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   <news:title>スマートビルディングにおける機械学習とビッグデータの活用（Leveraging Machine Learning and Big Data for Smart Buildings: A Comprehensive Survey）</news:title>
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   <news:title>分散メトロポリスサンプラーと最適並列性（Distributed Metropolis Sampler with Optimal Parallelism）</news:title>
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    <news:language>ja</news:language>
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   <news:title>SAS画像セグメンテーションにおける可能性主義的手法の比較（Comparison of Possibilistic Fuzzy Local Information C-Means and Possibilistic K-Nearest Neighbors for Synthetic Aperture Sonar Image Segmentation）</news:title>
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   <news:title>コードスタイル自動修正ツールの実務的意義（STYLE-ANALYZER: fixing code style inconsistencies with interpretable unsupervised algorithms）</news:title>
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   <news:title>略語の文脈解読を完全自動化する手法（Unsupervised Abbreviation Disambiguation）</news:title>
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   <news:title>ロボット視覚のための軽量マルチタスク指標の提案（The RGB-D Triathlon: Towards Agile Visual Toolboxes for Robots）</news:title>
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   <news:title>3D 深層学習の頑健性（Robustness of 3D Deep Learning in an Adversarial Setting）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>球面上のU-Netが脳表面解析を変える（Spherical U-Net on Cortical Surfaces: Methods and Applications）</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>超音波ブラインドスティックによる自立支援（Ultrasonic Blind Stick For Completely Blind People To Avoid Any Kind Of Obstacles）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>表面科学と触媒における原子スケール機械学習の実装（An Atomistic Machine Learning Package for Surface Science and Catalysis）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>Key.Netによる特徴点検出の再考（Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters）</news:title>
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   <news:title>中間特徴空間を制限することで実現する敵対的防御（Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>意義に応じた情報ボトルネックによるドメイン適応セマンティックセグメンテーション（Significance-aware Information Bottleneck for Domain Adaptive Semantic Segmentation）</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>敵対的残差粗視化（Adversarial-Residual-Coarse-Graining）</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>Tree Search Networkによるスパース回帰の革新（Tree Search Network for Sparse Regression）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:language>ja</news:language>
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   <news:title>フィルタの非線形集約による画像ノイズ除去の改善（Non-linear aggregation of filters to improve image denoising）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
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    <news:language>ja</news:language>
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   <news:title>機械学習を組み込む安全クリティカルシステムの工学的課題（Engineering problems in machine learning systems）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>DefectNetによる不均衡データ上の多クラス欠陥検出（DEFECTNET: MULTI-CLASS FAULT DETECTION ON HIGHLY-IMBALANCED DATASETS）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>密集領域における精密検出の手法（Precise Detection in Densely Packed Scenes）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>果物認識のための畳み込みニューラルネットワークによる分類器の実装（Implementation of Fruits Recognition Classifier using Convolutional Neural Network Algorithm）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>話者不均衡な音声コーパスを用いたマルチスピーカニューラル音声合成の学習 (Training Multi-Speaker Neural Text-to-Speech Systems using Speaker-Imbalanced Speech Corpora)</news:title>
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   <news:title>COCO TSによる実画像注釈生成で変わるシーンテキスト分割（COCO TS Dataset: Pixel–level Annotations Based on Weak Supervision for Scene Text Segmentation）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726776</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-24T15:39:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANをGANで学習する試み（GAN You Do the GAN GAN?）</news:title>
   <news:publication_date>2026-08-24T15:38:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726772</loc>
  <lastmod>2026-08-24T15:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テレコムにおける顧客解約予測（Customer churn prediction in telecom using machine learning in big data platform）</news:title>
   <news:publication_date>2026-08-24T15:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726770</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドと機械を組み合わせた多項目スクリーニング（Combining Crowd and Machines for Multi-predicate Item Screening）</news:title>
   <news:publication_date>2026-08-24T15:38:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726768</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JSIS3Dによる3D点群の意味・個体同時分割（JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds）</news:title>
   <news:publication_date>2026-08-24T15:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726766</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化多チャネルによる敵対的攻撃耐性の強化（Defending against adversarial attacks by randomized diversification）</news:title>
   <news:publication_date>2026-08-24T15:37:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726764</loc>
  <lastmod>2026-08-24T14:46:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム特徴の力と限界（On the Power and Limitations of Random Features for Understanding Neural Networks）</news:title>
   <news:publication_date>2026-08-24T14:46:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726762</loc>
  <lastmod>2026-08-24T14:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工衛星画像における建造物計数の深層学習と注意重み付け（DEEP BUILT-STRUCTURE COUNTING IN SATELLITE IMAGERY USING ATTENTION BASED RE-WEIGHTING）</news:title>
   <news:publication_date>2026-08-24T14:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726760</loc>
  <lastmod>2026-08-24T14:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一屋外画像からのエンドツーエンドタイムラプス生成（End-to-End Time-Lapse Video Synthesis from a Single Outdoor Image）</news:title>
   <news:publication_date>2026-08-24T14:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726758</loc>
  <lastmod>2026-08-24T14:25:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチホップ知識経路で人間の欲求を解き明かす（Ranking and Selecting Multi-Hop Knowledge Paths to Better Predict Human Needs）</news:title>
   <news:publication_date>2026-08-24T14:25:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726756</loc>
  <lastmod>2026-08-24T14:25:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内容重み付け深層画像圧縮（Learning Content-Weighted Deep Image Compression）</news:title>
   <news:publication_date>2026-08-24T14:25:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726754</loc>
  <lastmod>2026-08-24T14:24:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Learn2MACによるURLLC向けオンライン学習型多元接続（Learn2MAC: Online Learning Multiple Access for URLLC Applications）</news:title>
   <news:publication_date>2026-08-24T14:24:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726752</loc>
  <lastmod>2026-08-24T14:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化を使った確率モデル推論の頑健化（Robust Optimisation Monte Carlo）</news:title>
   <news:publication_date>2026-08-24T14:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726750</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726748</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床時系列解析における転移学習の実践的示唆（Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-24T13:33:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726746</loc>
  <lastmod>2026-08-24T13:33:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模交通標識検出・認識のための深層学習（Deep Learning for Large-Scale Traffic-Sign Detection and Recognition）</news:title>
   <news:publication_date>2026-08-24T13:33:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726744</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー生成コンテンツにおける音楽エンティティ認識 (Recognizing Musical Entities in User-generated Content)</news:title>
   <news:publication_date>2026-08-24T13:32:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726742</loc>
  <lastmod>2026-08-24T13:32:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制御可能な特徴空間による画像復元（CFSNet: Toward a Controllable Feature Space for Image Restoration）</news:title>
   <news:publication_date>2026-08-24T13:32:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726740</loc>
  <lastmod>2026-08-24T13:32:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726738</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像の反射（リフレクション）除去におけるミスアライメント学習とネットワーク強化（Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726736</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-24T12:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726734</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間時間メモリネットワークによる動画物体セグメンテーション（Video Object Segmentation using Space-Time Memory Networks）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726732</loc>
  <lastmod>2026-08-24T12:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個々のユニットが果たす相対的寄与の可視化（Relative Attributing Propagation）</news:title>
   <news:publication_date>2026-08-24T12:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726730</loc>
  <lastmod>2026-08-24T12:28:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResUNet-aによる高解像度空中画像の意味セグメンテーション（ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data）</news:title>
   <news:publication_date>2026-08-24T12:28:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726728</loc>
  <lastmod>2026-08-24T12:28:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模エネルギー収穫ネットワークの分散電力制御（Distributed Power Control for Large Energy Harvesting Networks: A Multi-Agent Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-08-24T12:28:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726726</loc>
  <lastmod>2026-08-24T12:28:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組合せ埋め込みネットワークによる深層グラフマッチングの学習（Learning Combinatorial Embedding Networks for Deep Graph Matching）</news:title>
   <news:publication_date>2026-08-24T12:28:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726724</loc>
  <lastmod>2026-08-24T12:27:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-24T12:27:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726722</loc>
  <lastmod>2026-08-24T11:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adaptive Bayesian Linear Regression for Automated Machine Learning（Adaptive Bayesian Linear Regression for Automated Machine Learning）</news:title>
   <news:publication_date>2026-08-24T11:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726720</loc>
  <lastmod>2026-08-24T11:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-24T11:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726718</loc>
  <lastmod>2026-08-24T11:34:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡な産業時系列に対するGANベースの故障診断手法（A Novel GAN-based Fault Diagnosis Approach for Imbalanced Industrial Time Series）</news:title>
   <news:publication_date>2026-08-24T11:34:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726716</loc>
  <lastmod>2026-08-24T11:34:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期会話における発話行為認識の階層構造モデルの適応（Adaptation of Hierarchical Structured Models for Speech Act Recognition in Asynchronous Conversation）</news:title>
   <news:publication_date>2026-08-24T11:34:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726714</loc>
  <lastmod>2026-08-24T11:34:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数ソースの弱教師付き学習による注目領域検出（Multi-source weak supervision for saliency detection）</news:title>
   <news:publication_date>2026-08-24T11:34:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726712</loc>
  <lastmod>2026-08-24T11:33:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ハイパースペクトル画像の深層クラスタリングとクラス内距離制約（Deep Clustering With Intra-class Distance Constraint for Hyperspectral Images）</news:title>
   <news:publication_date>2026-08-24T11:33:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726710</loc>
  <lastmod>2026-08-24T11:32:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー疎再構成同調埋め込みによる次元削減（Co-regularized Multi-view Sparse Reconstruction Embedding for Dimension Reduction）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セグメンテーション協調による弱教師付き物体検出（Weakly Supervised Object Detection with Segmentation Collaboration）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>階層型自己符号化器による階層的画像圧縮（Layered Image Compression using Scalable Auto-encoder）</news:title>
   <news:publication_date>2026-08-24T10:29:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726704</loc>
  <lastmod>2026-08-24T10:17:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全データに対する差分位相コントラストCTの深層学習再構成フレームワーク（A Deep Learning Reconstruction Framework for Differential Phase-Contrast Computed Tomography with Incomplete Data）</news:title>
   <news:publication_date>2026-08-24T10:17:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726702</loc>
  <lastmod>2026-08-24T10:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的な人物再識別における可視性認識型部位特徴学習（Perceive Where to Focus: Learning Visibility-aware Part-level Features for Partial Person Re-identiﬁcation）</news:title>
   <news:publication_date>2026-08-24T10:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726700</loc>
  <lastmod>2026-08-24T10:17:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュースメディアの信頼性と政治的イデオロギーを同時に推定する手法（Multi-Task Ordinal Regression for Jointly Predicting the Trustworthiness and the Leading Political Ideology of News Media）</news:title>
   <news:publication_date>2026-08-24T10:17:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/726698</loc>
  <lastmod>2026-08-24T10:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を切り分ける無監督異常検知（Unsupervised Contextual Anomaly Detection using Joint Deep Variational Generative Models）</news:title>
   <news:publication_date>2026-08-24T10:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-24T09:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界単一画像超解像の新基準と新モデル（Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model）</news:title>
   <news:publication_date>2026-08-24T09:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726694</loc>
  <lastmod>2026-08-24T09:24:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間アンサンブル学習と予測不確実性の校正（Adaptive Ensemble Learning of Spatiotemporal Processes with Calibrated Predictive Uncertainty）</news:title>
   <news:publication_date>2026-08-24T09:24:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726692</loc>
  <lastmod>2026-08-24T09:24:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期マニータスキングランタイムの比較研究（A Comparative Study of Asynchronous Many–Tasking Runtimes: Cilk, Charm++, ParalleX and AM++）</news:title>
   <news:publication_date>2026-08-24T09:24:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726690</loc>
  <lastmod>2026-08-24T09:24:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二相流レジーム予測に向けたLSTMベース深層再帰型ニューラルネットワーク（Two-phase flow regime prediction using LSTM based deep recurrent neural network）</news:title>
   <news:publication_date>2026-08-24T09:24:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726688</loc>
  <lastmod>2026-08-24T09:23:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野菜切断タスクの意味的埋め込み空間の学習（Learning Semantic Embedding Spaces for Slicing Vegetables）</news:title>
   <news:publication_date>2026-08-24T09:23:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726686</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続イベント列の要約と系列エピソードの統計モデル（Summarizing Event Sequences with Serial Episodes: A Statistical Model and an Application）</news:title>
   <news:publication_date>2026-08-24T09:23:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726684</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形文脈バンディットにおけるほぼ最小最大レグレット（Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits）</news:title>
   <news:publication_date>2026-08-24T08:32:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726682</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半透明水彩顔料混色の予測モデル（PREDICTION MODEL FOR SEMITRANSPARENT WATERCOLOR PIGMENT MIXTURES USING DEEP LEARNING WITH A DATASET OF TRANSMITTANCE AND REFLECTANCE）</news:title>
   <news:publication_date>2026-08-24T08:25:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726680</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WiFiで人体を「見る」技術の衝撃（Person-in-WiFi: Fine-grained Person Perception using WiFi）</news:title>
   <news:publication_date>2026-08-24T08:25:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726678</loc>
  <lastmod>2026-08-24T08:25:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーツ単位で生成するGANの設計と意義（COCO-GAN: Generation by Parts via Conditional Coordinating）</news:title>
   <news:publication_date>2026-08-24T08:25:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726676</loc>
  <lastmod>2026-08-24T08:23:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似ダイナミクスをもつロボット間の知識転移による高精度即興軌道追従 (Knowledge Transfer Between Robots with Similar Dynamics for High-Accuracy Impromptu Trajectory Tracking)</news:title>
   <news:publication_date>2026-08-24T08:23:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726674</loc>
  <lastmod>2026-08-24T08:23:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境との相互作用が不可欠である分離表現学習の再定義（Symmetry-Based Disentangled Representation Learning requires Interaction with Environments）</news:title>
   <news:publication_date>2026-08-24T08:23:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726672</loc>
  <lastmod>2026-08-24T08:23:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイアス制御を組み込んだ敵対的学習による人物再識別の改良（Person Re-identification with Bias-controlled Adversarial Training）</news:title>
   <news:publication_date>2026-08-24T08:23:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726670</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>署名認証を一変させるSiamese-CNN手法（OSVNet: Convolutional Siamese Network for Writer Independent Online Signature Verification）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726668</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ルール制約付き深層強化学習によるレーンチェンジ意思決定（Lane Change Decision-making through Deep Reinforcement Learning with Rule-based Constraints）</news:title>
   <news:publication_date>2026-08-24T07:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726666</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MortonNetによる点群の自己教師あり局所特徴学習（MortonNet: Self-Supervised Learning of Local Features in 3D Point Clouds）</news:title>
   <news:publication_date>2026-08-24T07:30:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726664</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平滑スプラインと条件付きガウスグラフィカルモデルを組み合わせた半パラメトリック密度推定（Combining Smoothing Spline with Conditional Gaussian Graphical Model for Density and Graph Estimation）</news:title>
   <news:publication_date>2026-08-24T07:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726662</loc>
  <lastmod>2026-08-24T07:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒト視覚に着想を得た注意機構で知覚重視型超解像の損失指標を改善する（A HVS-inspired Attention to Improve Loss Metrics for CNN-based Perception-Oriented Super-Resolution）</news:title>
   <news:publication_date>2026-08-24T07:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726660</loc>
  <lastmod>2026-08-24T07:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電圧品質時系列分類における畳み込みニューラルネットワーク（Voltage Quality Time Series Classification using Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-24T07:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726658</loc>
  <lastmod>2026-08-24T07:29:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしで安定な3Dキーポイントを学習する手法の要点（USIP: Unsupervised Stable Interest Point Detection from 3D Point Clouds）</news:title>
   <news:publication_date>2026-08-24T07:29:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726656</loc>
  <lastmod>2026-08-24T06:38:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データの非パラメトリック密度推定（Nonparametric Density Estimation for High-Dimensional Data – Algorithms and Applications）</news:title>
   <news:publication_date>2026-08-24T06:38:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726654</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界に着目したマルチフォーカス画像合成（BOUNDARY AWARE MULTI-FOCUS IMAGE FUSION USING DEEP NEURAL NETWORK）</news:title>
