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   <news:title>MIMO DF中継路における深層学習検出ネットワーク（Deep Learning Detection Networks in MIMO Decode-Forward Relay Channels）</news:title>
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   <news:title>高齢者支援する感情応答型ロボット伴走者（An Affective Robot Companion for Assisting the Elderly in a Cognitive Game Scenario）</news:title>
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   <news:title>限られた学習データにおける深層学習の最前線と課題（STATE–OF–THE–ART AND GAPS FOR DEEP LEARNING ON LIMITED TRAINING DATA IN REMOTE SENSING）</news:title>
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   <news:title>Landsatと全球標高データを融合した三次元都市構造マッピング（Mapping Three-dimensional Urban Structure by Fusing Landsat and Global Elevation Data）</news:title>
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   <news:title>Deepwoundを用いた術後創傷評価と手術部位監視（Deepwound: Automated Postoperative Wound Assessment and Surgical Site Surveillance through Convolutional Neural Networks）</news:title>
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   <news:title>IoTにおける情報鮮度の最適化（Joint Status Sampling and Updating for Minimizing Age of Information in the Internet of Things）</news:title>
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   <news:title>シリウスAbの探索：コロナグラフィー熱赤外高コントラストイメージングにおけるアルゴリズム的背景推定とPSF推定性能の比較 (The hunt for Sirius Ab: Comparison of algorithmic sky and PSF estimation performance in deep coronagraphic thermal-IR high contrast imaging)</news:title>
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   <news:title>効率的なキーワード検出における時間遅延ニューラルネットワークの活用（Efficient keyword spotting using time delay neural networks）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>胸部X線画像における汎用的肺領域分割の枠組み（A Generic Approach to Lung Field Segmentation from Chest Radiographs using Deep Space and Shape Learning）</news:title>
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    <news:language>ja</news:language>
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   <news:title>GPUアーキテクチャ向けデータ並列ハッシュ法の概観（Data-Parallel Hashing Techniques for GPU Architectures）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>ソースコードにおける自動脆弱性検出の深層表現学習（Automated Vulnerability Detection in Source Code Using Deep Representation Learning）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>構造化ベイズ型ガウス過程潜在変数モデルによる高次元逆問題の扱い（Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversion）</news:title>
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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>GANを使った多様体正則化による半教師あり学習（Manifold regularization with GANs for semi-supervised learning）</news:title>
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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>生成的事前分布による位相復元（Phase Retrieval Under a Generative Prior）</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>銀河中心領域におけるVVVサーベイのRR Lyrae集団（THE VVV Survey RR Lyrae Population in the Galactic Centre Region）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>量子機械学習の基礎（The fundamentals of quantum machine learning）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>コーデッド・データシャッフリングの基礎限界（On the Fundamental Limits of Coded Data Shufﬂing for Distributed Machine Learning）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization（Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization）</news:title>
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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>産業用マルチセンサー衝突回避におけるLiDARとカメラ検出の融合（LiDAR and Camera Detection Fusion in a Real-Time Industrial Multi-Sensor Collision Avoidance System）</news:title>
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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>高次元生物データから細胞の目的関数を推定する意義（Estimating Cellular Goals from High-Dimensional Biological Data）</news:title>
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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>大規模導入実験科目の変容（Transforming a large introductory lab course）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-25T17:05:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepMoveによる場所表現の学習（DeepMove: Learning Place Representations through Large Scale Movement Data）</news:title>
   <news:publication_date>2026-05-25T17:05:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/694182</loc>
  <lastmod>2026-05-25T16:14:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>モールス符号データセットと機械学習への応用（Morse Code Datasets for Machine Learning）</news:title>
   <news:publication_date>2026-05-25T16:14:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/694180</loc>
  <lastmod>2026-05-25T16:14:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Make ℓ1 Regularization Effective in Training Sparse CNN（Make ℓ1 Regularization Effective in Training Sparse CNN）</news:title>
   <news:publication_date>2026-05-25T16:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-25T16:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークにおける抽象推論の計測（Measuring abstract reasoning in neural networks）</news:title>
   <news:publication_date>2026-05-25T16:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/694176</loc>
  <lastmod>2026-05-25T16:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>友が多すぎると敵はいらない？—分類モデルの脆弱性と性能の同根性（With Friends Like These, Who Needs Adversaries?）</news:title>
   <news:publication_date>2026-05-25T16:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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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>差分プライバシー下での偽発見率制御（Differentially Private False Discovery Rate Control）</news:title>
   <news:publication_date>2026-05-25T16:13:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-25T16:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>複数の位置ベース類似度を組み込んだ協調ランキングによる店舗提案（A Collaborative Ranking Model with Multiple Location-based Similarities for Venue Suggestion）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-25T16:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>動的グラウンド集合で強化した逐次決定論的点過程による教師ありビデオ要約（Reinforcing Sequential Determinantal Point Processes with Dynamic Ground Sets for Supervised Video Summarization）</news:title>
   <news:publication_date>2026-05-25T16:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694168</loc>
  <lastmod>2026-05-25T15:21:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔軟な深層学習特化のためのハードウェア・ソフトウェア設計図（A Hardware-Software Blueprint for Flexible Deep Learning Specialization）</news:title>
   <news:publication_date>2026-05-25T15:21:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694166</loc>
  <lastmod>2026-05-25T15:12:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散変分表現学習（Distributed Variational Representation Learning）</news:title>
   <news:publication_date>2026-05-25T15:12:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694164</loc>
  <lastmod>2026-05-25T15:11:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UIパターンを計測する計算手法（A Computational Method for Evaluating UI Patterns）</news:title>
   <news:publication_date>2026-05-25T15:11:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694162</loc>
  <lastmod>2026-05-25T15:11:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠中の脳波イベントを一括検出する深層学習アーキテクチャ（A DEEP LEARNING ARCHITECTURE TO DETECT EVENTS IN EEG SIGNALS DURING SLEEP）</news:title>
   <news:publication_date>2026-05-25T15:11:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694160</loc>
  <lastmod>2026-05-25T15:11:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習の熱力学（The Thermodynamics of Machine Learning）</news:title>
   <news:publication_date>2026-05-25T15:11:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694158</loc>
  <lastmod>2026-05-25T15:11:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Indy：産業施設での空間ナビゲーション技能を鍛える仮想現実ゲーム（Indy: a virtual reality multi-player game for navigation skills training）</news:title>
   <news:publication_date>2026-05-25T15:11:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694156</loc>
  <lastmod>2026-05-25T15:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測データに基づく連続・多次元意思決定の最適化（Optimization over Continuous and Multi-dimensional Decisions with Observational Data）</news:title>
   <news:publication_date>2026-05-25T15:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694154</loc>
  <lastmod>2026-05-25T14:19:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイバーバンドルを用いた現場波面補正による二光子レンズレスマイクロ内視鏡（Two-Photon Lensless Micro-endoscopy with in-situ Wavefront Correction）</news:title>
   <news:publication_date>2026-05-25T14:19:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694152</loc>
  <lastmod>2026-05-25T14:10:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>死後（ポストモーテム）虹彩画像の自動セグメンテーション（Post-mortem Iris Image Segmentation with Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-25T14:10:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694150</loc>
  <lastmod>2026-05-25T14:10:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復評価を導入したLSTMの設計思想と実装的示唆（Iterative evaluation of LSTM cells）</news:title>
   <news:publication_date>2026-05-25T14:10:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694148</loc>
  <lastmod>2026-05-25T14:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実数空間における木構造の線形表現（Trees in the Real Field）</news:title>
   <news:publication_date>2026-05-25T14:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694146</loc>
  <lastmod>2026-05-25T14:09:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中スラスタのモデリングとソフトフォールト診断（Modeling and Soft-fault Diagnosis of Underwater Thrusters with Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-25T14:09:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694144</loc>
  <lastmod>2026-05-25T14:08:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数の分布を生成する深層モデル VFunc: 関数空間で不確実性を扱う発想（VFunc: A Deep Generative Model for Functions）</news:title>
   <news:publication_date>2026-05-25T14:08:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694142</loc>
  <lastmod>2026-05-25T14:08:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列の統計的依存性を階層的相関再構成で利用する（Exploiting statistical dependencies of time series with hierarchical correlation reconstruction）</news:title>
   <news:publication_date>2026-05-25T14:08:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694140</loc>
  <lastmod>2026-05-25T13:16:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分カプセルによる画像解析と合成（Variational Capsules for Image Analysis and Synthesis）</news:title>
   <news:publication_date>2026-05-25T13:16:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694138</loc>
  <lastmod>2026-05-25T13:16:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エントロピーに基づくバルク幾何学の再構築（Bulk geometry from entanglement entropy of CFT）</news:title>
   <news:publication_date>2026-05-25T13:16:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694136</loc>
  <lastmod>2026-05-25T13:15:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型ニューラルネットワークによるユーザー再訪予測（A Recurrent Neural Network Survival Model: Predicting Web User Return Time）</news:title>
   <news:publication_date>2026-05-25T13:15:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694134</loc>
  <lastmod>2026-05-25T13:14:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変精度LSTMをFPGAで加速するための設計とライブラリ拡張（FINN-L: Library Extensions and Design Trade-off Analysis for Variable Precision LSTM Networks on FPGAs）</news:title>
   <news:publication_date>2026-05-25T13:14:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694132</loc>
  <lastmod>2026-05-25T13:14:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブルPPGによる心臓異常の検出（Recognising Cardiac Abnormalities in Wearable Device Photoplethysmography (PPG) with Deep Learning）</news:title>
   <news:publication_date>2026-05-25T13:14:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694130</loc>
  <lastmod>2026-05-25T13:14:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一走行からキロメートル規模の実装可能なナビゲーション方策を学習する（Learning Deployable Navigation Policies at Kilometer Scale from a Single Traversal）</news:title>
   <news:publication_date>2026-05-25T13:14:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694128</loc>
  <lastmod>2026-05-25T13:13:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>従業員離職の予測と予防介入（Proactive Intervention to Downtrend Employee Attrition using Artificial Intelligence Techniques）</news:title>
   <news:publication_date>2026-05-25T13:13:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694126</loc>
  <lastmod>2026-05-25T12:21:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔軟なゲートを持つ再帰型ニューラルネットワーク（Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions）</news:title>
   <news:publication_date>2026-05-25T12:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694124</loc>
  <lastmod>2026-05-25T12:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>死後虹彩の提示攻撃検出（Presentation Attack Detection for Cadaver Iris）</news:title>
   <news:publication_date>2026-05-25T12:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694122</loc>
  <lastmod>2026-05-25T12:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胎児腹部大動脈のリアルタイム径測定に向けた時間方向畳み込みネットワーク（Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound）</news:title>
   <news:publication_date>2026-05-25T12:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694120</loc>
  <lastmod>2026-05-25T12:19:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3C 279の史上最大ガンマ線フレアの観測と理論的課題（Challenges in reconciling observations and theory of the brightest high-energy flare ever of 3C 279）</news:title>
   <news:publication_date>2026-05-25T12:19:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694118</loc>
  <lastmod>2026-05-25T12:19:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>死後虹彩認識における画像特徴の知覚（Perception of Image Features in Post-Mortem Iris Recognition: Humans vs Machines）</news:title>
   <news:publication_date>2026-05-25T12:19:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694116</loc>
  <lastmod>2026-05-25T12:19:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アパレル属性分類のための二層混合ネットワークアンサンブル（Two-Layer Mixture Network Ensemble for Apparel Attributes Classification）</news:title>
   <news:publication_date>2026-05-25T12:19:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694114</loc>
  <lastmod>2026-05-25T12:19:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeSTNetによる空間変形の解消と頑健化（DeSTNet: Densely Fused Spatial Transformer Networks）</news:title>
   <news:publication_date>2026-05-25T12:19:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694112</loc>
  <lastmod>2026-05-25T11:27:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異点回避の学習（Learning Singularity Avoidance）</news:title>
   <news:publication_date>2026-05-25T11:27:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694110</loc>
  <lastmod>2026-05-25T11:26:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負値行列分解のための改良SVD初期化と低ランク補正（Improved SVD-based Initialization for Nonnegative Matrix Factorization using Low-Rank Correction）</news:title>
   <news:publication_date>2026-05-25T11:26:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694108</loc>
  <lastmod>2026-05-25T11:26:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANにおける壊滅的忘却とモード崩壊の関係（Catastrophic forgetting and mode collapse in GANs）</news:title>
   <news:publication_date>2026-05-25T11:26:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694106</loc>
  <lastmod>2026-05-25T11:25:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠測データ下の因果探索（Causal Discovery in the Presence of Missing Data）</news:title>
   <news:publication_date>2026-05-25T11:25:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694104</loc>
  <lastmod>2026-05-25T11:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によるエンドツーエンド・クラスタリング（Learning Neural Models for End-to-End Clustering）</news:title>
   <news:publication_date>2026-05-25T11:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694102</loc>
  <lastmod>2026-05-25T11:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Medusaが示すメモリ相互接続の新しい設計（Medusa: A Scalable Interconnect for Many-Port DNN Accelerators and Wide DRAM Controller Interfaces）</news:title>
   <news:publication_date>2026-05-25T11:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694100</loc>
  <lastmod>2026-05-25T11:24:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マクロ経済時系列のクラスタリング手法が変える構造分析（Clustering Macroeconomic Time Series）</news:title>
   <news:publication_date>2026-05-25T11:24:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694098</loc>
  <lastmod>2026-05-25T10:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース範囲制約学習と医用画像の自動グレーディング（Sparse Range-constrained Learning and Its Application for Medical Image Grading）</news:title>
   <news:publication_date>2026-05-25T10:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694096</loc>
  <lastmod>2026-05-25T10:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ESSにおけるソフトウェア中心の中性子検出データ処理（Software-based data acquisition and processing for neutron detectors at European Spallation Source — early experience from four detector designs）</news:title>
   <news:publication_date>2026-05-25T10:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694094</loc>
  <lastmod>2026-05-25T10:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動物体解析：未来位置と軌跡予測の概観（Moving Objects Analytics: Survey on Future Location &amp;amp; Trajectory Prediction Methods）</news:title>
   <news:publication_date>2026-05-25T10:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694092</loc>
  <lastmod>2026-05-25T10:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLU深層ニューラルネットワークと線形有限要素の関係（ReLU Deep Neural Networks and Linear Finite Elements）</news:title>
   <news:publication_date>2026-05-25T10:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694090</loc>
  <lastmod>2026-05-25T10:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型深層信念ネットワークから抽出する知識によるリアルタイム決定制御（Knowledge Extracted from Recurrent Deep Belief Network for Real Time Deterministic Control）</news:title>
   <news:publication_date>2026-05-25T10:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694088</loc>
  <lastmod>2026-05-25T10:23:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データ解析のための適応学習型再帰時系列ディープビリーフネットワーク（Adaptive Learning Method of Recurrent Temporal Deep Belief Network to Analyze Time Series Data）</news:title>
   <news:publication_date>2026-05-25T10:23:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694086</loc>
  <lastmod>2026-05-25T10:23:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な深度推定を実現する注意ベース分類ネットワーク（Deep attention-based classification network for robust depth prediction）</news:title>
   <news:publication_date>2026-05-25T10:23:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694084</loc>
  <lastmod>2026-05-25T09:32:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書知識を取り込む中国語単語分割の新手法（Neural Chinese Word Segmentation with Dictionary Knowledge）</news:title>
   <news:publication_date>2026-05-25T09:32:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694082</loc>
  <lastmod>2026-05-25T09:32:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列予測のための量子リザバーコンピュータの最適化（Optimizing a quantum reservoir computer for time series prediction）</news:title>
   <news:publication_date>2026-05-25T09:32:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694080</loc>
  <lastmod>2026-05-25T09:31:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習時間を短縮するAdaptive DBNの工夫（Shortening Time Required for Adaptive Structural Learning Method of Deep Belief Network with Multi-Modal Data Arrangement）</news:title>
   <news:publication_date>2026-05-25T09:31:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694078</loc>
  <lastmod>2026-05-25T09:31:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンスベースのエントロピー・ファジィSVMによる不均衡データ分類（Instance-based entropy fuzzy support vector machine for imbalanced data）</news:title>
   <news:publication_date>2026-05-25T09:31:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694076</loc>
  <lastmod>2026-05-25T09:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Decoder-Encoder出力ノイズを用いた生成的敵対ネットワーク（Generative Adversarial Networks with Decoder-Encoder Output Noise）</news:title>
   <news:publication_date>2026-05-25T09:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694074</loc>
