる高次元逆問題の扱い（Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversion）</news:title>
   <news:publication_date>2026-05-25T18:00:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694202</loc>
  <lastmod>2026-05-25T17:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANを使った多様体正則化による半教師あり学習（Manifold regularization with GANs for semi-supervised learning）</news:title>
   <news:publication_date>2026-05-25T17:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694200</loc>
  <lastmod>2026-05-25T17:59:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的事前分布による位相復元（Phase Retrieval Under a Generative Prior）</news:title>
   <news:publication_date>2026-05-25T17:59:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694198</loc>
  <lastmod>2026-05-25T17:59:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河中心領域におけるVVVサーベイのRR Lyrae集団（THE VVV Survey RR Lyrae Population in the Galactic Centre Region）</news:title>
   <news:publication_date>2026-05-25T17:59:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694196</loc>
  <lastmod>2026-05-25T17:08:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子機械学習の基礎（The fundamentals of quantum machine learning）</news:title>
   <news:publication_date>2026-05-25T17:08:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694194</loc>
  <lastmod>2026-05-25T17:07:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コーデッド・データシャッフリングの基礎限界（On the Fundamental Limits of Coded Data Shufﬂing for Distributed Machine Learning）</news:title>
   <news:publication_date>2026-05-25T17:07:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694192</loc>
  <lastmod>2026-05-25T17:07:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization（Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization）</news:title>
   <news:publication_date>2026-05-25T17:07:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694190</loc>
  <lastmod>2026-05-25T17:06:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業用マルチセンサー衝突回避におけるLiDARとカメラ検出の融合（LiDAR and Camera Detection Fusion in a Real-Time Industrial Multi-Sensor Collision Avoidance System）</news:title>
   <news:publication_date>2026-05-25T17:06:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694188</loc>
  <lastmod>2026-05-25T17:06:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元生物データから細胞の目的関数を推定する意義（Estimating Cellular Goals from High-Dimensional Biological Data）</news:title>
   <news:publication_date>2026-05-25T17:06:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694186</loc>
  <lastmod>2026-05-25T17:06:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模導入実験科目の変容（Transforming a large introductory lab course）</news:title>
   <news:publication_date>2026-05-25T17:06:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694184</loc>
  <lastmod>2026-05-25T17:05:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepMoveによる場所表現の学習（DeepMove: Learning Place Representations through Large Scale Movement Data）</news:title>
   <news:publication_date>2026-05-25T17:05:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694182</loc>
  <lastmod>2026-05-25T16:14:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モールス符号データセットと機械学習への応用（Morse Code Datasets for Machine Learning）</news:title>
   <news:publication_date>2026-05-25T16:14:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694180</loc>
  <lastmod>2026-05-25T16:14:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Make ℓ1 Regularization Effective in Training Sparse CNN（Make ℓ1 Regularization Effective in Training Sparse CNN）</news:title>
   <news:publication_date>2026-05-25T16:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694178</loc>
  <lastmod>2026-05-25T16:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークにおける抽象推論の計測（Measuring abstract reasoning in neural networks）</news:title>
   <news:publication_date>2026-05-25T16:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694176</loc>
  <lastmod>2026-05-25T16:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>友が多すぎると敵はいらない？—分類モデルの脆弱性と性能の同根性（With Friends Like These, Who Needs Adversaries?）</news:title>
   <news:publication_date>2026-05-25T16:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694174</loc>
  <lastmod>2026-05-25T16:13:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシー下での偽発見率制御（Differentially Private False Discovery Rate Control）</news:title>
   <news:publication_date>2026-05-25T16:13:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694172</loc>
  <lastmod>2026-05-25T16:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の位置ベース類似度を組み込んだ協調ランキングによる店舗提案（A Collaborative Ranking Model with Multiple Location-based Similarities for Venue Suggestion）</news:title>
   <news:publication_date>2026-05-25T16:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694170</loc>
  <lastmod>2026-05-25T16:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的グラウンド集合で強化した逐次決定論的点過程による教師ありビデオ要約（Reinforcing Sequential Determinantal Point Processes with Dynamic Ground Sets for Supervised Video Summarization）</news:title>
   <news:publication_date>2026-05-25T16:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694168</loc>
  <lastmod>2026-05-25T15:21:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔軟な深層学習特化のためのハードウェア・ソフトウェア設計図（A Hardware-Software Blueprint for Flexible Deep Learning Specialization）</news:title>
   <news:publication_date>2026-05-25T15:21:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694166</loc>
  <lastmod>2026-05-25T15:12:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散変分表現学習（Distributed Variational Representation Learning）</news:title>
   <news:publication_date>2026-05-25T15:12:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694164</loc>
  <lastmod>2026-05-25T15:11:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UIパターンを計測する計算手法（A Computational Method for Evaluating UI Patterns）</news:title>
   <news:publication_date>2026-05-25T15:11:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694162</loc>
  <lastmod>2026-05-25T15:11:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠中の脳波イベントを一括検出する深層学習アーキテクチャ（A DEEP LEARNING ARCHITECTURE TO DETECT EVENTS IN EEG SIGNALS DURING SLEEP）</news:title>
   <news:publication_date>2026-05-25T15:11:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694160</loc>
  <lastmod>2026-05-25T15:11:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習の熱力学（The Thermodynamics of Machine Learning）</news:title>
   <news:publication_date>2026-05-25T15:11:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694158</loc>
  <lastmod>2026-05-25T15:11:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Indy：産業施設での空間ナビゲーション技能を鍛える仮想現実ゲーム（Indy: a virtual reality multi-player game for navigation skills training）</news:title>
   <news:publication_date>2026-05-25T15:11:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694156</loc>
  <lastmod>2026-05-25T15:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測データに基づく連続・多次元意思決定の最適化（Optimization over Continuous and Multi-dimensional Decisions with Observational Data）</news:title>
   <news:publication_date>2026-05-25T15:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694154</loc>
  <lastmod>2026-05-25T14:19:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイバーバンドルを用いた現場波面補正による二光子レンズレスマイクロ内視鏡（Two-Photon Lensless Micro-endoscopy with in-situ Wavefront Correction）</news:title>
   <news:publication_date>2026-05-25T14:19:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694152</loc>
  <lastmod>2026-05-25T14:10:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>死後（ポストモーテム）虹彩画像の自動セグメンテーション（Post-mortem Iris Image Segmentation with Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-25T14:10:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694150</loc>
  <lastmod>2026-05-25T14:10:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復評価を導入したLSTMの設計思想と実装的示唆（Iterative evaluation of LSTM cells）</news:title>
   <news:publication_date>2026-05-25T14:10:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694148</loc>
  <lastmod>2026-05-25T14:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実数空間における木構造の線形表現（Trees in the Real Field）</news:title>
   <news:publication_date>2026-05-25T14:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694146</loc>
  <lastmod>2026-05-25T14:09:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中スラスタのモデリングとソフトフォールト診断（Modeling and Soft-fault Diagnosis of Underwater Thrusters with Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-25T14:09:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694144</loc>
  <lastmod>2026-05-25T14:08:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数の分布を生成する深層モデル VFunc: 関数空間で不確実性を扱う発想（VFunc: A Deep Generative Model for Functions）</news:title>
   <news:publication_date>2026-05-25T14:08:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694142</loc>
  <lastmod>2026-05-25T14:08:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列の統計的依存性を階層的相関再構成で利用する（Exploiting statistical dependencies of time series with hierarchical correlation reconstruction）</news:title>
   <news:publication_date>2026-05-25T14:08:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694140</loc>
  <lastmod>2026-05-25T13:16:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分カプセルによる画像解析と合成（Variational Capsules for Image Analysis and Synthesis）</news:title>
   <news:publication_date>2026-05-25T13:16:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694138</loc>
  <lastmod>2026-05-25T13:16:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エントロピーに基づくバルク幾何学の再構築（Bulk geometry from entanglement entropy of CFT）</news:title>
   <news:publication_date>2026-05-25T13:16:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694136</loc>
  <lastmod>2026-05-25T13:15:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型ニューラルネットワークによるユーザー再訪予測（A Recurrent Neural Network Survival Model: Predicting Web User Return Time）</news:title>
   <news:publication_date>2026-05-25T13:15:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694134</loc>
  <lastmod>2026-05-25T13:14:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変精度LSTMをFPGAで加速するための設計とライブラリ拡張（FINN-L: Library Extensions and Design Trade-off Analysis for Variable Precision LSTM Networks on FPGAs）</news:title>
   <news:publication_date>2026-05-25T13:14:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694132</loc>
  <lastmod>2026-05-25T13:14:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブルPPGによる心臓異常の検出（Recognising Cardiac Abnormalities in Wearable Device Photoplethysmography (PPG) with Deep Learning）</news:title>
   <news:publication_date>2026-05-25T13:14:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694130</loc>
  <lastmod>2026-05-25T13:14:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一走行からキロメートル規模の実装可能なナビゲーション方策を学習する（Learning Deployable Navigation Policies at Kilometer Scale from a Single Traversal）</news:title>
   <news:publication_date>2026-05-25T13:14:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694128</loc>
  <lastmod>2026-05-25T13:13:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>従業員離職の予測と予防介入（Proactive Intervention to Downtrend Employee Attrition using Artificial Intelligence Techniques）</news:title>
   <news:publication_date>2026-05-25T13:13:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694126</loc>
  <lastmod>2026-05-25T12:21:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔軟なゲートを持つ再帰型ニューラルネットワーク（Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions）</news:title>
   <news:publication_date>2026-05-25T12:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694124</loc>
  <lastmod>2026-05-25T12:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>死後虹彩の提示攻撃検出（Presentation Attack Detection for Cadaver Iris）</news:title>
   <news:publication_date>2026-05-25T12:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694122</loc>
  <lastmod>2026-05-25T12:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胎児腹部大動脈のリアルタイム径測定に向けた時間方向畳み込みネットワーク（Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound）</news:title>
   <news:publication_date>2026-05-25T12:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694120</loc>
  <lastmod>2026-05-25T12:19:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3C 279の史上最大ガンマ線フレアの観測と理論的課題（Challenges in reconciling observations and theory of the brightest high-energy flare ever of 3C 279）</news:title>
   <news:publication_date>2026-05-25T12:19:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694118</loc>
  <lastmod>2026-05-25T12:19:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>死後虹彩認識における画像特徴の知覚（Perception of Image Features in Post-Mortem Iris Recognition: Humans vs Machines）</news:title>
   <news:publication_date>2026-05-25T12:19:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694116</loc>
  <lastmod>2026-05-25T12:19:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アパレル属性分類のための二層混合ネットワークアンサンブル（Two-Layer Mixture Network Ensemble for Apparel Attributes Classification）</news:title>