   <news:publication_date>2026-08-24T06:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726652</loc>
  <lastmod>2026-08-24T06:37:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SIFT記述子を用いた回転不変な畳み込みニューラルネットワーク（Exploiting SIFT Descriptor for Rotation Invariant Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-24T06:37:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726650</loc>
  <lastmod>2026-08-24T06:37:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を考慮する機械翻訳（Machine translation considering context information using Encoder-Decoder model）</news:title>
   <news:publication_date>2026-08-24T06:37:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726648</loc>
  <lastmod>2026-08-24T06:37:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的特徴空間の適応的調整によるゼロショット認識の改善（ADAPTIVE ADJUSTMENT WITH SEMANTIC FEATURE SPACE FOR ZERO-SHOT RECOGNITION）</news:title>
   <news:publication_date>2026-08-24T06:37:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726646</loc>
  <lastmod>2026-08-24T06:36:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EE-AEによる排他性強化型自己符号化器（EE-AE: Exclusivity Enhanced Autoencoder）</news:title>
   <news:publication_date>2026-08-24T06:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726644</loc>
  <lastmod>2026-08-24T06:36:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定常時系列の非パラメトリック漸近解析（Asymptotic nonparametric statistical analysis of stationary time series）</news:title>
   <news:publication_date>2026-08-24T06:36:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726642</loc>
  <lastmod>2026-08-24T05:45:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続的年齢解析の普遍的変分フレームワーク（UVA: A Universal Variational Framework for Continuous Age Analysis）</news:title>
   <news:publication_date>2026-08-24T05:45:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726640</loc>
  <lastmod>2026-08-24T05:44:53Z</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>2026-08-24T05:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-24T05:44:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-24T05:44:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-24T05:44:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話の文脈を用いた感情検出手法の提案（ANA at SemEval-2019 Task 3: Contextual Emotion detection in Conversations through hierarchical LSTMs and BERT）</news:title>
   <news:publication_date>2026-08-24T05:44:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726634</loc>
  <lastmod>2026-08-24T05:44:14Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-24T05:44:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726632</loc>
  <lastmod>2026-08-24T05:44:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習と多次元表現による不整脈検出（On Arrhythmia Detection by Deep Learning and Multidimensional Representation）</news:title>
   <news:publication_date>2026-08-24T05:44:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726630</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層ネットワークのコミュニティ検出における階層的確率的ブロックモデル（Hierarchical stochastic block model for community detection in multiplex networks）</news:title>
   <news:publication_date>2026-08-24T05:43:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726628</loc>
  <lastmod>2026-08-24T04:52:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>座標と支配方程式のデータ駆動発見（Data-driven discovery of coordinates and governing equations）</news:title>
   <news:publication_date>2026-08-24T04:52:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726626</loc>
  <lastmod>2026-08-24T04:51:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽フレア前兆の同定：SDO/HMI画像とSHARPパラメータの時系列解析 (Identifying Solar Flare Precursors Using Time Series of SDO/HMI Images and SHARP Parameters)</news:title>
   <news:publication_date>2026-08-24T04:51:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726624</loc>
  <lastmod>2026-08-24T04:51:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形構造系における入力・状態の同時推定を可能にするGPLFM（A Gaussian Process Latent Force Model for Joint Input-State Estimation in Linear Structural Systems）</news:title>
   <news:publication_date>2026-08-24T04:51:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726622</loc>
  <lastmod>2026-08-24T04:51:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小限監視の構造化学習によるニューラル関係抽出（Structured Minimally Supervised Learning for Neural Relation Extraction）</news:title>
   <news:publication_date>2026-08-24T04:51:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726620</loc>
  <lastmod>2026-08-24T04:51:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動学習に基づくモデル予測制御の合成（Synthesis of model predictive control based on data-driven learning）</news:title>
   <news:publication_date>2026-08-24T04:51:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726618</loc>
  <lastmod>2026-08-24T04:51:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>システムレベル視点からのスケーラブルでロバストな適応制御（Scalable Robust Adaptive Control from the System Level Perspective）</news:title>
   <news:publication_date>2026-08-24T04:51:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726616</loc>
  <lastmod>2026-08-24T04:50:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キーフレーズ生成を要約問題として再考する（Keyphrase Generation: A Text Summarization Struggle）</news:title>
   <news:publication_date>2026-08-24T04:50:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726614</loc>
  <lastmod>2026-08-24T04:00:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ増幅による統一的性質推定法（Data Amplification: A Unified and Competitive Approach to Property Estimation）</news:title>
   <news:publication_date>2026-08-24T04:00:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726612</loc>
  <lastmod>2026-08-24T03:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子核質量の統計的学習可能性（Statistical learnability of nuclear masses）</news:title>
   <news:publication_date>2026-08-24T03:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726610</loc>
  <lastmod>2026-08-24T03:59:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未対応点群の実スキャン補完を可能にした手法（Unpaired Point Cloud Completion on Real Scans Using Adversarial Training）</news:title>
   <news:publication_date>2026-08-24T03:59:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726608</loc>
  <lastmod>2026-08-24T03:59:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GraSPyによるグラフ統計ライブラリ（GraSPy: Graph Statistics in Python）</news:title>
   <news:publication_date>2026-08-24T03:59:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726606</loc>
  <lastmod>2026-08-24T03:59:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮説検定によるブラックボックスモデルの解釈（Interpreting Black Box Models via Hypothesis Testing）</news:title>
   <news:publication_date>2026-08-24T03:59:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726604</loc>
  <lastmod>2026-08-24T03:58:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SE2Net: エッジ強調による顕著物体検出の改良（SE2Net: Siamese Edge-Enhancement Network for Salient Object Detection）</news:title>
   <news:publication_date>2026-08-24T03:58:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726602</loc>
  <lastmod>2026-08-24T03:58:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張ディスク銀河探索（The Extended Disk Galaxy Exploration Science Survey）</news:title>
   <news:publication_date>2026-08-24T03:58:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726600</loc>
  <lastmod>2026-08-24T03:06:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子生成対向ネットワークによる確率分布の学習とロード（Quantum Generative Adversarial Networks for Learning and Loading Random Distributions）</news:title>
   <news:publication_date>2026-08-24T03:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726598</loc>
  <lastmod>2026-08-24T03:06:05Z</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高速道路自動運転の実用性（Autonomous Highway Driving using Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-24T03:06:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726596</loc>
  <lastmod>2026-08-24T03:05:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NetKet: 多体系量子系のための機械学習ツールキット (NetKet: A Machine Learning Toolkit for Many-Body Quantum Systems)</news:title>
   <news:publication_date>2026-08-24T03:05:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726594</loc>
  <lastmod>2026-08-24T03:05:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子–イオン衝突器が拓く核内パートン分布の精密化（Nuclear Parton Distributions from Lepton-Nucleus Scattering and the Impact of an Electron-Ion Collider）</news:title>
   <news:publication_date>2026-08-24T03:05:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726592</loc>
  <lastmod>2026-08-24T03:04:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>早期時系列分類のためのRAPID（RAPID: Real-time Automated Photometric IDentification）</news:title>
   <news:publication_date>2026-08-24T03:04:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726590</loc>
  <lastmod>2026-08-24T03:04:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ミニバッチでの高速学習と精度維持の両立（Yet Another Accelerated SGD: ResNet-50 Training on ImageNet in 74.7 seconds）</news:title>
   <news:publication_date>2026-08-24T03:04:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726588</loc>
  <lastmod>2026-08-24T03:03:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野生データによる破局的忘却の克服（Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild）</news:title>
   <news:publication_date>2026-08-24T03:03:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726586</loc>
  <lastmod>2026-08-24T02:12:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>甲状腺細胞診の全スライド画像から悪性度を予測する手法（Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images）</news:title>
   <news:publication_date>2026-08-24T02:12:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726584</loc>
  <lastmod>2026-08-24T02:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マクスウェルの悪魔の資源理論（A resource theory of Maxwell’s demons）</news:title>
   <news:publication_date>2026-08-24T02:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726582</loc>
  <lastmod>2026-08-24T02:11:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味知識を取り込んだゼロショットテキスト分類（Integrating Semantic Knowledge to Tackle Zero-shot Text Classification）</news:title>
   <news:publication_date>2026-08-24T02:11:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726580</loc>
  <lastmod>2026-08-24T02:09:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語に依存しないソースコード要約のための畳み込みニューラルネットワーク（A Convolutional Neural Network for Language-Agnostic Source Code Summarization）</news:title>
   <news:publication_date>2026-08-24T02:09:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726578</loc>
  <lastmod>2026-08-24T02:09:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子核における短距離相関のAb initio評価（Ab initio short-range-correlation scaling factors from light to medium-mass nuclei）</news:title>
   <news:publication_date>2026-08-24T02:09:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726576</loc>
  <lastmod>2026-08-24T02:09:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラスロジスティック回帰ネットワークの収束証明（A Proof of Convergence of Multi-Class Logistic Regression Network）</news:title>
   <news:publication_date>2026-08-24T02:09:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726574</loc>
  <lastmod>2026-08-24T02:09:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔軟フィラメントの懸濁手法（Methods for suspensions of passive and active filaments）</news:title>
   <news:publication_date>2026-08-24T02:09:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726572</loc>
  <lastmod>2026-08-24T01:17:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ構造を活かす局所活性化関数の設計（Invariance-Preserving Localized Activation Functions for Graph Neural Networks）</news:title>
   <news:publication_date>2026-08-24T01:17:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726570</loc>
  <lastmod>2026-08-24T01:09:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偽陽性制御ラッソ（The False Positive Control Lasso）</news:title>
   <news:publication_date>2026-08-24T01:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726568</loc>
  <lastmod>2026-08-24T01:09:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極めて遠方の銀河で制約するダークマターモデル（Constraining Dark Matter models with extremely distant galaxies）</news:title>
   <news:publication_date>2026-08-24T01:09:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726566</loc>
  <lastmod>2026-08-24T01:08:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-24T01:08:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-24T01:07:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的堅牢性とモデル圧縮を両立する道（Adversarial Robustness vs. Model Compression, or Both?）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726562</loc>
  <lastmod>2026-08-24T01:07:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>論理プログラムによる関係表現学習（Learning Relational Representations with Auto-encoding Logic Programs）</news:title>
   <news:publication_date>2026-08-24T01:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726560</loc>
  <lastmod>2026-08-24T01:07:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前処理を減らし現場データで強くなる前進：T2強調MRIにおける前立腺領域分割のクロスデータセット評価（CNN-based Prostate Zonal Segmentation on T2-weighted MR Images: A Cross-dataset Study）</news:title>
   <news:publication_date>2026-08-24T01:07:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726558</loc>
  <lastmod>2026-08-24T00:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感覚データの確率的予測と生成的敵対ネットワーク（Probabilistic Forecasting of Sensory Data with Generative Adversarial Networks – ForGAN）</news:title>
   <news:publication_date>2026-08-24T00:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726556</loc>
  <lastmod>2026-08-24T00:15:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデータでより学ぶ：GANベースの医療画像拡張（Learning More with Less: GAN-based Medical Image Augmentation）</news:title>
   <news:publication_date>2026-08-24T00:15:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726554</loc>
  <lastmod>2026-08-24T00:14:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一ビットADCs環境下のMIMO受信での頑健なデータ検出（Robust Data Detection for MIMO Systems with One-Bit ADCs: A Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-08-24T00:14:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726552</loc>
  <lastmod>2026-08-24T00:14:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意のぼかしカーネルに対応する深層プラグアンドプレイス超解像（Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels）</news:title>
   <news:publication_date>2026-08-24T00:14:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726550</loc>
  <lastmod>2026-08-24T00:14:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック語の再ランク付けによる解釈性向上（Re-Ranking Words to Improve Interpretability of Automatically Generated Topics）</news:title>
   <news:publication_date>2026-08-24T00:14:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726548</loc>
  <lastmod>2026-08-24T00:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>静電容量式心電図の雑音除去のための深層ニューラルネットワーク（Deep Network for Capacitive ECG Denoising）</news:title>
   <news:publication_date>2026-08-24T00:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726546</loc>
  <lastmod>2026-08-24T00:13:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層残差ネットワークに対する証明可能な防御（A Provable Defense for Deep Residual Networks）</news:title>
   <news:publication_date>2026-08-24T00:13:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726544</loc>
  <lastmod>2026-08-23T23:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳を模した深層再帰強化学習による模擬自動運転エージェント（Towards Brain-inspired System: Deep Recurrent Reinforcement Learning for Simulated Self-driving Agent）</news:title>
   <news:publication_date>2026-08-23T23:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726542</loc>
  <lastmod>2026-08-23T23:22:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGA内蔵ECCによるアンダーボルティング障害の緩和評価（Evaluating Built-in ECC of FPGA on-chip Memories for the Mitigation of Undervolting Faults）</news:title>
   <news:publication_date>2026-08-23T23:22:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726540</loc>
  <lastmod>2026-08-23T23:22:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反射材を含む合成画像での物体検出器の学習（Training Object Detectors on Synthetic Images Containing Reflecting Materials）</news:title>
   <news:publication_date>2026-08-23T23:22:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726538</loc>
  <lastmod>2026-08-23T23:21:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>被験者横断の転移学習による人体行動認識（Cross-Subject Transfer Learning in Human Activity Recognition Systems using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-23T23:21:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726536</loc>
  <lastmod>2026-08-23T23:21:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称深層意味量子化による画像検索（Asymmetric Deep Semantic Quantization for Image Retrieval）</news:title>
   <news:publication_date>2026-08-23T23:21:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726534</loc>
  <lastmod>2026-08-23T23:21:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLとシステム研究の新境地（MLSys: The New Frontier of Machine Learning Systems）</news:title>
   <news:publication_date>2026-08-23T23:21:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726532</loc>
  <lastmod>2026-08-23T23:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的アプローチによる前方モデル学習：ライフゲームでの成果（A Local Approach to Forward Model Learning: Results on the Game of Life Game）</news:title>
   <news:publication_date>2026-08-23T23:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726530</loc>
  <lastmod>2026-08-23T22:28:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レーダー測定に基づく深層空間一貫占有地図（Deep, spatially coherent Occupancy Maps based on Radar Measurements）</news:title>
   <news:publication_date>2026-08-23T22:28:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726528</loc>
  <lastmod>2026-08-23T22:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市場操作をセキュリティ問題として捉える（Market Manipulation as a Security Problem）</news:title>
   <news:publication_date>2026-08-23T22:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726526</loc>
  <lastmod>2026-08-23T22:28:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン多目的回帰決定木と積み重ねリーフモデル（Online Multi-target regression trees with stacked leaf models）</news:title>
   <news:publication_date>2026-08-23T22:28:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726524</loc>
  <lastmod>2026-08-23T22:27:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かさを扱う証拠理論的深層逆センサモデル（Deep, spatially coherent Inverse Sensor Models with Uncertainty Incorporation using the evidential Framework）</news:title>
   <news:publication_date>2026-08-23T22:27:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726522</loc>
  <lastmod>2026-08-23T22:27:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的変分から決定的オートエンコーダへ（From Variational to Deterministic Autoencoders）</news:title>
   <news:publication_date>2026-08-23T22:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726520</loc>
  <lastmod>2026-08-23T22:27:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BaTiO3における強誘電体間転移の中間スケール起源（Mesoscopic Origin of Ferroelectric-Ferroelectric Transition in BaTiO3）</news:title>
   <news:publication_date>2026-08-23T22:27:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726518</loc>
  <lastmod>2026-08-23T22:26:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>登場人物の感情関係を機械に学習させる方法（Learning to Classify Emotional Relationships of Fictional Characters）</news:title>
   <news:publication_date>2026-08-23T22:26:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726516</loc>
  <lastmod>2026-08-23T21:35:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合分布を用いたオンライン分散削減（Online Variance Reduction with Mixtures）</news:title>
   <news:publication_date>2026-08-23T21:35:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726514</loc>
  <lastmod>2026-08-23T21:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声からの感情予測に対する注意機構付きエンドツーエンド多重課題学習（ATTENTION-AUGMENTED END-TO-END MULTI-TASK LEARNING FOR EMOTION PREDICTION FROM SPEECH）</news:title>
   <news:publication_date>2026-08-23T21:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726512</loc>
  <lastmod>2026-08-23T21:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分微分方程式に基づく家畜データ同化のための統計学習ツール（An innovative Statistical Learning Tool based on Partial Differential Equations for livestock Data Assimilation）</news:title>