  <lastmod>2026-05-25T09:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所特徴を持つ階層ベイズ線形回帰による確率的力学の近似 (A Hierarchical Bayesian Linear Regression Model with Local Features for Stochastic Dynamics Approximation)</news:title>
   <news:publication_date>2026-05-25T09:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694072</loc>
  <lastmod>2026-05-25T09:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前確率シフト下の定量化：比率推定器とその拡張（Quantification Under Prior Probability Shift: the Ratio Estimator and its Extensions）</news:title>
   <news:publication_date>2026-05-25T09:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694070</loc>
  <lastmod>2026-05-25T08:39:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声からの感情認識：関連する特徴選択と多数決手法の強調（Emotion Recognition from Human Speech: Emphasizing on Relevant Feature Selection and Majority Voting Technique）</news:title>
   <news:publication_date>2026-05-25T08:39:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694068</loc>
  <lastmod>2026-05-25T08:38:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生産歩留まりデータ解析における興味深いプロットの発見（Discovering Interesting Plots in Production Yield Data Analytics）</news:title>
   <news:publication_date>2026-05-25T08:38:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694066</loc>
  <lastmod>2026-05-25T08:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seq2Seqによるマルチモーダル感情分析（Multimodal Sequence to Sequence Models for Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-25T08:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694064</loc>
  <lastmod>2026-05-25T08:38:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚注意の集約による深層不均衡属性分類（Deep Imbalanced Attribute Classification using Visual Attention Aggregation）</news:title>
   <news:publication_date>2026-05-25T08:38:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694062</loc>
  <lastmod>2026-05-25T08:38:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化におけるGDAとOGDAの極限点の理解（The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization）</news:title>
   <news:publication_date>2026-05-25T08:38:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694060</loc>
  <lastmod>2026-05-25T08:37:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接障壁領域における232Thと238Uの光核分裂研究（Near-barrier Photofission in 232Th and 238U）</news:title>
   <news:publication_date>2026-05-25T08:37:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694058</loc>
  <lastmod>2026-05-25T08:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多数個体の自己励起型情報拡散過程の漸近挙動（The asymptotic behaviors of self excitation information diffusion processes for a large number of individuals）</news:title>
   <news:publication_date>2026-05-25T08:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694056</loc>
  <lastmod>2026-05-25T07:46:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層構造生成モデルの実務的インパクト（Deep Structured Generative Models）</news:title>
   <news:publication_date>2026-05-25T07:46:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694054</loc>
  <lastmod>2026-05-25T07:37:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイナンスのための量子コンピューティング：概観と展望（Quantum computing for finance: overview and prospects）</news:title>
   <news:publication_date>2026-05-25T07:37:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694052</loc>
  <lastmod>2026-05-25T07:37:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光に現れる量子タービュランスの構造（Quantum Turbulent Structure in Light）</news:title>
   <news:publication_date>2026-05-25T07:37:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694050</loc>
  <lastmod>2026-05-25T07:37:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常検出の統一的枠組み（A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks）</news:title>
   <news:publication_date>2026-05-25T07:37:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694048</loc>
  <lastmod>2026-05-25T07:36:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepDiffによるヒストン修飾からの差次的遺伝子発現予測（DeepDiff: Deep-learning for predicting Differential gene expression from histone modifications）</news:title>
   <news:publication_date>2026-05-25T07:36:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694046</loc>
  <lastmod>2026-05-25T07:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広視野での地上層適応光学による像質改善（Improved Image Quality Over 10′ Fields with the ‘Imaka Ground Layer Adaptive Optics Experiment）</news:title>
   <news:publication_date>2026-05-25T07:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694044</loc>
  <lastmod>2026-05-25T07:36:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>包括的なアルツハイマー病進行予測のための深層学習（Deep learning for comprehensive forecasting of Alzheimer’s Disease progression）</news:title>
   <news:publication_date>2026-05-25T07:36:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694042</loc>
  <lastmod>2026-05-25T06:44:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化された勾配ブースティング（Automatic Gradient Boosting）</news:title>
   <news:publication_date>2026-05-25T06:44:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694040</loc>
  <lastmod>2026-05-25T06:36:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタイライズド画像キャプション生成における適応学習と注意機構（Factual or Emotional: Stylized Image Captioning with Adaptive Learning and Attention）</news:title>
   <news:publication_date>2026-05-25T06:36:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694038</loc>
  <lastmod>2026-05-25T06:35:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密度推定器を教えることで学ぶ暗黙的生成モデル（Learning Implicit Generative Models By Teaching Density Estimators）</news:title>
   <news:publication_date>2026-05-25T06:35:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694036</loc>
  <lastmod>2026-05-25T06:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子着想の古典アルゴリズムによるレコメンデーション（A quantum-inspired classical algorithm for recommendation systems）</news:title>
   <news:publication_date>2026-05-25T06:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694034</loc>
  <lastmod>2026-05-25T06:35:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース深層強化学習の理論的保証を与えるアルゴリズムフレームワーク（ALGORITHMIC FRAMEWORK FOR MODEL-BASED DEEP REINFORCEMENT LEARNING WITH THEORETICAL GUARANTEES）</news:title>
   <news:publication_date>2026-05-25T06:35:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694032</loc>
  <lastmod>2026-05-25T06:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Google Street Viewから学ぶ道路の実情（Street Sense: Learning from Google Street View）</news:title>
   <news:publication_date>2026-05-25T06:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694030</loc>
  <lastmod>2026-05-25T06:34:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>天体イベントの画像列を直接学習する深層学習（Deep Learning for Image Sequence Classification of Astronomical Events）</news:title>
   <news:publication_date>2026-05-25T06:34:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694028</loc>
  <lastmod>2026-05-25T05:43:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自由呼吸・非同期心臓MRIの高速再構成を実現するMoDL‑STORM（MODEL-BASED FREE‑BREATHING CARDIAC MRI RECONSTRUCTION USING DEEP LEARNED &amp;amp; STORM PRIORS: MODL‑STORM）</news:title>
   <news:publication_date>2026-05-25T05:43:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/694026</loc>
  <lastmod>2026-05-25T05:33:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケールを効率的に学ぶBig‑Little Net（BIG-LITTLE NET: AN EFFICIENT MULTI-SCALE FEATURE REPRESENTATION FOR VISUAL AND SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-05-25T05:33:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-25T04:41:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-25T04:40:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-25T04:40:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-25T04:39:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-25T03:48:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-25T03:48:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-25T03:46:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>低リソース音声データにおける深層学習による音声転写の実践（Deep Learning for Audio Transcription on Low-Resource Datasets）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Mask R-CNNによる病変解析と診断（Lesion Analysis and Diagnosis with Mask-RCNN）</news:title>
   <news:publication_date>2026-05-25T02:55:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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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>銀河地図作成とSkyMapperによる内部ハローの構造解析（Galactic cartography with SkyMapper: I. Population sub-structure and the stellar number density of the inner halo）</news:title>
   <news:publication_date>2026-05-25T02:54:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-25T02:54:07Z</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>不完全かつ異種混在データを扱うVAEの枠組み（Handling Incomplete Heterogeneous Data using VAEs）</news:title>
   <news:publication_date>2026-05-25T02:53:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-25T02:53:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習によるパートン・シャワーの模倣（Deep Learning as a Parton Shower）</news:title>
   <news:publication_date>2026-05-25T02:53:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-25T02:01:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>窓開閉の行動モデルに深層学習を使う意義（Window Opening Model using Deep Learning Methods）</news:title>
   <news:publication_date>2026-05-25T01:52:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>本質テンソル学習によるマルチビュースペクトルクラスタリング（Essential Tensor Learning for Multi-view Spectral Clustering）</news:title>
   <news:publication_date>2026-05-25T01:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693966</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的マルチスケールLSTMの再検討（Revisiting the Hierarchical Multiscale LSTM）</news:title>
   <news:publication_date>2026-05-25T01:51:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-25T01:51:22Z</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>非パラメトリックベイズ重複確率的ブロックモデルの小分散漸近 (Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels)</news:title>
   <news:publication_date>2026-05-25T01:51:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲーム理論に基づく深層ニューラルネットワークの近似検証（A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees）</news:title>
   <news:publication_date>2026-05-25T01:50:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在的行動タイプを同定するための実験の最適設計 (Optimal design of experiments to identify latent behavioral types)</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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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>凸制約付き目的関数の双対最適化と勾配リプシッツ性仮定不要の収束保証（Dual optimization for convex constrained objectives without the gradient-Lipschitz assumption）</news:title>
   <news:publication_date>2026-05-25T00:59:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693952</loc>
  <lastmod>2026-05-25T00:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形構造方程式モデルの代数的同値性（Algebraic Equivalence of Linear Structural Equation Models）</news:title>
   <news:publication_date>2026-05-25T00:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693950</loc>
  <lastmod>2026-05-25T00:58:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群処理のためのマルチ解像度木ネットワーク（Multiresolution Tree Networks for 3D Point Cloud Processing）</news:title>
   <news:publication_date>2026-05-25T00:58:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693948</loc>
  <lastmod>2026-05-25T00:58:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習のハイパーパラメータ最適化ライブラリ DLOPT（DLOPT: Deep Learning Optimization Library）</news:title>
   <news:publication_date>2026-05-25T00:58:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693946</loc>
  <lastmod>2026-05-25T00:58:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推薦システムにおける表現のプライバシーと公平性を守る敵対的訓練（Privacy and Fairness in Recommender Systems via Adversarial Training of User Representations）</news:title>
   <news:publication_date>2026-05-25T00:58:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693944</loc>
  <lastmod>2026-05-25T00:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アクティブターゲットTPCデータにおける自動軌跡認識（Automatic trajectory recognition in Active Target Time Projection Chambers data by means of hierarchical clustering）</news:title>
   <news:publication_date>2026-05-25T00:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693942</loc>
  <lastmod>2026-05-25T00:06:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>走行計画と通信を同時に最適化する強化学習アプローチ（A Reinforcement Learning Approach to Jointly Adapt Vehicular Communications and Planning for Optimized Driving）</news:title>
   <news:publication_date>2026-05-25T00:06:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693940</loc>
  <lastmod>2026-05-25T00:05:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロブログ上の自動デマ検出の総説（Automatic Rumor Detection on Microblogs: A Survey）</news:title>
   <news:publication_date>2026-05-25T00:05:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693938</loc>
  <lastmod>2026-05-25T00:04:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種情報ネットワークの包括的転写による埋め込み学習の簡素化（Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks）</news:title>
   <news:publication_date>2026-05-25T00:04:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693936</loc>
  <lastmod>2026-05-25T00:04:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Belief Networkからの知識獲得によるファインチューニング手法（Fine Tuning Method by using Knowledge Acquisition from Deep Belief Network）</news:title>
   <news:publication_date>2026-05-25T00:04:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693934</loc>
  <lastmod>2026-05-25T00:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み環境での深層学習による笑顔検出（Embedded Implementation of a Deep Learning Smile Detector）</news:title>
   <news:publication_date>2026-05-25T00:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693932</loc>
  <lastmod>2026-05-25T00:03:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層生成アルゴリズムによるDBNの適応学習法（An Adaptive Learning Method of Deep Belief Network by Layer Generation Algorithm）</news:title>
   <news:publication_date>2026-05-25T00:03:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693930</loc>
  <lastmod>2026-05-24T23:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一動画デモから未知の作業を実行するためのタスクグラフ学習（Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration）</news:title>
   <news:publication_date>2026-05-24T23:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693928</loc>
  <lastmod>2026-05-24T23:12:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>振幅スペクトログラムからの位相再構成（PHASE RECONSTRUCTION FROM AMPLITUDE SPECTROGRAMS BASED ON VON-MISES-DISTRIBUTION DEEP NEURAL NETWORK）</news:title>
   <news:publication_date>2026-05-24T23:12:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693926</loc>
  <lastmod>2026-05-24T23:11:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RBMの適応学習法 — ニューロン生成と消去アルゴリズムによる最適化 (An Adaptive Learning Method of Restricted Boltzmann Machine by Neuron Generation and Annihilation Algorithm)</news:title>
   <news:publication_date>2026-05-24T23:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693924</loc>
  <lastmod>2026-05-24T23:10:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SceneEDNetによるシーンフロー推定（SceneEDNet: A Deep Learning Approach for Scene Flow Estimation）</news:title>
   <news:publication_date>2026-05-24T23:10:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693922</loc>
  <lastmod>2026-05-24T23:10:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペアワイズ共変量調整ブロックモデルによるコミュニティ検出（Pairwise Covariates-Adjusted Block Model for Community Detection）</news:title>
   <news:publication_date>2026-05-24T23:10:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693920</loc>
  <lastmod>2026-05-24T23:10:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムポリマーと一般化されたバーン過程（Random Polymers and Generalized Urn Processes）</news:title>
   <news:publication_date>2026-05-24T23:10:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693918</loc>
  <lastmod>2026-05-24T23:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一Tucker分解ネットワークを用いた可変ビット率の損失型画像圧縮（Learning a Single Tucker Decomposition Network for Lossy Image Compression with Multiple Bits-Per-Pixel Rates）</news:title>
   <news:publication_date>2026-05-24T23:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693916</loc>
  <lastmod>2026-05-24T22:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>竜巻による物的被害を予測するゼロ膨張ニューラルネットワーク（Predicting property damage from tornadoes with zero-inflated neural networks）</news:title>
   <news:publication_date>2026-05-24T22:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693914</loc>
  <lastmod>2026-05-24T22:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングによる脳アトラスの構築（Developing Brain Atlas through Deep Learning）</news:title>
   <news:publication_date>2026-05-24T22:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693912</loc>
  <lastmod>2026-05-24T22:17:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘルムホルツ法：知覚圧縮を使って機械学習の複雑性を下げる方法（The Helmholtz Method: Using Perceptual Compression to Reduce Machine Learning Complexity）</news:title>
   <news:publication_date>2026-05-24T22:17:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693910</loc>
  <lastmod>2026-05-24T22:17:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUに最適化されたセカント法に基づく次元削減アルゴリズム（A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction）</news:title>
   <news:publication_date>2026-05-24T22:17:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693908</loc>
  <lastmod>2026-05-24T22:16:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師あり学習における二値分類の新しい変分モデル (A New Variational Model for Binary Classification in the Supervised Learning Context)</news:title>
   <news:publication_date>2026-05-24T22:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693906</loc>
  <lastmod>2026-05-24T22:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等分散仮定による因果発見の単純化（On Causal Discovery with Equal Variance Assumption）</news:title>
   <news:publication_date>2026-05-24T22:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693904</loc>
  <lastmod>2026-05-24T22:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像における心胸郭比の自動推定のための教師なしドメイン適応（Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio）</news:title>
   <news:publication_date>2026-05-24T22:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693902</loc>
  <lastmod>2026-05-24T21:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>警察による殺害は誰か〜階層型LSTMに対する教師付きアテンションの導入（Who is Killed by Police: Introducing Supervised Attention for Hierarchical LSTMs）</news:title>
   <news:publication_date>2026-05-24T21:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693900</loc>
  <lastmod>2026-05-24T21:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AudioMNISTによる音声分野の説明可能なAIの試金石（AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark）</news:title>
   <news:publication_date>2026-05-24T21:15:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693898</loc>
  <lastmod>2026-05-24T21:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群に対する高忠実度意味的形状補完（High Fidelity Semantic Shape Completion for Point Clouds using Latent Optimization）</news:title>
   <news:publication_date>2026-05-24T21:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693896</loc>
  <lastmod>2026-05-24T21:13:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>材料空間の階層的可視化（Hierarchical Visualization of Materials Space with Graph Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-24T21:13:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693894</loc>
  <lastmod>2026-05-24T21:13:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンティティとテキストを同時に埋め込む手法（Jointly Embedding Entities and Text with Distant Supervision）</news:title>
   <news:publication_date>2026-05-24T21:13:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693892</loc>
  <lastmod>2026-05-24T21:13:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IGLOO: 長い系列を効率的に扱うための新しい切り口（IGLOO: Slicing the Feature Space to Represent Sequences）</news:title>
   <news:publication_date>2026-05-24T21:13:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693890</loc>
  <lastmod>2026-05-24T21:12:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>切り詰めた時間逆伝播で再帰ネットワークを学習する（On Training Recurrent Networks with Truncated Backpropagation Through Time in Speech Recognition）</news:title>