   <news:publication_date>2026-05-25T12:19:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694114</loc>
  <lastmod>2026-05-25T12:19:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeSTNetによる空間変形の解消と頑健化（DeSTNet: Densely Fused Spatial Transformer Networks）</news:title>
   <news:publication_date>2026-05-25T12:19:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694112</loc>
  <lastmod>2026-05-25T11:27:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異点回避の学習（Learning Singularity Avoidance）</news:title>
   <news:publication_date>2026-05-25T11:27:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694110</loc>
  <lastmod>2026-05-25T11:26:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負値行列分解のための改良SVD初期化と低ランク補正（Improved SVD-based Initialization for Nonnegative Matrix Factorization using Low-Rank Correction）</news:title>
   <news:publication_date>2026-05-25T11:26:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694108</loc>
  <lastmod>2026-05-25T11:26:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANにおける壊滅的忘却とモード崩壊の関係（Catastrophic forgetting and mode collapse in GANs）</news:title>
   <news:publication_date>2026-05-25T11:26:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694106</loc>
  <lastmod>2026-05-25T11:25:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠測データ下の因果探索（Causal Discovery in the Presence of Missing Data）</news:title>
   <news:publication_date>2026-05-25T11:25:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694104</loc>
  <lastmod>2026-05-25T11:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によるエンドツーエンド・クラスタリング（Learning Neural Models for End-to-End Clustering）</news:title>
   <news:publication_date>2026-05-25T11:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694102</loc>
  <lastmod>2026-05-25T11:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Medusaが示すメモリ相互接続の新しい設計（Medusa: A Scalable Interconnect for Many-Port DNN Accelerators and Wide DRAM Controller Interfaces）</news:title>
   <news:publication_date>2026-05-25T11:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694100</loc>
  <lastmod>2026-05-25T11:24:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マクロ経済時系列のクラスタリング手法が変える構造分析（Clustering Macroeconomic Time Series）</news:title>
   <news:publication_date>2026-05-25T11:24:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694098</loc>
  <lastmod>2026-05-25T10:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース範囲制約学習と医用画像の自動グレーディング（Sparse Range-constrained Learning and Its Application for Medical Image Grading）</news:title>
   <news:publication_date>2026-05-25T10:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694096</loc>
  <lastmod>2026-05-25T10:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ESSにおけるソフトウェア中心の中性子検出データ処理（Software-based data acquisition and processing for neutron detectors at European Spallation Source — early experience from four detector designs）</news:title>
   <news:publication_date>2026-05-25T10:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694094</loc>
  <lastmod>2026-05-25T10:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動物体解析：未来位置と軌跡予測の概観（Moving Objects Analytics: Survey on Future Location &amp;amp; Trajectory Prediction Methods）</news:title>
   <news:publication_date>2026-05-25T10:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694092</loc>
  <lastmod>2026-05-25T10:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLU深層ニューラルネットワークと線形有限要素の関係（ReLU Deep Neural Networks and Linear Finite Elements）</news:title>
   <news:publication_date>2026-05-25T10:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694090</loc>
  <lastmod>2026-05-25T10:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型深層信念ネットワークから抽出する知識によるリアルタイム決定制御（Knowledge Extracted from Recurrent Deep Belief Network for Real Time Deterministic Control）</news:title>
   <news:publication_date>2026-05-25T10:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694088</loc>
  <lastmod>2026-05-25T10:23:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データ解析のための適応学習型再帰時系列ディープビリーフネットワーク（Adaptive Learning Method of Recurrent Temporal Deep Belief Network to Analyze Time Series Data）</news:title>
   <news:publication_date>2026-05-25T10:23:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694086</loc>
  <lastmod>2026-05-25T10:23:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な深度推定を実現する注意ベース分類ネットワーク（Deep attention-based classification network for robust depth prediction）</news:title>
   <news:publication_date>2026-05-25T10:23:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694084</loc>
  <lastmod>2026-05-25T09:32:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書知識を取り込む中国語単語分割の新手法（Neural Chinese Word Segmentation with Dictionary Knowledge）</news:title>
   <news:publication_date>2026-05-25T09:32:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694082</loc>
  <lastmod>2026-05-25T09:32:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列予測のための量子リザバーコンピュータの最適化（Optimizing a quantum reservoir computer for time series prediction）</news:title>
   <news:publication_date>2026-05-25T09:32:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694080</loc>
  <lastmod>2026-05-25T09:31:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習時間を短縮するAdaptive DBNの工夫（Shortening Time Required for Adaptive Structural Learning Method of Deep Belief Network with Multi-Modal Data Arrangement）</news:title>
   <news:publication_date>2026-05-25T09:31:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694078</loc>
  <lastmod>2026-05-25T09:31:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンスベースのエントロピー・ファジィSVMによる不均衡データ分類（Instance-based entropy fuzzy support vector machine for imbalanced data）</news:title>
   <news:publication_date>2026-05-25T09:31:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694076</loc>
  <lastmod>2026-05-25T09:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Decoder-Encoder出力ノイズを用いた生成的敵対ネットワーク（Generative Adversarial Networks with Decoder-Encoder Output Noise）</news:title>
   <news:publication_date>2026-05-25T09:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694074</loc>
  <lastmod>2026-05-25T09:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所特徴を持つ階層ベイズ線形回帰による確率的力学の近似 (A Hierarchical Bayesian Linear Regression Model with Local Features for Stochastic Dynamics Approximation)</news:title>
   <news:publication_date>2026-05-25T09:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694072</loc>
  <lastmod>2026-05-25T09:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前確率シフト下の定量化：比率推定器とその拡張（Quantification Under Prior Probability Shift: the Ratio Estimator and its Extensions）</news:title>
   <news:publication_date>2026-05-25T09:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694070</loc>
  <lastmod>2026-05-25T08:39:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声からの感情認識：関連する特徴選択と多数決手法の強調（Emotion Recognition from Human Speech: Emphasizing on Relevant Feature Selection and Majority Voting Technique）</news:title>
   <news:publication_date>2026-05-25T08:39:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694068</loc>
  <lastmod>2026-05-25T08:38:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生産歩留まりデータ解析における興味深いプロットの発見（Discovering Interesting Plots in Production Yield Data Analytics）</news:title>
   <news:publication_date>2026-05-25T08:38:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694066</loc>
  <lastmod>2026-05-25T08:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seq2Seqによるマルチモーダル感情分析（Multimodal Sequence to Sequence Models for Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-25T08:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694064</loc>
  <lastmod>2026-05-25T08:38:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚注意の集約による深層不均衡属性分類（Deep Imbalanced Attribute Classification using Visual Attention Aggregation）</news:title>
   <news:publication_date>2026-05-25T08:38:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694062</loc>
  <lastmod>2026-05-25T08:38:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化におけるGDAとOGDAの極限点の理解（The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization）</news:title>
   <news:publication_date>2026-05-25T08:38:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694060</loc>
  <lastmod>2026-05-25T08:37:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接障壁領域における232Thと238Uの光核分裂研究（Near-barrier Photofission in 232Th and 238U）</news:title>
   <news:publication_date>2026-05-25T08:37:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694058</loc>
  <lastmod>2026-05-25T08:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多数個体の自己励起型情報拡散過程の漸近挙動（The asymptotic behaviors of self excitation information diffusion processes for a large number of individuals）</news:title>
   <news:publication_date>2026-05-25T08:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694056</loc>
  <lastmod>2026-05-25T07:46:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層構造生成モデルの実務的インパクト（Deep Structured Generative Models）</news:title>
   <news:publication_date>2026-05-25T07:46:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694054</loc>
  <lastmod>2026-05-25T07:37:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイナンスのための量子コンピューティング：概観と展望（Quantum computing for finance: overview and prospects）</news:title>
   <news:publication_date>2026-05-25T07:37:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694052</loc>
  <lastmod>2026-05-25T07:37:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光に現れる量子タービュランスの構造（Quantum Turbulent Structure in Light）</news:title>
   <news:publication_date>2026-05-25T07:37:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694050</loc>
  <lastmod>2026-05-25T07:37:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常検出の統一的枠組み（A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks）</news:title>
   <news:publication_date>2026-05-25T07:37:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694048</loc>
  <lastmod>2026-05-25T07:36:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepDiffによるヒストン修飾からの差次的遺伝子発現予測（DeepDiff: Deep-learning for predicting Differential gene expression from histone modifications）</news:title>
   <news:publication_date>2026-05-25T07:36:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694046</loc>
  <lastmod>2026-05-25T07:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広視野での地上層適応光学による像質改善（Improved Image Quality Over 10′ Fields with the ‘Imaka Ground Layer Adaptive Optics Experiment）</news:title>
   <news:publication_date>2026-05-25T07:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694044</loc>
  <lastmod>2026-05-25T07:36:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>包括的なアルツハイマー病進行予測のための深層学習（Deep learning for comprehensive forecasting of Alzheimer’s Disease progression）</news:title>
   <news:publication_date>2026-05-25T07:36:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694042</loc>
  <lastmod>2026-05-25T06:44:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化された勾配ブースティング（Automatic Gradient Boosting）</news:title>
   <news:publication_date>2026-05-25T06:44:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694040</loc>
  <lastmod>2026-05-25T06:36:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタイライズド画像キャプション生成における適応学習と注意機構（Factual or Emotional: Stylized Image Captioning with Adaptive Learning and Attention）</news:title>
   <news:publication_date>2026-05-25T06:36:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694038</loc>
  <lastmod>2026-05-25T06:35:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密度推定器を教えることで学ぶ暗黙的生成モデル（Learning Implicit Generative Models By Teaching Density Estimators）</news:title>
   <news:publication_date>2026-05-25T06:35:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694036</loc>
  <lastmod>2026-05-25T06:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子着想の古典アルゴリズムによるレコメンデーション（A quantum-inspired classical algorithm for recommendation systems）</news:title>
   <news:publication_date>2026-05-25T06:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694034</loc>
  <lastmod>2026-05-25T06:35:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース深層強化学習の理論的保証を与えるアルゴリズムフレームワーク（ALGORITHMIC FRAMEWORK FOR MODEL-BASED DEEP REINFORCEMENT LEARNING WITH THEORETICAL GUARANTEES）</news:title>
   <news:publication_date>2026-05-25T06:35:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694032</loc>
  <lastmod>2026-05-25T06:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Google Street Viewから学ぶ道路の実情（Street Sense: Learning from Google Street View）</news:title>
   <news:publication_date>2026-05-25T06:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694030</loc>
  <lastmod>2026-05-25T06:34:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>天体イベントの画像列を直接学習する深層学習（Deep Learning for Image Sequence Classification of Astronomical Events）</news:title>
   <news:publication_date>2026-05-25T06:34:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694028</loc>