   <news:publication_date>2026-08-23T21:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726510</loc>
  <lastmod>2026-08-23T21:25:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バグ報告の重複検出とクラスタリングを同時に学習する手法（Train One Get One Free: Partially Supervised Neural Network for Bug Report Duplicate Detection and Clustering）</news:title>
   <news:publication_date>2026-08-23T21:25:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726508</loc>
  <lastmod>2026-08-23T21:24:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フェルミラブの高速サイクロトロン導入による2.4MW化の設計（Rapid-Cycling Synchrotron for Multi-Megawatt Proton Facility at Fermilab）</news:title>
   <news:publication_date>2026-08-23T21:24:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726506</loc>
  <lastmod>2026-08-23T21:24:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Snore-GANsによるいびき音分類のための合成データ増強（Snore-GANs: Improving Automatic Snore Sound Classification with Synthesized Data）</news:title>
   <news:publication_date>2026-08-23T21:24:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726504</loc>
  <lastmod>2026-08-23T21:24:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MCTSに基づく自動交渉エージェント（MCTS-based Automated Negotiation Agent）</news:title>
   <news:publication_date>2026-08-23T21:24:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726502</loc>
  <lastmod>2026-08-23T20:33:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト読み上げと声質変換の統合学習（Joint training framework for text-to-speech and voice conversion using multi-source Tacotron and WaveNet）</news:title>
   <news:publication_date>2026-08-23T20:33:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726500</loc>
  <lastmod>2026-08-23T20:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前知識を組み込む「Informed Machine Learning」の体系化（Informed Machine Learning – A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems）</news:title>
   <news:publication_date>2026-08-23T20:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726498</loc>
  <lastmod>2026-08-23T20:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少量学習を用いた深層敵対的学習による動画ベース人物再識別（Few-Shot Deep Adversarial Learning for Video-based Person Re-identification）</news:title>
   <news:publication_date>2026-08-23T20:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726496</loc>
  <lastmod>2026-08-23T20:23:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル損失を用いたニューラル音声波形モデルの訓練（Training a Neural Speech Waveform Model using Spectral Losses of Short-Time Fourier Transform and Continuous Wavelet Transform）</news:title>
   <news:publication_date>2026-08-23T20:23:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726494</loc>
  <lastmod>2026-08-23T20:22:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度情報で手と物体を分離する実時間手法（DenseAttentionSeg: Segment Hands from Interacted Objects Using Depth Input）</news:title>
   <news:publication_date>2026-08-23T20:22:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726492</loc>
  <lastmod>2026-08-23T20:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUを用いた深層表現の分解と領域性（Deep Representation with ReLU Neural Networks）</news:title>
   <news:publication_date>2026-08-23T20:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726490</loc>
  <lastmod>2026-08-23T20:22:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MCMCベースの最尤学習によるエネルギーベースモデルの解剖（On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models）</news:title>
   <news:publication_date>2026-08-23T20:22:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726488</loc>
  <lastmod>2026-08-23T19:30:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの4Dスパシオ・アングラー一貫ライトフィールド合成（Synthesizing a 4D Spatio-Angular Consistent Light Field from a Single Image）</news:title>
   <news:publication_date>2026-08-23T19:30:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726486</loc>
  <lastmod>2026-08-23T19:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化入力とモジュール化による学習改善（Using Structured Input and Modularity for Improved Learning）</news:title>
   <news:publication_date>2026-08-23T19:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726484</loc>
  <lastmod>2026-08-23T19:30:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書からのキー情報抽出を高速にするCUTIE（CUTIE: Learning to Understand Documents with Convolutional Universal Text Information Extractor）</news:title>
   <news:publication_date>2026-08-23T19:30:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726482</loc>
  <lastmod>2026-08-23T19:29:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボル表現を学習させたニューラルネットの組合せ的汎化（Training neural networks to encode symbols enables combinatorial generalization）</news:title>
   <news:publication_date>2026-08-23T19:29:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726480</loc>
  <lastmod>2026-08-23T19:29:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FOFE-netによる知識ベース問答の簡潔かつ効果的な枠組み（A General FOFE-net Framework for Simple and Effective Question Answering over Knowledge Bases）</news:title>
   <news:publication_date>2026-08-23T19:29:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726478</loc>
  <lastmod>2026-08-23T19:29:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Local Aggregationによる視覚表現の教師なし学習（Local Aggregation for Unsupervised Learning of Visual Embeddings）</news:title>
   <news:publication_date>2026-08-23T19:29:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726476</loc>
  <lastmod>2026-08-23T19:28:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークへの方位情報付与（Lending Orientation to Neural Networks for Cross-view Geo-localization）</news:title>
   <news:publication_date>2026-08-23T19:28:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726474</loc>
  <lastmod>2026-08-23T18:37:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン専門家を対象としたユーザー中心設計による科学可視化研究（A User-centered Design Study in Scientific Visualization Targeting Domain Experts）</news:title>
   <news:publication_date>2026-08-23T18:37:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726472</loc>
  <lastmod>2026-08-23T18:37:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>食事ごとの血糖値予測の困難性（The Challenge of Predicting Meal-to-meal Blood Glucose Concentrations for Patients with Type I Diabetes）</news:title>
   <news:publication_date>2026-08-23T18:37:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726470</loc>
  <lastmod>2026-08-23T18:36:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度航空画像からの建物抽出を効率化するネットワーク（ESFNet: Efficient Network for Building Extraction from High-Resolution Aerial Images）</news:title>
   <news:publication_date>2026-08-23T18:36:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726468</loc>
  <lastmod>2026-08-23T18:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図を使った生体認証のための機械学習フレームワーク（A Machine Learning Framework for Biometric Authentication using Electrocardiogram）</news:title>
   <news:publication_date>2026-08-23T18:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726466</loc>
  <lastmod>2026-08-23T18:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量MRIとCNNによる前立腺病変分類の深堀り（A Deep Dive into Understanding Tumor Foci Classification using Multiparametric MRI Based on Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-23T18:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726464</loc>
  <lastmod>2026-08-23T18:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続的注意による良質な表現学習（Learning Good Representation via Continuous Attention）</news:title>
   <news:publication_date>2026-08-23T18:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726462</loc>
  <lastmod>2026-08-23T17:45:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メムトランジスタ交差配列を用いたメモリ内SVMフレームワーク（Neuromorphic In-Memory Computing Framework using Memtransistor Cross-bar based Support Vector Machines）</news:title>
   <news:publication_date>2026-08-23T17:45:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726460</loc>
  <lastmod>2026-08-23T17:44:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カリキュラムを用いた強化学習の改善（Improved Reinforcement Learning with Curriculum）</news:title>
   <news:publication_date>2026-08-23T17:44:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726458</loc>
  <lastmod>2026-08-23T17:44:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的ランジュバン法による対数凸密度からのサンプリング（Implicit Langevin Algorithms for Sampling From Log-concave Densities）</news:title>
   <news:publication_date>2026-08-23T17:44:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726456</loc>
  <lastmod>2026-08-23T17:43:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚質問応答の関係認識グラフ注意ネットワーク（Relation-Aware Graph Attention Network for Visual Question Answering）</news:title>
   <news:publication_date>2026-08-23T17:43:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726454</loc>
  <lastmod>2026-08-23T17:43:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一水中マイクロホンの多周波数振幅データによる深層学習源位定位（Deep-learning source localization using multi-frequency magnitude-only data）</news:title>
   <news:publication_date>2026-08-23T17:43:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726452</loc>
  <lastmod>2026-08-23T17:43:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>閉じチャネル分率の密度依存性の観測（Observation of the density dependence of the closed-channel fraction of a 6Li superfluid）</news:title>
   <news:publication_date>2026-08-23T17:43:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726450</loc>
  <lastmod>2026-08-23T17:43:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メッシュに基づく深層強化学習ポリシーの頑健性解析（Mesh-based Tools to Analyze Deep Reinforcement Learning Policies for Underactuated Biped Locomotion）</news:title>
   <news:publication_date>2026-08-23T17:43:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726448</loc>
  <lastmod>2026-08-23T16:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声に基づいた単語埋め込みによるA2W音声認識の改善（ACOUSTICALLY GROUNDED WORD EMBEDDINGS FOR IMPROVED ACOUSTICS-TO-WORD SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-08-23T16:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726446</loc>
  <lastmod>2026-08-23T16:51:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FrameNet: 単一RGB画像からの局所正準3Dフレーム推定（FrameNet: Learning Local Canonical Frames of 3D Surfaces from a Single RGB Image）</news:title>
   <news:publication_date>2026-08-23T16:51:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726444</loc>
  <lastmod>2026-08-23T16:51:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーパラメータ選択のコスト解析と実務的示唆（An analysis of the cost of hyper-parameter selection via split-sample validation, with applications to penalized regression）</news:title>
   <news:publication_date>2026-08-23T16:51:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726442</loc>
  <lastmod>2026-08-23T16:50:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超大規模グラフ埋め込みを可能にした仕組み（PyTorch‑BigGraph: A Large-scale Graph Embedding System）</news:title>
   <news:publication_date>2026-08-23T16:50:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726440</loc>
  <lastmod>2026-08-23T16:50:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意駆動型生成対抗ネットワークによる教師なし画像変換（Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation）</news:title>
   <news:publication_date>2026-08-23T16:50:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726438</loc>
  <lastmod>2026-08-23T16:50:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカル記述子に基づく画像対クラス距離の再考（Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning）</news:title>
   <news:publication_date>2026-08-23T16:50:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726436</loc>
  <lastmod>2026-08-23T16:50:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トーラス型オートエンコーダが示す潜在空間設計の新地平（Toroidal AutoEncoder）</news:title>
   <news:publication_date>2026-08-23T16:50:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726434</loc>
  <lastmod>2026-08-23T15:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像分類のための深層スパイキング畳み込みニューラルネットワーク（Deep Convolutional Spiking Neural Networks for Image Classification）</news:title>
   <news:publication_date>2026-08-23T15:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726432</loc>
  <lastmod>2026-08-23T15:58:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビット反転攻撃によるニューラルネット破壊（Bit-Flip Attack: Crushing Neural Network with Progressive Bit Search）</news:title>
   <news:publication_date>2026-08-23T15:58:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726430</loc>
  <lastmod>2026-08-23T15:57:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的な汚損と摂動に対するニューラルネットワークの堅牢性ベンチマーク（BENCHMARKING NEURAL NETWORK ROBUSTNESS TO COMMON CORRUPTIONS AND PERTURBATIONS）</news:title>
   <news:publication_date>2026-08-23T15:57:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726428</loc>
  <lastmod>2026-08-23T15:56:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声から電気喉頭波形への変換における敵対的近似推論（Adversarial Approximate Inference for Speech to Electroglottograph Conversion）</news:title>
   <news:publication_date>2026-08-23T15:56:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726426</loc>
  <lastmod>2026-08-23T15:56:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DEEP-FRIによる検証信頼度の改善（DEEP-FRI: Sampling Outside the Box Improves Soundness）</news:title>
   <news:publication_date>2026-08-23T15:56:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726424</loc>
  <lastmod>2026-08-23T15:56:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>iGenによる構成可能ソフトウェアの動的相互作用推論（iGen: Dynamic Interaction Inference for Configurable Software）</news:title>
   <news:publication_date>2026-08-23T15:56:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726422</loc>
  <lastmod>2026-08-23T15:56:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙マイクロ波背景放射のバリオン密度推定と等方性解析（Baryon density extraction and isotropy analysis of Cosmic Microwave Background using Deep Learning）</news:title>
   <news:publication_date>2026-08-23T15:56:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726420</loc>
  <lastmod>2026-08-23T15:04:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォルムアルデヒド深遠探査（A Formaldehyde Deep Field）</news:title>
   <news:publication_date>2026-08-23T15:04:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726418</loc>
  <lastmod>2026-08-23T15:04:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的ドメイン適応のための事例転移学習（Learning to Transfer Examples for Partial Domain Adaptation）</news:title>
   <news:publication_date>2026-08-23T15:04:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726416</loc>
  <lastmod>2026-08-23T15:03:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳インターフェースの情報理論的特徴変換学習（Information Theoretic Feature Transformation Learning for Brain Interfaces）</news:title>
   <news:publication_date>2026-08-23T15:03:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726414</loc>
  <lastmod>2026-08-23T15:03:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バリオンで描く：深層生成モデルを用いたガスの付加によるN体シミュレーション拡張（Painting with baryons: augmenting N-body simulations with gas using deep generative models）</news:title>
   <news:publication_date>2026-08-23T15:03:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726412</loc>
  <lastmod>2026-08-23T15:03:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注釈点を活用した高精度カウント手法（Counting with Focus for Free）</news:title>
   <news:publication_date>2026-08-23T15:03:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726410</loc>
  <lastmod>2026-08-23T15:02:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D全脳セグメンテーションの空間局所化ネットワークタイル（Spatially Localized Atlas Network Tiles）</news:title>
   <news:publication_date>2026-08-23T15:02:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726408</loc>
  <lastmod>2026-08-23T15:02:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FaSTGANによる高速動画物体セグメンテーション（Fast video object segmentation with Spatio-Temporal GANs）</news:title>
   <news:publication_date>2026-08-23T15:02:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726406</loc>
  <lastmod>2026-08-23T14:11:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BERTからのタスク固有知識の蒸留（Distilling Task-Specific Knowledge from BERT into Simple Neural Networks）</news:title>
   <news:publication_date>2026-08-23T14:11:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726404</loc>
  <lastmod>2026-08-23T14:11:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮革の自動欠陥セグメンテーション（Automatic Defect Segmentation on Leather with Deep Learning）</news:title>
   <news:publication_date>2026-08-23T14:11:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726402</loc>
  <lastmod>2026-08-23T14:11:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IMAEによるノイズ耐性学習の再考 — MAEの重み分散がもたらす意味（IMAE FOR NOISE-ROBUST LEARNING: MEAN ABSO-LUTE ERROR DOES NOT TREAT EXAMPLES EQUALLY AND GRADIENT MAGNITUDE’S VARIANCE MATTERS）</news:title>
   <news:publication_date>2026-08-23T14:11:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726400</loc>
  <lastmod>2026-08-23T14:11:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地理統計学のための近傍ニューラルネットワーク（Nearest-Neighbor Neural Networks for Geostatistics）</news:title>
   <news:publication_date>2026-08-23T14:11:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726398</loc>
  <lastmod>2026-08-23T14:10:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在クラス分析でARDSのサブフェノタイプを見つけ、機械学習予測を改善する（Using Latent Class Analysis to Identify ARDS Sub-phenotypes for Enhanced Machine Learning Predictive Performance）</news:title>
   <news:publication_date>2026-08-23T14:10:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726396</loc>
  <lastmod>2026-08-23T14:10:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程回帰を用いた効率的なパラメータ再構成（Using Gaussian process regression for efficient parameter reconstruction）</news:title>
   <news:publication_date>2026-08-23T14:10:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726394</loc>
  <lastmod>2026-08-23T14:10:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多数タスク学習とタスクルーティング（Many Task Learning with Task Routing）</news:title>
   <news:publication_date>2026-08-23T14:10:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726392</loc>
  <lastmod>2026-08-23T13:19:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的機械学習による自動化された調査コーダーの構築（Building Automated Survey Coders via Interactive Machine Learning）</news:title>
   <news:publication_date>2026-08-23T13:19:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726390</loc>
  <lastmod>2026-08-23T13:19:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトホロウキャピラリにおける高エネルギー紫外線分散波放射（High-energy ultraviolet dispersive-wave emission in compact hollow capillary systems）</news:title>
   <news:publication_date>2026-08-23T13:19:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726388</loc>
  <lastmod>2026-08-23T13:18:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シグネチャベース侵入検知にベイズ的仮説形成を拡張する（Extending Signature-based Intrusion Detection Systems With Bayesian Abductive Reasoning）</news:title>
   <news:publication_date>2026-08-23T13:18:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726386</loc>
  <lastmod>2026-08-23T13:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB-D合成視点の参照なし品質評価指標GANs-NQM（GANs-NQM: A Generative Adversarial Networks based No Reference Quality Assessment Metric for RGB-D Synthesized Views）</news:title>
   <news:publication_date>2026-08-23T13:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726384</loc>
  <lastmod>2026-08-23T13:17:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲーティング機構を導入したDNN埋め込みによる話者認証の改良（Deep Neural Network Embeddings with Gating Mechanisms for Text-Independent Speaker Verification）</news:title>
   <news:publication_date>2026-08-23T13:17:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726382</loc>
  <lastmod>2026-08-23T13:17:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる音声コーパス間の感情認識を安定して一般化する手法（Barking up the Right Tree: Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG)）</news:title>
   <news:publication_date>2026-08-23T13:17:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726380</loc>
  <lastmod>2026-08-23T13:17:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による重み付け（Learning to Weight for Text Classification）</news:title>
   <news:publication_date>2026-08-23T13:17:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726378</loc>