   <news:publication_date>2026-05-24T21:12:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693888</loc>
  <lastmod>2026-05-24T20:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初年次大型実験授業の変革がもたらした初期効果（Initial impacts of the transformation of a large introductory lab course focused on developing experimental skills and expert epistemology）</news:title>
   <news:publication_date>2026-05-24T20:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693886</loc>
  <lastmod>2026-05-24T20:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様なロボット行動の進化に向けた組合せ多目的進化アルゴリズムの提案（Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm）</news:title>
   <news:publication_date>2026-05-24T20:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693884</loc>
  <lastmod>2026-05-24T20:12:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大系列発散を用いたプロセス監視（Process Monitoring Using Maximum Sequence Divergence）</news:title>
   <news:publication_date>2026-05-24T20:12:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693882</loc>
  <lastmod>2026-05-24T20:12:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリックな学習-to-ランクの探求（Towards Non-Parametric Learning to Rank）</news:title>
   <news:publication_date>2026-05-24T20:12:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693880</loc>
  <lastmod>2026-05-24T20:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延情報下のオンライン評価：凸最適化の視点（Online Scoring with Delayed Information: A Convex Optimization Viewpoint）</news:title>
   <news:publication_date>2026-05-24T20:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693878</loc>
  <lastmod>2026-05-24T20:11:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習におけるアンサンブルカルマンフィルタを用いたスパースGaussian Process回帰（Ensemble Kalman Filtering for Online Gaussian Process Regression and Learning）</news:title>
   <news:publication_date>2026-05-24T20:11:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693876</loc>
  <lastmod>2026-05-24T20:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆の感情を捉える注意機構（An Attention Model for group-level emotion recognition）</news:title>
   <news:publication_date>2026-05-24T20:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693874</loc>
  <lastmod>2026-05-24T19:19:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数グラフのための扱いやすいn-距離（Tractable n-Metrics for Multiple Graphs）</news:title>
   <news:publication_date>2026-05-24T19:19:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693872</loc>
  <lastmod>2026-05-24T19:19:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル駆動の弱教師あり学習による多モーダル変形画像レジストレーションの実用化（Label-driven weakly-supervised learning for multimodal deformable image registration）</news:title>
   <news:publication_date>2026-05-24T19:19:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693870</loc>
  <lastmod>2026-05-24T19:18:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Talk The Walk: 地図と対話で観光客を導く対話型ナビゲーション（Talk The Walk: Navigating Grids in New York City through Grounded Dialogue）</news:title>
   <news:publication_date>2026-05-24T19:18:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693868</loc>
  <lastmod>2026-05-24T19:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダの再構成画像を群最適化で改良する（Using Swarm Optimization To Enhance Autoencoder’s Images）</news:title>
   <news:publication_date>2026-05-24T19:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693866</loc>
  <lastmod>2026-05-24T19:18:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習研究の問題点と健全な再生の道（Troubling Trends in Machine Learning Scholarship）</news:title>
   <news:publication_date>2026-05-24T19:18:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693864</loc>
  <lastmod>2026-05-24T19:18:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>提案クラスタ学習による弱教師あり物体検出の新戦略（PCL: Proposal Cluster Learning for Weakly Supervised Object Detection）</news:title>
   <news:publication_date>2026-05-24T19:18:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693862</loc>
  <lastmod>2026-05-24T19:17:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素全畳み込みニューラルネットワークによるMR画像再構成（Complex Fully Convolutional Neural Networks for MR Image Reconstruction）</news:title>
   <news:publication_date>2026-05-24T19:17:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693860</loc>
  <lastmod>2026-05-24T18:26:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェットサブ構造のスペクトル解析とニューラルネットワーク（Spectral Analysis of Jet Substructure with Neural Networks: Boosted Higgs Case）</news:title>
   <news:publication_date>2026-05-24T18:26:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693858</loc>
  <lastmod>2026-05-24T18:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーンテキスト認識に対する適応的敵対的攻撃（Adaptive Adversarial Attack on Scene Text Recognition）</news:title>
   <news:publication_date>2026-05-24T18:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693856</loc>
  <lastmod>2026-05-24T18:16:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称性と多体系励起状態のニューラルネットワーク量子状態（Symmetries and many-body excited states with neural-network quantum states）</news:title>
   <news:publication_date>2026-05-24T18:16:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693854</loc>
  <lastmod>2026-05-24T18:15:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フロンティア・フィールド銀河団のレンズモデル評価（An Evaluation of 10 Lensing Models of the Frontier Fields Cluster MACSJ0416.1-2403）</news:title>
   <news:publication_date>2026-05-24T18:15:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693852</loc>
  <lastmod>2026-05-24T18:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチコアHW/SWコーデザインによるK-means高速化（Using Multi-Core HW/SW Co-design Architecture for Accelerating K-means Clustering Algorithm）</news:title>
   <news:publication_date>2026-05-24T18:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693850</loc>
  <lastmod>2026-05-24T18:15:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英語の訛りを統計的に補正する手法（Foreign English Accent Adjustment by Learning Phonetic Patterns）</news:title>
   <news:publication_date>2026-05-24T18:15:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693848</loc>
  <lastmod>2026-05-24T18:14:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限個の未知評価額を仮定した動的価格設定（Dynamic Pricing with Finitely Many Unknown Valuations）</news:title>
   <news:publication_date>2026-05-24T18:14:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693846</loc>
  <lastmod>2026-05-24T17:23:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次モンテカルロ期待値最大化における適応学習による効率的収束（Efficient convergence through adaptive learning in sequential Monte Carlo Expectation Maximization）</news:title>
   <news:publication_date>2026-05-24T17:23:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693844</loc>
  <lastmod>2026-05-24T17:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>座標変換で暴露された畳み込みニューラルネットワークの落とし穴（An intriguing failing of convolutional neural networks and the CoordConv solution）</news:title>
   <news:publication_date>2026-05-24T17:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693842</loc>
  <lastmod>2026-05-24T17:14:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ニューラルネットワークのベンチマーク—古典NNとの比較で示された効率性（Benchmarking Neural Networks For Quantum Computations）</news:title>
   <news:publication_date>2026-05-24T17:14:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693840</loc>
  <lastmod>2026-05-24T17:12:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的進化的特徴選択による放射線画像の選別（Multi-objective Feature Selection with Modified Entropy Termination and Evidential Reasoning）</news:title>
   <news:publication_date>2026-05-24T17:12:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693838</loc>
  <lastmod>2026-05-24T17:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発達期における抑制のブレインワイド発達を深層学習で探る（Exploring Brain-wide Development of Inhibition through Deep Learning）</news:title>
   <news:publication_date>2026-05-24T17:12:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693836</loc>
  <lastmod>2026-05-24T17:12:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FHIRChainによる臨床データの安全かつスケーラブルな共有（FHIRChain: Applying Blockchain to Securely and Scalably Share Clinical Data）</news:title>
   <news:publication_date>2026-05-24T17:12:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693834</loc>
  <lastmod>2026-05-24T17:12:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>渦と磁場がつむぐ“大きさの逆転”──渦度・ヘリシティと双方向カスケードの概観（Helicity dynamics, inverse and bi-directional cascades in fluid and magnetohydrodynamic turbulence: A brief review）</news:title>
   <news:publication_date>2026-05-24T17:12:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693832</loc>
  <lastmod>2026-05-24T16:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNを用いたNIDS強化の方法（RNNIDS: Enhancing Network Intrusion Detection Systems through Deep Learning）</news:title>
   <news:publication_date>2026-05-24T16:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693830</loc>
  <lastmod>2026-05-24T16:19:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的モデル平均による効率的な分散深層学習（Efficient Decentralized Deep Learning by Dynamic Model Averaging）</news:title>
   <news:publication_date>2026-05-24T16:19:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693828</loc>
  <lastmod>2026-05-24T16:19:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーソナライズされた語彙学習チュータの設計と評価（Design and Evaluation of a Tutor Platform for Personalized Vocabulary Learning）</news:title>
   <news:publication_date>2026-05-24T16:19:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693826</loc>
  <lastmod>2026-05-24T16:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身近な材料と低コストセンサーで物理を学ぶ（Low-Cost Experiments with Everyday Objects for Homework Assignments）</news:title>
   <news:publication_date>2026-05-24T16:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693824</loc>
  <lastmod>2026-05-24T16:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延が未知のバンディット・オンライン学習（Bandit Online Learning with Unknown Delays）</news:title>
   <news:publication_date>2026-05-24T16:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693822</loc>
  <lastmod>2026-05-24T16:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Thresholded ConvNet Ensemblesによるテクニカル予測の要点（Thresholded ConvNet Ensembles: Neural Networks for Technical Forecasting）</news:title>
   <news:publication_date>2026-05-24T16:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693820</loc>
  <lastmod>2026-05-24T16:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似k空間モデルと深層学習による高速光音響再構成（Approximate k-space models and Deep Learning for fast photoacoustic reconstruction）</news:title>
   <news:publication_date>2026-05-24T16:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693818</loc>
  <lastmod>2026-05-24T15:26:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エリートアスリートにおける心肺パラメータの因果経路発見（Discovery of causal paths in cardiorespiratory parameters: a time-independent approach in elite athletes）</news:title>
   <news:publication_date>2026-05-24T15:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693816</loc>
  <lastmod>2026-05-24T15:25:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い文脈化単語埋め込み、アンサンブル、ツリーバンク連結によるUDパーシングの改善（Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank Concatenation）</news:title>
   <news:publication_date>2026-05-24T15:25:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693814</loc>
  <lastmod>2026-05-24T15:25:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースネットワークのためのBeta Neutral-to-the-Leftモデルのサンプリングと推論（Sampling and Inference for Beta Neutral-to-the-Left Models of Sparse Networks）</news:title>
   <news:publication_date>2026-05-24T15:25:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693812</loc>
  <lastmod>2026-05-24T15:24:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層マルチモーダルクラスタリングによる教師なし音声映像学習（Deep Multimodal Clustering for Unsupervised Audiovisual Learning）</news:title>
   <news:publication_date>2026-05-24T15:24:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693810</loc>
  <lastmod>2026-05-24T15:24:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形計測とニューラルネットワークによるMRPCの時間再構成法（The study of a new time reconstruction method for MRPC read out by waveform digitizer）</news:title>
   <news:publication_date>2026-05-24T15:24:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693808</loc>
  <lastmod>2026-05-24T15:23:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NMT-Keras：対話型・継続学習に注力した柔軟な機械翻訳ツールキット（NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning）</news:title>
   <news:publication_date>2026-05-24T15:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693806</loc>
  <lastmod>2026-05-24T15:23:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分実行で強化するText-to-SQL（Robust Text-to-SQL Generation with Execution-Guided Decoding）</news:title>
   <news:publication_date>2026-05-24T15:23:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693804</loc>
  <lastmod>2026-05-24T14:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓不整脈発生源のコンピュータ支援局在化（Computer Assisted Localization of a Heart Arrhythmia）</news:title>
   <news:publication_date>2026-05-24T14:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693802</loc>
  <lastmod>2026-05-24T14:31:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共分散と濃度グラフ行列のシミュレーション（SIMULATING COVARIANCE AND CONCENTRATION GRAPH MATRICES）</news:title>
   <news:publication_date>2026-05-24T14:31:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693800</loc>
  <lastmod>2026-05-24T14:31:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画要約を分類で導く強化学習（Video Summarisation by Classification with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-24T14:31:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693798</loc>
  <lastmod>2026-05-24T14:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次診断における能動学習ヒューリスティクスの評価（Evaluating Active Learning Heuristics for Sequential Diagnosis）</news:title>
   <news:publication_date>2026-05-24T14:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693796</loc>
  <lastmod>2026-05-24T14:31:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ChestNetによる胸部X線画像の診断向上（ChestNet: A Deep Neural Network for Classification of Thoracic Diseases on Chest Radiography）</news:title>
   <news:publication_date>2026-05-24T14:31:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693794</loc>
  <lastmod>2026-05-24T14:30:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>精度学習に基づくニューラルネットワーク設計：平行線投影から扇形線投影への変換（Deriving Neural Network Architectures using Precision Learning: Parallel-to-fan beam Conversion）</news:title>
   <news:publication_date>2026-05-24T14:30:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693792</loc>
  <lastmod>2026-05-24T14:30:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークを用いた時間差分学習におけるリーケージ伝播の研究 (Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem)</news:title>
   <news:publication_date>2026-05-24T14:30:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693790</loc>
  <lastmod>2026-05-24T13:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌声処理における深層学習の到達点と実務への示唆（Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners）</news:title>
   <news:publication_date>2026-05-24T13:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693788</loc>
  <lastmod>2026-05-24T13:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置認識型自己注意（Position-aware Self-attention）によるスロットフィリングの改良（Position-aware Self-attention with Relative Positional Encodings for Slot Filling）</news:title>
   <news:publication_date>2026-05-24T13:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693786</loc>
  <lastmod>2026-05-24T13:39:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動サービスロボットの自然言語命令理解を深層学習で実装する（A deep learning approach for understanding natural language commands for mobile service robots）</news:title>
   <news:publication_date>2026-05-24T13:39:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693784</loc>
  <lastmod>2026-05-24T13:39:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Glow：可逆1×1畳み込みを用いた生成フロー（Glow: Generative Flow with Invertible 1×1 Convolutions）</news:title>
   <news:publication_date>2026-05-24T13:39:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693782</loc>
  <lastmod>2026-05-24T13:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pioneer Networks: Progressively Growing Generative Autoencoder（Pioneer Networks: Progressively Growing Generative Autoencoder）</news:title>
   <news:publication_date>2026-05-24T13:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693780</loc>
  <lastmod>2026-05-24T13:38:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形・循環・潜在交絡を扱う制約ベース因果探索（Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders）</news:title>
   <news:publication_date>2026-05-24T13:38:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693778</loc>
  <lastmod>2026-05-24T13:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>血糖値予測のための畳み込み再帰型ニューラルネットワーク（Convolutional Recurrent Neural Networks for Glucose Prediction）</news:title>
   <news:publication_date>2026-05-24T13:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693776</loc>
  <lastmod>2026-05-24T12:47:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実写に近い合成画像で高精度なシーンテキスト検出・認識を実現する手法（Verisimilar Image Synthesis for Accurate Detection and Recognition of Texts in Scenes）</news:title>
   <news:publication_date>2026-05-24T12:47:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693774</loc>
  <lastmod>2026-05-24T12:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OntoSenseNetを用いた語義注釈と感情分析の接点（Towards Enhancing Lexical Resource and Using Sense-annotations of OntoSenseNet for Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-24T12:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693772</loc>
  <lastmod>2026-05-24T12:46:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XNOR Neural Engine: マイクロコントローラ向けBNNアクセラレータ（XNOR Neural Engine: a Hardware Accelerator IP for 21.6 fJ/op Binary Neural Network Inference）</news:title>
   <news:publication_date>2026-05-24T12:46:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693770</loc>
  <lastmod>2026-05-24T12:45:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Restricted Boltzmann Machineのサイズ削減手法（Decreasing the size of the Restricted Boltzmann machine）</news:title>
   <news:publication_date>2026-05-24T12:45:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693768</loc>
  <lastmod>2026-05-24T12:45:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市環境における視覚的ローカリゼーションのための動的物体セグメンテーション (Dynamic Objects Segmentation for Visual Localization in Urban Environments)</news:title>
   <news:publication_date>2026-05-24T12:45:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693766</loc>
  <lastmod>2026-05-24T12:45:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ネットワークでの関数学習はモジュール性を要し多主体ダイナミクスを生む（Learning Functions in Large Networks requires Modularity and produces Multi-Agent Dynamics）</news:title>
   <news:publication_date>2026-05-24T12:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693764</loc>
  <lastmod>2026-05-24T12:45:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘッダービッディングにおけるSSP入札戦略の最適化（Optimization of a SSP’s Header Bidding Strategy using Thompson Sampling）</news:title>
   <news:publication_date>2026-05-24T12:45:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693762</loc>
  <lastmod>2026-05-24T11:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍探索のための学習型インデックス（Learning to Index for Nearest Neighbor Search）</news:title>
   <news:publication_date>2026-05-24T11:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693760</loc>
  <lastmod>2026-05-24T11:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分グラフパターンと非線形モデルの同時学習（Jointly learning relevant subgraph patterns and nonlinear models of their indicators）</news:title>
   <news:publication_date>2026-05-24T11:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693758</loc>
  <lastmod>2026-05-24T11:53:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多体局在と熱化の境界を機械学習で可視化する（Interpretable Machine Learning Study of Many-Body Localization Transition in Disordered Quantum Ising Spin Chains）</news:title>
   <news:publication_date>2026-05-24T11:53:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693756</loc>