  <lastmod>2026-05-25T05:43:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自由呼吸・非同期心臓MRIの高速再構成を実現するMoDL‑STORM（MODEL-BASED FREE‑BREATHING CARDIAC MRI RECONSTRUCTION USING DEEP LEARNED &amp;amp; STORM PRIORS: MODL‑STORM）</news:title>
   <news:publication_date>2026-05-25T05:43:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694026</loc>
  <lastmod>2026-05-25T05:33:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケールを効率的に学ぶBig‑Little Net（BIG-LITTLE NET: AN EFFICIENT MULTI-SCALE FEATURE REPRESENTATION FOR VISUAL AND SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-05-25T05:33:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694024</loc>
  <lastmod>2026-05-25T05:33:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大人数向け入門物理の反転授業が変えたもの（Flipping the Large-Enrollment Introductory Physics Classroom）</news:title>
   <news:publication_date>2026-05-25T05:33:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694022</loc>
  <lastmod>2026-05-25T05:32:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Balmer優勢ショックに基づくIa型超新星の高温前駆体排除（BALMER-DOMINATED SHOCKS EXCLUDE HOT PROGENITORS FOR MANY TYPE IA SUPERNOVAE）</news:title>
   <news:publication_date>2026-05-25T05:32:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694020</loc>
  <lastmod>2026-05-25T05:32:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意識と認知の要素：情報位相幾何学の視点から（Elements of Consciousness and Cognition: an Information Topology Perspective）</news:title>
   <news:publication_date>2026-05-25T05:32:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694018</loc>
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 </url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news: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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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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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: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:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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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>2026-05-25T01:51:14Z</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>ゲーム理論に基づく深層ニューラルネットワークの近似検証（A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees）</news:title>
   <news:publication_date>2026-05-25T01:50:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在的行動タイプを同定するための実験の最適設計 (Optimal design of experiments to identify latent behavioral types)</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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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:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推薦システムにおける表現のプライバシーと公平性を守る敵対的訓練（Privacy and Fairness in Recommender Systems via Adversarial Training of User Representations）</news:title>
   <news:publication_date>2026-05-25T00:58:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693944</loc>
  <lastmod>2026-05-25T00:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アクティブターゲットTPCデータにおける自動軌跡認識（Automatic trajectory recognition in Active Target Time Projection Chambers data by means of hierarchical clustering）</news:title>
   <news:publication_date>2026-05-25T00:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693942</loc>
  <lastmod>2026-05-25T00:06:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>走行計画と通信を同時に最適化する強化学習アプローチ（A Reinforcement Learning Approach to Jointly Adapt Vehicular Communications and Planning for Optimized Driving）</news:title>
   <news:publication_date>2026-05-25T00:06:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693940</loc>
  <lastmod>2026-05-25T00:05:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロブログ上の自動デマ検出の総説（Automatic Rumor Detection on Microblogs: A Survey）</news:title>
   <news:publication_date>2026-05-25T00:05:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693938</loc>
  <lastmod>2026-05-25T00:04:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種情報ネットワークの包括的転写による埋め込み学習の簡素化（Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks）</news:title>
   <news:publication_date>2026-05-25T00:04:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693936</loc>
  <lastmod>2026-05-25T00:04:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Belief Networkからの知識獲得によるファインチューニング手法（Fine Tuning Method by using Knowledge Acquisition from Deep Belief Network）</news:title>
   <news:publication_date>2026-05-25T00:04:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693934</loc>
  <lastmod>2026-05-25T00:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み環境での深層学習による笑顔検出（Embedded Implementation of a Deep Learning Smile Detector）</news:title>
   <news:publication_date>2026-05-25T00:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693932</loc>
  <lastmod>2026-05-25T00:03:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層生成アルゴリズムによるDBNの適応学習法（An Adaptive Learning Method of Deep Belief Network by Layer Generation Algorithm）</news:title>
   <news:publication_date>2026-05-25T00:03:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693930</loc>
  <lastmod>2026-05-24T23:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一動画デモから未知の作業を実行するためのタスクグラフ学習（Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration）</news:title>
   <news:publication_date>2026-05-24T23:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693928</loc>
  <lastmod>2026-05-24T23:12:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>振幅スペクトログラムからの位相再構成（PHASE RECONSTRUCTION FROM AMPLITUDE SPECTROGRAMS BASED ON VON-MISES-DISTRIBUTION DEEP NEURAL NETWORK）</news:title>
   <news:publication_date>2026-05-24T23:12:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693926</loc>
  <lastmod>2026-05-24T23:11:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RBMの適応学習法 — ニューロン生成と消去アルゴリズムによる最適化 (An Adaptive Learning Method of Restricted Boltzmann Machine by Neuron Generation and Annihilation Algorithm)</news:title>
   <news:publication_date>2026-05-24T23:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693924</loc>
  <lastmod>2026-05-24T23:10:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SceneEDNetによるシーンフロー推定（SceneEDNet: A Deep Learning Approach for Scene Flow Estimation）</news:title>
   <news:publication_date>2026-05-24T23:10:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693922</loc>
  <lastmod>2026-05-24T23:10:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペアワイズ共変量調整ブロックモデルによるコミュニティ検出（Pairwise Covariates-Adjusted Block Model for Community Detection）</news:title>
   <news:publication_date>2026-05-24T23:10:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693920</loc>
  <lastmod>2026-05-24T23:10:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムポリマーと一般化されたバーン過程（Random Polymers and Generalized Urn Processes）</news:title>
   <news:publication_date>2026-05-24T23:10:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693918</loc>
  <lastmod>2026-05-24T23:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一Tucker分解ネットワークを用いた可変ビット率の損失型画像圧縮（Learning a Single Tucker Decomposition Network for Lossy Image Compression with Multiple Bits-Per-Pixel Rates）</news:title>
   <news:publication_date>2026-05-24T23:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693916</loc>
  <lastmod>2026-05-24T22:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>竜巻による物的被害を予測するゼロ膨張ニューラルネットワーク（Predicting property damage from tornadoes with zero-inflated neural networks）</news:title>
   <news:publication_date>2026-05-24T22:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693914</loc>
  <lastmod>2026-05-24T22:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングによる脳アトラスの構築（Developing Brain Atlas through Deep Learning）</news:title>
   <news:publication_date>2026-05-24T22:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693912</loc>
  <lastmod>2026-05-24T22:17:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘルムホルツ法：知覚圧縮を使って機械学習の複雑性を下げる方法（The Helmholtz Method: Using Perceptual Compression to Reduce Machine Learning Complexity）</news:title>
   <news:publication_date>2026-05-24T22:17:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693910</loc>
  <lastmod>2026-05-24T22:17:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUに最適化されたセカント法に基づく次元削減アルゴリズム（A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction）</news:title>
   <news:publication_date>2026-05-24T22:17:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693908</loc>
  <lastmod>2026-05-24T22:16:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師あり学習における二値分類の新しい変分モデル (A New Variational Model for Binary Classification in the Supervised Learning Context)</news:title>
   <news:publication_date>2026-05-24T22:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693906</loc>
  <lastmod>2026-05-24T22:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等分散仮定による因果発見の単純化（On Causal Discovery with Equal Variance Assumption）</news:title>
   <news:publication_date>2026-05-24T22:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693904</loc>
  <lastmod>2026-05-24T22:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像における心胸郭比の自動推定のための教師なしドメイン適応（Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio）</news:title>
   <news:publication_date>2026-05-24T22:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693902</loc>
  <lastmod>2026-05-24T21:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>警察による殺害は誰か〜階層型LSTMに対する教師付きアテンションの導入（Who is Killed by Police: Introducing Supervised Attention for Hierarchical LSTMs）</news:title>
   <news:publication_date>2026-05-24T21:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693900</loc>
  <lastmod>2026-05-24T21:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AudioMNISTによる音声分野の説明可能なAIの試金石（AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark）</news:title>
   <news:publication_date>2026-05-24T21:15:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693898</loc>
  <lastmod>2026-05-24T21:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群に対する高忠実度意味的形状補完（High Fidelity Semantic Shape Completion for Point Clouds using Latent Optimization）</news:title>
   <news:publication_date>2026-05-24T21:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693896</loc>
  <lastmod>2026-05-24T21:13:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>材料空間の階層的可視化（Hierarchical Visualization of Materials Space with Graph Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-24T21:13:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693894</loc>
  <lastmod>2026-05-24T21:13:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンティティとテキストを同時に埋め込む手法（Jointly Embedding Entities and Text with Distant Supervision）</news:title>
   <news:publication_date>2026-05-24T21:13:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693892</loc>
  <lastmod>2026-05-24T21:13:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IGLOO: 長い系列を効率的に扱うための新しい切り口（IGLOO: Slicing the Feature Space to Represent Sequences）</news:title>
   <news:publication_date>2026-05-24T21:13:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693890</loc>
  <lastmod>2026-05-24T21:12:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>切り詰めた時間逆伝播で再帰ネットワークを学習する（On Training Recurrent Networks with Truncated Backpropagation Through Time in Speech Recognition）</news:title>
   <news:publication_date>2026-05-24T21:12:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693888</loc>
  <lastmod>2026-05-24T20:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初年次大型実験授業の変革がもたらした初期効果（Initial impacts of the transformation of a large introductory lab course focused on developing experimental skills and expert epistemology）</news:title>
   <news:publication_date>2026-05-24T20:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693886</loc>
  <lastmod>2026-05-24T20:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様なロボット行動の進化に向けた組合せ多目的進化アルゴリズムの提案（Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm）</news:title>
   <news:publication_date>2026-05-24T20:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693884</loc>
  <lastmod>2026-05-24T20:12:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大系列発散を用いたプロセス監視（Process Monitoring Using Maximum Sequence Divergence）</news:title>
   <news:publication_date>2026-05-24T20:12:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693882</loc>
  <lastmod>2026-05-24T20:12:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリックな学習-to-ランクの探求（Towards Non-Parametric Learning to Rank）</news:title>
   <news:publication_date>2026-05-24T20:12:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693880</loc>
  <lastmod>2026-05-24T20:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延情報下のオンライン評価：凸最適化の視点（Online Scoring with Delayed Information: A Convex Optimization Viewpoint）</news:title>
   <news:publication_date>2026-05-24T20:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693878</loc>
  <lastmod>2026-05-24T20:11:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習におけるアンサンブルカルマンフィルタを用いたスパースGaussian Process回帰（Ensemble Kalman Filtering for Online Gaussian Process Regression and Learning）</news:title>