  <lastmod>2026-08-23T12:24:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化された適応重要度サンプリングの収束率（Convergence rates for optimised adaptive importance samplers）</news:title>
   <news:publication_date>2026-08-23T12:24:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726376</loc>
  <lastmod>2026-08-23T12:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1.6 kb/sのリアルタイム広帯域ニューラルボコーダ（A Real-Time Wideband Neural Vocoder at 1.6 kb/s Using LPCNet）</news:title>
   <news:publication_date>2026-08-23T12:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726374</loc>
  <lastmod>2026-08-23T12:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次統計量を使ったマルチタスク学習によるx-vector音声話者認証（Multi-Task Learning with High-Order Statistics for X-vector based Text-Independent Speaker Verification）</news:title>
   <news:publication_date>2026-08-23T12:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726372</loc>
  <lastmod>2026-08-23T12:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造と属性を統合するネットワーク埋め込みの実務的示唆（Multimodal Deep Network Embedding with Integrated Structure and Attribute Information）</news:title>
   <news:publication_date>2026-08-23T12:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726370</loc>
  <lastmod>2026-08-23T12:22:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化データの学習可能関数を数える（Counting the learnable functions of structured data）</news:title>
   <news:publication_date>2026-08-23T12:22:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726368</loc>
  <lastmod>2026-08-23T12:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のように記述する：画像キャプション生成における多様性の重要性（Describing like Humans: on Diversity in Image Captioning）</news:title>
   <news:publication_date>2026-08-23T12:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726366</loc>
  <lastmod>2026-08-23T12:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラミング概念と構文パターンの対応付けによるコード検索の改善（Crowd Sourced Data Analysis: Mapping of Programming Concepts to Syntactical Patterns）</news:title>
   <news:publication_date>2026-08-23T12:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726364</loc>
  <lastmod>2026-08-23T11:31:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己学習データの誤ラベル対処による低資源系列ラベリングの堅牢学習（Handling Noisy Labels for Robustly Learning from Self-Training Data for Low-Resource Sequence Labeling）</news:title>
   <news:publication_date>2026-08-23T11:31:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726362</loc>
  <lastmod>2026-08-23T11:31:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>翻訳モデルの診断手法の提案（Train, Sort, Explain: Learning to Diagnose Translation Models）</news:title>
   <news:publication_date>2026-08-23T11:31:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726360</loc>
  <lastmod>2026-08-23T11:31:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空中マニピュレーション：逆運動学、同定、RIC制御と実装 (Inverse Kinematics, Identification, RIC-based Control, and implementation of an Aerial Manipulator)</news:title>
   <news:publication_date>2026-08-23T11:31:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726358</loc>
  <lastmod>2026-08-23T11:29:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希土類低減永久磁石の計算設計（Computational Design of the Rare-Earth Reduced Permanent Magnets）</news:title>
   <news:publication_date>2026-08-23T11:29:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726356</loc>
  <lastmod>2026-08-23T11:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル活性化関数による学習の安定性と一般化の解析（On the Stability and Generalization of Learning with Kernel Activation Functions）</news:title>
   <news:publication_date>2026-08-23T11:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726354</loc>
  <lastmod>2026-08-23T11:29:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経路最適化の正則化とデノイジングオートエンコーダ（Regularizing Trajectory Optimization with Denoising Autoencoders）</news:title>
   <news:publication_date>2026-08-23T11:29:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726352</loc>
  <lastmod>2026-08-23T11:29:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラボリック近似に基づくラインサーチによるDNN最適化（Parabolic Approximation Line Search for DNNs）</news:title>
   <news:publication_date>2026-08-23T11:29:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726350</loc>
  <lastmod>2026-08-23T10:37:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>五重クォークと四重クォーク状態（Pentaquark and Tetraquark states）</news:title>
   <news:publication_date>2026-08-23T10:37:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726348</loc>
  <lastmod>2026-08-23T10:36:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ構造を学習するGNNの枠組み（Learning Discrete Structures for Graph Neural Networks）</news:title>
   <news:publication_date>2026-08-23T10:36:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726346</loc>
  <lastmod>2026-08-23T10:36:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基底ユークリッドノルムの最適次数学習による全変動(LEARNING OPTIMAL ORDERS OF THE UNDERLYING EUCLIDEAN NORM IN TOTAL VARIATION IMAGE DENOISING)</news:title>
   <news:publication_date>2026-08-23T10:36:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726344</loc>
  <lastmod>2026-08-23T10:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層流体表面における進行重力波の厳密解（Exact solution for progressive gravity waves on the surface of a deep fluid）</news:title>
   <news:publication_date>2026-08-23T10:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726342</loc>
  <lastmod>2026-08-23T10:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結合ダイナミカルシステムにおける構造学習と動的因果モデリング（Structure Learning in Coupled Dynamical Systems and Dynamic Causal Modelling）</news:title>
   <news:publication_date>2026-08-23T10:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726340</loc>
  <lastmod>2026-08-23T10:35:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンバランスな感情分類における談話マーカーを使った強化（Imbalanced Sentiment Classification Enhanced with Discourse Marker）</news:title>
   <news:publication_date>2026-08-23T10:35:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726338</loc>
  <lastmod>2026-08-23T10:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電波銀河の形状分類における転移学習の応用（Transfer learning for radio galaxy classification）</news:title>
   <news:publication_date>2026-08-23T10:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726336</loc>
  <lastmod>2026-08-23T09:44:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポスト真実時代のフェイクニュース抑止に向けたブロックチェーンの応用（Using Blockchain to Rein in The New Post-Truth World and Check The Spread of Fake News）</news:title>
   <news:publication_date>2026-08-23T09:44:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726334</loc>
  <lastmod>2026-08-23T09:44:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次意思決定のためのメタ学習サロゲートモデル（Meta-Learning surrogate models for sequential decision making）</news:title>
   <news:publication_date>2026-08-23T09:44:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726332</loc>
  <lastmod>2026-08-23T09:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中規模ソフトウェアコンサルティング企業における知識管理（Knowledge Management in Medium-Sized Software Consulting Companies）</news:title>
   <news:publication_date>2026-08-23T09:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726330</loc>
  <lastmod>2026-08-23T09:43:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像変換による分布シフトへの脆弱性に対処する手法（Addressing Model Vulnerability to Distributional Shifts over Image Transformation Sets）</news:title>
   <news:publication_date>2026-08-23T09:43:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726328</loc>
  <lastmod>2026-08-23T09:43:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可視光通信における雑音低減の実践的方法（A Noise Mitigation Approach for VLC Systems）</news:title>
   <news:publication_date>2026-08-23T09:43:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726326</loc>
  <lastmod>2026-08-23T09:42:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AED-Netによる異常事象検出（AED-Net: An Abnormal Event Detection Network）</news:title>
   <news:publication_date>2026-08-23T09:42:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726324</loc>
  <lastmod>2026-08-23T09:42:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Feature Intertwiner を用いた物体検出の新視点（FEATURE INTERTWINER FOR OBJECT DETECTION）</news:title>
   <news:publication_date>2026-08-23T09:42:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726322</loc>
  <lastmod>2026-08-23T08:50:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフカーネルの総覧（A Survey on Graph Kernels）</news:title>
   <news:publication_date>2026-08-23T08:50:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726320</loc>
  <lastmod>2026-08-23T08:50:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>談話マーカーを発掘する：教師なし文表現学習のために（Mining Discourse Markers for Unsupervised Sentence Representation Learning）</news:title>
   <news:publication_date>2026-08-23T08:50:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726318</loc>
  <lastmod>2026-08-23T08:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Feature-fusion Encoder-Decoder Network による肝病変自動セグメンテーション（FEATURE FUSION ENCODER DECODER NETWORK FOR AUTOMATIC LIVER LESION SEGMENTATION）</news:title>
   <news:publication_date>2026-08-23T08:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726316</loc>
  <lastmod>2026-08-23T08:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チェレンコフ検出器の高速シミュレーションにおける生成モデルの応用（Cherenkov Detectors Fast Simulation Using Neural Networks）</news:title>
   <news:publication_date>2026-08-23T08:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726314</loc>
  <lastmod>2026-08-23T08:50:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SRDGANによる実世界単一画像超解像のノイズ事前分布学習（SRDGAN: learning the noise prior for Super Resolution with Dual Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-23T08:50:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726312</loc>
  <lastmod>2026-08-23T08:49:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ADMET予測における飛躍的改善：PotentialNetによる深い特徴化（Step Change Improvement in ADMET Prediction with PotentialNet Deep Featurization）</news:title>
   <news:publication_date>2026-08-23T08:49:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726310</loc>
  <lastmod>2026-08-23T08:49:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱ラベル音響イベント検出の階層プーリング構造（Hierarchical Pooling Structure for Weakly Labeled Sound Event Detection）</news:title>
   <news:publication_date>2026-08-23T08:49:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726308</loc>
  <lastmod>2026-08-23T07:58:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワッサースタイン依存度による表現学習の新展開（Wasserstein Dependency Measure for Representation Learning）</news:title>
   <news:publication_date>2026-08-23T07:58:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726306</loc>
  <lastmod>2026-08-23T07:58:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガイダンスフレーム選択の学習による動画物体分割の改善（BubbleNets: Learning to Select the Guidance Frame in Video Object Segmentation by Deep Sorting Frames）</news:title>
   <news:publication_date>2026-08-23T07:58:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726304</loc>
  <lastmod>2026-08-23T07:58:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話における照応表現解決のための文脈的クエリ書き換え（A dataset for resolving referring expressions in spoken dialogue via contextual query rewrites (CQR))</news:title>
   <news:publication_date>2026-08-23T07:58:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726302</loc>
  <lastmod>2026-08-23T07:57:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層監督による非線形集約による顕著物体検出（DNA: Deeply-supervised Nonlinear Aggregation for Salient Object Detection）</news:title>
   <news:publication_date>2026-08-23T07:57:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726300</loc>
  <lastmod>2026-08-23T07:57:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心房細動を深層特徴と畳み込みネットワークで検出する手法（Atrial Fibrillation Detection Using Deep Features and Convolutional Networks）</news:title>
   <news:publication_date>2026-08-23T07:57:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726298</loc>
  <lastmod>2026-08-23T07:57:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型注意機構付き時系列畳み込みネットワークによる医療時系列分類（Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks）</news:title>
   <news:publication_date>2026-08-23T07:57:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726296</loc>
  <lastmod>2026-08-23T07:57:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションから実機へ：ドメインランダマイゼーションのパラメータ選定（How to pick the domain randomization parameters for sim-to-real transfer of reinforcement learning policies?）</news:title>
   <news:publication_date>2026-08-23T07:57:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726294</loc>
  <lastmod>2026-08-23T07:06:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部疾患の局在化のためのマスク化変分潜在表現（InfoMask: Masked Variational Latent Representation to Localize Chest Disease）</news:title>
   <news:publication_date>2026-08-23T07:06:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726292</loc>
  <lastmod>2026-08-23T07:06:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AutoSlimによるチャネル最適化の一撃（AutoSlim: Towards One-Shot Architecture Search for Channel Numbers）</news:title>
   <news:publication_date>2026-08-23T07:06:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726290</loc>
  <lastmod>2026-08-23T07:06:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸シナリオプログラムの事後確率境界と検証テスト（A Posteriori Probabilistic Bounds of Convex Scenario Programs with Validation Tests）</news:title>
   <news:publication_date>2026-08-23T07:06:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726288</loc>
  <lastmod>2026-08-23T07:05:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医用画像と機械学習の動向と展望 (Radiological images and machine learning: trends, perspectives, and prospects)</news:title>
   <news:publication_date>2026-08-23T07:05:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726286</loc>
  <lastmod>2026-08-23T07:05:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドベース会議のためのメディア処理資源割当機構（Resource Allocation Mechanism for Media Handling Services in Cloud Multimedia Conferencing）</news:title>
   <news:publication_date>2026-08-23T07:05:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726284</loc>
  <lastmod>2026-08-23T07:05:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多座標コストバランシングによる技能習得（Skill Acquisition via Automated Multi-Coordinate Cost Balancing）</news:title>
   <news:publication_date>2026-08-23T07:05:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726282</loc>
  <lastmod>2026-08-23T07:04:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果性の視点から問うアルゴリズムの公平性（Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality）</news:title>
   <news:publication_date>2026-08-23T07:04:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726280</loc>
  <lastmod>2026-08-23T06:13:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WiFi指紋による屋内測位に対するRNNの適用（Recurrent Neural Networks For Accurate RSSI Indoor Localization）</news:title>
   <news:publication_date>2026-08-23T06:13:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726278</loc>
  <lastmod>2026-08-23T06:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多隠れ層リカレントニューラルネットワークと改良グレイウルフ最適化（A Multi Hidden Recurrent Neural Network with a Modified Grey Wolf Optimizer）</news:title>
   <news:publication_date>2026-08-23T06:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726276</loc>
  <lastmod>2026-08-23T06:03:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係性マッチングと適応・較正によるゼロショット画像認識（Zero-shot Image Recognition Using Relational Matching, Adaptation and Calibration）</news:title>
   <news:publication_date>2026-08-23T06:03:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726274</loc>
  <lastmod>2026-08-23T06:02:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線画像由来データの安定した予測（STABLE PREDICTION WITH RADIOMICS DATA）</news:title>
   <news:publication_date>2026-08-23T06:02:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726272</loc>
  <lastmod>2026-08-23T06:02:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークセキュリティ向け深層学習に対抗する敵対的手法の評価（Rallying Adversarial Techniques against Deep Learning for Network Security）</news:title>
   <news:publication_date>2026-08-23T06:02:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726270</loc>
  <lastmod>2026-08-23T06:02:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Inf-Convolutionによる非凸複合最適化の最適化（Optimization of Inf-Convolution Regularized Nonconvex Composite Problems）</news:title>
   <news:publication_date>2026-08-23T06:02:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726268</loc>
  <lastmod>2026-08-23T06:01:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超球面上で自己正規化活性化を用いたエコー・ステート・ネットワーク（Echo State Networks with Self-Normalizing Activations on the Hyper-Sphere）</news:title>
   <news:publication_date>2026-08-23T06:01:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726266</loc>
  <lastmod>2026-08-23T05:11:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外れ値に強い空間認識（Outlier-Robust Spatial Perception: Hardness, General-Purpose Algorithms, and Guarantees）</news:title>
   <news:publication_date>2026-08-23T05:11:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726264</loc>
  <lastmod>2026-08-23T05:11:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>早期停止を用いた勾配降下法はラベルノイズに対し理論的に頑健である（Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks）</news:title>
   <news:publication_date>2026-08-23T05:11:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726262</loc>
  <lastmod>2026-08-23T05:10:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGバイオメトリクスにおける敵対的深層学習 (Adversarial Deep Learning in EEG Biometrics)</news:title>
   <news:publication_date>2026-08-23T05:10:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726260</loc>
  <lastmod>2026-08-23T05:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星形成銀河Haro 11における恒星フィードバックの大規模影響（The impact of Stellar feedback from velocity-dependent ionized gas maps. – A MUSE view of Haro 11）</news:title>
   <news:publication_date>2026-08-23T05:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726258</loc>
  <lastmod>2026-08-23T05:10:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Laplace Landmark Localization（Laplace Landmark Localization）</news:title>
   <news:publication_date>2026-08-23T05:10:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726256</loc>
  <lastmod>2026-08-23T05:10:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像と文章の弱教師あり対応付けで語句を位置特定するAlign2Ground（Align2Ground: Weakly Supervised Phrase Grounding Guided by Image-Caption Alignment）</news:title>
   <news:publication_date>2026-08-23T05:10:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726254</loc>
  <lastmod>2026-08-23T05:09:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発話順序がクラウドソースされた感情アノテーションに及ぼす影響（MuSE-ING ON THE IMPACT OF UTTERANCE ORDERING ON CROWDSOURCED EMOTION ANNOTATIONS）</news:title>
   <news:publication_date>2026-08-23T05:09:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726252</loc>
  <lastmod>2026-08-23T04:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブレーンとブレインズ：深層強化学習で文字列空間を探索する（Branes with Brains: Exploring String Vacua with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-23T04:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726250</loc>
  <lastmod>2026-08-23T04:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的堅牢性と勾配解釈性の橋渡し（BRIDGING ADVERSARIAL ROBUSTNESS AND GRADIENT INTERPRETABILITY）</news:title>
   <news:publication_date>2026-08-23T04:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726248</loc>
  <lastmod>2026-08-23T04:18:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交互的多様体近接勾配法によるSparse PCAとSparse CCA（An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA）</news:title>
   <news:publication_date>2026-08-23T04:18:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726246</loc>
  <lastmod>2026-08-23T04:17:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のようにテキストを処理する — 視覚的に攻撃し護るNLPシステム（Text Processing Like Humans Do: Visually Attacking and Shielding NLP Systems）</news:title>
   <news:publication_date>2026-08-23T04:17:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726244</loc>
  <lastmod>2026-08-23T04:16:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続制御のための自己回帰ポリシー（Autoregressive Policies for Continuous Control Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-23T04:16:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726242</loc>