  <lastmod>2026-05-24T11:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化されたコミュニティの統計的有意性の検定（Computing the statistical significance of optimized communities in networks）</news:title>
   <news:publication_date>2026-05-24T11:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693754</loc>
  <lastmod>2026-05-24T11:52:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン語義記述子なしでのゼロショットドメイン適応（Zero-shot Domain Adaptation without Domain Semantic Descriptors）</news:title>
   <news:publication_date>2026-05-24T11:52:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693752</loc>
  <lastmod>2026-05-24T11:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的アフィン変換を階層的に学習するPARN（Pyramidal Affine Regression Networks for Dense Semantic Correspondence）</news:title>
   <news:publication_date>2026-05-24T11:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693750</loc>
  <lastmod>2026-05-24T11:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周囲と調和する車両画像生成（Vehicle Image Generation Going Well with the Surroundings）</news:title>
   <news:publication_date>2026-05-24T11:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693748</loc>
  <lastmod>2026-05-24T11:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CSI学習に基づく能動的安全符号化方式（CSI Learning Based Active Secure Coding Scheme For Detectable Wiretap Channel）</news:title>
   <news:publication_date>2026-05-24T11:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693746</loc>
  <lastmod>2026-05-24T11:00:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Domain2Vecによるドメイン一般化の設計（Domain2Vec: Deep Domain Generalization）</news:title>
   <news:publication_date>2026-05-24T11:00:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693744</loc>
  <lastmod>2026-05-24T10:59:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール注意によるセマンティックセグメンテーションの改良（Attention to Refine through Multi-Scales for Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-24T10:59:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693742</loc>
  <lastmod>2026-05-24T10:58:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分方策ベース強化学習による3D医療画像のランドマーク検出（Partial Policy-based Reinforcement Learning for Anatomical Landmark Localization in 3D Medical Images）</news:title>
   <news:publication_date>2026-05-24T10:58:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693740</loc>
  <lastmod>2026-05-24T10:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像分類の脆弱性解析（Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks）</news:title>
   <news:publication_date>2026-05-24T10:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693738</loc>
  <lastmod>2026-05-24T10:58:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル非依存の教師付き局所説明（Model Agnostic Supervised Local Explanations）</news:title>
   <news:publication_date>2026-05-24T10:58:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693736</loc>
  <lastmod>2026-05-24T10:58:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アラビア語感情分析のためのCNNとLSTMの統合モデル（A Combined CNN and LSTM Model for Arabic Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-24T10:58:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693734</loc>
  <lastmod>2026-05-24T10:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RANSモデルの構造的不確かさを定量化するベイジアン深層ニューラルネットワーク（Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks）</news:title>
   <news:publication_date>2026-05-24T10:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693732</loc>
  <lastmod>2026-05-24T10:06:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語の具体性と画像想起性の予測（Predicting Concreteness and Imageability of Words Within and Across Languages via Word Embeddings）</news:title>
   <news:publication_date>2026-05-24T10:06:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693730</loc>
  <lastmod>2026-05-24T10:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EL画像による太陽電池モジュールセルの欠陥自動分類（Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images）</news:title>
   <news:publication_date>2026-05-24T10:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693728</loc>
  <lastmod>2026-05-24T10:05:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習ベースのアクター・クリティックによる自動深層圧縮（Auto Deep Compression by Reinforcement Learning Based Actor-Critic Structure）</news:title>
   <news:publication_date>2026-05-24T10:05:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693726</loc>
  <lastmod>2026-05-24T10:05:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SuperBITによる高解像度広視野バルーン望遠鏡の概観と成果（Overview, design, and flight results from SuperBIT: a high-resolution, wide-field, visible-to-near-UV balloon-borne astronomical telescope）</news:title>
   <news:publication_date>2026-05-24T10:05:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693724</loc>
  <lastmod>2026-05-24T10:05:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフのコミュニティ検出における統計的限界と半正定値緩和（Stochastic Block Model for Hypergraphs: Statistical limits and a semidefinite programming approach）</news:title>
   <news:publication_date>2026-05-24T10:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693722</loc>
  <lastmod>2026-05-24T10:04:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バグ・チケット自動ラベリングにおける階層注意機構を用いたRNN手法（Automated labeling of bugs and tickets using attention-based mechanisms in recurrent neural networks）</news:title>
   <news:publication_date>2026-05-24T10:04:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693720</loc>
  <lastmod>2026-05-24T09:13:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークに基づく無線資源配分（Resource Allocation Based on Deep Neural Networks for Cognitive Radio Networks）</news:title>
   <news:publication_date>2026-05-24T09:13:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693718</loc>
  <lastmod>2026-05-24T09:06:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイエネルギー物理学における機械学習の共同ホワイトペーパー（Machine Learning in High Energy Physics Community White Paper）</news:title>
   <news:publication_date>2026-05-24T09:06:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693716</loc>
  <lastmod>2026-05-24T09:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離可能性を最優先にするのは最善ではない（Separability Is Not the Best Goal for Machine Learning）</news:title>
   <news:publication_date>2026-05-24T09:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693714</loc>
  <lastmod>2026-05-24T09:05:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きなマージンを用いた少数ショット学習（Large Margin Few-Shot Learning）</news:title>
   <news:publication_date>2026-05-24T09:05:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693712</loc>
  <lastmod>2026-05-24T09:04:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チケットシステムにおける非対称テキスト類似学習の実務的応用（Replicated Siamese LSTM in Ticketing System for Similarity Learning and Retrieval in Asymmetric Texts）</news:title>
   <news:publication_date>2026-05-24T09:04:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693710</loc>
  <lastmod>2026-05-24T09:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>準パラメトリック画像修復（Semi-parametric Image Inpainting）</news:title>
   <news:publication_date>2026-05-24T09:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693708</loc>
  <lastmod>2026-05-24T09:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列情報を学習するリカレントニューラルネットワーク（Learning The Sequential Temporal Information with Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-24T09:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693706</loc>
  <lastmod>2026-05-24T08:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gaia GraLによる天体重力レンズ探索の盲検的検出（Gaia GraL: Gaia DR2 Gravitational Lens Systems. III. A systematic blind search for new lensed systems）</news:title>
   <news:publication_date>2026-05-24T08:12:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693704</loc>
  <lastmod>2026-05-24T08:11:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的確率的グラフレット埋め込み（Hierarchical Stochastic Graphlet Embedding）</news:title>
   <news:publication_date>2026-05-24T08:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693702</loc>
  <lastmod>2026-05-24T08:10:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深く監督された回転等変性ネットワークによる皮膚鏡画像の病変セグメンテーション（Deeply Supervised Rotation Equivariant Network for Lesion Segmentation in Dermoscopy Images）</news:title>
   <news:publication_date>2026-05-24T08:10:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693700</loc>
  <lastmod>2026-05-24T08:10:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>802.11ネットワークにおけるMAC層レート制御の総括（MAC-Layer Rate Control for 802.11 Networks: Lesson Learned and Looking Forward）</news:title>
   <news:publication_date>2026-05-24T08:10:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693698</loc>
  <lastmod>2026-05-24T08:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイジアン最適化入門（A Tutorial on Bayesian Optimization）</news:title>
   <news:publication_date>2026-05-24T08:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693696</loc>
  <lastmod>2026-05-24T08:10:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動プログラミングによる深層学習の改良（Improving Deep Learning through Automatic Programming）</news:title>
   <news:publication_date>2026-05-24T08:10:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693694</loc>
  <lastmod>2026-05-24T08:09:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間インスタンス学習：クラス監視からのアクションチューブ（Spatio-Temporal Instance Learning: Action Tubes from Class Supervision）</news:title>
   <news:publication_date>2026-05-24T08:09:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693692</loc>
  <lastmod>2026-05-24T07:18:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>金融取引をゲームとして捉える―深層強化学習による自動売買の可能性（Financial Trading as a Game: A Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-05-24T07:18:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693690</loc>
  <lastmod>2026-05-24T07:10:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分学習における蒸留と疑似リハーサルの偏り除去（Distillation Techniques for Pseudo-rehearsal Based Incremental Learning）</news:title>
   <news:publication_date>2026-05-24T07:10:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693688</loc>
  <lastmod>2026-05-24T07:10:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負のL1ノルム制約を持つベイズ最小二乗法の提案（BALSON: BAYESIAN LEAST SQUARES OPTIMIZATION WITH NONNEGATIVE L1-NORM CONSTRAINT）</news:title>
   <news:publication_date>2026-05-24T07:10:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693686</loc>
  <lastmod>2026-05-24T07:09:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モード視点が拓く統計の新時代（The Modal Age of Statistics）</news:title>
   <news:publication_date>2026-05-24T07:09:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693684</loc>
  <lastmod>2026-05-24T07:08:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フリンジパターン解析における深層学習（Fringe pattern analysis using deep learning）</news:title>
   <news:publication_date>2026-05-24T07:08:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693682</loc>
  <lastmod>2026-05-24T07:08:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非常に深い残差チャネル注意ネットワークによる画像超解像（Image Super-Resolution Using Very Deep Residual Channel Attention Networks）</news:title>
   <news:publication_date>2026-05-24T07:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693680</loc>
  <lastmod>2026-05-24T07:08:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>鳥の音を聞き分ける密結合CNNの実践（Densely Connected CNNs for Bird Audio Detection）</news:title>
   <news:publication_date>2026-05-24T07:08:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693678</loc>
  <lastmod>2026-05-24T06:17:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シナプスの位置と接続方向を同時に検出する手法の要諦（Detecting Synapse Location and Connectivity by Signed Proximity Estimation and Pruning with Deep Nets）</news:title>
   <news:publication_date>2026-05-24T06:17:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693676</loc>
  <lastmod>2026-05-24T06:16:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>母音フォルマント類型の深層生成モデル（A Deep Generative Model of Vowel Formant Typology）</news:title>
   <news:publication_date>2026-05-24T06:16:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693674</loc>
  <lastmod>2026-05-24T06:16:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群のデータ駆動アップサンプリング（Data-driven Upsampling of Point Clouds）</news:title>
   <news:publication_date>2026-05-24T06:16:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693672</loc>
  <lastmod>2026-05-24T06:16:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークのみで侵害するAndroidプライバシー（Nothing But Net: Invading Android User Privacy Using Only Network Access Patterns）</news:title>
   <news:publication_date>2026-05-24T06:16:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693670</loc>
  <lastmod>2026-05-24T06:16:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トリム推定量のロバスト学習とマニフォールドサンプリング（Robust Learning of Trimmed Estimators via Manifold Sampling）</news:title>
   <news:publication_date>2026-05-24T06:16:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693668</loc>
  <lastmod>2026-05-24T06:15:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼性の高いmmWave通信のための機械学習：遮へい予測と事前ハンドオフ（Machine Learning for Reliable mmWave Systems: Blockage Prediction and Proactive Handoff）</news:title>
   <news:publication_date>2026-05-24T06:15:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693666</loc>
  <lastmod>2026-05-24T06:15:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた地質パラメータ化とヒストリーマッチの革新（A Deep-Learning-Based Geological Parameterization for History Matching Complex Models）</news:title>
   <news:publication_date>2026-05-24T06:15:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693664</loc>
  <lastmod>2026-05-24T05:24:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相特徴を用いたDNNベース音楽音源分離の改良 (Improving DNN-based Music Source Separation using Phase Features)</news:title>
   <news:publication_date>2026-05-24T05:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693662</loc>
  <lastmod>2026-05-24T05:24:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSource: 深層学習による点状天体検出の実務的意義（DeepSource: Point Source Detection using Deep Learning）</news:title>
   <news:publication_date>2026-05-24T05:24:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693660</loc>
  <lastmod>2026-05-24T05:24:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速なパラメータ調整のための近似Leave-One-Out（Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions）</news:title>
   <news:publication_date>2026-05-24T05:24:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693658</loc>
  <lastmod>2026-05-24T05:23:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cellular Controlled Delay TCP（Cellular Controlled Delay TCP (C2TCP)）</news:title>
   <news:publication_date>2026-05-24T05:23:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693656</loc>
  <lastmod>2026-05-24T05:23:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合量子ラビモデル（The Mixed Quantum Rabi Model）</news:title>
   <news:publication_date>2026-05-24T05:23:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693654</loc>
  <lastmod>2026-05-24T05:23:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペクトル画像分類のための教師付き幾何認識写像アプローチ（A Supervised Geometry-Aware Mapping Approach for Classification of Hyperspectral Images）</news:title>
   <news:publication_date>2026-05-24T05:23:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693652</loc>
  <lastmod>2026-05-24T05:23:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VFPredによる心室細動検出：信号処理と機械学習の融合（VFPred: A Fusion of Signal Processing and Machine Learning techniques in Detecting Ventricular Fibrillation from ECG Signals）</news:title>
   <news:publication_date>2026-05-24T05:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693650</loc>
  <lastmod>2026-05-24T04:32:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢でスケーラブルな微分可能ニューラルコンピュータ（Robust and Scalable Differentiable Neural Computer for Question Answering）</news:title>
   <news:publication_date>2026-05-24T04:32:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693648</loc>
  <lastmod>2026-05-24T04:32:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>白内障等級付けのためのトーナメント型ランキングCNN（Tournament Based Ranking CNN for the Cataract grading）</news:title>
   <news:publication_date>2026-05-24T04:32:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693646</loc>
  <lastmod>2026-05-24T04:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンショット質感セグメンテーション（One-shot Texture Segmentation）</news:title>
   <news:publication_date>2026-05-24T04:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693644</loc>
  <lastmod>2026-05-24T04:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲームの複雑性が合成エージェントのプレイ行動に与える影響（How game complexity affects the playing behavior of synthetic agents）</news:title>
   <news:publication_date>2026-05-24T04:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693642</loc>
  <lastmod>2026-05-24T04:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外観と動き条件によるビデオ予測 (Video Prediction with Appearance and Motion Conditions)</news:title>
   <news:publication_date>2026-05-24T04:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693640</loc>
  <lastmod>2026-05-24T04:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SQL学習のための推薦システムとヒント生成（Recommender system for learning SQL using hints）</news:title>
   <news:publication_date>2026-05-24T04:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693638</loc>
  <lastmod>2026-05-24T04:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仕事が重要なとき：古典的ネットワーク構造をグラフCNNへ変換する手法 (When Work Matters: Transforming Classical Network Structures to Graph CNN)</news:title>
   <news:publication_date>2026-05-24T04:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693636</loc>
  <lastmod>2026-05-24T03:38:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽観的ミラーディセントによる鞍点問題の前進（OPTIMISTIC MIRROR DESCENT IN SADDLE-POINT PROBLEMS: GOING THE EXTRA (GRADIENT) MILE）</news:title>
   <news:publication_date>2026-05-24T03:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693634</loc>
  <lastmod>2026-05-24T03:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>滑空とパーチングのための深層強化学習（Deep-Reinforcement-Learning for Gliding and Perching Bodies）</news:title>
   <news:publication_date>2026-05-24T03:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693632</loc>
  <lastmod>2026-05-24T03:38:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中核保存に基づくネットワーク表現学習（Core2Vec: A core-preserving feature learning framework for networks）</news:title>
   <news:publication_date>2026-05-24T03:38:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693630</loc>
  <lastmod>2026-05-24T03:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的入力を持つリザバーコンピューティングの普遍性（Reservoir Computing Universality With Stochastic Inputs）</news:title>
   <news:publication_date>2026-05-24T03:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693628</loc>
  <lastmod>2026-05-24T03:37:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Anytime Neural Prediction via Slicing Networks Vertically（Anytime Neural Prediction via Slicing Networks Vertically）</news:title>
   <news:publication_date>2026-05-24T03:37:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693626</loc>
  <lastmod>2026-05-24T03:37:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳幼児の運動データから発達リスクを予測する（Predicting Infant Motor Development Status using Day Long Movement Data from Wearable Sensors）</news:title>
   <news:publication_date>2026-05-24T03:37:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693624</loc>
  <lastmod>2026-05-24T03:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配ハイパーアラインメント（Gradient Hyperalignment for multi-subject fMRI data alignment）</news:title>
   <news:publication_date>2026-05-24T03:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693622</loc>
  <lastmod>2026-05-24T02:45:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的確率的新奇検出と敵対的オートエンコーダ（Generative Probabilistic Novelty Detection with Adversarial Autoencoders）</news:title>
   <news:publication_date>2026-05-24T02:45:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693620</loc>
  <lastmod>2026-05-24T02:45:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Goldilocksゾーン：ニューラルネットワークの損失ランドスケープの理解に向けて（The Goldilocks zone: Towards better understanding of neural network loss landscapes）</news:title>
   <news:publication_date>2026-05-24T02:45:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693618</loc>