   <news:publication_date>2026-05-24T20:11:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693876</loc>
  <lastmod>2026-05-24T20:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆の感情を捉える注意機構（An Attention Model for group-level emotion recognition）</news:title>
   <news:publication_date>2026-05-24T20:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693874</loc>
  <lastmod>2026-05-24T19:19:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数グラフのための扱いやすいn-距離（Tractable n-Metrics for Multiple Graphs）</news:title>
   <news:publication_date>2026-05-24T19:19:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693872</loc>
  <lastmod>2026-05-24T19:19:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル駆動の弱教師あり学習による多モーダル変形画像レジストレーションの実用化（Label-driven weakly-supervised learning for multimodal deformable image registration）</news:title>
   <news:publication_date>2026-05-24T19:19:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693870</loc>
  <lastmod>2026-05-24T19:18:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Talk The Walk: 地図と対話で観光客を導く対話型ナビゲーション（Talk The Walk: Navigating Grids in New York City through Grounded Dialogue）</news:title>
   <news:publication_date>2026-05-24T19:18:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693868</loc>
  <lastmod>2026-05-24T19:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダの再構成画像を群最適化で改良する（Using Swarm Optimization To Enhance Autoencoder’s Images）</news:title>
   <news:publication_date>2026-05-24T19:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693866</loc>
  <lastmod>2026-05-24T19:18:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習研究の問題点と健全な再生の道（Troubling Trends in Machine Learning Scholarship）</news:title>
   <news:publication_date>2026-05-24T19:18:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693864</loc>
  <lastmod>2026-05-24T19:18:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>提案クラスタ学習による弱教師あり物体検出の新戦略（PCL: Proposal Cluster Learning for Weakly Supervised Object Detection）</news:title>
   <news:publication_date>2026-05-24T19:18:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693862</loc>
  <lastmod>2026-05-24T19:17:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素全畳み込みニューラルネットワークによるMR画像再構成（Complex Fully Convolutional Neural Networks for MR Image Reconstruction）</news:title>
   <news:publication_date>2026-05-24T19:17:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693860</loc>
  <lastmod>2026-05-24T18:26:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェットサブ構造のスペクトル解析とニューラルネットワーク（Spectral Analysis of Jet Substructure with Neural Networks: Boosted Higgs Case）</news:title>
   <news:publication_date>2026-05-24T18:26:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693858</loc>
  <lastmod>2026-05-24T18:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーンテキスト認識に対する適応的敵対的攻撃（Adaptive Adversarial Attack on Scene Text Recognition）</news:title>
   <news:publication_date>2026-05-24T18:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693856</loc>
  <lastmod>2026-05-24T18:16:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称性と多体系励起状態のニューラルネットワーク量子状態（Symmetries and many-body excited states with neural-network quantum states）</news:title>
   <news:publication_date>2026-05-24T18:16:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693854</loc>
  <lastmod>2026-05-24T18:15:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フロンティア・フィールド銀河団のレンズモデル評価（An Evaluation of 10 Lensing Models of the Frontier Fields Cluster MACSJ0416.1-2403）</news:title>
   <news:publication_date>2026-05-24T18:15:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693852</loc>
  <lastmod>2026-05-24T18:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチコアHW/SWコーデザインによるK-means高速化（Using Multi-Core HW/SW Co-design Architecture for Accelerating K-means Clustering Algorithm）</news:title>
   <news:publication_date>2026-05-24T18:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693850</loc>
  <lastmod>2026-05-24T18:15:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英語の訛りを統計的に補正する手法（Foreign English Accent Adjustment by Learning Phonetic Patterns）</news:title>
   <news:publication_date>2026-05-24T18:15:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693848</loc>
  <lastmod>2026-05-24T18:14:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限個の未知評価額を仮定した動的価格設定（Dynamic Pricing with Finitely Many Unknown Valuations）</news:title>
   <news:publication_date>2026-05-24T18:14:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693846</loc>
  <lastmod>2026-05-24T17:23:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次モンテカルロ期待値最大化における適応学習による効率的収束（Efficient convergence through adaptive learning in sequential Monte Carlo Expectation Maximization）</news:title>
   <news:publication_date>2026-05-24T17:23:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693844</loc>
  <lastmod>2026-05-24T17:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>座標変換で暴露された畳み込みニューラルネットワークの落とし穴（An intriguing failing of convolutional neural networks and the CoordConv solution）</news:title>
   <news:publication_date>2026-05-24T17:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693842</loc>
  <lastmod>2026-05-24T17:14:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ニューラルネットワークのベンチマーク—古典NNとの比較で示された効率性（Benchmarking Neural Networks For Quantum Computations）</news:title>
   <news:publication_date>2026-05-24T17:14:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693840</loc>
  <lastmod>2026-05-24T17:12:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的進化的特徴選択による放射線画像の選別（Multi-objective Feature Selection with Modified Entropy Termination and Evidential Reasoning）</news:title>
   <news:publication_date>2026-05-24T17:12:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693838</loc>
  <lastmod>2026-05-24T17:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発達期における抑制のブレインワイド発達を深層学習で探る（Exploring Brain-wide Development of Inhibition through Deep Learning）</news:title>
   <news:publication_date>2026-05-24T17:12:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693836</loc>
  <lastmod>2026-05-24T17:12:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FHIRChainによる臨床データの安全かつスケーラブルな共有（FHIRChain: Applying Blockchain to Securely and Scalably Share Clinical Data）</news:title>
   <news:publication_date>2026-05-24T17:12:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693834</loc>
  <lastmod>2026-05-24T17:12:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>渦と磁場がつむぐ“大きさの逆転”──渦度・ヘリシティと双方向カスケードの概観（Helicity dynamics, inverse and bi-directional cascades in fluid and magnetohydrodynamic turbulence: A brief review）</news:title>
   <news:publication_date>2026-05-24T17:12:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693832</loc>
  <lastmod>2026-05-24T16:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNを用いたNIDS強化の方法（RNNIDS: Enhancing Network Intrusion Detection Systems through Deep Learning）</news:title>
   <news:publication_date>2026-05-24T16:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693830</loc>
  <lastmod>2026-05-24T16:19:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的モデル平均による効率的な分散深層学習（Efficient Decentralized Deep Learning by Dynamic Model Averaging）</news:title>
   <news:publication_date>2026-05-24T16:19:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693828</loc>
  <lastmod>2026-05-24T16:19:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーソナライズされた語彙学習チュータの設計と評価（Design and Evaluation of a Tutor Platform for Personalized Vocabulary Learning）</news:title>
   <news:publication_date>2026-05-24T16:19:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693826</loc>
  <lastmod>2026-05-24T16:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身近な材料と低コストセンサーで物理を学ぶ（Low-Cost Experiments with Everyday Objects for Homework Assignments）</news:title>
   <news:publication_date>2026-05-24T16:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693824</loc>
  <lastmod>2026-05-24T16:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延が未知のバンディット・オンライン学習（Bandit Online Learning with Unknown Delays）</news:title>
   <news:publication_date>2026-05-24T16:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693822</loc>
  <lastmod>2026-05-24T16:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Thresholded ConvNet Ensemblesによるテクニカル予測の要点（Thresholded ConvNet Ensembles: Neural Networks for Technical Forecasting）</news:title>
   <news:publication_date>2026-05-24T16:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693820</loc>
  <lastmod>2026-05-24T16:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似k空間モデルと深層学習による高速光音響再構成（Approximate k-space models and Deep Learning for fast photoacoustic reconstruction）</news:title>
   <news:publication_date>2026-05-24T16:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693818</loc>
  <lastmod>2026-05-24T15:26:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エリートアスリートにおける心肺パラメータの因果経路発見（Discovery of causal paths in cardiorespiratory parameters: a time-independent approach in elite athletes）</news:title>
   <news:publication_date>2026-05-24T15:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693816</loc>
  <lastmod>2026-05-24T15:25:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い文脈化単語埋め込み、アンサンブル、ツリーバンク連結によるUDパーシングの改善（Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank Concatenation）</news:title>
   <news:publication_date>2026-05-24T15:25:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693814</loc>
  <lastmod>2026-05-24T15:25:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースネットワークのためのBeta Neutral-to-the-Leftモデルのサンプリングと推論（Sampling and Inference for Beta Neutral-to-the-Left Models of Sparse Networks）</news:title>
   <news:publication_date>2026-05-24T15:25:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693812</loc>
  <lastmod>2026-05-24T15:24:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層マルチモーダルクラスタリングによる教師なし音声映像学習（Deep Multimodal Clustering for Unsupervised Audiovisual Learning）</news:title>
   <news:publication_date>2026-05-24T15:24:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693810</loc>
  <lastmod>2026-05-24T15:24:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形計測とニューラルネットワークによるMRPCの時間再構成法（The study of a new time reconstruction method for MRPC read out by waveform digitizer）</news:title>
   <news:publication_date>2026-05-24T15:24:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693808</loc>
  <lastmod>2026-05-24T15:23:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NMT-Keras：対話型・継続学習に注力した柔軟な機械翻訳ツールキット（NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning）</news:title>
   <news:publication_date>2026-05-24T15:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693806</loc>
  <lastmod>2026-05-24T15:23:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分実行で強化するText-to-SQL（Robust Text-to-SQL Generation with Execution-Guided Decoding）</news:title>
   <news:publication_date>2026-05-24T15:23:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693804</loc>
  <lastmod>2026-05-24T14:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓不整脈発生源のコンピュータ支援局在化（Computer Assisted Localization of a Heart Arrhythmia）</news:title>
   <news:publication_date>2026-05-24T14:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693802</loc>
  <lastmod>2026-05-24T14:31:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共分散と濃度グラフ行列のシミュレーション（SIMULATING COVARIANCE AND CONCENTRATION GRAPH MATRICES）</news:title>
   <news:publication_date>2026-05-24T14:31:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693800</loc>
  <lastmod>2026-05-24T14:31:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画要約を分類で導く強化学習（Video Summarisation by Classification with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-24T14:31:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693798</loc>
  <lastmod>2026-05-24T14:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次診断における能動学習ヒューリスティクスの評価（Evaluating Active Learning Heuristics for Sequential Diagnosis）</news:title>
   <news:publication_date>2026-05-24T14:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693796</loc>
  <lastmod>2026-05-24T14:31:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ChestNetによる胸部X線画像の診断向上（ChestNet: A Deep Neural Network for Classification of Thoracic Diseases on Chest Radiography）</news:title>
   <news:publication_date>2026-05-24T14:31:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693794</loc>
  <lastmod>2026-05-24T14:30:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>精度学習に基づくニューラルネットワーク設計：平行線投影から扇形線投影への変換（Deriving Neural Network Architectures using Precision Learning: Parallel-to-fan beam Conversion）</news:title>
   <news:publication_date>2026-05-24T14:30:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693792</loc>
  <lastmod>2026-05-24T14:30:40Z</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を用いた時間差分学習におけるリーケージ伝播の研究 (Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem)</news:title>