  <lastmod>2026-08-23T04:16:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現豊かな音声合成の潜在空間可視化と解釈（Visualization and Interpretation of Latent Spaces for Controlling Expressive Speech Synthesis through Audio Analysis）</news:title>
   <news:publication_date>2026-08-23T04:16:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726240</loc>
  <lastmod>2026-08-23T04:16:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制御理論的視点によるDouglas–Rachford分割法の解析とパラメータ選定（A Control-Theoretic Approach to Analysis and Parameter Selection of Douglas-Rachford Splitting）</news:title>
   <news:publication_date>2026-08-23T04:16:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726238</loc>
  <lastmod>2026-08-23T03:23:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期保有者の行動で予測する仮想財の寿命（From the Hands of an Early Adopter’s Avatar to Virtual Junkyards: Analysis of Virtual Goods’ Lifetime Survival）</news:title>
   <news:publication_date>2026-08-23T03:23:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726236</loc>
  <lastmod>2026-08-23T03:23:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群の局所記述子学習（DEEPPOINT3D: LEARNING DISCRIMINATIVE LOCAL DESCRIPTORS USING DEEP METRIC LEARNING ON 3D POINT CLOUDS）</news:title>
   <news:publication_date>2026-08-23T03:23:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726234</loc>
  <lastmod>2026-08-23T03:22:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的システムの簡潔な解析モデル構築（Constructing Parsimonious Analytic Models for Dynamic Systems via Symbolic Regression）</news:title>
   <news:publication_date>2026-08-23T03:22:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726232</loc>
  <lastmod>2026-08-23T03:22:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの初期化を見つめ直す（A Sober Look at Neural Network Initializations）</news:title>
   <news:publication_date>2026-08-23T03:22:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726230</loc>
  <lastmod>2026-08-23T03:21:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポルトガル南西・南沿岸の深海甲殻類底引き網漁業が海洋生態系に与える影響のモデリング（Modelling the impact of deep-water crustacean trawl fishery in the marine ecosystem off Portuguese Southwestern and South Coasts: I) the trophic web and trophic flows）</news:title>
   <news:publication_date>2026-08-23T03:21:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726228</loc>
  <lastmod>2026-08-23T03:21:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸スクエアルート損失回帰の高効率解法（A sparse semismooth Newton based proximal majorization-minimization algorithm for nonconvex square-root-loss regression problems）</news:title>
   <news:publication_date>2026-08-23T03:21:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726226</loc>
  <lastmod>2026-08-23T03:20:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からの2D→3Dリフティングによる3D物体検出（Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles）</news:title>
   <news:publication_date>2026-08-23T03:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726224</loc>
  <lastmod>2026-08-23T02:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コウモリアルゴリズムの大域収束解析（Global Convergence Analysis of the Bat Algorithm Using a Markovian Framework and Dynamical System Theory）</news:title>
   <news:publication_date>2026-08-23T02:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726222</loc>
  <lastmod>2026-08-23T02:29:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Import2vecによるライブラリ埋め込み学習（Import2vec: Learning Embeddings for Software Libraries）</news:title>
   <news:publication_date>2026-08-23T02:29:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726220</loc>
  <lastmod>2026-08-23T02:29:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディア信号で仮想通貨ニュースを感知する手法（Sensing Social Media Signals for Cryptocurrency News）</news:title>
   <news:publication_date>2026-08-23T02:29:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726218</loc>
  <lastmod>2026-08-23T02:29:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度顔画像の匿名化を両立する仕組み（k-Same-Siamese-GAN）</news:title>
   <news:publication_date>2026-08-23T02:29:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726216</loc>
  <lastmod>2026-08-23T02:29:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>掘削中の地質変化をリアルタイムで捉える手法（Real-time data-driven detection of the rock type alteration during a directional drilling）</news:title>
   <news:publication_date>2026-08-23T02:29:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726214</loc>
  <lastmod>2026-08-23T02:28:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続時間を扱う推薦グラフの新展開（Link Stream Graph for Temporal Recommendations）</news:title>
   <news:publication_date>2026-08-23T02:28:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726212</loc>
  <lastmod>2026-08-23T02:28:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像再構成を行わないイメージングサイトメトリー（Imaging cytometry without image reconstruction (ghost cytometry))</news:title>
   <news:publication_date>2026-08-23T02:28:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726210</loc>
  <lastmod>2026-08-23T01:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ショウジョウバエの社会行動フェノタイピングを2D+3DハイブリッドCNNで行う手法（Social Behavioral Phenotyping of Drosophila with a 2D-3D Hybrid CNN Framework）</news:title>
   <news:publication_date>2026-08-23T01:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726208</loc>
  <lastmod>2026-08-23T01:37:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自発的な顔の微表情認識を3D時空間畳み込みで扱う（Spontaneous Facial Micro-Expression Recognition using 3D Spatiotemporal Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-23T01:37:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726206</loc>
  <lastmod>2026-08-23T01:37:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能なAIの落とし穴：加法的説明を信用するな（Do Not Trust Additive Explanations）</news:title>
   <news:publication_date>2026-08-23T01:37:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/726204</loc>
  <lastmod>2026-08-23T01:36:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ化スパース行列乗算によるグラフ畳み込み高速化（Batched Sparse Matrix Multiplication for Accelerating Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-23T01:36:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726202</loc>
  <lastmod>2026-08-23T01:36:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みニューラルネットワークにおける非定型前処理の理解（Understanding Unconventional Preprocessors in Deep Convolutional Neural Networks for Face Identification）</news:title>
   <news:publication_date>2026-08-23T01:36:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/726200</loc>
  <lastmod>2026-08-23T01:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ埋め込み相互作用視点から見る知識グラフ埋め込みの分析（Analyzing Knowledge Graph Embedding Methods from a Multi-Embedding Interaction Perspective）</news:title>
   <news:publication_date>2026-08-23T01:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/726198</loc>
  <lastmod>2026-08-23T01:36:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き運動伝播による自己教師あり学習（Self-Supervised Learning via Conditional Motion Propagation）</news:title>
   <news:publication_date>2026-08-23T01:36:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/726196</loc>
  <lastmod>2026-08-23T00:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン教科書問題に対する学生の関与のネットワーク解析 (Network analyses of student engagement with online textbook problems)</news:title>
   <news:publication_date>2026-08-23T00:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726194</loc>
  <lastmod>2026-08-23T00:43:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙知識を用いない視覚に基づく言語から文意味表現を学ぶ（Learning semantic sentence representations from visually grounded language without lexical knowledge）</news:title>
   <news:publication_date>2026-08-23T00:43:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726192</loc>
  <lastmod>2026-08-23T00:43:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率進化の動的制御――深層強化学習による適応的薬剤投与（Dynamic Control of Stochastic Evolution: A Deep Reinforcement Learning Approach to Adaptively Targeting Emergent Drug Resistance）</news:title>
   <news:publication_date>2026-08-23T00:43:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/726190</loc>
  <lastmod>2026-08-23T00:43:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2次元ケンドール形状の辞書学習（Dictionary Learning for Two-Dimensional Kendall Shapes）</news:title>
   <news:publication_date>2026-08-23T00:43:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726188</loc>
  <lastmod>2026-08-23T00:42:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様性と協調による少数ショット分類の恩恵（Diversity with Cooperation: Ensemble Methods for Few-Shot Classification）</news:title>
   <news:publication_date>2026-08-23T00:42:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726186</loc>
  <lastmod>2026-08-23T00:42:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段階テキスト正規化とマルチソース学習（Multilevel Text Normalization with Sequence-to-Sequence Networks and Multisource Learning）</news:title>
   <news:publication_date>2026-08-23T00:42:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726184</loc>
  <lastmod>2026-08-23T00:42:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化された勾配フリー敵対的攻撃の大規模化が示す既存攻撃による堅牢性の過大評価 (Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks)</news:title>
   <news:publication_date>2026-08-23T00:42:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726182</loc>
  <lastmod>2026-08-22T23:50:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>速度不変のタイムサーフェスによるイベントカメラのコーナー検出（Speed Invariant Time Surface for Learning to Detect Corner Points with Event-Based Cameras）</news:title>
   <news:publication_date>2026-08-22T23:50:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726180</loc>
  <lastmod>2026-08-22T23:50:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数情報源を能動的に使うベイズ求積法（Active Multi-Information Source Bayesian Quadrature）</news:title>
   <news:publication_date>2026-08-22T23:50:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726178</loc>
  <lastmod>2026-08-22T23:50:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的注意生成対抗ネットワークによるクロスドメイン感情分類（Hierarchical Attention Generative Adversarial Networks for Cross-domain Sentiment Classification）</news:title>
   <news:publication_date>2026-08-22T23:50:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726176</loc>
  <lastmod>2026-08-22T23:49:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自閉スペクトラム症（ASD）検出の新たな機械学習フレームワーク（A novel machine learning based framework for detection of Autism Spectrum Disorder (ASD))</news:title>
   <news:publication_date>2026-08-22T23:49:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726174</loc>
  <lastmod>2026-08-22T23:49:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎化されたオフポリシー・アクタークリティック（Generalized Off-Policy Actor-Critic）</news:title>
   <news:publication_date>2026-08-22T23:49:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726172</loc>
  <lastmod>2026-08-22T23:49:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rパッケージによる自動化EDAの現状と経営への示唆（The Landscape of R Packages for Automated Exploratory Data Analysis）</news:title>
   <news:publication_date>2026-08-22T23:49:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726170</loc>
  <lastmod>2026-08-22T23:48:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散基盤上での大規模深層学習：課題・技術・ツール（Scalable Deep Learning on Distributed Infrastructures: Challenges, Techniques and Tools）</news:title>
   <news:publication_date>2026-08-22T23:48:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726168</loc>
  <lastmod>2026-08-22T22:57:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語テキストを用いた画像検索：画像とテキストのクロスモーダル学習アプローチ（Image search using multilingual texts: a cross-modal learning approach between image and text）</news:title>
   <news:publication_date>2026-08-22T22:57:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726166</loc>
  <lastmod>2026-08-22T22:56:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変形可能カーネルネットワークによる深度マップのガイド付きアップサンプリング（Deformable Kernel Networks for Guided Depth Map Upsampling）</news:title>
   <news:publication_date>2026-08-22T22:56:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726164</loc>
  <lastmod>2026-08-22T22:55:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚情報を持つ文書からのマルチモーダル情報抽出を可能にするグラフ畳み込み（Graph Convolution for Multimodal Information Extraction from Visually Rich Documents）</news:title>
   <news:publication_date>2026-08-22T22:55:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726162</loc>
  <lastmod>2026-08-22T22:55:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数ホッピング通信に対する畳み込み攻撃（Convolution Attack on Frequency-Hopping by Full-Duplex Radios）</news:title>
   <news:publication_date>2026-08-22T22:55:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726160</loc>
  <lastmod>2026-08-22T22:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元でスパースな表現を使う利点（How Can We Be So Dense? The Benefits of Using Highly Sparse Representations）</news:title>
   <news:publication_date>2026-08-22T22:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726158</loc>
  <lastmod>2026-08-22T22:55:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元バスケット型アメリカンオプション評価における分散削減と機械学習の融合（Variance Reduction Applied to Machine Learning for Pricing Bermudan/American Options in High Dimension）</news:title>
   <news:publication_date>2026-08-22T22:55:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726156</loc>
  <lastmod>2026-08-22T22:55:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少データ問題と表現学習の総覧（Small Data Challenges in Big Data Era: A Survey of Recent Progress on Unsupervised and Semi-Supervised Methods）</news:title>
   <news:publication_date>2026-08-22T22:55:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726154</loc>
  <lastmod>2026-08-22T22:02:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度画像生成のためのAuto-Embedding GAN（Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis）</news:title>
   <news:publication_date>2026-08-22T22:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726152</loc>
  <lastmod>2026-08-22T22:02:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈要因を取り入れた経路選択モデルの高精度化（Improving Route Choice Models by Incorporating Contextual Factors via Knowledge Distillation）</news:title>
   <news:publication_date>2026-08-22T22:02:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726150</loc>
  <lastmod>2026-08-22T22:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラの色変換を真似ることで合成物を自然に見せる方法（Mimicking the In-Camera Color Pipeline for Camera-Aware Object Compositing）</news:title>
   <news:publication_date>2026-08-22T22:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726148</loc>
  <lastmod>2026-08-22T22:02:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>投擲ロボットの学習：任意物体を投げるTossingBot（TossingBot: Learning to Throw Arbitrary Objects with Residual Physics）</news:title>
   <news:publication_date>2026-08-22T22:02:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726146</loc>
  <lastmod>2026-08-22T22:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合マルチビューデータへの特徴選択（Feature Selection for Data Integration with Mixed Multi-View Data）</news:title>
   <news:publication_date>2026-08-22T22:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726144</loc>
  <lastmod>2026-08-22T22:01:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ない注釈で学ぶ深層共訓練による画像セグメンテーション（Deep Co-Training for Semi-Supervised Image Segmentation）</news:title>
   <news:publication_date>2026-08-22T22:01:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726142</loc>
  <lastmod>2026-08-22T22:01:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNの予測を「分解して説明する」手法の本質（On Attribution of Recurrent Neural Network Predictions via Additive Decomposition）</news:title>
   <news:publication_date>2026-08-22T22:01:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726140</loc>
  <lastmod>2026-08-22T21:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BAE-NETによる形状の共分割を促すブランチ型オートエンコーダ（BAE-NET: Branched Autoencoder for Shape Co-Segmentation）</news:title>
   <news:publication_date>2026-08-22T21:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726138</loc>
  <lastmod>2026-08-22T21:10:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量ロバスト推定の敵対的ロバストネス（On the Adversarial Robustness of Multivariate Robust Estimation）</news:title>
   <news:publication_date>2026-08-22T21:10:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726136</loc>
  <lastmod>2026-08-22T21:09:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震データ解釈におけるニューラルネットワークの実務応用（Neural-networks for geophysicists and their application to seismic data interpretation）</news:title>
   <news:publication_date>2026-08-22T21:09:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726134</loc>
  <lastmod>2026-08-22T21:08:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツイートの位置情報プライバシー侵害（Infringement of Tweets Geo-Location Privacy: an approach based on Graph Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-22T21:08:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726132</loc>
  <lastmod>2026-08-22T21:08:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組織学画像からの大腸癌診断：転移学習とCNNの比較検討（Colorectal cancer diagnosis from histology images: A comparative study）</news:title>
   <news:publication_date>2026-08-22T21:08:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726130</loc>
  <lastmod>2026-08-22T21:08:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集中型ベイズ実験計画のための層別多重重要度サンプリング（A layered multiple importance sampling scheme for focused optimal Bayesian experimental design）</news:title>
   <news:publication_date>2026-08-22T21:08:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726128</loc>
  <lastmod>2026-08-22T21:08:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル回帰におけるロバスト損失とIRLSによる最適化（Kernel based regression with robust loss function via iteratively reweighted least squares）</news:title>
   <news:publication_date>2026-08-22T21:08:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726126</loc>
  <lastmod>2026-08-22T20:16:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空撮における向き推定の汎化改善（Improved Generalization of Heading Direction Estimation for Aerial Filming Using Semi-Supervised Regression）</news:title>
   <news:publication_date>2026-08-22T20:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726124</loc>
  <lastmod>2026-08-22T20:16:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク化データにおける局所線形回帰（Localized Linear Regression in Networked Data）</news:title>
   <news:publication_date>2026-08-22T20:16:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726122</loc>
  <lastmod>2026-08-22T20:16:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低資源医用画像分類におけるCNN表現の評価（ON EVALUATING CNN REPRESENTATIONS FOR LOW RESOURCE MEDICAL IMAGE CLASSIFICATION）</news:title>
   <news:publication_date>2026-08-22T20:16:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726120</loc>
  <lastmod>2026-08-22T20:14:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化炭素ナノチューブに基づく可変ハイパーボリックメタマテリアル（Tunable Hyperbolic Metamaterials Based on Self-Assembled Carbon Nanotubes）</news:title>
   <news:publication_date>2026-08-22T20:14:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726118</loc>
  <lastmod>2026-08-22T20:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pix2Vex: 画像から形状を復元する滑らかな微分可能レンダラー（Pix2Vex: Image-to-Geometry Reconstruction using a Smooth Differentiable Renderer）</news:title>
   <news:publication_date>2026-08-22T20:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726116</loc>
  <lastmod>2026-08-22T20:14:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>せん断粒状断層における断続的摩擦ダイナミクスの機械学習解析（Machine Learning Reveals the State of Intermittent Frictional Dynamics in a Sheared Granular Fault）</news:title>
   <news:publication_date>2026-08-22T20:14:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726114</loc>
  <lastmod>2026-08-22T20:14:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きマルチソースTrAdaBoost（Weighted Multisource Tradaboost）</news:title>
   <news:publication_date>2026-08-22T20:14:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726112</loc>