  <lastmod>2026-05-24T02:37:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス悪性度予測のための合成サンプリング（Synthetic Sampling for Multi-Class Malignancy Prediction）</news:title>
   <news:publication_date>2026-05-24T02:37:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693616</loc>
  <lastmod>2026-05-24T02:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療記録からトピックを抽出する非教師的グラフ分割法（From Text to Topics in Healthcare Records: An Unsupervised Graph Partitioning Methodology）</news:title>
   <news:publication_date>2026-05-24T02:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693614</loc>
  <lastmod>2026-05-24T02:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SmartSeedによる効率的なファジング向けシード生成（SmartSeed: Smart Seed Generation for Efficient Fuzzing）</news:title>
   <news:publication_date>2026-05-24T02:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693612</loc>
  <lastmod>2026-05-24T02:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程とカーネル法の関係と等価性（Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences）</news:title>
   <news:publication_date>2026-05-24T02:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693610</loc>
  <lastmod>2026-05-24T02:35:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多値ルールセットによる患者院内死亡予測の解釈可能モデル（Interpretable Patient Mortality Prediction with Multi-value Rule Sets）</news:title>
   <news:publication_date>2026-05-24T02:35:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693608</loc>
  <lastmod>2026-05-24T01:44:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化と解釈可能な患者心電図プロファイル（Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery）</news:title>
   <news:publication_date>2026-05-24T01:44:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693606</loc>
  <lastmod>2026-05-24T01:44:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Virtual Stereo Odometryを用いた単眼DSOの進化（Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry）</news:title>
   <news:publication_date>2026-05-24T01:44:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693604</loc>
  <lastmod>2026-05-24T01:43:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M-ADDAによる非監督ドメイン適応と深層距離学習の統合（M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning）</news:title>
   <news:publication_date>2026-05-24T01:43:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693602</loc>
  <lastmod>2026-05-24T01:43:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D回転に強い畳み込みネットワークの設計（3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data）</news:title>
   <news:publication_date>2026-05-24T01:43:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693600</loc>
  <lastmod>2026-05-24T01:43:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木幅に基づく計算可能性の新たな限界（New Limits of Treewidth-based Tractability in Optimization）</news:title>
   <news:publication_date>2026-05-24T01:43:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693598</loc>
  <lastmod>2026-05-24T01:43:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全にスケーラブルなガウス過程と部分空間誘導入力（Fully Scalable Gaussian Processes using Subspace Inducing Inputs）</news:title>
   <news:publication_date>2026-05-24T01:43:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693596</loc>
  <lastmod>2026-05-24T01:43:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載画像の境界線で位置推定をする技術の要点解説（VLASE: Vehicle Localization by Aggregating Semantic Edges）</news:title>
   <news:publication_date>2026-05-24T01:43:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/693594</loc>
  <lastmod>2026-05-24T00:52:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙再電離末期に見つかった強力な電波明るいクエーサー（A POWERFUL RADIO-LOUD QUASAR AT THE END OF COSMIC REIONIZATION）</news:title>
   <news:publication_date>2026-05-24T00:52:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693592</loc>
  <lastmod>2026-05-24T00:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>荷電カレント深部非弾性散乱におけるジェット生成のNNLO QCD補正（NNLO QCD Corrections to Jet Production in Charged Current Deep Inelastic Scattering）</news:title>
   <news:publication_date>2026-05-24T00:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693590</loc>
  <lastmod>2026-05-24T00:51:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ作業におけるリーダーシップ属性と行動の記述と比較（Denoting and Comparing Leadership Attributes and Behaviors in Group Work）</news:title>
   <news:publication_date>2026-05-24T00:51:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693588</loc>
  <lastmod>2026-05-24T00:50:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的画像セグメンテーションのための全畳み込み二系統融合ネットワーク（A Fully Convolutional Two-Stream Fusion Network for Interactive Image Segmentation）</news:title>
   <news:publication_date>2026-05-24T00:50:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693586</loc>
  <lastmod>2026-05-24T00:50:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動するラベルの下で「意味のある」表現を学ぶ方法（Deep Multiple Instance Feature Learning via Variational Autoencoder）</news:title>
   <news:publication_date>2026-05-24T00:50:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693584</loc>
  <lastmod>2026-05-24T00:49:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>YouTubeを用いた患者教育：ユーザー生成動画から医療知識を抽出する深層学習の試み (YouTube for Patient Education: A Deep Learning Approach for Understanding Medical Knowledge from User-Generated Videos)</news:title>
   <news:publication_date>2026-05-24T00:49:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693582</loc>
  <lastmod>2026-05-24T00:49:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数選択チャネルと少ビットADCにおける共同チャネル推定・復号（Joint Channel-Estimation/Decoding with Frequency-Selective Channels and Few-Bit ADCs）</news:title>
   <news:publication_date>2026-05-24T00:49:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693580</loc>
  <lastmod>2026-05-23T23:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルツハイマー病の病状推移を深層学習で予測する（Forecasting Disease Trajectories in Alzheimer’s Disease Using Deep Learning）</news:title>
   <news:publication_date>2026-05-23T23:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693578</loc>
  <lastmod>2026-05-23T23:56:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>典型的な携帯電話利用習慣：激しい使用は否定的な幸福感を予測しない（Typical Phone Use Habits: Intense Use Does Not Predict Negative Well-Being）</news:title>
   <news:publication_date>2026-05-23T23:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693576</loc>
  <lastmod>2026-05-23T23:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な機械学習による非平衡系の相境界推定（Interpretable machine learning for inferring the phase boundaries in a nonequilibrium system）</news:title>
   <news:publication_date>2026-05-23T23:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693574</loc>
  <lastmod>2026-05-23T23:56:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セキュリティ関連コミットの自動分類の実践的手法 (A Practical Approach to the Automatic Classification of Security-Relevant Commits)</news:title>
   <news:publication_date>2026-05-23T23:56:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693572</loc>
  <lastmod>2026-05-23T23:56:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損データを考慮したマルチタスク学習（Multi-Task Learning with Incomplete Data for Healthcare）</news:title>
   <news:publication_date>2026-05-23T23:56:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693570</loc>
  <lastmod>2026-05-23T23:56:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボリュメトリック医用スキャンにおける器官の深層逐次セグメンテーション（Deep Sequential Segmentation of Organs in Volumetric Medical Scans）</news:title>
   <news:publication_date>2026-05-23T23:56:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693568</loc>
  <lastmod>2026-05-23T23:55:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接線畳み込みによる3D密度予測の革新（Tangent Convolutions for Dense Prediction in 3D）</news:title>
   <news:publication_date>2026-05-23T23:55:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693566</loc>
  <lastmod>2026-05-23T23:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病理画像分類における逆能動学習とAtrous DenseNetの統合（Reversed Active Learning and Atrous DenseNet for Pathological Image Classification）</news:title>
   <news:publication_date>2026-05-23T23:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693564</loc>
  <lastmod>2026-05-23T23:03:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球も少し扁平だと空気の流れがこう変わる（Simple geometric approximations for global atmospheres on moderately oblate planets）</news:title>
   <news:publication_date>2026-05-23T23:03:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693562</loc>
  <lastmod>2026-05-23T23:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソースコード上の一行差分を機械学習で予測する競技プラットフォーム（The CodRep Machine Learning on Source Code Competition）</news:title>
   <news:publication_date>2026-05-23T23:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693560</loc>
  <lastmod>2026-05-23T23:01:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非連結マルコフ決定過程におけるほぼ最適な探索と活用（Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes）</news:title>
   <news:publication_date>2026-05-23T23:01:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693558</loc>
  <lastmod>2026-05-23T23:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習によるエンドツーエンドレースドライビング（End-to-End Race Driving with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-23T23:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693556</loc>
  <lastmod>2026-05-23T23:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア開発の成果物から授業効果を測る（Beyond Surveys: Analyzing Software Development Artifacts to Assess Teaching Efforts）</news:title>
   <news:publication_date>2026-05-23T23:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693554</loc>
  <lastmod>2026-05-23T23:01:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化予測によるラベルランキングのアプローチ（A Structured Prediction Approach for Label Ranking）</news:title>
   <news:publication_date>2026-05-23T23:01:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693552</loc>
  <lastmod>2026-05-23T22:09:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳構造グラフによるアルツハイマー病の早期検出（Graph of brain structures grading for early detection of Alzheimer’s disease）</news:title>
   <news:publication_date>2026-05-23T22:09:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693550</loc>
  <lastmod>2026-05-23T22:01:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースビューCT再構成のためのDeep Back Projection（DEEP BACK PROJECTION FOR SPARSE-VIEW CT RECONSTRUCTION）</news:title>
   <news:publication_date>2026-05-23T22:01:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693548</loc>
  <lastmod>2026-05-23T22:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列変分特徴抽出による行動予測（A Variational Time Series Feature Extractor for Action Prediction）</news:title>
   <news:publication_date>2026-05-23T22:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693546</loc>
  <lastmod>2026-05-23T21:59:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系列ラベリングにおけるサム・プロダクト・ネットワーク（Sum-Product Networks for Sequence Labeling）</news:title>
   <news:publication_date>2026-05-23T21:59:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693544</loc>
  <lastmod>2026-05-23T21:59:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリ拡張ポリシー最適化によるプログラム合成と意味解析の革新（Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing）</news:title>
   <news:publication_date>2026-05-23T21:59:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693542</loc>
  <lastmod>2026-05-23T21:59:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果と情報圧縮で欠損に強くなる方法（Cause‑Effect Deep Information Bottleneck For Systematically Missing Covariates）</news:title>
   <news:publication_date>2026-05-23T21:59:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693540</loc>
  <lastmod>2026-05-23T21:58:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JUMPER：読みながら判断するテキスト分類（JUMPER: Learning When to Make Classification Decisions in Reading）</news:title>
   <news:publication_date>2026-05-23T21:58:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693538</loc>
  <lastmod>2026-05-23T21:07:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抽出型文書要約を一体学習で実現する手法（Neural Document Summarization by Jointly Learning to Score and Select Sentences）</news:title>
   <news:publication_date>2026-05-23T21:07:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693536</loc>
  <lastmod>2026-05-23T21:07:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化NFVオーケストレーションと監視の最適化（z-TORCH: An Automated NFV Orchestration and Monitoring Solution）</news:title>
   <news:publication_date>2026-05-23T21:07:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693534</loc>
  <lastmod>2026-05-23T21:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数試行で学習するロボット方策探索の概観 (A survey on policy search algorithms for learning robot controllers in a handful of trials)</news:title>
   <news:publication_date>2026-05-23T21:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693532</loc>
  <lastmod>2026-05-23T21:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次コピーネットワークの要点（Sequential Copying Networks）</news:title>
   <news:publication_date>2026-05-23T21:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693530</loc>
  <lastmod>2026-05-23T21:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>嗜好が変化するエージェントへのインセンティブ設計を扱う組合せバンディット（Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences）</news:title>
   <news:publication_date>2026-05-23T21:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693528</loc>
  <lastmod>2026-05-23T21:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシーを保ったオンライン部分集合最適化（Differentially Private Online Submodular Optimization）</news:title>
   <news:publication_date>2026-05-23T21:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693526</loc>
  <lastmod>2026-05-23T21:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列畳み込みネットワークによる特徴強化（Parallel Convolutional Networks for Image Recognition via a Discriminator）</news:title>
   <news:publication_date>2026-05-23T21:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693524</loc>
  <lastmod>2026-05-23T20:14:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌声スタイル転送におけるCycleBEGANの提案（Singing Style Transfer Using Cycle-Consistent Boundary Equilibrium Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-23T20:14:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693522</loc>
  <lastmod>2026-05-23T20:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力駆動環境における強化学習の分散削減（VARIANCE REDUCTION FOR REINFORCEMENT LEARNING IN INPUT-DRIVEN ENVIRONMENTS）</news:title>
   <news:publication_date>2026-05-23T20:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693520</loc>
  <lastmod>2026-05-23T20:12:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学院教育における問題発見と創造性の向上（Towards Better Problem Finding and Creativity in Graduate School Education）</news:title>
   <news:publication_date>2026-05-23T20:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693518</loc>
  <lastmod>2026-05-23T20:12:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼性の異なる複数ソースからの転移学習の信頼性向上（Towards more Reliable Transfer Learning）</news:title>
   <news:publication_date>2026-05-23T20:12:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693516</loc>
  <lastmod>2026-05-23T20:12:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mask TextSpotter：任意形状の文字を同時検出・認識するエンドツーエンド手法（Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes）</news:title>
   <news:publication_date>2026-05-23T20:12:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693514</loc>
  <lastmod>2026-05-23T20:12:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度画像検索のための敵対的学習（Adversarial Learning for Fine-grained Image Search）</news:title>
   <news:publication_date>2026-05-23T20:12:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693512</loc>
  <lastmod>2026-05-23T20:11:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河面の三次元星間塵還元マップ（Three-dimensional interstellar dust reddening maps of the Galactic plane）</news:title>
   <news:publication_date>2026-05-23T20:11:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693510</loc>
  <lastmod>2026-05-23T19:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散自己段階学習の実装と意義（Distributed Self-Paced Learning in Alternating Direction Method of Multipliers）</news:title>
   <news:publication_date>2026-05-23T19:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693508</loc>
  <lastmod>2026-05-23T19:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習に基づく球面復号（Deep Learning Based Sphere Decoding）</news:title>
   <news:publication_date>2026-05-23T19:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693506</loc>
  <lastmod>2026-05-23T19:19:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U-SLADSによる動的樹枝構造サンプリング（U-SLADS: Unsupervised Learning Approach for Dynamic Dendrite Sampling）</news:title>
   <news:publication_date>2026-05-23T19:19:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693504</loc>
  <lastmod>2026-05-23T19:19:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差保証付き最適停止の多項式時間アルゴリズム（Polynomial time algorithm for optimal stopping with fixed accuracy）</news:title>
   <news:publication_date>2026-05-23T19:19:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693502</loc>
  <lastmod>2026-05-23T19:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>概念仕様と抽象化に基づく意味表現（A Concept Specification and Abstraction-based Semantic Representation）</news:title>
   <news:publication_date>2026-05-23T19:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693500</loc>
  <lastmod>2026-05-23T19:18:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進行型空間再帰ニューラルネットワークによるイントラ予測（Progressive Spatial Recurrent Neural Network for Intra Prediction）</news:title>
   <news:publication_date>2026-05-23T19:18:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693498</loc>
  <lastmod>2026-05-23T19:18:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界のコードを扱うプログラム合成データセットの意義（NAPS: Natural Program Synthesis Dataset）</news:title>
   <news:publication_date>2026-05-23T19:18:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693496</loc>
  <lastmod>2026-05-23T18:26:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転動作プリミティブの効率的な符号化（Encoding Motion Primitives for Autonomous Vehicles using Virtual Velocity Constraints and Neural Network Scheduling）</news:title>
   <news:publication_date>2026-05-23T18:26:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693494</loc>
  <lastmod>2026-05-23T18:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ拡張によるデジタルマンモグラフィーにおける構築異常検出（Data Augmentation for Detection of Architectural Distortion in Digital Mammography using Deep Learning Approach）</news:title>
   <news:publication_date>2026-05-23T18:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693492</loc>
  <lastmod>2026-05-23T18:18:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情誘発下のEEGを用いた個人識別と深層学習の実装知見（Affective EEG-Based Person Identification Using the Deep Learning Approach）</news:title>
   <news:publication_date>2026-05-23T18:18:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693490</loc>
  <lastmod>2026-05-23T18:17:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース深層ニューラルネットワークの厳密解法（Sparse Deep Neural Network Exact Solutions）</news:title>
   <news:publication_date>2026-05-23T18:17:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693488</loc>
  <lastmod>2026-05-23T18:17:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様なデータサイエンス学習への航海（Navigating Diverse Data Science Learning: Critical Reflections Towards Future Practice）</news:title>
   <news:publication_date>2026-05-23T18:17:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693486</loc>
  <lastmod>2026-05-23T18:17:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズを学習することで敵対的攻撃に強くなる（Implicit Generative Modeling of Random Noise during Training improves Adversarial Robustness）</news:title>
   <news:publication_date>2026-05-23T18:17:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693484</loc>
  <lastmod>2026-05-23T18:16:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サービスロボティクスにおける知識表現の総覧（A Survey of Knowledge Representation in Service Robotics）</news:title>
   <news:publication_date>2026-05-23T18:16:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693482</loc>
  <lastmod>2026-05-23T17:25:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サービスとしてのブロックチェーン：分散型かつ安全なコンピューティングパラダイム（Blockchain as a Service: A Decentralized and Secure Computing Paradigm）</news:title>
