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   <news:title>荒れ地走破のための適応的テンセグリティ走行（Adaptive Tensegrity Locomotion on Rough Terrain via Reinforcement Learning）</news:title>
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   <news:title>マルチスケール再帰型で知覚と歪みを制御する超解像（Multi–Scale Recursive and Perception–Distortion Controllable Image Super–Resolution）</news:title>
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   <news:title>ディフラクティブパターンと系譜の対応（Diffractive patterns in deep-inelastic scattering and parton genealogy）</news:title>
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   <news:title>交通カメラ画像の意味的トピック解析（Semantic Topic Analysis of Traffic Camera Images）</news:title>
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   <news:title>高精度ロボット組立の姿勢推定をシミュレーション深度画像で学習する（Learning Pose Estimation for High-Precision Robotic Assembly Using Simulated Depth Images）</news:title>
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   <news:title>高次元因果グラフィカルモデルにおける個別媒介効果と介入効果の推論 (INFERENCE FOR INDIVIDUAL MEDIATION EFFECTS AND INTERVENTIONAL EFFECTS IN SPARSE HIGH-DIMENSIONAL CAUSAL GRAPHICAL MODELS)</news:title>
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   <news:title>ロバストなセンサ融合によるロボット姿勢推定（Robust Sensor Fusion for Robot Attitude Estimation）</news:title>
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   <news:title>近位大腿骨骨折の弱教師あり局所化と分類（Weakly-Supervised Localization and Classification of Proximal Femur Fractures）</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>複数の強化学習エージェントを協調させる学習法（LEARNING TO COORDINATE MULTIPLE REINFORCEMENT LEARNING AGENTS FOR DIVERSE QUERY REFORMULATION）</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>競合間の情報共有が変えるインセンティブ設計（Sharing information with competitors）</news:title>
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   <news:title>条件付きWaveGAN（Conditional WaveGAN）</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>生成的リプレイとフィードバック接続による継続学習戦略（Generative replay with feedback connections as a general strategy for continual learning）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>同期位相測定器を用いたIPSO最適化ELMによる電力系統過渡安定性予測（Optimized Extreme Learning Machine for Power System Transient Stability Prediction Using Synchrophasors）</news:title>
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   <news:title>変分自己回帰ネットワークによる統計力学問題の解法（Solving Statistical Mechanics Using Variational Autoregressive Networks）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>テキスト分類における反事実的公平性と頑健性（Counterfactual Fairness in Text Classification through Robustness）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>適応型ロボットセンシングの逐次除去アプローチ（A Successive-Elimination Approach to Adaptive Robotic Sensing）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>網膜光干渉断層撮影のノイズ除去に深層学習を用いる意義（A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>軽量な音楽テクスチャ転送システム（A Lightweight Music Texture Transfer System）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>カーネルベース低ランクスパースモデルによる単一画像超解像（Kernel Based Low-Rank Sparse Model for Single Image Super-Resolution）</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>複数基準を統合する能動学習の新枠組み（A novel active learning framework for classification: using weighted rank aggregation to achieve multiple query criteria）</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>Adaptive Image Stream Classification via Convolutional Neural Network with Intrinsic Similarity Metrics（Adaptive Image Stream Classification via Convolutional Neural Network with Intrinsic Similarity Metrics）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>単眼カメラで実現するリアルタイム3D姿勢推定（Real-time 3D Pose Estimation with a Monocular Camera Using Deep Learning and Object Priors）</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>スカラー算術による可変精度処理：深層ニューラルネットワーク向けカスタム精度（Scalar Arithmetic Multiple Data: Customizable Precision for Deep Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>動画ストリーミング学習におけるクロスレイヤー効果（Cross-Layer Effects on Training Neural Algorithms for Video Streaming）</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>ビデオ分類におけるビットレートと精度のトレードオフ（Rate-Accuracy Trade-Off In Video Classification With Deep Convolutional Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ディープラーニングとホログラフィックQCD (Deep Learning and Holographic QCD)</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>スパース化された勾配法の収束性（The Convergence of Sparsified Gradient Methods）</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>回転に頑健な畳み込みニューラルネットワークによる一次視覚野モデル化（A Rotation-Equivariant Convolutional Neural Network Model of Primary Visual Cortex）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Kernel Neural Ranking Modelの一貫性と変動（Consistency and Variation in Kernel Neural Ranking Model）</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>物理則を用いたネットワークのトポロジー学習（Physics Informed Topology Learning in Networks of Linear Dynamical Systems）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/701782</loc>
  <lastmod>2026-06-17T16:01:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ICU死亡リスク予測のための教師付き非負値行列因子分解（Supervised Nonnegative Matrix Factorization to Predict ICU Mortality Risk）</news:title>
   <news:publication_date>2026-06-17T16:01:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701780</loc>
  <lastmod>2026-06-17T16:00:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタ解析におけるベンチマーキングの指針（Benchmarking in cluster analysis: A white paper）</news:title>
   <news:publication_date>2026-06-17T16:00:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701778</loc>
  <lastmod>2026-06-17T16:00:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸オンライン勾配上昇による後悔最小化の一歩（On the Regret Minimization of Nonconvex Online Gradient Ascent for Online PCA）</news:title>
   <news:publication_date>2026-06-17T16:00:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701776</loc>
  <lastmod>2026-06-17T15:59:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模低ランク・非滑らか行列最適化の高速確率的アルゴリズム（Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems）</news:title>
   <news:publication_date>2026-06-17T15:59:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701774</loc>
  <lastmod>2026-06-17T15:59:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pareto前線の中心に重点を置いた予算付き多目的最適化（Budgeted Multi-Objective Optimization with a Focus on the Central Part of the Pareto Front - Extended Version）</news:title>
   <news:publication_date>2026-06-17T15:59:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701772</loc>
  <lastmod>2026-06-17T15:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓CT血管撮影における心筋セグメンテーションの改善（Improving Myocardium Segmentation in Cardiac CT Angiography using Spectral Information）</news:title>