   <news:publication_date>2026-05-24T14:30:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693790</loc>
  <lastmod>2026-05-24T13:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌声処理における深層学習の到達点と実務への示唆（Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners）</news:title>
   <news:publication_date>2026-05-24T13:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693788</loc>
  <lastmod>2026-05-24T13:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置認識型自己注意（Position-aware Self-attention）によるスロットフィリングの改良（Position-aware Self-attention with Relative Positional Encodings for Slot Filling）</news:title>
   <news:publication_date>2026-05-24T13:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693786</loc>
  <lastmod>2026-05-24T13:39:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動サービスロボットの自然言語命令理解を深層学習で実装する（A deep learning approach for understanding natural language commands for mobile service robots）</news:title>
   <news:publication_date>2026-05-24T13:39:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693784</loc>
  <lastmod>2026-05-24T13:39:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Glow：可逆1×1畳み込みを用いた生成フロー（Glow: Generative Flow with Invertible 1×1 Convolutions）</news:title>
   <news:publication_date>2026-05-24T13:39:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693782</loc>
  <lastmod>2026-05-24T13:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pioneer Networks: Progressively Growing Generative Autoencoder（Pioneer Networks: Progressively Growing Generative Autoencoder）</news:title>
   <news:publication_date>2026-05-24T13:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693780</loc>
  <lastmod>2026-05-24T13:38:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形・循環・潜在交絡を扱う制約ベース因果探索（Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders）</news:title>
   <news:publication_date>2026-05-24T13:38:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693778</loc>
  <lastmod>2026-05-24T13:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>血糖値予測のための畳み込み再帰型ニューラルネットワーク（Convolutional Recurrent Neural Networks for Glucose Prediction）</news:title>
   <news:publication_date>2026-05-24T13:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693776</loc>
  <lastmod>2026-05-24T12:47:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実写に近い合成画像で高精度なシーンテキスト検出・認識を実現する手法（Verisimilar Image Synthesis for Accurate Detection and Recognition of Texts in Scenes）</news:title>
   <news:publication_date>2026-05-24T12:47:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693774</loc>
  <lastmod>2026-05-24T12:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OntoSenseNetを用いた語義注釈と感情分析の接点（Towards Enhancing Lexical Resource and Using Sense-annotations of OntoSenseNet for Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-24T12:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693772</loc>
  <lastmod>2026-05-24T12:46:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XNOR Neural Engine: マイクロコントローラ向けBNNアクセラレータ（XNOR Neural Engine: a Hardware Accelerator IP for 21.6 fJ/op Binary Neural Network Inference）</news:title>
   <news:publication_date>2026-05-24T12:46:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693770</loc>
  <lastmod>2026-05-24T12:45:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Restricted Boltzmann Machineのサイズ削減手法（Decreasing the size of the Restricted Boltzmann machine）</news:title>
   <news:publication_date>2026-05-24T12:45:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693768</loc>
  <lastmod>2026-05-24T12:45:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市環境における視覚的ローカリゼーションのための動的物体セグメンテーション (Dynamic Objects Segmentation for Visual Localization in Urban Environments)</news:title>
   <news:publication_date>2026-05-24T12:45:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693766</loc>
  <lastmod>2026-05-24T12:45:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ネットワークでの関数学習はモジュール性を要し多主体ダイナミクスを生む（Learning Functions in Large Networks requires Modularity and produces Multi-Agent Dynamics）</news:title>
   <news:publication_date>2026-05-24T12:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693764</loc>
  <lastmod>2026-05-24T12:45:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘッダービッディングにおけるSSP入札戦略の最適化（Optimization of a SSP’s Header Bidding Strategy using Thompson Sampling）</news:title>
   <news:publication_date>2026-05-24T12:45:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693762</loc>
  <lastmod>2026-05-24T11:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍探索のための学習型インデックス（Learning to Index for Nearest Neighbor Search）</news:title>
   <news:publication_date>2026-05-24T11:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693760</loc>
  <lastmod>2026-05-24T11:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分グラフパターンと非線形モデルの同時学習（Jointly learning relevant subgraph patterns and nonlinear models of their indicators）</news:title>
   <news:publication_date>2026-05-24T11:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693758</loc>
  <lastmod>2026-05-24T11:53:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多体局在と熱化の境界を機械学習で可視化する（Interpretable Machine Learning Study of Many-Body Localization Transition in Disordered Quantum Ising Spin Chains）</news:title>
   <news:publication_date>2026-05-24T11:53:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693756</loc>
  <lastmod>2026-05-24T11:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化されたコミュニティの統計的有意性の検定（Computing the statistical significance of optimized communities in networks）</news:title>
   <news:publication_date>2026-05-24T11:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693754</loc>
  <lastmod>2026-05-24T11:52:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン語義記述子なしでのゼロショットドメイン適応（Zero-shot Domain Adaptation without Domain Semantic Descriptors）</news:title>
   <news:publication_date>2026-05-24T11:52:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693752</loc>
  <lastmod>2026-05-24T11:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的アフィン変換を階層的に学習するPARN（Pyramidal Affine Regression Networks for Dense Semantic Correspondence）</news:title>
   <news:publication_date>2026-05-24T11:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693750</loc>
  <lastmod>2026-05-24T11:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周囲と調和する車両画像生成（Vehicle Image Generation Going Well with the Surroundings）</news:title>
   <news:publication_date>2026-05-24T11:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693748</loc>
  <lastmod>2026-05-24T11:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CSI学習に基づく能動的安全符号化方式（CSI Learning Based Active Secure Coding Scheme For Detectable Wiretap Channel）</news:title>
   <news:publication_date>2026-05-24T11:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693746</loc>
  <lastmod>2026-05-24T11:00:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Domain2Vecによるドメイン一般化の設計（Domain2Vec: Deep Domain Generalization）</news:title>
   <news:publication_date>2026-05-24T11:00:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693744</loc>
  <lastmod>2026-05-24T10:59:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール注意によるセマンティックセグメンテーションの改良（Attention to Refine through Multi-Scales for Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-24T10:59:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693742</loc>
  <lastmod>2026-05-24T10:58:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分方策ベース強化学習による3D医療画像のランドマーク検出（Partial Policy-based Reinforcement Learning for Anatomical Landmark Localization in 3D Medical Images）</news:title>
   <news:publication_date>2026-05-24T10:58:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693740</loc>
  <lastmod>2026-05-24T10:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像分類の脆弱性解析（Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks）</news:title>
   <news:publication_date>2026-05-24T10:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693738</loc>
  <lastmod>2026-05-24T10:58:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル非依存の教師付き局所説明（Model Agnostic Supervised Local Explanations）</news:title>
   <news:publication_date>2026-05-24T10:58:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693736</loc>
  <lastmod>2026-05-24T10:58:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アラビア語感情分析のためのCNNとLSTMの統合モデル（A Combined CNN and LSTM Model for Arabic Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-24T10:58:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693734</loc>
  <lastmod>2026-05-24T10:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RANSモデルの構造的不確かさを定量化するベイジアン深層ニューラルネットワーク（Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks）</news:title>
   <news:publication_date>2026-05-24T10:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693732</loc>
  <lastmod>2026-05-24T10:06:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語の具体性と画像想起性の予測（Predicting Concreteness and Imageability of Words Within and Across Languages via Word Embeddings）</news:title>
   <news:publication_date>2026-05-24T10:06:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693730</loc>
  <lastmod>2026-05-24T10:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EL画像による太陽電池モジュールセルの欠陥自動分類（Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images）</news:title>
   <news:publication_date>2026-05-24T10:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693728</loc>
  <lastmod>2026-05-24T10:05:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習ベースのアクター・クリティックによる自動深層圧縮（Auto Deep Compression by Reinforcement Learning Based Actor-Critic Structure）</news:title>
   <news:publication_date>2026-05-24T10:05:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693726</loc>
  <lastmod>2026-05-24T10:05:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SuperBITによる高解像度広視野バルーン望遠鏡の概観と成果（Overview, design, and flight results from SuperBIT: a high-resolution, wide-field, visible-to-near-UV balloon-borne astronomical telescope）</news:title>
   <news:publication_date>2026-05-24T10:05:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693724</loc>
  <lastmod>2026-05-24T10:05:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフのコミュニティ検出における統計的限界と半正定値緩和（Stochastic Block Model for Hypergraphs: Statistical limits and a semidefinite programming approach）</news:title>
   <news:publication_date>2026-05-24T10:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693722</loc>
  <lastmod>2026-05-24T10:04:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バグ・チケット自動ラベリングにおける階層注意機構を用いたRNN手法（Automated labeling of bugs and tickets using attention-based mechanisms in recurrent neural networks）</news:title>
   <news:publication_date>2026-05-24T10:04:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693720</loc>
  <lastmod>2026-05-24T09:13:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークに基づく無線資源配分（Resource Allocation Based on Deep Neural Networks for Cognitive Radio Networks）</news:title>
   <news:publication_date>2026-05-24T09:13:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693718</loc>
  <lastmod>2026-05-24T09:06:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイエネルギー物理学における機械学習の共同ホワイトペーパー（Machine Learning in High Energy Physics Community White Paper）</news:title>
   <news:publication_date>2026-05-24T09:06:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693716</loc>
  <lastmod>2026-05-24T09:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離可能性を最優先にするのは最善ではない（Separability Is Not the Best Goal for Machine Learning）</news:title>
   <news:publication_date>2026-05-24T09:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693714</loc>
  <lastmod>2026-05-24T09:05:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きなマージンを用いた少数ショット学習（Large Margin Few-Shot Learning）</news:title>
   <news:publication_date>2026-05-24T09:05:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693712</loc>
  <lastmod>2026-05-24T09:04:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チケットシステムにおける非対称テキスト類似学習の実務的応用（Replicated Siamese LSTM in Ticketing System for Similarity Learning and Retrieval in Asymmetric Texts）</news:title>
   <news:publication_date>2026-05-24T09:04:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693710</loc>
  <lastmod>2026-05-24T09:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>準パラメトリック画像修復（Semi-parametric Image Inpainting）</news:title>
   <news:publication_date>2026-05-24T09:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693708</loc>
  <lastmod>2026-05-24T09:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列情報を学習するリカレントニューラルネットワーク（Learning The Sequential Temporal Information with Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-24T09:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693706</loc>
  <lastmod>2026-05-24T08:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gaia GraLによる天体重力レンズ探索の盲検的検出（Gaia GraL: Gaia DR2 Gravitational Lens Systems. III. A systematic blind search for new lensed systems）</news:title>
   <news:publication_date>2026-05-24T08:12:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693704</loc>