   <news:publication_date>2026-05-23T17:25:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693480</loc>
  <lastmod>2026-05-23T17:25:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的Levenberg–Marquardt法によるノイズ耐性最適化（A stochastic Levenberg–Marquardt method using random models with complexity results）</news:title>
   <news:publication_date>2026-05-23T17:25:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693478</loc>
  <lastmod>2026-05-23T17:25:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Protein-Protein Interaction抽出におけるShortest Dependency Pathを用いた双方向LSTMの効果（Feature Assisted bi-directional LSTM Model for Protein-Protein Interaction Identification from Biomedical Texts）</news:title>
   <news:publication_date>2026-05-23T17:25:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693476</loc>
  <lastmod>2026-05-23T17:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳房DCE-MRIの自動深層学習ベースの正規化（Automatic deep learning-based normalization of breast dynamic contrast-enhanced magnetic resonance images）</news:title>
   <news:publication_date>2026-05-23T17:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693474</loc>
  <lastmod>2026-05-23T17:24:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的証拠連鎖によるスケーラブルなレコメンダー（Scalable Recommender Systems through Recursive Evidence Chains）</news:title>
   <news:publication_date>2026-05-23T17:24:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693472</loc>
  <lastmod>2026-05-23T17:24:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gridbot：脳の航法系を模倣するスパイキングニューラルネットワークで制御される自律ロボット (Gridbot: An autonomous robot controlled by a Spiking Neural Network mimicking the brain’s navigational system)</news:title>
   <news:publication_date>2026-05-23T17:24:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693470</loc>
  <lastmod>2026-05-23T17:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン多対象追跡のための時空間KSVD辞書学習（Spatiotemporal KSVD Dictionary Learning for Online Multi-target Tracking）</news:title>
   <news:publication_date>2026-05-23T17:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693468</loc>
  <lastmod>2026-05-23T16:33:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的経路積分オートエンコーダによる表現学習と計画（Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems）</news:title>
   <news:publication_date>2026-05-23T16:33:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693466</loc>
  <lastmod>2026-05-23T16:32:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Siamese-LSTMによる3Dヒューマンアクション認識（3D Human Action Recognition with Siamese-LSTM Based Deep Metric Learning）</news:title>
   <news:publication_date>2026-05-23T16:32:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693464</loc>
  <lastmod>2026-05-23T16:32:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LHCにおける作用素の特定を学ぶ：t¯tb¯b最終状態の解析（Learning to pinpoint effective operators at the LHC: a study of the t¯tb¯b signature）</news:title>
   <news:publication_date>2026-05-23T16:32:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693462</loc>
  <lastmod>2026-05-23T16:32:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的遅延フィードバックを伴う線形バンディット（Linear Bandits with Stochastic Delayed Feedback）</news:title>
   <news:publication_date>2026-05-23T16:32:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693460</loc>
  <lastmod>2026-05-23T16:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による弱レンズシアー測定の革新（Weak-lensing shear measurement with machine learning）</news:title>
   <news:publication_date>2026-05-23T16:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693458</loc>
  <lastmod>2026-05-23T16:31:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在的な3次元キーポイントの発見とエンドツーエンド幾何推論（Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning）</news:title>
   <news:publication_date>2026-05-23T16:31:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693456</loc>
  <lastmod>2026-05-23T16:31:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子構造固有関数を用いたスケーラブルなガウス過程（Scalable Gaussian Processes with Grid-Structured Eigenfunctions）</news:title>
   <news:publication_date>2026-05-23T16:31:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693454</loc>
  <lastmod>2026-05-23T15:40:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる背景差分アルゴリズムを統合するCNNによる前景検出の改良（Combining Background Subtraction Algorithms with Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-23T15:40:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693452</loc>
  <lastmod>2026-05-23T15:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標志向トラジェクトリによる効率的探索（Goal-oriented Trajectories for Efficient Exploration）</news:title>
   <news:publication_date>2026-05-23T15:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693450</loc>
  <lastmod>2026-05-23T15:39:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経路積分の曲率が引き起こす影響を解く—平均場Matsubara力学による回転振動スペクトル解析（Mean-field Matsubara dynamics: analysis of path-integral curvature effects in rovibrational spectra）</news:title>
   <news:publication_date>2026-05-23T15:39:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693448</loc>
  <lastmod>2026-05-23T15:38:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーボン富化岩石型系外惑星の鉱物学と居住可能性の実験的解明（Mineralogy, structure and habitability of carbon-enriched rocky exoplanets: A laboratory approach）</news:title>
   <news:publication_date>2026-05-23T15:38:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693446</loc>
  <lastmod>2026-05-23T15:38:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河平面を貫く球状星団の軌道と崩壊の兆候（THE ORBIT OF THE NEW MILKY WAY GLOBULAR CLUSTER FSR1716 = VVV-GC05）</news:title>
   <news:publication_date>2026-05-23T15:38:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693444</loc>
  <lastmod>2026-05-23T15:38:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銅と二酸化ケイ素のための高精度機械学習力場の構築（Construction of accurate machine learning force fields for copper and silicon dioxide）</news:title>
   <news:publication_date>2026-05-23T15:38:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693442</loc>
  <lastmod>2026-05-23T15:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットによる同時等化と復号の提案（Joint Neural Network Equalizer and Decoder）</news:title>
   <news:publication_date>2026-05-23T15:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693440</loc>
  <lastmod>2026-05-23T14:46:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TensorFlowにおける大規模モデル支援のグラフ書き換え（TFLMS: Large Model Support in TensorFlow by Graph Rewriting）</news:title>
   <news:publication_date>2026-05-23T14:46:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693438</loc>
  <lastmod>2026-05-23T14:46:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一貫した生成クエリネットワーク（Consistent Generative Query Networks）</news:title>
   <news:publication_date>2026-05-23T14:46:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693436</loc>
  <lastmod>2026-05-23T14:46:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分オートエンコーダで学ぶ地図表現とSLAM（Learning Latent Maps for SLAM with Variational Autoencoders）</news:title>
   <news:publication_date>2026-05-23T14:46:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693434</loc>
  <lastmod>2026-05-23T14:45:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師なし欠陥分割を改善する構造類似度の適用（Improving Unsupervised Defect Segmentation by Applying Structural Similarity To Autoencoders）</news:title>
   <news:publication_date>2026-05-23T14:45:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693432</loc>
  <lastmod>2026-05-23T14:45:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高性能TensorFlowベースのOCRパッケージ Calamari（Calamari − A High-Performance Tensorflow-based Deep Learning Package for Optical Character Recognition）</news:title>
   <news:publication_date>2026-05-23T14:45:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693430</loc>
  <lastmod>2026-05-23T14:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常ベクトル自己回帰時系列からの動的ネットワーク同定（DYNAMIC NETWORK IDENTIFICATION FROM NON-STATIONARY VECTOR AUTOREGRESSIVE TIME SERIES）</news:title>
   <news:publication_date>2026-05-23T14:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693428</loc>
  <lastmod>2026-05-23T14:44:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンデマンド型複数空中基地局の配置法（On-Demand Deployment of Multiple Aerial Base Stations for Traffic Offloading and Network Recovery）</news:title>
   <news:publication_date>2026-05-23T14:44:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693426</loc>
  <lastmod>2026-05-23T13:53:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点情報を見直した効率的群衆カウント（Revisiting Perspective Information for Efficient Crowd Counting）</news:title>
   <news:publication_date>2026-05-23T13:53:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693424</loc>
  <lastmod>2026-05-23T13:53:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>商品陳列物の弱教師ありインスタンスセグメンテーション（Acquire, Augment, Segment &amp;amp; Enjoy: Weakly Supervised Instance Segmentation of Supermarket Products）</news:title>
   <news:publication_date>2026-05-23T13:53:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693422</loc>
  <lastmod>2026-05-23T13:52:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疎表現と非負値行列因子分解による画像ノイズ除去（Sparse Representation and Non-Negative Matrix Factorization for Image Denoising）</news:title>
   <news:publication_date>2026-05-23T13:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693420</loc>
  <lastmod>2026-05-23T13:52:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肉牛の個体分割を簡潔にする手法（Beef Cattle Instance Segmentation Using Fully Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-23T13:52:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693418</loc>
  <lastmod>2026-05-23T13:51:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Bayesian dropoutの落とし穴と修正（Variational Bayesian dropout: pitfalls and ﬁxes）</news:title>
   <news:publication_date>2026-05-23T13:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693416</loc>
  <lastmod>2026-05-23T13:51:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>何が記憶に残るのか — プログラミングMOOCsにおける定着率の実証的知見 (What Stays in Mind? - Retention Rates in Programming MOOCs)</news:title>
   <news:publication_date>2026-05-23T13:51:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693414</loc>
  <lastmod>2026-05-23T13:51:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Arcades: 音声制御スマートホームのための適応型深層意思決定モデル（Arcades: A deep model for adaptive decision making in voice controlled smart-home）</news:title>
   <news:publication_date>2026-05-23T13:51:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693412</loc>
  <lastmod>2026-05-23T13:00:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド技術と拡張現実の展望（The Cloud Technologies and Augmented Reality: the Prospects of Use）</news:title>
   <news:publication_date>2026-05-23T13:00:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693410</loc>
  <lastmod>2026-05-23T12:59:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>開いた量子系における厳密マスター方程式と一般的な非マルコフ動力学（Exact Master Equation and General Non-Markovian Dynamics in Open Quantum Systems）</news:title>
   <news:publication_date>2026-05-23T12:59:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693408</loc>
  <lastmod>2026-05-23T12:59:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンロゴ検出チャレンジ（Open Logo Detection Challenge）</news:title>
   <news:publication_date>2026-05-23T12:59:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693406</loc>
  <lastmod>2026-05-23T12:58:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層スパース信号表現（Deeply-Sparse Signal rePresentations, DS2P）</news:title>
   <news:publication_date>2026-05-23T12:58:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693404</loc>
  <lastmod>2026-05-23T12:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アーキテクチャ性能評価のためのBoo(n)指標（A Boo(n) for Evaluating Architecture Performance）</news:title>
   <news:publication_date>2026-05-23T12:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693402</loc>
  <lastmod>2026-05-23T12:58:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジグソーパズル再構成における局所特徴共起の活用（JIGSAW PUZZLE SOLVING USING LOCAL FEATURE CO-OCCURRENCES IN DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-05-23T12:58:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693400</loc>
  <lastmod>2026-05-23T12:57:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Doomを題材にした補助目的を用いる深層強化学習（Deep Reinforcement Learning for Doom using Unsupervised Auxiliary Tasks）</news:title>
   <news:publication_date>2026-05-23T12:57:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693398</loc>
  <lastmod>2026-05-23T12:06:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小カメラ視点からのボリュメトリックパフォーマンスキャプチャ（Volumetric performance capture from minimal camera viewpoints）</news:title>
   <news:publication_date>2026-05-23T12:06:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693396</loc>
  <lastmod>2026-05-23T12:05:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ロボット運動の最適化と学習制御（Optimizing the Execution of Dynamic Robot Movements with Learning Control）</news:title>
   <news:publication_date>2026-05-23T12:05:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693394</loc>
  <lastmod>2026-05-23T12:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>区間尤度に基づくVAE学習──Kullback-Leibler及びR´enyi積分境界（Learning in Variational Autoencoders with Kullback-Leibler and Renyi Integral Bounds）</news:title>
   <news:publication_date>2026-05-23T12:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693392</loc>
  <lastmod>2026-05-23T12:04:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケール適応型アンカーによる単発テキスト検出器（A Single Shot Text Detector with Scale-adaptive Anchors）</news:title>
   <news:publication_date>2026-05-23T12:04:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693390</loc>
  <lastmod>2026-05-23T12:04:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層行列に基づく多重解像度ニューラルネットワーク（A multiscale neural network based on hierarchical matrices）</news:title>
   <news:publication_date>2026-05-23T12:04:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693388</loc>
  <lastmod>2026-05-23T12:03:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層Bi-GRU-CRFによる中国語語彙解析（Chinese Lexical Analysis with Deep Bi-GRU-CRF Network）</news:title>
   <news:publication_date>2026-05-23T12:03:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693386</loc>
  <lastmod>2026-05-23T12:03:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一鉄テトラフェニルポルフィリンダイアド上の電荷移動ダイナミクスの探索 (Probing Charge Transfer Dynamics in a Single Iron Tetraphenylporphyrin Dyad Adsorbed on an Insulating Surface)</news:title>
   <news:publication_date>2026-05-23T12:03:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693384</loc>
  <lastmod>2026-05-23T11:12:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>さまざまな単語埋め込みが感情分類に与える影響（A Review of Different Word Embeddings for Sentiment Classification using Deep Learning）</news:title>
   <news:publication_date>2026-05-23T11:12:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693382</loc>
  <lastmod>2026-05-23T11:11:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ難読化による学習データのプライバシー保護（Privacy-preserving Machine Learning through Data Obfuscation）</news:title>
   <news:publication_date>2026-05-23T11:11:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693380</loc>
  <lastmod>2026-05-23T11:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ethereumスマートコントラクトの脆弱性検出を画像化で行う手法（Hunting the Ethereum Smart Contract: Color-inspired Inspection of Potential Attacks）</news:title>
   <news:publication_date>2026-05-23T11:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693378</loc>
  <lastmod>2026-05-23T11:10:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディコンボリューション型バックプロジェクトフィルタCT再構成法（Deconvolution-Based Backproject-Filter (BPF) Computed Tomography Image Reconstruction Method Using Deep Learning Technique）</news:title>
   <news:publication_date>2026-05-23T11:10:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693376</loc>
  <lastmod>2026-05-23T11:10:42Z</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から抽出する実行可能な知見――家庭内暴力（Domestic Violence）議論の活用（Extracting Actionable Knowledge from Domestic Violence Discourses on Social Media）</news:title>
   <news:publication_date>2026-05-23T11:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693374</loc>
  <lastmod>2026-05-23T11:10:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジスティック回帰とニューラルネットワークを再解釈する：Dempster–Shafer理論の視点（Logistic Regression, Neural Networks and Dempster-Shafer Theory: a New Perspective）</news:title>
   <news:publication_date>2026-05-23T11:10:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693372</loc>
  <lastmod>2026-05-23T11:10:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なオンライン量子状態推定とMEG法（Efficient online quantum state estimation using a matrix-exponentiated gradient method）</news:title>
   <news:publication_date>2026-05-23T11:10:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693370</loc>
  <lastmod>2026-05-23T10:19:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意思決定ごとの多段階時系列差分学習と制御変量（Per-decision Multi-step Temporal Difference Learning with Control Variates）</news:title>
   <news:publication_date>2026-05-23T10:19:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693368</loc>
  <lastmod>2026-05-23T10:19:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スポンサードサーチにおける収益管理の学習理論とアルゴリズム（Learning Theory and Algorithms for Revenue Management in Sponsored Search）</news:title>
   <news:publication_date>2026-05-23T10:19:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693366</loc>
  <lastmod>2026-05-23T10:18:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PortraitGANによる表情とモダリティの同時操作（PortraitGAN for Simultaneous Emotion and Modality Manipulation）</news:title>
   <news:publication_date>2026-05-23T10:18:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693364</loc>
  <lastmod>2026-05-23T10:18:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティクス保存型敵対学習による深層クロスモダリティ適応（Deep Cross-modality Adaptation via Semantics Preserving Adversarial Learning for Sketch-based 3D Shape Retrieval）</news:title>
   <news:publication_date>2026-05-23T10:18:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693362</loc>
  <lastmod>2026-05-23T10:18:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半勾配に基づく積み上げ分布による離散サンプリング（Discrete Sampling using Semigradient-based Product Mixtures）</news:title>
   <news:publication_date>2026-05-23T10:18:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693360</loc>
  <lastmod>2026-05-23T10:18:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダーを用いた行列補完のデータ依存正則化（Regularizing Autoencoder-Based Matrix Completion Models via Manifold Learning）</news:title>
   <news:publication_date>2026-05-23T10:18:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693358</loc>
  <lastmod>2026-05-23T10:17:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TextTopicNetによる自己教師あり視覚特徴学習（TextTopicNet - Self-Supervised Learning of Visual Features Through Embedding Images on Semantic Text Spaces）</news:title>
   <news:publication_date>2026-05-23T10:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693356</loc>
  <lastmod>2026-05-23T09:26:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化表現学習による医用画像の逆問題への応用（Learning Personalized Representation for Inverse Problems in Medical Imaging Using Deep Neural Network）</news:title>
   <news:publication_date>2026-05-23T09:26:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693354</loc>
  <lastmod>2026-05-23T09:20:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文法駆動のツリー・トゥ・ツリーによるプログラム言語翻訳（Program Language Translation Using a Grammar-Driven Tree-to-Tree Model）</news:title>
   <news:publication_date>2026-05-23T09:20:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693352</loc>
  <lastmod>2026-05-23T09:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BOHBによる大規模ハイパーパラメータ最適化の実用化（BOHB: Robust and Efficient Hyperparameter Optimization at Scale）</news:title>
   <news:publication_date>2026-05-23T09:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693350</loc>
  <lastmod>2026-05-23T09:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>X線スペクトルから導く赤方偏移（XZ: Deriving redshifts from X-ray spectra of obscured AGN）</news:title>
   <news:publication_date>2026-05-23T09:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693348</loc>