  <lastmod>2026-08-22T19:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep segmentation networks predict survival of non-small cell lung cancer（Deep segmentation networks predict survival of non-small cell lung cancer）</news:title>
   <news:publication_date>2026-08-22T19:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726110</loc>
  <lastmod>2026-08-22T19:21:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多波長・多信号で迫るブラックホール合体の新展望（Multi-Messenger Astrophysics Opportunities with Stellar-Mass Binary Black Hole Mergers）</news:title>
   <news:publication_date>2026-08-22T19:21:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726108</loc>
  <lastmod>2026-08-22T19:21:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブルッフボディ上のランダム圧力場の動的モード分解（Dynamic mode decomposition of random pressure fields over bluff bodies）</news:title>
   <news:publication_date>2026-08-22T19:21:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726106</loc>
  <lastmod>2026-08-22T19:20:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスモーダルデータプログラミングによる迅速な医療機械学習（Cross-Modal Data Programming Enables Rapid Medical Machine Learning）</news:title>
   <news:publication_date>2026-08-22T19:20:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726104</loc>
  <lastmod>2026-08-22T19:20:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー保護を組み込んだ能動学習によるユーザー意図分類（Privacy-preserving Active Learning on Sensitive Data for User Intent Classification）</news:title>
   <news:publication_date>2026-08-22T19:20:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726102</loc>
  <lastmod>2026-08-22T19:20:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SuSiによる教師ありセルフオーガナイジングマップの実装と評価（SUSI: SUPERVISED SELF-ORGANIZING MAPS FOR REGRESSION AND CLASSIFICATION IN PYTHON）</news:title>
   <news:publication_date>2026-08-22T19:20:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726100</loc>
  <lastmod>2026-08-22T19:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー貯蔵の運用最適化を学ぶ：Deep Q-Networkによるリアルタイム制御（Energy Storage Management via Deep Q-Networks）</news:title>
   <news:publication_date>2026-08-22T19:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726098</loc>
  <lastmod>2026-08-22T18:27:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河の寄せ集め履歴を統合スペクトルから読み解く（A galaxy’s accretion history unveiled from its integrated spectrum）</news:title>
   <news:publication_date>2026-08-22T18:27:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726096</loc>
  <lastmod>2026-08-22T18:27:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移における被覆型活動銀河核の狭線領域の性質（Obscured AGN at 1.5 &amp;lt; z &amp;lt; 3.0 from the zCOSMOS-deep Survey）</news:title>
   <news:publication_date>2026-08-22T18:27:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726094</loc>
  <lastmod>2026-08-22T18:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分速単位の光学トランジェント探索が開く新領域（Probing the extragalactic fast transient sky at minute timescales with DECam）</news:title>
   <news:publication_date>2026-08-22T18:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726092</loc>
  <lastmod>2026-08-22T18:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移銀河の恒星金属量と質量の関係（The VANDELS survey: the stellar metallicities of star-forming galaxies at 2.5 &amp;lt; z &amp;lt; 5.0）</news:title>
   <news:publication_date>2026-08-22T18:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726090</loc>
  <lastmod>2026-08-22T18:24:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VANDELSサーベイが示す大質量休止銀河の形成史（The VANDELS survey: the star-formation histories of massive quiescent galaxies at 1.0 &amp;lt; z &amp;lt; 1.3）</news:title>
   <news:publication_date>2026-08-22T18:24:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726088</loc>
  <lastmod>2026-08-22T18:24:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>saVANtによるVAN強化（saVANt—VANs Enhanced by Importance and MCMC Sampling）</news:title>
   <news:publication_date>2026-08-22T18:24:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726086</loc>
  <lastmod>2026-08-22T18:23:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常軌跡検出を敵対的学習で行う手法（Adversarially Learned Abnormal Trajectory Classifier）</news:title>
   <news:publication_date>2026-08-22T18:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726084</loc>
  <lastmod>2026-08-22T17:32:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子特異的持続ホモロジーとタンパク質柔軟性解析への応用 (Atom-specific persistent homology and its application to protein flexibility analysis)</news:title>
   <news:publication_date>2026-08-22T17:32:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726082</loc>
  <lastmod>2026-08-22T17:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジで近リアルタイムに学習する物体検出の仕組み（RILOD: Near Real-Time Incremental Learning for Object Detection at the Edge）</news:title>
   <news:publication_date>2026-08-22T17:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726080</loc>
  <lastmod>2026-08-22T17:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転のためのマルチモーダルデータセットnuScenes（nuScenes: A multimodal dataset for autonomous driving）</news:title>
   <news:publication_date>2026-08-22T17:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726078</loc>
  <lastmod>2026-08-22T17:30:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン独立SVMによる脳デコーディングの転移学習（Domain Independent SVM for Transfer Learning in Brain Decoding）</news:title>
   <news:publication_date>2026-08-22T17:30:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726076</loc>
  <lastmod>2026-08-22T17:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習ネットワークをスパイキング化して耐性を高める（Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to Atari Breakout game）</news:title>
   <news:publication_date>2026-08-22T17:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726074</loc>
  <lastmod>2026-08-22T17:29:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正確で快適かつ人間らしい運転の学習（Learning Accurate, Comfortable and Human-like Driving）</news:title>
   <news:publication_date>2026-08-22T17:29:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726072</loc>
  <lastmod>2026-08-22T17:29:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>危機対応のためのツイート分類における深層学習とGloVeの有効性（Deep Learning and GloVe for Crisis Tweet Classification）</news:title>
   <news:publication_date>2026-08-22T17:29:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726070</loc>
  <lastmod>2026-08-22T16:38:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多項式時間でのShapley値近似による深層ニューラルネットワークの説明（Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Values Approximation）</news:title>
   <news:publication_date>2026-08-22T16:38:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726068</loc>
  <lastmod>2026-08-22T16:38:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非常に低解像度顔画像の照合とID保持型深層顔超解像ネットワーク（Verification of Very Low-Resolution Faces Using An Identity-Preserving Deep Face Super-resolution Network）</news:title>
   <news:publication_date>2026-08-22T16:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726066</loc>
  <lastmod>2026-08-22T16:37:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化された非線形変数選択（Structured Nonlinear Variable Selection）</news:title>
   <news:publication_date>2026-08-22T16:37:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726064</loc>
  <lastmod>2026-08-22T16:37:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド古典量子線形方程式ソルバー（Hybrid classical-quantum linear solver using Noisy Intermediate-Scale Quantum machines）</news:title>
   <news:publication_date>2026-08-22T16:37:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726062</loc>
  <lastmod>2026-08-22T16:36:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回帰問題におけるTSKファジィシステム最適化（Optimize TSK Fuzzy Systems for Regression Problems: Mini-Batch Gradient Descent with Regularization, DropRule, and AdaBound）</news:title>
   <news:publication_date>2026-08-22T16:36:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726060</loc>
  <lastmod>2026-08-22T16:36:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロシューマー協力ゲームのスケーラビリティ改善（Improving the Scalability of a Prosumer Cooperative Game with K-Means Clustering）</news:title>
   <news:publication_date>2026-08-22T16:36:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726058</loc>
  <lastmod>2026-08-22T16:36:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイアス補正が分散確率最適化に与える影響（On the Influence of Bias-Correction on Distributed Stochastic Optimization）</news:title>
   <news:publication_date>2026-08-22T16:36:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726056</loc>
  <lastmod>2026-08-22T15:44:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な5Gに向けて：LTEアップリンク妨害の実験的評価からの教訓（Towards Resilient 5G: Lessons Learned from Experimental Evaluations of LTE Uplink Jamming）</news:title>
   <news:publication_date>2026-08-22T15:44:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726054</loc>
  <lastmod>2026-08-22T15:44:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ実装向けのディープデモザイシング（Deep Demosaicing for Edge Implementation）</news:title>
   <news:publication_date>2026-08-22T15:44:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726052</loc>
  <lastmod>2026-08-22T15:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安価な安静時EEGによる抑うつ検出の機械学習レビュー（Machine learning approaches in Detecting the Depression from Resting-state Electroencephalogram (EEG): A Review Study）</news:title>
   <news:publication_date>2026-08-22T15:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726050</loc>
  <lastmod>2026-08-22T15:43:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種データセットにおけるワードスポッティングの信頼度評価（Exploring Confidence Measures for Word Spotting in Heterogeneous Datasets）</news:title>
   <news:publication_date>2026-08-22T15:43:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726048</loc>
  <lastmod>2026-08-22T15:43:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習済み多様表現の組み合わせが実現する人間の知覚的類似性（High-Level Perceptual Similarity is Enabled by Learning Diverse Tasks）</news:title>
   <news:publication_date>2026-08-22T15:43:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726046</loc>
  <lastmod>2026-08-22T15:43:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分ラベル付きネットワークデータの分類とLogistic Network Lasso（Classifying Partially Labeled Networked Data via Logistic Network Lasso）</news:title>
   <news:publication_date>2026-08-22T15:43:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726044</loc>
  <lastmod>2026-08-22T15:43:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かなデータから信頼できる事例を選ぶ方法（A method on selecting reliable samples based on fuzziness in positive and unlabeled learning）</news:title>
   <news:publication_date>2026-08-22T15:43:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726042</loc>
  <lastmod>2026-08-22T14:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線ネットワークにおける干渉予測（Interference Prediction in Wireless Networks: Stochastic Geometry meets Recursive Filtering）</news:title>
   <news:publication_date>2026-08-22T14:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726040</loc>
  <lastmod>2026-08-22T14:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ主導の機械学習システム設計（Data Science and Digital Systems: The 3Ds of Machine Learning Systems Design）</news:title>
   <news:publication_date>2026-08-22T14:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726038</loc>
  <lastmod>2026-08-22T14:51:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの写真実写的顔ディテール合成 (Photo-Realistic Facial Details Synthesis From Single Image)</news:title>
   <news:publication_date>2026-08-22T14:51:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726036</loc>
  <lastmod>2026-08-22T14:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いたベイズ推論の高速化（Accelerated Bayesian inference using deep learning）</news:title>
   <news:publication_date>2026-08-22T14:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726034</loc>
  <lastmod>2026-08-22T14:50:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オランダF3地震データセット：地震解釈の機械学習向け新公開データセット（Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation）</news:title>
   <news:publication_date>2026-08-22T14:50:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726032</loc>
  <lastmod>2026-08-22T14:50:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アクティブスタッキングによる心拍数推定（Active Stacking for Heart Rate Estimation）</news:title>
   <news:publication_date>2026-08-22T14:50:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726030</loc>
  <lastmod>2026-08-22T13:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロ構造画像から物性を予測するデータ駆動手法（Data-Driven Microstructure Property Relations）</news:title>
   <news:publication_date>2026-08-22T13:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726028</loc>
  <lastmod>2026-08-22T13:46:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルエッジコンピューティングにおける計算複製の活用（Exploiting Computation Replication for Mobile Edge Computing）</news:title>
   <news:publication_date>2026-08-22T13:46:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726026</loc>
  <lastmod>2026-08-22T13:46:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽のテンポと調（キー）推定を軸方向フィルタ付きCNNで解く（Musical Tempo and Key Estimation using Convolutional Neural Networks with Directional Filters）</news:title>
   <news:publication_date>2026-08-22T13:46:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726024</loc>
  <lastmod>2026-08-22T13:45:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク再構築とコミュニティ検出（Network reconstruction and community detection from dynamics）</news:title>
   <news:publication_date>2026-08-22T13:45:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726022</loc>
  <lastmod>2026-08-22T13:45:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模インタラクティブ物体セグメンテーションと人間アノテータ（Large-scale interactive object segmentation with human annotators）</news:title>
   <news:publication_date>2026-08-22T13:45:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726020</loc>
  <lastmod>2026-08-22T13:45:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何学に着想を得た決定ベース攻撃（A geometry-inspired decision-based attack）</news:title>
   <news:publication_date>2026-08-22T13:45:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726018</loc>
  <lastmod>2026-08-22T13:45:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライブ映像における顔のピクセレーション手法の実装と評価（Pixelation is NOT Done in Videos Yet）</news:title>
   <news:publication_date>2026-08-22T13:45:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726016</loc>
  <lastmod>2026-08-22T12:53:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスモーダル部分空間学習：カーネル相関最大化と識別構造保持（Cross-modal Subspace Learning via Kernel Correlation Maximization and Discriminative Structure Preserving）</news:title>
   <news:publication_date>2026-08-22T12:53:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726014</loc>
  <lastmod>2026-08-22T12:53:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stacked Monte Carloを用いたオプション価格評価の分散削減（STACKED MONTE CARLO FOR OPTION PRICING）</news:title>
   <news:publication_date>2026-08-22T12:53:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726012</loc>
  <lastmod>2026-08-22T12:52:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RecSys-DANによるクロスドメイン推薦の実務的意義（RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems）</news:title>
   <news:publication_date>2026-08-22T12:52:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726010</loc>
  <lastmod>2026-08-22T12:51:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>どこを見ればよいかを学ぶ―IHC画像スコアリングに対する注目モデル（Learning Where to See: A Novel Attention Model for Automated Immunohistochemical Scoring）</news:title>
   <news:publication_date>2026-08-22T12:51:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726008</loc>
  <lastmod>2026-08-22T12:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高精度なインスタンス認識型セマンティック3Dマップの構築（High-quality Instance-aware Semantic 3D Map Using RGB-D Camera）</news:title>
   <news:publication_date>2026-08-22T12:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726006</loc>
  <lastmod>2026-08-22T12:51:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙データからICMEを自動検出する深層学習法（Automatic detection of Interplanetary Coronal Mass Ejections from in-situ data: a deep learning approach）</news:title>
   <news:publication_date>2026-08-22T12:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726004</loc>
  <lastmod>2026-08-22T12:51:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間的一貫性を備えた深度予測と意味理解の統合（Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach）</news:title>
   <news:publication_date>2026-08-22T12:51:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726002</loc>
  <lastmod>2026-08-22T11:59:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的テンソルネットワークによる教師あり学習モデル（Generative Tensor Network Classification Model for Supervised Machine Learning）</news:title>
   <news:publication_date>2026-08-22T11:59:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726000</loc>
  <lastmod>2026-08-22T11:49:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>いつ量子コンピュータは実用化するのか（When will we have a quantum computer?）</news:title>
   <news:publication_date>2026-08-22T11:49:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725998</loc>
  <lastmod>2026-08-22T11:49:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超音波検査データの拡張で機械学習が超人性能を示す（Augmented Ultrasonic Data for Machine Learning）</news:title>
   <news:publication_date>2026-08-22T11:49:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725996</loc>
  <lastmod>2026-08-22T11:47:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械間相互運用性と機械間翻訳モデル（Interoperability and machine-to-machine translation model with mappings to machine learning tasks）</news:title>
   <news:publication_date>2026-08-22T11:47:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725994</loc>
  <lastmod>2026-08-22T11:47:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒト表現型と遺伝子の関係を大規模に作る手法（A Silver Standard Corpus of Human Phenotype-Gene Relations）</news:title>
   <news:publication_date>2026-08-22T11:47:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-22T11:47:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小規模データセット向け画像分類器の改善：学習率適応による高速化と精度向上（Improving image classifiers for small datasets by learning rate adaptations）</news:title>
   <news:publication_date>2026-08-22T11:47:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/725990</loc>
  <lastmod>2026-08-22T11:47:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多声部歌唱合成をGANで実現する試み（WGANSing: A Multi-Voice Singing Voice Synthesizer Based on the Wasserstein-GAN）</news:title>
   <news:publication_date>2026-08-22T11:47:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725988</loc>
  <lastmod>2026-08-22T10:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン表現による知識グラフ埋め込み（Domain Representation for Knowledge Graph Embedding）</news:title>
   <news:publication_date>2026-08-22T10:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725986</loc>
  <lastmod>2026-08-22T10:44:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル非教師ありハッシングによる高速クロスモーダル検索（Unsupervised Multi-modal Hashing for Cross-Modal Retrieval）</news:title>
   <news:publication_date>2026-08-22T10:44:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725984</loc>
  <lastmod>2026-08-22T10:43:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外科ナビゲーション向けソフト組織挙動の学習（Learning Soft Tissue Behavior of Organs for Surgical Navigation with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-22T10:43:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725982</loc>
  <lastmod>2026-08-22T10:42:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Autoencoding Binary Classifiersによる教師付き異常検出の革新（Autoencoding Binary Classifiers for Supervised Anomaly Detection）</news:title>
   <news:publication_date>2026-08-22T10:42:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725980</loc>
  <lastmod>2026-08-22T10:42:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的グラフ回帰の理論と実装的示唆（On the Theory of Dynamic Graph Regression Problem）</news:title>
   <news:publication_date>2026-08-22T10:42:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725978</loc>
  <lastmod>2026-08-22T10:42:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽器トランジェントを学習する条件付けRNN（Conditioning a Recurrent Neural Network to synthesize musical instrument transients）</news:title>
   <news:publication_date>2026-08-22T10:42:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725976</loc>