  <lastmod>2026-05-24T08:11:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的確率的グラフレット埋め込み（Hierarchical Stochastic Graphlet Embedding）</news:title>
   <news:publication_date>2026-05-24T08:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693702</loc>
  <lastmod>2026-05-24T08:10:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深く監督された回転等変性ネットワークによる皮膚鏡画像の病変セグメンテーション（Deeply Supervised Rotation Equivariant Network for Lesion Segmentation in Dermoscopy Images）</news:title>
   <news:publication_date>2026-05-24T08:10:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693700</loc>
  <lastmod>2026-05-24T08:10:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>802.11ネットワークにおけるMAC層レート制御の総括（MAC-Layer Rate Control for 802.11 Networks: Lesson Learned and Looking Forward）</news:title>
   <news:publication_date>2026-05-24T08:10:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693698</loc>
  <lastmod>2026-05-24T08:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイジアン最適化入門（A Tutorial on Bayesian Optimization）</news:title>
   <news:publication_date>2026-05-24T08:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693696</loc>
  <lastmod>2026-05-24T08:10:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動プログラミングによる深層学習の改良（Improving Deep Learning through Automatic Programming）</news:title>
   <news:publication_date>2026-05-24T08:10:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693694</loc>
  <lastmod>2026-05-24T08:09:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間インスタンス学習：クラス監視からのアクションチューブ（Spatio-Temporal Instance Learning: Action Tubes from Class Supervision）</news:title>
   <news:publication_date>2026-05-24T08:09:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693692</loc>
  <lastmod>2026-05-24T07:18:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>金融取引をゲームとして捉える―深層強化学習による自動売買の可能性（Financial Trading as a Game: A Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-05-24T07:18:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693690</loc>
  <lastmod>2026-05-24T07:10:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分学習における蒸留と疑似リハーサルの偏り除去（Distillation Techniques for Pseudo-rehearsal Based Incremental Learning）</news:title>
   <news:publication_date>2026-05-24T07:10:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693688</loc>
  <lastmod>2026-05-24T07:10:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負のL1ノルム制約を持つベイズ最小二乗法の提案（BALSON: BAYESIAN LEAST SQUARES OPTIMIZATION WITH NONNEGATIVE L1-NORM CONSTRAINT）</news:title>
   <news:publication_date>2026-05-24T07:10:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693686</loc>
  <lastmod>2026-05-24T07:09:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モード視点が拓く統計の新時代（The Modal Age of Statistics）</news:title>
   <news:publication_date>2026-05-24T07:09:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693684</loc>
  <lastmod>2026-05-24T07:08:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フリンジパターン解析における深層学習（Fringe pattern analysis using deep learning）</news:title>
   <news:publication_date>2026-05-24T07:08:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693682</loc>
  <lastmod>2026-05-24T07:08:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非常に深い残差チャネル注意ネットワークによる画像超解像（Image Super-Resolution Using Very Deep Residual Channel Attention Networks）</news:title>
   <news:publication_date>2026-05-24T07:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693680</loc>
  <lastmod>2026-05-24T07:08:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>鳥の音を聞き分ける密結合CNNの実践（Densely Connected CNNs for Bird Audio Detection）</news:title>
   <news:publication_date>2026-05-24T07:08:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693678</loc>
  <lastmod>2026-05-24T06:17:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シナプスの位置と接続方向を同時に検出する手法の要諦（Detecting Synapse Location and Connectivity by Signed Proximity Estimation and Pruning with Deep Nets）</news:title>
   <news:publication_date>2026-05-24T06:17:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693676</loc>
  <lastmod>2026-05-24T06:16:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>母音フォルマント類型の深層生成モデル（A Deep Generative Model of Vowel Formant Typology）</news:title>
   <news:publication_date>2026-05-24T06:16:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693674</loc>
  <lastmod>2026-05-24T06:16:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群のデータ駆動アップサンプリング（Data-driven Upsampling of Point Clouds）</news:title>
   <news:publication_date>2026-05-24T06:16:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693672</loc>
  <lastmod>2026-05-24T06:16:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークのみで侵害するAndroidプライバシー（Nothing But Net: Invading Android User Privacy Using Only Network Access Patterns）</news:title>
   <news:publication_date>2026-05-24T06:16:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693670</loc>
  <lastmod>2026-05-24T06:16:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トリム推定量のロバスト学習とマニフォールドサンプリング（Robust Learning of Trimmed Estimators via Manifold Sampling）</news:title>
   <news:publication_date>2026-05-24T06:16:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693668</loc>
  <lastmod>2026-05-24T06:15:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼性の高いmmWave通信のための機械学習：遮へい予測と事前ハンドオフ（Machine Learning for Reliable mmWave Systems: Blockage Prediction and Proactive Handoff）</news:title>
   <news:publication_date>2026-05-24T06:15:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693666</loc>
  <lastmod>2026-05-24T06:15:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた地質パラメータ化とヒストリーマッチの革新（A Deep-Learning-Based Geological Parameterization for History Matching Complex Models）</news:title>
   <news:publication_date>2026-05-24T06:15:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693664</loc>
  <lastmod>2026-05-24T05:24:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相特徴を用いたDNNベース音楽音源分離の改良 (Improving DNN-based Music Source Separation using Phase Features)</news:title>
   <news:publication_date>2026-05-24T05:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693662</loc>
  <lastmod>2026-05-24T05:24:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSource: 深層学習による点状天体検出の実務的意義（DeepSource: Point Source Detection using Deep Learning）</news:title>
   <news:publication_date>2026-05-24T05:24:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693660</loc>
  <lastmod>2026-05-24T05:24:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速なパラメータ調整のための近似Leave-One-Out（Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions）</news:title>
   <news:publication_date>2026-05-24T05:24:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693658</loc>
  <lastmod>2026-05-24T05:23:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cellular Controlled Delay TCP（Cellular Controlled Delay TCP (C2TCP)）</news:title>
   <news:publication_date>2026-05-24T05:23:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693656</loc>
  <lastmod>2026-05-24T05:23:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合量子ラビモデル（The Mixed Quantum Rabi Model）</news:title>
   <news:publication_date>2026-05-24T05:23:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693654</loc>
  <lastmod>2026-05-24T05:23:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペクトル画像分類のための教師付き幾何認識写像アプローチ（A Supervised Geometry-Aware Mapping Approach for Classification of Hyperspectral Images）</news:title>
   <news:publication_date>2026-05-24T05:23:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693652</loc>
  <lastmod>2026-05-24T05:23:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VFPredによる心室細動検出：信号処理と機械学習の融合（VFPred: A Fusion of Signal Processing and Machine Learning techniques in Detecting Ventricular Fibrillation from ECG Signals）</news:title>
   <news:publication_date>2026-05-24T05:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693650</loc>
  <lastmod>2026-05-24T04:32:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢でスケーラブルな微分可能ニューラルコンピュータ（Robust and Scalable Differentiable Neural Computer for Question Answering）</news:title>
   <news:publication_date>2026-05-24T04:32:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693648</loc>
  <lastmod>2026-05-24T04:32:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>白内障等級付けのためのトーナメント型ランキングCNN（Tournament Based Ranking CNN for the Cataract grading）</news:title>
   <news:publication_date>2026-05-24T04:32:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693646</loc>
  <lastmod>2026-05-24T04:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンショット質感セグメンテーション（One-shot Texture Segmentation）</news:title>
   <news:publication_date>2026-05-24T04:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693644</loc>
  <lastmod>2026-05-24T04:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲームの複雑性が合成エージェントのプレイ行動に与える影響（How game complexity affects the playing behavior of synthetic agents）</news:title>
   <news:publication_date>2026-05-24T04:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693642</loc>
  <lastmod>2026-05-24T04:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外観と動き条件によるビデオ予測 (Video Prediction with Appearance and Motion Conditions)</news:title>
   <news:publication_date>2026-05-24T04:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693640</loc>
  <lastmod>2026-05-24T04:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SQL学習のための推薦システムとヒント生成（Recommender system for learning SQL using hints）</news:title>
   <news:publication_date>2026-05-24T04:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693638</loc>
  <lastmod>2026-05-24T04:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仕事が重要なとき：古典的ネットワーク構造をグラフCNNへ変換する手法 (When Work Matters: Transforming Classical Network Structures to Graph CNN)</news:title>
   <news:publication_date>2026-05-24T04:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693636</loc>
  <lastmod>2026-05-24T03:38:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽観的ミラーディセントによる鞍点問題の前進（OPTIMISTIC MIRROR DESCENT IN SADDLE-POINT PROBLEMS: GOING THE EXTRA (GRADIENT) MILE）</news:title>
   <news:publication_date>2026-05-24T03:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693634</loc>
  <lastmod>2026-05-24T03:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>滑空とパーチングのための深層強化学習（Deep-Reinforcement-Learning for Gliding and Perching Bodies）</news:title>
   <news:publication_date>2026-05-24T03:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693632</loc>
  <lastmod>2026-05-24T03:38:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中核保存に基づくネットワーク表現学習（Core2Vec: A core-preserving feature learning framework for networks）</news:title>
   <news:publication_date>2026-05-24T03:38:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693630</loc>
  <lastmod>2026-05-24T03:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的入力を持つリザバーコンピューティングの普遍性（Reservoir Computing Universality With Stochastic Inputs）</news:title>
   <news:publication_date>2026-05-24T03:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693628</loc>
  <lastmod>2026-05-24T03:37:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Anytime Neural Prediction via Slicing Networks Vertically（Anytime Neural Prediction via Slicing Networks Vertically）</news:title>
   <news:publication_date>2026-05-24T03:37:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693626</loc>
  <lastmod>2026-05-24T03:37:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳幼児の運動データから発達リスクを予測する（Predicting Infant Motor Development Status using Day Long Movement Data from Wearable Sensors）</news:title>
   <news:publication_date>2026-05-24T03:37:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693624</loc>
  <lastmod>2026-05-24T03:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配ハイパーアラインメント（Gradient Hyperalignment for multi-subject fMRI data alignment）</news:title>
   <news:publication_date>2026-05-24T03:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693622</loc>
  <lastmod>2026-05-24T02:45:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的確率的新奇検出と敵対的オートエンコーダ（Generative Probabilistic Novelty Detection with Adversarial Autoencoders）</news:title>
   <news:publication_date>2026-05-24T02:45:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693620</loc>
  <lastmod>2026-05-24T02:45:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Goldilocksゾーン：ニューラルネットワークの損失ランドスケープの理解に向けて（The Goldilocks zone: Towards better understanding of neural network loss landscapes）</news:title>
   <news:publication_date>2026-05-24T02:45:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693618</loc>
  <lastmod>2026-05-24T02:37:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス悪性度予測のための合成サンプリング（Synthetic Sampling for Multi-Class Malignancy Prediction）</news:title>
   <news:publication_date>2026-05-24T02:37:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693616</loc>
  <lastmod>2026-05-24T02:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療記録からトピックを抽出する非教師的グラフ分割法（From Text to Topics in Healthcare Records: An Unsupervised Graph Partitioning Methodology）</news:title>