  <lastmod>2026-05-23T09:17:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seq2RDFによる自然文からのトリプル抽出（Seq2RDF: An end-to-end application for deriving Triples from Natural Language Text）</news:title>
   <news:publication_date>2026-05-23T09:17:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693346</loc>
  <lastmod>2026-05-23T09:17:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子ベースの変分推論の理解と加速（Understanding and Accelerating Particle-Based Variational Inference）</news:title>
   <news:publication_date>2026-05-23T09:17:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693344</loc>
  <lastmod>2026-05-23T09:17:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療セカンドオピニオンのための不確実性直接予測（Direct Uncertainty Prediction for Medical Second Opinions）</news:title>
   <news:publication_date>2026-05-23T09:17:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693342</loc>
  <lastmod>2026-05-23T08:25:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模統計モデリングとセンサー／アクチュエータ選択のための近接アルゴリズム（Proximal algorithms for large-scale statistical modeling and sensor/actuator selection）</news:title>
   <news:publication_date>2026-05-23T08:25:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693340</loc>
  <lastmod>2026-05-23T08:24:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推薦システムと自己動機付けユーザー（Recommendation Systems and Self Motivated Users）</news:title>
   <news:publication_date>2026-05-23T08:24:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693338</loc>
  <lastmod>2026-05-23T08:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AGNと星形成の関係をXMM-Newtonで解く（Disentangling the AGN and star formation connection using XMM-Newton）</news:title>
   <news:publication_date>2026-05-23T08:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693336</loc>
  <lastmod>2026-05-23T08:23:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Model Featuresによる強化学習の転移（Transfer with Model Features）</news:title>
   <news:publication_date>2026-05-23T08:23:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693334</loc>
  <lastmod>2026-05-23T08:23:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的な画像劣化と表面変化に対するニューラルネットワークの堅牢性評価（Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations）</news:title>
   <news:publication_date>2026-05-23T08:23:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693332</loc>
  <lastmod>2026-05-23T08:22:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LaneNet: 実時間車載レーン検出ネットワーク（LaneNet: Real-Time Lane Detection Networks for Autonomous Driving）</news:title>
   <news:publication_date>2026-05-23T08:22:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693330</loc>
  <lastmod>2026-05-23T08:22:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レクスとヤックで学ぶコンパイラ教育の共同利用法（Methodic of joint using the tools of automation of lexical and parsing analysis）</news:title>
   <news:publication_date>2026-05-23T08:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693328</loc>
  <lastmod>2026-05-23T07:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動詞の意味タイプ自動識別に向けた取り組み（Towards Automation of Sense-type Identification of Verbs in OntoSenseNet(Telugu)）</news:title>
   <news:publication_date>2026-05-23T07:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693326</loc>
  <lastmod>2026-05-23T07:23:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPIDERによる非凸最適化の効率化（Spider: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator）</news:title>
   <news:publication_date>2026-05-23T07:23:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693324</loc>
  <lastmod>2026-05-23T07:22:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報学士に求められるプログラミング能力の構築（Bachelor of Informatics Competence in Programming）</news:title>
   <news:publication_date>2026-05-23T07:22:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693322</loc>
  <lastmod>2026-05-23T07:22:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MandarinとCantoneseのF0輪郭予測手法の比較とAdditive-BLSTMの提案（Generating Mandarin and Cantonese F0 Contours with Decision Trees and BLSTMs）</news:title>
   <news:publication_date>2026-05-23T07:22:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693320</loc>
  <lastmod>2026-05-23T07:21:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプル効率の高い強化学習とSTEVE（Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion）</news:title>
   <news:publication_date>2026-05-23T07:21:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693318</loc>
  <lastmod>2026-05-23T07:21:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テルグ語の語単位感情注釈によるベンチマークコーパスの構築（BCSAT: A Benchmark Corpus for Sentiment Analysis in Telugu Using Word-level Annotations）</news:title>
   <news:publication_date>2026-05-23T07:21:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693316</loc>
  <lastmod>2026-05-23T07:21:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランクド・リワードによる自己対戦強化学習の単一プレイヤー最適化への応用（Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial Optimization）</news:title>
   <news:publication_date>2026-05-23T07:21:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693314</loc>
  <lastmod>2026-05-23T06:29:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MIXGANによるドメイン概念の混合生成（MIXGAN: Learning Concepts from Different Domains for Mixture Generation）</news:title>
   <news:publication_date>2026-05-23T06:29:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693312</loc>
  <lastmod>2026-05-23T06:29:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散電力網の状態推定を学習で初期化する新手法（Data-Driven Learning-Based Optimization for Distribution System State Estimation）</news:title>
   <news:publication_date>2026-05-23T06:29:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693310</loc>
  <lastmod>2026-05-23T06:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語から空間関係を理解する（Encoding Spatial Relations from Natural Language）</news:title>
   <news:publication_date>2026-05-23T06:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693308</loc>
  <lastmod>2026-05-23T06:28:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブサンプリングによるプライバシー増幅（Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences）</news:title>
   <news:publication_date>2026-05-23T06:28:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693306</loc>
  <lastmod>2026-05-23T06:28:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間自己回帰による新規性検出（Latent Space Autoregression for Novelty Detection）</news:title>
   <news:publication_date>2026-05-23T06:28:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693304</loc>
  <lastmod>2026-05-23T06:27:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三次元受動スカラー混合における急峻な「崖」と飽和するスケーリング指数（Steep cliffs and saturated exponents in three dimensional scalar turbulence）</news:title>
   <news:publication_date>2026-05-23T06:27:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693302</loc>
  <lastmod>2026-05-23T06:27:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙地図による視覚的3D自己位置推定（Learning models for visual 3D localization with implicit mapping）</news:title>
   <news:publication_date>2026-05-23T06:27:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693300</loc>
  <lastmod>2026-05-23T05:35:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングによる多色ローカリゼーション顕微鏡の可能性（Multicolor localization microscopy by deep learning）</news:title>
   <news:publication_date>2026-05-23T05:35:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693298</loc>
  <lastmod>2026-05-23T05:34:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cimple: 命令並列性とメモリ並列性を引き出すDSL（Cimple: Instruction and Memory Level Parallelism）</news:title>
   <news:publication_date>2026-05-23T05:34:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693296</loc>
  <lastmod>2026-05-23T05:34:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新生児の痛み表情認識における転移学習の実用性（Neonatal Pain Expression Recognition Using Transfer Learning）</news:title>
   <news:publication_date>2026-05-23T05:34:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693294</loc>
  <lastmod>2026-05-23T05:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Conformal PredictorsとEnsemble学習で信頼性を付与したMCIからアルツハイマーへの予後予測（Ensemble learning with Conformal Predictors: Targeting credible predictions of conversion from Mild Cognitive Impairment to Alzheimer’s Disease）</news:title>
   <news:publication_date>2026-05-23T05:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693292</loc>
  <lastmod>2026-05-23T05:33:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Processes（Neural Processes）</news:title>
   <news:publication_date>2026-05-23T05:33:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693290</loc>
  <lastmod>2026-05-23T05:33:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LHeCとFCC-heにおけるBSM物理学（BSM physics at the LHeC and the FCC-he）</news:title>
   <news:publication_date>2026-05-23T05:33:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693288</loc>
  <lastmod>2026-05-23T05:33:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サッカー試合結果予測の統計モデル比較と検証手法（Modeling outcomes of soccer matches）</news:title>
   <news:publication_date>2026-05-23T05:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693286</loc>
  <lastmod>2026-05-23T04:41:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QMCによる変分推論の高速化（Quasi-Monte Carlo Variational Inference）</news:title>
   <news:publication_date>2026-05-23T04:41:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693284</loc>
  <lastmod>2026-05-23T04:41:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Conditional Neural Processes（Conditional Neural Processes）</news:title>
   <news:publication_date>2026-05-23T04:41:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693282</loc>
  <lastmod>2026-05-23T04:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察者の脳波からエラー情報を読み解く際のロボット設計の影響（The role of robot design in decoding error-related information from EEG signals of a human observer）</news:title>
   <news:publication_date>2026-05-23T04:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693280</loc>
  <lastmod>2026-05-23T04:40:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BayesGradによるグラフCNN予測の説明（BayesGrad: Explaining Predictions of Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-05-23T04:40:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693278</loc>
  <lastmod>2026-05-23T04:40:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SEN1-2データセットによるSAR-光学データ融合の深層学習（THE SEN1-2 DATASET FOR DEEP LEARNING IN SAR-OPTICAL DATA FUSION）</news:title>
   <news:publication_date>2026-05-23T04:40:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693276</loc>
  <lastmod>2026-05-23T04:39:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次（Quadratic）ニューラルネットワークとファジィ論理の接点（Quadratic Neural Networks and Fuzzy Logic）</news:title>
   <news:publication_date>2026-05-23T04:39:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693274</loc>
  <lastmod>2026-05-23T04:39:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OFDMベースの多段水中音響センサネットワークにおける秘匿率最大化（Maximizing Secrecy Rate of an OFDM-based Multi-hop Underwater Acoustic Sensor Network）</news:title>
   <news:publication_date>2026-05-23T04:39:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693272</loc>
  <lastmod>2026-05-23T03:48:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広帯域時刻領域デジタル逆変換のサブバンド処理と深層学習（Wideband Time-Domain Digital Backpropagation via Subband Processing and Deep Learning）</news:title>
   <news:publication_date>2026-05-23T03:48:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693270</loc>
  <lastmod>2026-05-23T03:48:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床時系列データ解析における転移学習の応用（Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-23T03:48:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693268</loc>
  <lastmod>2026-05-23T03:48:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TextSnakeによる任意形状テキスト検出の柔軟な表現（TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes）</news:title>
   <news:publication_date>2026-05-23T03:48:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693266</loc>
  <lastmod>2026-05-23T03:46:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療記録の合成データ生成法の実務的意義（Generating Synthetic but Plausible Healthcare Record Datasets）</news:title>
   <news:publication_date>2026-05-23T03:46:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693264</loc>
  <lastmod>2026-05-23T03:46:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復デコンボリューションによる量子制御パルスの較正（Learning to Calibrate Quantum Control Pulses by Iterative Deconvolution）</news:title>
   <news:publication_date>2026-05-23T03:46:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693262</loc>
  <lastmod>2026-05-23T03:46:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習された分離されたゴール空間の好奇心駆動探索（Curiosity Driven Exploration of Learned Disentangled Goal Spaces）</news:title>
   <news:publication_date>2026-05-23T03:46:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693260</loc>
  <lastmod>2026-05-23T03:46:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による部分形状のファジー集合表現（Learning Fuzzy Set Representations of Partial Shapes on Dual Embedding Spaces）</news:title>
   <news:publication_date>2026-05-23T03:46:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693258</loc>
  <lastmod>2026-05-23T02:54:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な画像スタイル転送のための非相関特徴符号化 (Uncorrelated Feature Encoding for Faster Image Style Transfer)</news:title>
   <news:publication_date>2026-05-23T02:54:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693256</loc>
  <lastmod>2026-05-23T02:45:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層オートエンコーダによる人体姿勢推定と体形アップスケーリング（Deep Autoencoder for Combined Human Pose Estimation and Body Model Upscaling）</news:title>
   <news:publication_date>2026-05-23T02:45:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693254</loc>
  <lastmod>2026-05-23T02:44:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分解可能バンディット（Factored Bandits）</news:title>
   <news:publication_date>2026-05-23T02:44:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693252</loc>
  <lastmod>2026-05-23T02:44:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験的固定点分岐解析の実務的示唆（Empirical Fixed Point Bifurcation Analysis）</news:title>
   <news:publication_date>2026-05-23T02:44:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693250</loc>
  <lastmod>2026-05-23T02:43:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型ニューラルネットワークを用いた教師あり強化学習による動的治療推薦（Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation）</news:title>
   <news:publication_date>2026-05-23T02:43:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693248</loc>
  <lastmod>2026-05-23T02:43:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習における多様性（Diversity in Machine Learning）</news:title>
   <news:publication_date>2026-05-23T02:43:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693246</loc>
  <lastmod>2026-05-23T02:43:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主成分分析を用いたテキスト分類の比較研究（A Comparative Study on using Principle Component Analysis with Different Text Classifiers）</news:title>
   <news:publication_date>2026-05-23T02:43:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693244</loc>
  <lastmod>2026-05-23T01:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度検索のための深層サリエンシーハッシング（Deep Saliency Hashing for Fine-grained Retrieval）</news:title>
   <news:publication_date>2026-05-23T01:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693242</loc>
  <lastmod>2026-05-23T01:51:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情の二面性――極性（Polarity）と強度（Intensity）によるセンチメント解析の再定義 (Polarity and Intensity: the Two Aspects of Sentiment Analysis)</news:title>
   <news:publication_date>2026-05-23T01:51:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693240</loc>
  <lastmod>2026-05-23T01:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プラグ&amp;amp;プレイ型深層局所線形埋め込みによる映像フレーム補間（Video Frame Interpolation by Plug-and-Play Deep Locally Linear Embedding）</news:title>
   <news:publication_date>2026-05-23T01:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693238</loc>
  <lastmod>2026-05-23T01:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前景注意に基づく識別的特徴学習による人物再識別（Discriminative Feature Learning with Foreground Attention for Person Re-identification）</news:title>
   <news:publication_date>2026-05-23T01:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/693236</loc>
  <lastmod>2026-05-23T01:50:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成画像から実画像へ転移学習するVAEによる高精度位置検出（TRANSFER LEARNING FROM SYNTHETIC TO REAL IMAGES USING VARIATIONAL AUTOENCODERS FOR PRECISE POSITION DETECTION）</news:title>
   <news:publication_date>2026-05-23T01:50:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693234</loc>
  <lastmod>2026-05-23T01:50:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広告画像の意味を読むための共注意による記号と物体の整合（Understanding Visual Ads by Aligning Symbols and Objects using Co-Attention）</news:title>
   <news:publication_date>2026-05-23T01:50:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693232</loc>
  <lastmod>2026-05-23T01:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二層ルテネートにおけるモット転移近傍の電子質量増強と磁気相分離（Electron mass enhancement and magnetic phase separation near the Mott transition in double layer ruthenates）</news:title>
   <news:publication_date>2026-05-23T01:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693230</loc>
  <lastmod>2026-05-23T00:58:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未教師ありのドメイン適応で人物識別を横断的に改善する手法（Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification）</news:title>
   <news:publication_date>2026-05-23T00:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693228</loc>
  <lastmod>2026-05-23T00:58:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルにスパースなずれを加えて圧縮センシングを拡張する（Modeling Sparse Deviations for Compressed Sensing using Generative Models）</news:title>
   <news:publication_date>2026-05-23T00:58:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693226</loc>
  <lastmod>2026-05-23T00:58:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QoSに基づくWebサービスの探索と選択（Qos-Based Web Service Discovery And Selection Using Machine Learning）</news:title>
   <news:publication_date>2026-05-23T00:58:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693224</loc>
  <lastmod>2026-05-23T00:57:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力ごとにブロックを落とす学習（SGAD: Soft-Guided Adaptively-Dropped Neural Network）</news:title>
   <news:publication_date>2026-05-23T00:57:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693222</loc>
  <lastmod>2026-05-23T00:57:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小スケール歩行者検出の新手法（Small-scale Pedestrian Detection Based on Somatic Topology Localization and Temporal Feature Aggregation）</news:title>
   <news:publication_date>2026-05-23T00:57:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693220</loc>
  <lastmod>2026-05-23T00:56:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Batch Normalization の再構成による CNN 学習高速化（Restructuring Batch Normalization to Accelerate CNN Training）</news:title>
   <news:publication_date>2026-05-23T00:56:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693218</loc>
  <lastmod>2026-05-23T00:56:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データが乏しい実験でも機械学習は使える――合成データで覆い隠れた秩序を掘り起こす（Machine Learning in a data-limited regime: Augmenting experiments with synthetic data uncovers order in crumpled sheets）</news:title>
   <news:publication_date>2026-05-23T00:56:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693216</loc>
  <lastmod>2026-05-23T00:05:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きオートマトンと再帰型ニューラルネットワークの結びつき（Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning）</news:title>
   <news:publication_date>2026-05-23T00:05:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693214</loc>
  <lastmod>2026-05-22T23:56:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>到達領域を段階的に拡大するカリキュラム生成（Region Growing Curriculum Generation for Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-22T23:56:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693212</loc>
  <lastmod>2026-05-22T23:56:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイアスを排した画像スタイル転送の回帰的制御（Unbiased Image Style Transfer）</news:title>