  <lastmod>2026-08-22T10:42:15Z</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CNNと動的トリプレットロスによる生物音響分類の進展（Multiscale CNN based Deep Metric Learning for Bioacoustic Classification）</news:title>
   <news:publication_date>2026-08-22T10:42:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725974</loc>
  <lastmod>2026-08-22T09:50:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>影除去を学習するMask-ShadowGAN（Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data）</news:title>
   <news:publication_date>2026-08-22T09:50:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725972</loc>
  <lastmod>2026-08-22T09:50:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点予測を取り込む確率的負荷予測の二段階フレームワーク（Probabilistic Load Forecasting via Point Forecast Feature Integration）</news:title>
   <news:publication_date>2026-08-22T09:50:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725970</loc>
  <lastmod>2026-08-22T09:49:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化された畳み込みと効率的な言語認識（Generalized Convolution and Efficient Language Recognition）</news:title>
   <news:publication_date>2026-08-22T09:49:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725968</loc>
  <lastmod>2026-08-22T09:49:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる集約レベルにおける短期負荷予測と予測可能性の解析（Short-term Load Forecasting at Different Aggregation Levels with Predictability Analysis）</news:title>
   <news:publication_date>2026-08-22T09:49:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725966</loc>
  <lastmod>2026-08-22T09:49:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド密度汎関数の最適化におけるベイズ最適化の応用（Bayesian optimization for tuning and selecting hybrid-density functionals）</news:title>
   <news:publication_date>2026-08-22T09:49:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725964</loc>
  <lastmod>2026-08-22T09:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AlphaXによるニューラルアーキテクチャ探索（AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search）</news:title>
   <news:publication_date>2026-08-22T09:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725962</loc>
  <lastmod>2026-08-22T09:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ量子化に対するニューラルネットワークの頑健性（Robustness of Neural Networks to Parameter Quantization）</news:title>
   <news:publication_date>2026-08-22T09:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725960</loc>
  <lastmod>2026-08-22T08:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ルールベースエージェントの失敗シナリオ生成（Failure-Scenario Maker for Rule-Based Agent using Multi-agent Adversarial Reinforcement Learning and its Application to Autonomous Driving）</news:title>
   <news:publication_date>2026-08-22T08:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725958</loc>
  <lastmod>2026-08-22T08:48:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による非並列コーパスでの文章スタイル変換（Reinforcement Learning Based Text Style Transfer without Parallel Training Corpus）</news:title>
   <news:publication_date>2026-08-22T08:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725956</loc>
  <lastmod>2026-08-22T08:47:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工ヒューマン最適化（Artificial Human Optimization）分野の出発点（Novel Artificial Human Optimization Field Algorithms – The Beginning）</news:title>
   <news:publication_date>2026-08-22T08:47:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725954</loc>
  <lastmod>2026-08-22T08:47:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数グローバル記述子の組合せによる画像検索改善（Combination of Multiple Global Descriptors for Image Retrieval）</news:title>
   <news:publication_date>2026-08-22T08:47:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725952</loc>
  <lastmod>2026-08-22T08:45:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔ランドマーク検出における意味的一致の追求（Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection）</news:title>
   <news:publication_date>2026-08-22T08:45:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725950</loc>
  <lastmod>2026-08-22T08:45:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復平均の重み付けによる鞍点問題解法（Increasing iterate averaging for solving saddle-point problems）</news:title>
   <news:publication_date>2026-08-22T08:45:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725948</loc>
  <lastmod>2026-08-22T08:45:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造情報を用いたドメイン適応によるセマンティックセグメンテーションの強化（All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation）</news:title>
   <news:publication_date>2026-08-22T08:45:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725946</loc>
  <lastmod>2026-08-22T07:53:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セグメンテーション結果の異常を検知するアラームシステム（An Alarm System for Segmentation Algorithm Based on Shape Model）</news:title>
   <news:publication_date>2026-08-22T07:53:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725944</loc>
  <lastmod>2026-08-22T07:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デバイス上で学ぶ未登録語の連合学習（Federated Learning Of Out-Of-Vocabulary Words）</news:title>
   <news:publication_date>2026-08-22T07:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725942</loc>
  <lastmod>2026-08-22T07:52:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>翻訳で見落とす最適化機会（Lost in translation: Exposing hidden compiler optimization opportunities）</news:title>
   <news:publication_date>2026-08-22T07:52:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725940</loc>
  <lastmod>2026-08-22T07:51:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応可能なソフトウェアの性能モデルにおける再訓練型と増分学習の比較（On Using Retrained and Incremental Machine Learning for Modeling Performance of Adaptable Software: An Empirical Comparison）</news:title>
   <news:publication_date>2026-08-22T07:51:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725938</loc>
  <lastmod>2026-08-22T07:51:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固有値と一般化固有値問題のチュートリアル（Eigenvalue and Generalized Eigenvalue Problems: Tutorial）</news:title>
   <news:publication_date>2026-08-22T07:51:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725936</loc>
  <lastmod>2026-08-22T07:51:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続行動空間におけるQ学習とCross-Entropy Guided Policies（Q-Learning for Continuous Actions with Cross-Entropy Guided Policies）</news:title>
   <news:publication_date>2026-08-22T07:51:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725934</loc>
  <lastmod>2026-08-22T07:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応型自動脅威認識による手荷物CT解析の革新（An Approach for Adaptive Automatic Threat Recognition Within 3D Computed Tomography Images for Baggage Security Screening）</news:title>
   <news:publication_date>2026-08-22T07:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725932</loc>
  <lastmod>2026-08-22T06:50:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしドメイン適応とゼロショット視覚認識の統合 (Unifying Unsupervised Domain Adaptation and Zero-Shot Visual Recognition)</news:title>
   <news:publication_date>2026-08-22T06:50:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725930</loc>
  <lastmod>2026-08-22T06:50:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非差別的意思決定のための最適かつ公正な決定木の学習（Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making）</news:title>
   <news:publication_date>2026-08-22T06:50:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725928</loc>
  <lastmod>2026-08-22T06:49:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>白箱（ホワイトボックス）攻撃に対するランダム化離散化による防御（Defending against Whitebox Adversarial Attacks via Randomized Discretization）</news:title>
   <news:publication_date>2026-08-22T06:49:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725926</loc>
  <lastmod>2026-08-22T06:49:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応型ネットワークによる動きぼけ除去 (Motion Deblurring with an Adaptive Network)</news:title>
   <news:publication_date>2026-08-22T06:49:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725924</loc>
  <lastmod>2026-08-22T06:49:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カプセルネットワークの情報希薄化を抑える実践的改善法（Reducing the dilution: An analysis of the information sensitiveness of capsule network with a practical improvement method）</news:title>
   <news:publication_date>2026-08-22T06:49:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725922</loc>
  <lastmod>2026-08-22T06:49:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度数値表現が変えるDNNの実用性（Performance-Efficiency Trade-off of Low-Precision Numerical Formats in Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-22T06:49:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725920</loc>
  <lastmod>2026-08-22T05:57:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像から便を識別する深層学習の試み（Augmenting Gastrointestinal Health: A Deep Learning Approach to Human Stool Recognition and Characterization in Macroscopic Images）</news:title>
   <news:publication_date>2026-08-22T05:57:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/725918</loc>
  <lastmod>2026-08-22T05:57:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TSKファジィと機械学習の機能同値性が示す実務への示唆（On the Functional Equivalence of TSK Fuzzy Systems to Neural Networks, Mixture of Experts, CART, and Stacking Ensemble Regression）</news:title>
   <news:publication_date>2026-08-22T05:57:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725916</loc>
  <lastmod>2026-08-22T05:56:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的表面最適化と対数密度推定（General Probabilistic Surface Optimization and Log Density Estimation）</news:title>
   <news:publication_date>2026-08-22T05:56:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725914</loc>
  <lastmod>2026-08-22T05:55:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム条件付分布による分布的推論の体系化（The Random Conditional Distribution For Higher-Order Probabilistic Inference）</news:title>
   <news:publication_date>2026-08-22T05:55:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725912</loc>
  <lastmod>2026-08-22T05:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺内における局在化のための深層学習（Deep Learning for Localization in the Lung）</news:title>
   <news:publication_date>2026-08-22T05:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725910</loc>
  <lastmod>2026-08-22T05:55:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文エンコーダーにおける社会的バイアスの測定（On Measuring Social Biases in Sentence Encoders）</news:title>
   <news:publication_date>2026-08-22T05:55:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725908</loc>
  <lastmod>2026-08-22T05:54:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Machine learningと物理科学の接点（Machine learning and the physical sciences）</news:title>
   <news:publication_date>2026-08-22T05:54:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725906</loc>
  <lastmod>2026-08-22T05:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Shannonエントロピーに基づく質問埋め込み（Question Embeddings Based on Shannon Entropy）</news:title>
   <news:publication_date>2026-08-22T05:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725904</loc>
  <lastmod>2026-08-22T05:03:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像から学習データを作る画素平均化法（A Novel Pixel-Averaging Technique for Extracting Training Data from a Single Image, Used in ML-Based Image Enlargement）</news:title>
   <news:publication_date>2026-08-22T05:03:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725902</loc>
  <lastmod>2026-08-22T05:03:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gated Spatio-Temporal Energy Graphによる動画関係推論（Video Relationship Reasoning using Gated Spatio-Temporal Energy Graph）</news:title>
   <news:publication_date>2026-08-22T05:03:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725900</loc>
  <lastmod>2026-08-22T05:02:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現データを用いた生存予測のトピックモデリング手法（Gene Expression based Survival Prediction for Cancer Patients – A Topic Modeling Approach）</news:title>
   <news:publication_date>2026-08-22T05:02:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725898</loc>
  <lastmod>2026-08-22T05:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勝つことがすべてではない：ゲーム開発を支える知的エージェントの活用（Winning Isn’t Everything: Enhancing Game Development with Intelligent Agents）</news:title>
   <news:publication_date>2026-08-22T05:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725896</loc>
  <lastmod>2026-08-22T05:01:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子コンピューティングの次の一手（Next Steps in Quantum Computing: Computer Science’s Role）</news:title>
   <news:publication_date>2026-08-22T05:01:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725894</loc>
  <lastmod>2026-08-22T05:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Geometry-Awareなカリキュラム学習による単眼視覚オドメトリの習得（Learning Monocular Visual Odometry through Geometry-Aware Curriculum Learning）</news:title>
   <news:publication_date>2026-08-22T05:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725892</loc>
  <lastmod>2026-08-22T04:10:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽とダンスで学ぶ具現化された意味（Learning embodied semantics via music and dance）</news:title>
   <news:publication_date>2026-08-22T04:10:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725890</loc>
  <lastmod>2026-08-22T04:09:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークで学ぶロボット群の分散制御器学習 (Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks)</news:title>
   <news:publication_date>2026-08-22T04:09:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725888</loc>
  <lastmod>2026-08-22T04:09:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆最適計画による空域運用学習（Inverse Optimal Planning for Air Traffic Control）</news:title>
   <news:publication_date>2026-08-22T04:09:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725886</loc>
  <lastmod>2026-08-22T04:08:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロバッチ学習における重み標準化とバッチ・チャンネル正規化（Micro-Batch Training with Batch-Channel Normalization and Weight Standardization）</news:title>
   <news:publication_date>2026-08-22T04:08:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725884</loc>
  <lastmod>2026-08-22T04:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DUNE-PRISMによる軽質暗黒物質探索の新戦略（Hunting On- and Off-Axis for Light Dark Matter with DUNE-PRISM）</news:title>
   <news:publication_date>2026-08-22T04:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725882</loc>
  <lastmod>2026-08-22T04:08:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダークマター密度場からハローを描く物理的に動機付けられたニューラルネットワーク（Painting halos from cosmic density fields of dark matter with physically motivated neural networks）</news:title>
   <news:publication_date>2026-08-22T04:08:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725880</loc>
  <lastmod>2026-08-22T04:08:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>K2データにおける深層学習での系外惑星同定（Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data）</news:title>
   <news:publication_date>2026-08-22T04:08:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725878</loc>
  <lastmod>2026-08-22T03:14:43Z</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>2026-08-22T03:14:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725876</loc>
  <lastmod>2026-08-22T03:14:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー生成コンテンツの差分プライバシー表現学習（dpUGC: Learn Differentially Private Representation for User Generated Contents）</news:title>
   <news:publication_date>2026-08-22T03:14:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725874</loc>
  <lastmod>2026-08-22T02:22:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CODAによるスケール認識型敵対的密度適応による物体カウント改善（CODA: COUNTING OBJECTS VIA SCALE-AWARE ADVERSARIAL DENSITY ADAPTION）</news:title>
   <news:publication_date>2026-08-22T02:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725872</loc>
  <lastmod>2026-08-22T02:21:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多面的な社会的影響を深く捉える二重グラフ注意ネットワーク（Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems）</news:title>
   <news:publication_date>2026-08-22T02:21:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725870</loc>
  <lastmod>2026-08-22T02:20:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的コンテクストを用いたスケール適応型密特徴（Scale-Adaptive Neural Dense Features: Learning via Hierarchical Context Aggregation）</news:title>
   <news:publication_date>2026-08-22T02:20:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725868</loc>
  <lastmod>2026-08-22T02:20:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物から学ぶ「自己学習する知能」の枠組み（A Conceptual Bio-Inspired Framework for the Evolution of Artificial General Intelligence）</news:title>
   <news:publication_date>2026-08-22T02:20:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725866</loc>
  <lastmod>2026-08-22T02:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショット学習に基づく人体活動認識（Few-Shot Learning-Based Human Activity Recognition）</news:title>
   <news:publication_date>2026-08-22T02:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725864</loc>
  <lastmod>2026-08-22T02:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共同手-物体姿勢推定の一般化されたフィードバックループ（Generalized Feedback Loop for Joint Hand-Object Pose Estimation）</news:title>
   <news:publication_date>2026-08-22T02:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725862</loc>
  <lastmod>2026-08-22T01:28:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み強化学習のための深層オートエンコーダ活用（On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-22T01:28:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725860</loc>
  <lastmod>2026-08-22T01:27:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サレー市における子どもの脆弱性の可視化（Understanding Childhood Vulnerability in The City of Surrey）</news:title>
   <news:publication_date>2026-08-22T01:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725858</loc>
  <lastmod>2026-08-22T01:27:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LogBarrier擾乱攻撃の実践的解説 (THE LOGBARRIER ADVERSARIAL ATTACK)</news:title>
   <news:publication_date>2026-08-22T01:27:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725856</loc>
  <lastmod>2026-08-22T01:26:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>おおまかな確率的保証に基づくナッシュ均衡学習（Probably Approximately Correct Nash Equilibrium Learning）</news:title>
   <news:publication_date>2026-08-22T01:26:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725854</loc>
  <lastmod>2026-08-22T01:26:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一細胞アプローチによる細胞競合の解析（Single-cell approaches to cell competition: high-throughput imaging, machine learning and simulations）</news:title>
   <news:publication_date>2026-08-22T01:26:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725852</loc>
  <lastmod>2026-08-22T01:26:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所直交分解による高速内積探索の実務的解説（Local Orthogonal Decomposition for Maximum Inner Product Search）</news:title>
   <news:publication_date>2026-08-22T01:26:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725843</loc>
  <lastmod>2026-08-22T00:34:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コードスイッチング音声・言語処理の包括的レビュー（A Survey of Code-switched Speech and Language Processing）</news:title>
   <news:publication_date>2026-08-22T00:34:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-22T00:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sallyモジュールの構造と第二正規ヒルベルト係数の“ほぼ最小”ケース（ON THE STRUCTURE OF THE SALLY MODULE AND THE SECOND NORMAL HILBERT COEFFICIENT）</news:title>
   <news:publication_date>2026-08-22T00:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725839</loc>
  <lastmod>2026-08-22T00:32:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム対象の公正な分配について（On the fair division of a random object）</news:title>
   <news:publication_date>2026-08-22T00:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725837</loc>
  <lastmod>2026-08-22T00:32:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンゴ葉の病害識別のための領域注目型深層畳み込みニューラルネットワーク（Apple Leaf Disease Identification through Region-of-Interest-Aware Deep Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-22T00:32:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725835</loc>
  <lastmod>2026-08-22T00:32:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識CNNの雑音耐性トレーニングパラダイム（Noise-Tolerant Paradigm for Training Face Recognition CNNs）</news:title>
   <news:publication_date>2026-08-22T00:32:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725833</loc>