   <news:publication_date>2026-05-24T02:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693614</loc>
  <lastmod>2026-05-24T02:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SmartSeedによる効率的なファジング向けシード生成（SmartSeed: Smart Seed Generation for Efficient Fuzzing）</news:title>
   <news:publication_date>2026-05-24T02:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693612</loc>
  <lastmod>2026-05-24T02:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程とカーネル法の関係と等価性（Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences）</news:title>
   <news:publication_date>2026-05-24T02:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693610</loc>
  <lastmod>2026-05-24T02:35:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多値ルールセットによる患者院内死亡予測の解釈可能モデル（Interpretable Patient Mortality Prediction with Multi-value Rule Sets）</news:title>
   <news:publication_date>2026-05-24T02:35:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693608</loc>
  <lastmod>2026-05-24T01:44:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化と解釈可能な患者心電図プロファイル（Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery）</news:title>
   <news:publication_date>2026-05-24T01:44:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693606</loc>
  <lastmod>2026-05-24T01:44:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Virtual Stereo Odometryを用いた単眼DSOの進化（Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry）</news:title>
   <news:publication_date>2026-05-24T01:44:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693604</loc>
  <lastmod>2026-05-24T01:43:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M-ADDAによる非監督ドメイン適応と深層距離学習の統合（M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning）</news:title>
   <news:publication_date>2026-05-24T01:43:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693602</loc>
  <lastmod>2026-05-24T01:43:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D回転に強い畳み込みネットワークの設計（3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data）</news:title>
   <news:publication_date>2026-05-24T01:43:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693600</loc>
  <lastmod>2026-05-24T01:43:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木幅に基づく計算可能性の新たな限界（New Limits of Treewidth-based Tractability in Optimization）</news:title>
   <news:publication_date>2026-05-24T01:43:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693598</loc>
  <lastmod>2026-05-24T01:43:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全にスケーラブルなガウス過程と部分空間誘導入力（Fully Scalable Gaussian Processes using Subspace Inducing Inputs）</news:title>
   <news:publication_date>2026-05-24T01:43:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693596</loc>
  <lastmod>2026-05-24T01:43:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載画像の境界線で位置推定をする技術の要点解説（VLASE: Vehicle Localization by Aggregating Semantic Edges）</news:title>
   <news:publication_date>2026-05-24T01:43:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693594</loc>
  <lastmod>2026-05-24T00:52:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙再電離末期に見つかった強力な電波明るいクエーサー（A POWERFUL RADIO-LOUD QUASAR AT THE END OF COSMIC REIONIZATION）</news:title>
   <news:publication_date>2026-05-24T00:52:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693592</loc>
  <lastmod>2026-05-24T00:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>荷電カレント深部非弾性散乱におけるジェット生成のNNLO QCD補正（NNLO QCD Corrections to Jet Production in Charged Current Deep Inelastic Scattering）</news:title>
   <news:publication_date>2026-05-24T00:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693590</loc>
  <lastmod>2026-05-24T00:51:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ作業におけるリーダーシップ属性と行動の記述と比較（Denoting and Comparing Leadership Attributes and Behaviors in Group Work）</news:title>
   <news:publication_date>2026-05-24T00:51:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693588</loc>
  <lastmod>2026-05-24T00:50:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的画像セグメンテーションのための全畳み込み二系統融合ネットワーク（A Fully Convolutional Two-Stream Fusion Network for Interactive Image Segmentation）</news:title>
   <news:publication_date>2026-05-24T00:50:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693586</loc>
  <lastmod>2026-05-24T00:50:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動するラベルの下で「意味のある」表現を学ぶ方法（Deep Multiple Instance Feature Learning via Variational Autoencoder）</news:title>
   <news:publication_date>2026-05-24T00:50:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693584</loc>
  <lastmod>2026-05-24T00:49:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>YouTubeを用いた患者教育：ユーザー生成動画から医療知識を抽出する深層学習の試み (YouTube for Patient Education: A Deep Learning Approach for Understanding Medical Knowledge from User-Generated Videos)</news:title>
   <news:publication_date>2026-05-24T00:49:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693582</loc>
  <lastmod>2026-05-24T00:49:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数選択チャネルと少ビットADCにおける共同チャネル推定・復号（Joint Channel-Estimation/Decoding with Frequency-Selective Channels and Few-Bit ADCs）</news:title>
   <news:publication_date>2026-05-24T00:49:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693580</loc>
  <lastmod>2026-05-23T23:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルツハイマー病の病状推移を深層学習で予測する（Forecasting Disease Trajectories in Alzheimer’s Disease Using Deep Learning）</news:title>
   <news:publication_date>2026-05-23T23:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693578</loc>
  <lastmod>2026-05-23T23:56:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>典型的な携帯電話利用習慣：激しい使用は否定的な幸福感を予測しない（Typical Phone Use Habits: Intense Use Does Not Predict Negative Well-Being）</news:title>
   <news:publication_date>2026-05-23T23:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693576</loc>
  <lastmod>2026-05-23T23:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な機械学習による非平衡系の相境界推定（Interpretable machine learning for inferring the phase boundaries in a nonequilibrium system）</news:title>
   <news:publication_date>2026-05-23T23:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693574</loc>
  <lastmod>2026-05-23T23:56:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セキュリティ関連コミットの自動分類の実践的手法 (A Practical Approach to the Automatic Classification of Security-Relevant Commits)</news:title>
   <news:publication_date>2026-05-23T23:56:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693572</loc>
  <lastmod>2026-05-23T23:56:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損データを考慮したマルチタスク学習（Multi-Task Learning with Incomplete Data for Healthcare）</news:title>
   <news:publication_date>2026-05-23T23:56:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693570</loc>
  <lastmod>2026-05-23T23:56:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボリュメトリック医用スキャンにおける器官の深層逐次セグメンテーション（Deep Sequential Segmentation of Organs in Volumetric Medical Scans）</news:title>
   <news:publication_date>2026-05-23T23:56:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693568</loc>
  <lastmod>2026-05-23T23:55:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接線畳み込みによる3D密度予測の革新（Tangent Convolutions for Dense Prediction in 3D）</news:title>
   <news:publication_date>2026-05-23T23:55:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693566</loc>
  <lastmod>2026-05-23T23:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病理画像分類における逆能動学習とAtrous DenseNetの統合（Reversed Active Learning and Atrous DenseNet for Pathological Image Classification）</news:title>
   <news:publication_date>2026-05-23T23:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693564</loc>
  <lastmod>2026-05-23T23:03:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球も少し扁平だと空気の流れがこう変わる（Simple geometric approximations for global atmospheres on moderately oblate planets）</news:title>
   <news:publication_date>2026-05-23T23:03:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693562</loc>
  <lastmod>2026-05-23T23:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソースコード上の一行差分を機械学習で予測する競技プラットフォーム（The CodRep Machine Learning on Source Code Competition）</news:title>
   <news:publication_date>2026-05-23T23:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693560</loc>
  <lastmod>2026-05-23T23:01:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非連結マルコフ決定過程におけるほぼ最適な探索と活用（Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes）</news:title>
   <news:publication_date>2026-05-23T23:01:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693558</loc>
  <lastmod>2026-05-23T23:01:47Z</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エンドツーエンドレースドライビング（End-to-End Race Driving with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-23T23:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693556</loc>
  <lastmod>2026-05-23T23:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア開発の成果物から授業効果を測る（Beyond Surveys: Analyzing Software Development Artifacts to Assess Teaching Efforts）</news:title>
   <news:publication_date>2026-05-23T23:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693554</loc>
  <lastmod>2026-05-23T23:01:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化予測によるラベルランキングのアプローチ（A Structured Prediction Approach for Label Ranking）</news:title>
   <news:publication_date>2026-05-23T23:01:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693552</loc>
  <lastmod>2026-05-23T22:09:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳構造グラフによるアルツハイマー病の早期検出（Graph of brain structures grading for early detection of Alzheimer’s disease）</news:title>
   <news:publication_date>2026-05-23T22:09:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693550</loc>
  <lastmod>2026-05-23T22:01:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースビューCT再構成のためのDeep Back Projection（DEEP BACK PROJECTION FOR SPARSE-VIEW CT RECONSTRUCTION）</news:title>
   <news:publication_date>2026-05-23T22:01:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693548</loc>
  <lastmod>2026-05-23T22:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列変分特徴抽出による行動予測（A Variational Time Series Feature Extractor for Action Prediction）</news:title>
   <news:publication_date>2026-05-23T22:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693546</loc>
  <lastmod>2026-05-23T21:59:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系列ラベリングにおけるサム・プロダクト・ネットワーク（Sum-Product Networks for Sequence Labeling）</news:title>
   <news:publication_date>2026-05-23T21:59:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693544</loc>
  <lastmod>2026-05-23T21:59:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリ拡張ポリシー最適化によるプログラム合成と意味解析の革新（Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing）</news:title>
   <news:publication_date>2026-05-23T21:59:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693542</loc>
  <lastmod>2026-05-23T21:59:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果と情報圧縮で欠損に強くなる方法（Cause‑Effect Deep Information Bottleneck For Systematically Missing Covariates）</news:title>
   <news:publication_date>2026-05-23T21:59:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693540</loc>
  <lastmod>2026-05-23T21:58:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JUMPER：読みながら判断するテキスト分類（JUMPER: Learning When to Make Classification Decisions in Reading）</news:title>
   <news:publication_date>2026-05-23T21:58:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693538</loc>
  <lastmod>2026-05-23T21:07:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抽出型文書要約を一体学習で実現する手法（Neural Document Summarization by Jointly Learning to Score and Select Sentences）</news:title>
   <news:publication_date>2026-05-23T21:07:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693536</loc>
  <lastmod>2026-05-23T21:07:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化NFVオーケストレーションと監視の最適化（z-TORCH: An Automated NFV Orchestration and Monitoring Solution）</news:title>
   <news:publication_date>2026-05-23T21:07:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693534</loc>
  <lastmod>2026-05-23T21:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数試行で学習するロボット方策探索の概観 (A survey on policy search algorithms for learning robot controllers in a handful of trials)</news:title>
   <news:publication_date>2026-05-23T21:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693532</loc>
  <lastmod>2026-05-23T21:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次コピーネットワークの要点（Sequential Copying Networks）</news:title>
   <news:publication_date>2026-05-23T21:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693530</loc>
  <lastmod>2026-05-23T21:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>嗜好が変化するエージェントへのインセンティブ設計を扱う組合せバンディット（Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences）</news:title>
   <news:publication_date>2026-05-23T21:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693528</loc>
  <lastmod>2026-05-23T21:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシーを保ったオンライン部分集合最適化（Differentially Private Online Submodular Optimization）</news:title>