   <news:publication_date>2026-05-22T23:56:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693210</loc>
  <lastmod>2026-05-22T23:55:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データに対する特徴選択付き対角判別分析（Diagonal Discriminant Analysis with Feature Selection for High Dimensional Data）</news:title>
   <news:publication_date>2026-05-22T23:55:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693208</loc>
  <lastmod>2026-05-22T23:54:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Grassmannian上のエンドメンバー抽出（ENDMEMBER EXTRACTION ON THE GRASSMANNIAN）</news:title>
   <news:publication_date>2026-05-22T23:54:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693206</loc>
  <lastmod>2026-05-22T23:54:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床ノートから学ぶ患者表現と可解性評価（Patient representation learning and interpretable evaluation using clinical notes）</news:title>
   <news:publication_date>2026-05-22T23:54:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693204</loc>
  <lastmod>2026-05-22T23:54:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線通信への深層学習を用いたジャミング攻撃と防御（Deep Learning for Launching and Mitigating Wireless Jamming Attacks）</news:title>
   <news:publication_date>2026-05-22T23:54:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693202</loc>
  <lastmod>2026-05-22T23:02:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層モデリングとフォトメトリック赤方偏移の統計的較正（Hierarchical modeling and statistical calibration for photometric redshifts）</news:title>
   <news:publication_date>2026-05-22T23:02:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693200</loc>
  <lastmod>2026-05-22T23:02:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡散による捕獲と拡散相互作用の概念（Diffusion to Capture and the Concept of Diffusive Interactions）</news:title>
   <news:publication_date>2026-05-22T23:02:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693198</loc>
  <lastmod>2026-05-22T23:02:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビッグデータの視覚的パターンドリブン探索（Visual Pattern-Driven Exploration of Big Data）</news:title>
   <news:publication_date>2026-05-22T23:02:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693196</loc>
  <lastmod>2026-05-22T23:01:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚疾患画像の異常検知におけるVariational Autoencoderの応用（Anomaly Detection for Skin Disease Images Using Variational Autoencoder）</news:title>
   <news:publication_date>2026-05-22T23:01:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693194</loc>
  <lastmod>2026-05-22T23:01:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習のためのクラウド技術の起源（THE CLOUD TECHNOLOGIES OF LEARNING: ORIGIN）</news:title>
   <news:publication_date>2026-05-22T23:01:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693192</loc>
  <lastmod>2026-05-22T23:00:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン圧縮型テンソル分解 OCTen（OCTen: Online Compression-based Tensor Decomposition）</news:title>
   <news:publication_date>2026-05-22T23:00:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693190</loc>
  <lastmod>2026-05-22T23:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アナログ配列向け高効率ConvNet設計（Efficient ConvNets for Analog Arrays）</news:title>
   <news:publication_date>2026-05-22T23:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693188</loc>
  <lastmod>2026-05-22T22:08:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型資源配分の効率設計——エージェント報酬最適化による正確なPrice of Anarchyの解析（Utility Design for Distributed Resource Allocation – Part I: Characterizing and Optimizing the Exact Price of Anarchy）</news:title>
   <news:publication_date>2026-05-22T22:08:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693186</loc>
  <lastmod>2026-05-22T21:59:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳がん診断における分類アルゴリズムの比較（Breast Cancer Diagnosis via Classification Algorithms）</news:title>
   <news:publication_date>2026-05-22T21:59:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693184</loc>
  <lastmod>2026-05-22T21:58:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顧客サポートを高速かつ高精度にするCOTA（COTA: Improving the Speed and Accuracy of Customer Support through Ranking and Deep Networks）</news:title>
   <news:publication_date>2026-05-22T21:58:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693182</loc>
  <lastmod>2026-05-22T21:57:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多モーダル生体認証のための一般化双線形深層畳み込みニューラルネットワーク（GENERALIZED BILINEAR DEEP CONVOLUTIONAL NEURAL NETWORKS FOR MULTIMODAL BIOMETRIC IDENTIFICATION）</news:title>
   <news:publication_date>2026-05-22T21:57:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693180</loc>
  <lastmod>2026-05-22T21:57:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期宇宙の星形成に関する制約（Constraints on Early Star Formation from the 21-cm Global Signal）</news:title>
   <news:publication_date>2026-05-22T21:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693178</loc>
  <lastmod>2026-05-22T21:57:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポストスター ブラスト銀河の構造と消光経路の二分化（The structure of post-starburst galaxies at 0.5 &amp;lt; z &amp;lt; 2: evidence for two distinct quenching routes at different epochs）</news:title>
   <news:publication_date>2026-05-22T21:57:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693176</loc>
  <lastmod>2026-05-22T21:57:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークからの多層特徴抽象化によるマルチモーダル生体認証（Multi-Level Feature Abstraction from Convolutional Neural Networks for Multimodal Biometric Identification）</news:title>
   <news:publication_date>2026-05-22T21:57:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693174</loc>
  <lastmod>2026-05-22T21:05:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dタンパク質構造に基づくエンドツーエンド学習によるインターフェース予測（End-to-End Learning on 3D Protein Structure for Interface Prediction）</news:title>
   <news:publication_date>2026-05-22T21:05:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693172</loc>
  <lastmod>2026-05-22T21:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似サーベイ伝播法による統計的推論（Approximate Survey Propagation for Statistical Inference）</news:title>
   <news:publication_date>2026-05-22T21:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693170</loc>
  <lastmod>2026-05-22T21:04:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1人称マルチプレイヤーゲームで人間レベルを達成した研究（Human-level performance in first-person multiplayer games with population-based deep reinforcement learning）</news:title>
   <news:publication_date>2026-05-22T21:04:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693168</loc>
  <lastmod>2026-05-22T21:04:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間レベルに迫る文法誤り訂正の新戦略（Reaching Human-Level Performance in Automatic Grammatical Error Correction: An Empirical Study）</news:title>
   <news:publication_date>2026-05-22T21:04:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693166</loc>
  <lastmod>2026-05-22T21:03:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然と対峙する意思決定：不確実性下の因果発見（Playing against Nature: causal discovery for decision making under uncertainty）</news:title>
   <news:publication_date>2026-05-22T21:03:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693164</loc>
  <lastmod>2026-05-22T21:03:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン勾配降下法の計算力について（On the Computational Power of Online Gradient Descent）</news:title>
   <news:publication_date>2026-05-22T21:03:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693162</loc>
  <lastmod>2026-05-22T21:03:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索と活用の動的制御（Dynamic Control of Explore/Exploit Trade-Off In Bayesian Optimization）</news:title>
   <news:publication_date>2026-05-22T21:03:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693160</loc>
  <lastmod>2026-05-22T20:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり適応DenseNetによる胸部疾患分類と異常箇所同定（A Weakly Supervised Adaptive DenseNet for Classifying Thoracic Diseases and Identifying Abnormalities）</news:title>
   <news:publication_date>2026-05-22T20:12:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693158</loc>
  <lastmod>2026-05-22T20:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遮蔽と限られたセンサー範囲に対処する集合ベースの安全検証（Tackling Occlusions &amp;amp; Limited Sensor Range with Set-based Safety Verification）</news:title>
   <news:publication_date>2026-05-22T20:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693156</loc>
  <lastmod>2026-05-22T20:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応学習ダイナミクスの安定性解析（On the stability of an adaptive learning dynamics in traffic games）</news:title>
   <news:publication_date>2026-05-22T20:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693154</loc>
  <lastmod>2026-05-22T20:10:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細胞内シグナルネットワークにおける非連合学習の報告（Non-associative learning in intra-cellular signaling networks）</news:title>
   <news:publication_date>2026-05-22T20:10:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693152</loc>
  <lastmod>2026-05-22T20:10:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数領域における深層ニューラルネットワークの学習挙動（Training behavior of deep neural network in frequency domain）</news:title>
   <news:publication_date>2026-05-22T20:10:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693150</loc>
  <lastmod>2026-05-22T20:10:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SpaceNet: リモートセンシングデータセットとチャレンジ（SpaceNet: A Remote Sensing Dataset and Challenge）</news:title>
   <news:publication_date>2026-05-22T20:10:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693148</loc>
  <lastmod>2026-05-22T20:09:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子版GANによる離散分布生成の提案（Quantum generative adversarial network for generating discrete distribution）</news:title>
   <news:publication_date>2026-05-22T20:09:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693146</loc>
  <lastmod>2026-05-22T19:17:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形フォワードモデルに対する深層ニューラルネットワークによる超音波反射トモグラフィ再構成（DEEP NEURAL NETWORKS FOR NON-LINEAR MODEL-BASED ULTRASOUND RECONSTRUCTION）</news:title>
   <news:publication_date>2026-05-22T19:17:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693144</loc>
  <lastmod>2026-05-22T19:16:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所勾配平滑化による局所的敵対的攻撃の防御（Local Gradients Smoothing: Defense against localized adversarial attacks）</news:title>
   <news:publication_date>2026-05-22T19:16:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693142</loc>
  <lastmod>2026-05-22T19:16:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>整流を使った一本鎖DNAの配列決定（ssDNA sequencing by rectification）</news:title>
   <news:publication_date>2026-05-22T19:16:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693140</loc>
  <lastmod>2026-05-22T19:15:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マスターのプライバシーを守る符号化分散計算（Private Coded Computation for Machine Learning）</news:title>
   <news:publication_date>2026-05-22T19:15:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693138</loc>
  <lastmod>2026-05-22T19:15:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファッションのスタイルを学習してアイテムを補完する手法（Styling with Attention to Details）</news:title>
   <news:publication_date>2026-05-22T19:15:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693136</loc>
  <lastmod>2026-05-22T19:14:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>狭い深層ニューラルネットワークの判定領域について（On decision regions of narrow deep neural networks）</news:title>
   <news:publication_date>2026-05-22T19:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693134</loc>
  <lastmod>2026-05-22T19:14:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数カテゴリ変数を生成するGANの設計と評価（Generating Multi-Categorical Samples with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-22T19:14:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693132</loc>
  <lastmod>2026-05-22T18:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率ベースの独立サンプラーによるグラフィカル対数線形周辺モデルのベイズ定量学習（Probability Based Independence Sampler for Bayesian Quantitative Learning in Graphical Log-Linear Marginal Models）</news:title>
   <news:publication_date>2026-05-22T18:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693130</loc>
  <lastmod>2026-05-22T18:12:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>騒がしい学習データを扱う視覚検査のためのGANによる異常検知（Anomaly Detection Using GANs for Visual Inspection in Noisy Training Data）</news:title>
   <news:publication_date>2026-05-22T18:12:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693128</loc>
  <lastmod>2026-05-22T18:11:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公正分類の福祉と分配への影響（Welfare and Distributional Impacts of Fair Classification）</news:title>
   <news:publication_date>2026-05-22T18:11:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693126</loc>
  <lastmod>2026-05-22T18:11:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストなしで行間を読む：視覚・音響モダリティからのスケーラブルなマルチモーダル感情分類（Getting the subtext without the text: Scalable multimodal sentiment classification from visual and acoustic modalities）</news:title>
   <news:publication_date>2026-05-22T18:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693124</loc>
  <lastmod>2026-05-22T18:11:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり深層リカレントニューラルネットワークによる基本ダンスステップ生成（Weakly-Supervised Deep Recurrent Neural Networks for Basic Dance Step Generation）</news:title>
   <news:publication_date>2026-05-22T18:11:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693122</loc>
  <lastmod>2026-05-22T18:11:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SageMathCloudを用いた学生の協働支援の学習手法（The Learning Technique of the SageMathCloud Use for Students Collaboration Support）</news:title>
   <news:publication_date>2026-05-22T18:11:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693120</loc>
  <lastmod>2026-05-22T18:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SageMath Cloudを用いた高等学校数学教育の方法論（The Methodical Aspects of the Algebra and the Mathematical Analysis Study Using the SageMath Cloud）</news:title>
   <news:publication_date>2026-05-22T18:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693118</loc>
  <lastmod>2026-05-22T17:19:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教育機関のクラウド型コンピュータ数学システム（The Systems of Computer Mathematics in the Cloud-Based Learning Environment of Educational Institutions）</news:title>
   <news:publication_date>2026-05-22T17:19:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693116</loc>
  <lastmod>2026-05-22T17:18:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的チャネル非相関化ネットワーク（Stochastic Channel Decorrelation Network and Its Application to Visual Tracking）</news:title>
   <news:publication_date>2026-05-22T17:18:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693114</loc>
  <lastmod>2026-05-22T17:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド上の計算数学システムを用いた学習コンポーネントの設計と評価（The Design and Evaluation of the Cloud-based Learning Components with the Use of the Systems of Computer Mathematics）</news:title>
   <news:publication_date>2026-05-22T17:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693112</loc>
  <lastmod>2026-05-22T17:18:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の平均場最適制御定式化（A Mean-Field Optimal Control Formulation of Deep Learning）</news:title>
   <news:publication_date>2026-05-22T17:18:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693110</loc>
  <lastmod>2026-05-22T17:17:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガンマ線ログ法における欠損値復元の実用的提案（Recovering Gaps in the Gamma-Ray Logging Method）</news:title>
   <news:publication_date>2026-05-22T17:17:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693108</loc>
  <lastmod>2026-05-22T17:17:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジでの階層的容量配備（HIERARCHICAL CAPACITY PROVISIONING FOR FOG COMPUTING）</news:title>
   <news:publication_date>2026-05-22T17:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693106</loc>
  <lastmod>2026-05-22T17:17:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワン・クラス・カーネル・スペクトル回帰の要点（One-Class Kernel Spectral Regression）</news:title>
   <news:publication_date>2026-05-22T17:17:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693104</loc>
  <lastmod>2026-05-22T16:25:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BIN-CT による都市ごみ収集の最適化（BIN-CT: Urban Waste Collection based on Predicting the Container Fill Level）</news:title>
   <news:publication_date>2026-05-22T16:25:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693102</loc>
  <lastmod>2026-05-22T16:25:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画セグメンテーションの新潮流：VideoGCRFがもたらす一貫性ある予測（Deep Spatio-Temporal Random Fields for Efficient Video Segmentation）</news:title>
   <news:publication_date>2026-05-22T16:25:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693100</loc>
  <lastmod>2026-05-22T16:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HAMLETによる脳白質トラクト学習の革新（HAMLET: Hierarchical Harmonic Filters for Learning Tracts from Diffusion MRI）</news:title>
   <news:publication_date>2026-05-22T16:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693098</loc>
  <lastmod>2026-05-22T16:24:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動ポリシー推定とオフポリシー評価における較正の重要性（Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters）</news:title>
   <news:publication_date>2026-05-22T16:24:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693096</loc>
  <lastmod>2026-05-22T16:24:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマノイドロボットによる対話的聴覚探索による深層物体解析（Deep Neural Object Analysis by Interactive Auditory Exploration with a Humanoid Robot）</news:title>
   <news:publication_date>2026-05-22T16:24:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693094</loc>
  <lastmod>2026-05-22T16:24:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データ時代のガウス過程レビュー（When Gaussian Process Meets Big Data: A Review of Scalable GPs）</news:title>
   <news:publication_date>2026-05-22T16:24:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/693092</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>初期太陽系の短寿命放射性同位体の起源：AGB星および大質量星シナリオの問題点（On the Origin of the Early Solar System Radioactivities: Problems with the AGB and Massive Star Scenarios）</news:title>
   <news:publication_date>2026-05-22T16:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/693090</loc>
  <lastmod>2026-05-22T15:32:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現場でのキッティングを可能にするオンラインドメイン適応（Kitting in the Wild through Online Domain Adaptation）</news:title>
   <news:publication_date>2026-05-22T15:32:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/693088</loc>
  <lastmod>2026-05-22T15:32:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Semantic Video Classificationにおける深層構造とアンサンブルの有効性（Deep Architectures and Ensembles for Semantic Video Classification）</news:title>
   <news:publication_date>2026-05-22T15:32:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/693086</loc>
  <lastmod>2026-05-22T15:31:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>屋内シーンにおける高速なバウンディングボックス注釈法（Faster Bounding Box Annotation for Object Detection in Indoor Scenes）</news:title>
   <news:publication_date>2026-05-22T15:31:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/693084</loc>
  <lastmod>2026-05-22T15:30:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>距離尺度の線形結合によるサロゲートモデルの改良（Linear Combination of Distance Measures for Surrogate Models in Genetic Programming）</news:title>
   <news:publication_date>2026-05-22T15:30:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/693082</loc>
  <lastmod>2026-05-22T15:30:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的探索空間におけるクリギング最適化のためのカーネルの初期解析（A First Analysis of Kernels for Kriging-based Optimization in Hierarchical Search Spaces）</news:title>
   <news:publication_date>2026-05-22T15:30:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/693080</loc>
  <lastmod>2026-05-22T15:30:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-22T15:30:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/693078</loc>
  <lastmod>2026-05-22T15:29:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Coopetitive Soft Gating Ensemble（Coopetitive Soft Gating Ensemble）</news:title>
   <news:publication_date>2026-05-22T15:29:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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