  <lastmod>2026-08-22T00:31:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形システム同定のサンプル複雑度下限（Sample Complexity Lower Bounds for Linear System Identification）</news:title>
   <news:publication_date>2026-08-22T00:31:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725831</loc>
  <lastmod>2026-08-22T00:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測・ノイズ下でカオス的力学を学習するEM様手法（EM-like Learning Chaotic Dynamics from Noisy and Partial Observations）</news:title>
   <news:publication_date>2026-08-22T00:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725829</loc>
  <lastmod>2026-08-21T23:39:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配ハミルトニアンモンテカルロによる非凸最適化の収束解析（Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Learning）</news:title>
   <news:publication_date>2026-08-21T23:39:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725827</loc>
  <lastmod>2026-08-21T23:38:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合デモンストレーションからのマルチモーダル方策学習（Learning a Multi-Modal Policy via Imitating Demonstrations with Mixed Behaviors）</news:title>
   <news:publication_date>2026-08-21T23:38:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725825</loc>
  <lastmod>2026-08-21T23:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>降水パラメータ化のデータ駆動アプローチ（A Data-Driven Approach to Precipitation Parameterizations Using Convolutional Encoder-Decoder Neural Networks）</news:title>
   <news:publication_date>2026-08-21T23:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725823</loc>
  <lastmod>2026-08-21T23:37:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>政策論争における内生的連携形成（Endogenous Coalition Formation in Policy Debates）</news:title>
   <news:publication_date>2026-08-21T23:37:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725821</loc>
  <lastmod>2026-08-21T23:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多数のセンサーとアクチュエータで知覚と制御を成し遂げる考え方（Perceptual Control with Large Feature and Actuator Networks）</news:title>
   <news:publication_date>2026-08-21T23:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725819</loc>
  <lastmod>2026-08-21T23:37:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主に非循環有向ネットワークの地平線ダイナミクス（Network Horizon Dynamics I: Qualitative Aspects）</news:title>
   <news:publication_date>2026-08-21T23:37:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725817</loc>
  <lastmod>2026-08-21T22:45:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MetaPruningによる自動チャネルプルーニング（MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning）</news:title>
   <news:publication_date>2026-08-21T22:45:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725815</loc>
  <lastmod>2026-08-21T22:45:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>呼吸位相検出のための畳み込みニューラルネットワーク（Convolutional neural network for breathing phase detection in lung sounds）</news:title>
   <news:publication_date>2026-08-21T22:45:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725813</loc>
  <lastmod>2026-08-21T22:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的特徴から学ぶ少数ショット分類（Learning from Adversarial Features for Few-Shot Classification）</news:title>
   <news:publication_date>2026-08-21T22:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725811</loc>
  <lastmod>2026-08-21T22:44:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノ機械振動子のレーザー冷却でゼロ点エネルギーへ到達（Laser cooling of a nanomechanical oscillator to the zero-point energy）</news:title>
   <news:publication_date>2026-08-21T22:44:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725809</loc>
  <lastmod>2026-08-21T22:44:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-21T22:44:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725807</loc>
  <lastmod>2026-08-21T22:43:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズを前提にしたベクトル空間の整列（Aligning Vector-spaces with Noisy Supervised Lexicons）</news:title>
   <news:publication_date>2026-08-21T22:43:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725805</loc>
  <lastmod>2026-08-21T21:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>精度への道：機械学習で加速するシリコンのab initioシミュレーション（The road to accuracy: machine-learning-accelerated silicon ab initio simulations）</news:title>
   <news:publication_date>2026-08-21T21:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725803</loc>
  <lastmod>2026-08-21T21:52:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マニフォールド基準で導く転移学習（Manifold Criterion Guided Transfer Learning）</news:title>
   <news:publication_date>2026-08-21T21:52:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725801</loc>
  <lastmod>2026-08-21T21:52:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化敵対的訓練による堅牢なニューラルネットワーク（Robust Neural Networks using Randomized Adversarial Training）</news:title>
   <news:publication_date>2026-08-21T21:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725799</loc>
  <lastmod>2026-08-21T21:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイルのエントロピー信号と機械学習による電子文書内悪性コードの検出（Capturing the symptoms of malicious code in electronic documents by file’s entropy signal combined with Machine learning）</news:title>
   <news:publication_date>2026-08-21T21:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725797</loc>
  <lastmod>2026-08-21T21:51:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声から顔を生成する技術の要点（WAV2PIX: SPEECH-CONDITIONED FACE GENERATION USING GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-08-21T21:51:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725795</loc>
  <lastmod>2026-08-21T21:51:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブマイクロ秒で動く高性能DNNをFPGAへ実装する手法（Implementation of high-performance, sub-microsecond deep neural networks on FPGAs for trigger applications）</news:title>
   <news:publication_date>2026-08-21T21:51:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725793</loc>
  <lastmod>2026-08-21T21:51:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏光から学ぶ深層形状推定（Deep Shape from Polarization）</news:title>
   <news:publication_date>2026-08-21T21:51:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725791</loc>
  <lastmod>2026-08-21T21:00:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LOGAN: 潜在的過完備空間における非対応形状変換（LOGAN: Unpaired Shape Transform in Latent Overcomplete Space）</news:title>
   <news:publication_date>2026-08-21T21:00:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725789</loc>
  <lastmod>2026-08-21T21:00:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶を使って高速化するモバイル映像物体検出（Looking Fast and Slow: Memory-Guided Mobile Video Object Detection）</news:title>
   <news:publication_date>2026-08-21T21:00:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725787</loc>
  <lastmod>2026-08-21T20:59:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepRED: Deep Image PriorとREDを組み合わせた画像逆問題の新展開（DeepRED: Deep Image Prior Powered by RED）</news:title>
   <news:publication_date>2026-08-21T20:59:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725785</loc>
  <lastmod>2026-08-21T20:59:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習されたカーネルを用いるダウンスケーリングによる非均一単一画像のデブラー（Down-Scaling with Learned Kernels in Multi-Scale Deep Neural Networks for Non-Uniform Single Image Deblurring）</news:title>
   <news:publication_date>2026-08-21T20:59:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725783</loc>
  <lastmod>2026-08-21T20:59:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間減衰文脈による顕著物体検出の統合的手法（SAC-Net: Spatial Attenuation Context for Salient Object Detection）</news:title>
   <news:publication_date>2026-08-21T20:59:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725781</loc>
  <lastmod>2026-08-21T20:59:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波で指の個別動作を読み取るためのアンサンブル学習（An Ensemble Learning Based Classification of Individual Finger Movement from EEG）</news:title>
   <news:publication_date>2026-08-21T20:59:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725779</loc>
  <lastmod>2026-08-21T20:58:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層無監督ドメイン適応の高速化（Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning）</news:title>
   <news:publication_date>2026-08-21T20:58:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725777</loc>
  <lastmod>2026-08-21T20:07:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期的アニーリングスケジュールによるKL消失の抑制（Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing）</news:title>
   <news:publication_date>2026-08-21T20:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725775</loc>
  <lastmod>2026-08-21T19:56:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ImageNetの学習済み分類層を活かす転移学習の再考（Enhanced Transfer Learning with ImageNet Trained Classification Layer）</news:title>
   <news:publication_date>2026-08-21T19:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725773</loc>
  <lastmod>2026-08-21T19:56:02Z</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>2026-08-21T19:56:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725771</loc>
  <lastmod>2026-08-21T19:55:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習とセグメンテーション情報をGANで組み合わせた学習データ非依存の画像登録（COMBINING TRANSFER LEARNING AND SEGMENTATION INFORMATION WITH GANS FOR TRAINING DATA INDEPENDENT IMAGE REGISTRATION）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/725769</loc>
  <lastmod>2026-08-21T19:55:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約なしの顔表情ユニット検出を潜在特徴領域で行う（Unconstrained Facial Action Unit Detection via Latent Feature Domain）</news:title>
   <news:publication_date>2026-08-21T19:55:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725767</loc>
  <lastmod>2026-08-21T19:55:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Iris R-CNNによる非協調環境下の虹彩分割（Iris R-CNN: Accurate Iris Segmentation in Non-cooperative Environment）</news:title>
   <news:publication_date>2026-08-21T19:55:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725765</loc>
  <lastmod>2026-08-21T19:54:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意ショット学習のための特徴生成フレームワーク（f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning）</news:title>
   <news:publication_date>2026-08-21T19:54:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725763</loc>
  <lastmod>2026-08-21T19:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種表現で言語と知識をつなぐ手法（Connecting Language and Knowledge with Heterogeneous Representations for Neural Relation Extraction）</news:title>
   <news:publication_date>2026-08-21T19:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725761</loc>
  <lastmod>2026-08-21T18:52:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイクル一貫性を用いた画像→キャプションのエンドツーエンド学習（End-to-End Learning Using Cycle Consistency for Image-to-Caption Transformations）</news:title>
   <news:publication_date>2026-08-21T18:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725759</loc>
  <lastmod>2026-08-21T18:52:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医用画像報告の知識駆動型自動生成（Knowledge-driven Encode, Retrieve, Paraphrase）</news:title>
   <news:publication_date>2026-08-21T18:52:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725757</loc>
  <lastmod>2026-08-21T18:52:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次のKolmogorov–Smirnov検定（A Higher-Order Kolmogorov-Smirnov Test）</news:title>
   <news:publication_date>2026-08-21T18:52:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725755</loc>
  <lastmod>2026-08-21T18:52:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差非局所注意ネットワークによる画像復元（Residual Non-Local Attention Networks for Image Restoration）</news:title>
   <news:publication_date>2026-08-21T18:52:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725753</loc>
  <lastmod>2026-08-21T18:51:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>査読理解のための論証マイニング（Argument Mining for Understanding Peer Reviews）</news:title>
   <news:publication_date>2026-08-21T18:51:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725751</loc>
  <lastmod>2026-08-21T18:51:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁気共鳻画像再構成のための変換学習（Transform Learning for Magnetic Resonance Image Reconstruction: From Model-based Learning to Building Neural Networks）</news:title>
   <news:publication_date>2026-08-21T18:51:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725749</loc>
  <lastmod>2026-08-21T18:00:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>成長次元における最適線形識別器（OPTIMAL LINEAR DISCRIMINATORS FOR THE DISCRETE CHOICE MODEL IN GROWING DIMENSIONS）</news:title>
   <news:publication_date>2026-08-21T18:00:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725747</loc>
  <lastmod>2026-08-21T17:59:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>真のバッチ弟子学習と深層サクセッサーフィーチャー（Truly Batch Apprenticeship Learning with Deep Successor Features）</news:title>
   <news:publication_date>2026-08-21T17:59:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725745</loc>
  <lastmod>2026-08-21T17:58:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率ジャンプ線形系の安全な学習ベース制御（Safe Learning-Based Control of Stochastic Jump Linear Systems: a Distributionally Robust Approach）</news:title>
   <news:publication_date>2026-08-21T17:58:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725743</loc>
  <lastmod>2026-08-21T17:58:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス組織病理画像分類のための畳み込みニューラルネットワーク（Convolutional Neural Networks for Multi-class Histopathology Image Classification）</news:title>
   <news:publication_date>2026-08-21T17:58:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725741</loc>
  <lastmod>2026-08-21T17:58:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lasso Weighted k-meansが示す高次元クラスタリングの新基準（A Strongly Consistent Sparse k-means Clustering with Direct l1 Penalization on Variable Weights）</news:title>
   <news:publication_date>2026-08-21T17:58:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725739</loc>
  <lastmod>2026-08-21T17:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResNet型畳み込みニューラルネットワークの近似と非パラメトリック推定（Approximation and Non-parametric Estimation of ResNet-type Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-21T17:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725737</loc>
  <lastmod>2026-08-21T17:06:17Z</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の堅牢性の形式化（A Formalization of Robustness for Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-21T17:06:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725735</loc>
  <lastmod>2026-08-21T17:06:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-means初期化の一般化（Generalization of k-means Related Algorithms）</news:title>
   <news:publication_date>2026-08-21T17:06:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725733</loc>
  <lastmod>2026-08-21T17:05:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データと半教師あり学習で小規模・不均衡データを活用する手法（Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets）</news:title>
   <news:publication_date>2026-08-21T17:05:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725731</loc>
  <lastmod>2026-08-21T17:04:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>持続的気象パターン予測のための混合エキスパートモデル（A mixture of experts model for predicting persistent weather patterns）</news:title>
   <news:publication_date>2026-08-21T17:04:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725729</loc>
  <lastmod>2026-08-21T17:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別的部分グラフ学習によるネットワーク状態予測（Discriminative Subgraph Learning via Sparse Self-Representation）</news:title>
   <news:publication_date>2026-08-21T17:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725727</loc>
  <lastmod>2026-08-21T17:04:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SNR適応型ID-OCTAによる血管可視化の精度向上（SNR-adaptive ID-OCTA）</news:title>
   <news:publication_date>2026-08-21T17:04:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725725</loc>
  <lastmod>2026-08-21T17:03:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速アップリンク割当てとNOMAへのFederated Learning応用（Fast Uplink Grant for NOMA: a Federated Learning based Approach）</news:title>
   <news:publication_date>2026-08-21T17:03:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725723</loc>
  <lastmod>2026-08-21T16:12:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルによる近似クエリ処理（Approximate Query Processing for Data Exploration using Deep Generative Models）</news:title>
   <news:publication_date>2026-08-21T16:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725721</loc>
  <lastmod>2026-08-21T16:12:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル認識型関数混合ネットワークによる分光超解像（Pixel-aware Deep Function-mixture Network for Spectral Super-Resolution）</news:title>
   <news:publication_date>2026-08-21T16:12:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725719</loc>
  <lastmod>2026-08-21T16:12:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多属性選択率推定における深層学習の応用（Multi-Attribute Selectivity Estimation Using Deep Learning）</news:title>
   <news:publication_date>2026-08-21T16:12:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725717</loc>
  <lastmod>2026-08-21T16:11:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段階圧縮によるニューラルネットワークの効率化（MUSCO: Multi-Stage Compression of neural networks）</news:title>
   <news:publication_date>2026-08-21T16:11:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725715</loc>
  <lastmod>2026-08-21T16:11:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木星の大赤斑の深さを探る（Determining the depth of Jupiter’s Great Red Spot with Juno: a Slepian approach）</news:title>
   <news:publication_date>2026-08-21T16:11:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725713</loc>
  <lastmod>2026-08-21T16:11:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタ整列を教師で促す手法（Cluster Alignment with a Teacher for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-08-21T16:11:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725711</loc>
  <lastmod>2026-08-21T16:10:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高変形ソフト粒子の圧縮挙動とジャミング後の力学（Soft grain compression: beyond the jamming point）</news:title>
   <news:publication_date>2026-08-21T16:10:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725709</loc>
  <lastmod>2026-08-21T15:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深海面における非相互作用重力波の理論的展開（Non-interacting gravity waves on the surface of a deep fluid）</news:title>
   <news:publication_date>2026-08-21T15:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725707</loc>
  <lastmod>2026-08-21T15:19:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者抽出ニューラルネットワークの最適化（Optimization of Speaker Extraction Neural Network with Magnitude and Temporal Spectrum Approximation Loss）</news:title>
   <news:publication_date>2026-08-21T15:19:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725705</loc>
  <lastmod>2026-08-21T15:19:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な製品埋め込みに基づく深層レコメンダーエンジン（Deep recommender engine based on efficient product embeddings neural pipeline）</news:title>
   <news:publication_date>2026-08-21T15:19:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725703</loc>
  <lastmod>2026-08-21T15:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間量子化を用いた変分推論による敵対的耐性（Variational Inference with Latent Space Quantization for Adversarial Resilience）</news:title>
   <news:publication_date>2026-08-21T15:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725701</loc>
  <lastmod>2026-08-21T15:17:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HAXMLNetが示す極端多ラベル分類の新潮流（HAXMLNet: Hierarchical Attention Network for Extreme Multi-Label Text Classification）</news:title>
   <news:publication_date>2026-08-21T15:17:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725699</loc>
  <lastmod>2026-08-21T15:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床テキストにおける最短依存経路ベースのLSTMによる関係抽出（Relation extraction between the clinical entities based on the shortest dependency path based LSTM）</news:title>
   <news:publication_date>2026-08-21T15:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725697</loc>
  <lastmod>2026-08-21T15:17:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>要約生成を特徴量化してフェイクニュース検出を改善する手法（Neural Abstractive Text Summarization and Fake News Detection）</news:title>
   <news:publication_date>2026-08-21T15:17:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>