   <news:publication_date>2026-05-23T21:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693526</loc>
  <lastmod>2026-05-23T21:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列畳み込みネットワークによる特徴強化（Parallel Convolutional Networks for Image Recognition via a Discriminator）</news:title>
   <news:publication_date>2026-05-23T21:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693524</loc>
  <lastmod>2026-05-23T20:14:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌声スタイル転送におけるCycleBEGANの提案（Singing Style Transfer Using Cycle-Consistent Boundary Equilibrium Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-23T20:14:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693522</loc>
  <lastmod>2026-05-23T20:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力駆動環境における強化学習の分散削減（VARIANCE REDUCTION FOR REINFORCEMENT LEARNING IN INPUT-DRIVEN ENVIRONMENTS）</news:title>
   <news:publication_date>2026-05-23T20:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693520</loc>
  <lastmod>2026-05-23T20:12:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学院教育における問題発見と創造性の向上（Towards Better Problem Finding and Creativity in Graduate School Education）</news:title>
   <news:publication_date>2026-05-23T20:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693518</loc>
  <lastmod>2026-05-23T20:12:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼性の異なる複数ソースからの転移学習の信頼性向上（Towards more Reliable Transfer Learning）</news:title>
   <news:publication_date>2026-05-23T20:12:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693516</loc>
  <lastmod>2026-05-23T20:12:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mask TextSpotter：任意形状の文字を同時検出・認識するエンドツーエンド手法（Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes）</news:title>
   <news:publication_date>2026-05-23T20:12:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693514</loc>
  <lastmod>2026-05-23T20:12:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度画像検索のための敵対的学習（Adversarial Learning for Fine-grained Image Search）</news:title>
   <news:publication_date>2026-05-23T20:12:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693512</loc>
  <lastmod>2026-05-23T20:11:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河面の三次元星間塵還元マップ（Three-dimensional interstellar dust reddening maps of the Galactic plane）</news:title>
   <news:publication_date>2026-05-23T20:11:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693510</loc>
  <lastmod>2026-05-23T19:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散自己段階学習の実装と意義（Distributed Self-Paced Learning in Alternating Direction Method of Multipliers）</news:title>
   <news:publication_date>2026-05-23T19:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693508</loc>
  <lastmod>2026-05-23T19:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習に基づく球面復号（Deep Learning Based Sphere Decoding）</news:title>
   <news:publication_date>2026-05-23T19:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693506</loc>
  <lastmod>2026-05-23T19:19:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U-SLADSによる動的樹枝構造サンプリング（U-SLADS: Unsupervised Learning Approach for Dynamic Dendrite Sampling）</news:title>
   <news:publication_date>2026-05-23T19:19:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693504</loc>
  <lastmod>2026-05-23T19:19:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差保証付き最適停止の多項式時間アルゴリズム（Polynomial time algorithm for optimal stopping with fixed accuracy）</news:title>
   <news:publication_date>2026-05-23T19:19:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693502</loc>
  <lastmod>2026-05-23T19:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>概念仕様と抽象化に基づく意味表現（A Concept Specification and Abstraction-based Semantic Representation）</news:title>
   <news:publication_date>2026-05-23T19:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693500</loc>
  <lastmod>2026-05-23T19:18:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進行型空間再帰ニューラルネットワークによるイントラ予測（Progressive Spatial Recurrent Neural Network for Intra Prediction）</news:title>
   <news:publication_date>2026-05-23T19:18:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693498</loc>
  <lastmod>2026-05-23T19:18:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界のコードを扱うプログラム合成データセットの意義（NAPS: Natural Program Synthesis Dataset）</news:title>
   <news:publication_date>2026-05-23T19:18:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693496</loc>
  <lastmod>2026-05-23T18:26:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転動作プリミティブの効率的な符号化（Encoding Motion Primitives for Autonomous Vehicles using Virtual Velocity Constraints and Neural Network Scheduling）</news:title>
   <news:publication_date>2026-05-23T18:26:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693494</loc>
  <lastmod>2026-05-23T18:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ拡張によるデジタルマンモグラフィーにおける構築異常検出（Data Augmentation for Detection of Architectural Distortion in Digital Mammography using Deep Learning Approach）</news:title>
   <news:publication_date>2026-05-23T18:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693492</loc>
  <lastmod>2026-05-23T18:18:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情誘発下のEEGを用いた個人識別と深層学習の実装知見（Affective EEG-Based Person Identification Using the Deep Learning Approach）</news:title>
   <news:publication_date>2026-05-23T18:18:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693490</loc>
  <lastmod>2026-05-23T18:17:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース深層ニューラルネットワークの厳密解法（Sparse Deep Neural Network Exact Solutions）</news:title>
   <news:publication_date>2026-05-23T18:17:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693488</loc>
  <lastmod>2026-05-23T18:17:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様なデータサイエンス学習への航海（Navigating Diverse Data Science Learning: Critical Reflections Towards Future Practice）</news:title>
   <news:publication_date>2026-05-23T18:17:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693486</loc>
  <lastmod>2026-05-23T18:17:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズを学習することで敵対的攻撃に強くなる（Implicit Generative Modeling of Random Noise during Training improves Adversarial Robustness）</news:title>
   <news:publication_date>2026-05-23T18:17:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693484</loc>
  <lastmod>2026-05-23T18:16:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サービスロボティクスにおける知識表現の総覧（A Survey of Knowledge Representation in Service Robotics）</news:title>
   <news:publication_date>2026-05-23T18:16:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693482</loc>
  <lastmod>2026-05-23T17:25:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サービスとしてのブロックチェーン：分散型かつ安全なコンピューティングパラダイム（Blockchain as a Service: A Decentralized and Secure Computing Paradigm）</news:title>
   <news:publication_date>2026-05-23T17:25:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693480</loc>
  <lastmod>2026-05-23T17:25:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的Levenberg–Marquardt法によるノイズ耐性最適化（A stochastic Levenberg–Marquardt method using random models with complexity results）</news:title>
   <news:publication_date>2026-05-23T17:25:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693478</loc>
  <lastmod>2026-05-23T17:25:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Protein-Protein Interaction抽出におけるShortest Dependency Pathを用いた双方向LSTMの効果（Feature Assisted bi-directional LSTM Model for Protein-Protein Interaction Identification from Biomedical Texts）</news:title>
   <news:publication_date>2026-05-23T17:25:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693476</loc>
  <lastmod>2026-05-23T17:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳房DCE-MRIの自動深層学習ベースの正規化（Automatic deep learning-based normalization of breast dynamic contrast-enhanced magnetic resonance images）</news:title>
   <news:publication_date>2026-05-23T17:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693474</loc>
  <lastmod>2026-05-23T17:24:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的証拠連鎖によるスケーラブルなレコメンダー（Scalable Recommender Systems through Recursive Evidence Chains）</news:title>
   <news:publication_date>2026-05-23T17:24:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693472</loc>
  <lastmod>2026-05-23T17:24:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gridbot：脳の航法系を模倣するスパイキングニューラルネットワークで制御される自律ロボット (Gridbot: An autonomous robot controlled by a Spiking Neural Network mimicking the brain’s navigational system)</news:title>
   <news:publication_date>2026-05-23T17:24:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693470</loc>
  <lastmod>2026-05-23T17:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン多対象追跡のための時空間KSVD辞書学習（Spatiotemporal KSVD Dictionary Learning for Online Multi-target Tracking）</news:title>
   <news:publication_date>2026-05-23T17:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693468</loc>
  <lastmod>2026-05-23T16:33:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的経路積分オートエンコーダによる表現学習と計画（Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems）</news:title>
   <news:publication_date>2026-05-23T16:33:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693466</loc>
  <lastmod>2026-05-23T16:32:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Siamese-LSTMによる3Dヒューマンアクション認識（3D Human Action Recognition with Siamese-LSTM Based Deep Metric Learning）</news:title>
   <news:publication_date>2026-05-23T16:32:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693464</loc>
  <lastmod>2026-05-23T16:32:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LHCにおける作用素の特定を学ぶ：t¯tb¯b最終状態の解析（Learning to pinpoint effective operators at the LHC: a study of the t¯tb¯b signature）</news:title>
   <news:publication_date>2026-05-23T16:32:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693462</loc>
  <lastmod>2026-05-23T16:32:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的遅延フィードバックを伴う線形バンディット（Linear Bandits with Stochastic Delayed Feedback）</news:title>
   <news:publication_date>2026-05-23T16:32:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693460</loc>
  <lastmod>2026-05-23T16:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による弱レンズシアー測定の革新（Weak-lensing shear measurement with machine learning）</news:title>
   <news:publication_date>2026-05-23T16:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693458</loc>
  <lastmod>2026-05-23T16:31:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在的な3次元キーポイントの発見とエンドツーエンド幾何推論（Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning）</news:title>
   <news:publication_date>2026-05-23T16:31:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693456</loc>
  <lastmod>2026-05-23T16:31:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子構造固有関数を用いたスケーラブルなガウス過程（Scalable Gaussian Processes with Grid-Structured Eigenfunctions）</news:title>
   <news:publication_date>2026-05-23T16:31:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693454</loc>
  <lastmod>2026-05-23T15:40:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる背景差分アルゴリズムを統合するCNNによる前景検出の改良（Combining Background Subtraction Algorithms with Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-23T15:40:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693452</loc>
  <lastmod>2026-05-23T15:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標志向トラジェクトリによる効率的探索（Goal-oriented Trajectories for Efficient Exploration）</news:title>
   <news:publication_date>2026-05-23T15:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693450</loc>
  <lastmod>2026-05-23T15:39:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経路積分の曲率が引き起こす影響を解く—平均場Matsubara力学による回転振動スペクトル解析（Mean-field Matsubara dynamics: analysis of path-integral curvature effects in rovibrational spectra）</news:title>
   <news:publication_date>2026-05-23T15:39:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693448</loc>
  <lastmod>2026-05-23T15:38:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーボン富化岩石型系外惑星の鉱物学と居住可能性の実験的解明（Mineralogy, structure and habitability of carbon-enriched rocky exoplanets: A laboratory approach）</news:title>
   <news:publication_date>2026-05-23T15:38:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693446</loc>
  <lastmod>2026-05-23T15:38:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河平面を貫く球状星団の軌道と崩壊の兆候（THE ORBIT OF THE NEW MILKY WAY GLOBULAR CLUSTER FSR1716 = VVV-GC05）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693444</loc>
  <lastmod>2026-05-23T15:38:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銅と二酸化ケイ素のための高精度機械学習力場の構築（Construction of accurate machine learning force fields for copper and silicon dioxide）</news:title>
   <news:publication_date>2026-05-23T15:38:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693442</loc>
  <lastmod>2026-05-23T15:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットによる同時等化と復号の提案（Joint Neural Network Equalizer and Decoder）</news:title>
   <news:publication_date>2026-05-23T15:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>