   <news:publication_date>2026-06-17T15:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701770</loc>
  <lastmod>2026-06-17T15:58:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイナリニューラルネットワークの学習方法（Learning to Train a Binary Neural Network）</news:title>
   <news:publication_date>2026-06-17T15:58:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701768</loc>
  <lastmod>2026-06-17T15:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデータで適応するテキスト音声合成（SAMPLE EFFICIENT ADAPTIVE TEXT-TO-SPEECH）</news:title>
   <news:publication_date>2026-06-17T15:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701766</loc>
  <lastmod>2026-06-17T15:07:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的依存性：Pearsonの相関を超えて（Statistical dependence: Beyond Pearson’s ρ*）</news:title>
   <news:publication_date>2026-06-17T15:07:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701764</loc>
  <lastmod>2026-06-17T15:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フロー形式ネットワークトラフィック生成にGANを使う意義（Flow-based Network Traffic Generation using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-17T15:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701762</loc>
  <lastmod>2026-06-17T15:06:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNN入力の圧縮を実現する一次スキャッタリング変換（Compressing the Input for CNNs with the First-Order Scattering Transform）</news:title>
   <news:publication_date>2026-06-17T15:06:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701760</loc>
  <lastmod>2026-06-17T15:06:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光場（ライトフィールド）画像を高精細化する単純で強力な枠組み（A Simple Framework to Leverage State-Of-The-Art Single-Image Super-Resolution Methods to Restore Light Fields）</news:title>
   <news:publication_date>2026-06-17T15:06:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701758</loc>
  <lastmod>2026-06-17T15:06:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電気自動車充電のモデルフリー協調制御の定義と評価（Definition and evaluation of model-free coordination of electrical vehicle charging with reinforcement learning）</news:title>
   <news:publication_date>2026-06-17T15:06:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701756</loc>
  <lastmod>2026-06-17T15:05:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球面上での疎表現学習（Learning sparse representations on the sphere）</news:title>
   <news:publication_date>2026-06-17T15:05:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701754</loc>
  <lastmod>2026-06-17T14:14:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>右心室セグメンテーションのための生成的敵対モデル（A Generative Adversarial Model for Right Ventricle Segmentation）</news:title>
   <news:publication_date>2026-06-17T14:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701752</loc>
  <lastmod>2026-06-17T14:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話で前後をつなぐNEXUS Network（NEXUS Network: Connecting the Preceding and the Following in Dialogue Generation）</news:title>
   <news:publication_date>2026-06-17T14:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701750</loc>
  <lastmod>2026-06-17T14:13:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRIセグメンテーションの信頼性向上（Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI）</news:title>
   <news:publication_date>2026-06-17T14:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701748</loc>
  <lastmod>2026-06-17T14:12:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散学習における重みへのノイズ導入の効果（Introducing Noise in Decentralized Training of Neural Networks）</news:title>
   <news:publication_date>2026-06-17T14:12:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701746</loc>
  <lastmod>2026-06-17T14:12:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化マップによる相転移検出と位相同定（Self-organizing maps as a method for detecting phase transitions and phase identification）</news:title>
   <news:publication_date>2026-06-17T14:12:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701744</loc>
  <lastmod>2026-06-17T14:12:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロゼッタ/OSIRISによる67P塵雲の位相関数モデル（Models of Rosetta/OSIRIS 67P dust coma phase function）</news:title>
   <news:publication_date>2026-06-17T14:12:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701742</loc>
  <lastmod>2026-06-17T14:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者間心電図（ECG）分類における畳み込み・再帰ニューラルネットワーク（Inter-Patient ECG Classification with Convolutional and Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-17T14:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701740</loc>
  <lastmod>2026-06-17T13:20:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙論シミュレーションと深いサブミリ波観測の比較（Comparison of cosmological simulations and deep submillimetre galaxy surveys）</news:title>
   <news:publication_date>2026-06-17T13:20:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701738</loc>
  <lastmod>2026-06-17T13:20:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による画像ノイズ除去の実務的意義（Image Reconstruction Using Deep Learning）</news:title>
   <news:publication_date>2026-06-17T13:20:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701736</loc>
  <lastmod>2026-06-17T13:19:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人格印象に基づく3D顔合成（3D Face Synthesis Driven by Personality Impression）</news:title>
   <news:publication_date>2026-06-17T13:19:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701734</loc>
  <lastmod>2026-06-17T13:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層間伝播の安定化がもたらす精度向上（Smooth Inter-layer Propagation of Stabilized Neural Networks for Classification）</news:title>
   <news:publication_date>2026-06-17T13:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701732</loc>
  <lastmod>2026-06-17T13:18:41Z</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キュー型リサンプリングの提案（Queue-based Resampling for Online Class Imbalance Learning）</news:title>
   <news:publication_date>2026-06-17T13:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701730</loc>
  <lastmod>2026-06-17T13:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブル機器のBluetoothによる識別（Identification of Wearable Devices with Bluetooth）</news:title>
   <news:publication_date>2026-06-17T13:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701728</loc>
  <lastmod>2026-06-17T13:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的辞書学習と勾配降下法による収束保証（Efficient Dictionary Learning with Gradient Descent）</news:title>
   <news:publication_date>2026-06-17T13:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701726</loc>
  <lastmod>2026-06-17T12:26:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予期せぬ道路危険下のDNNベース自律走行モデル（Deep Neural Network-based Driving Model for Roadway Hazards）</news:title>
   <news:publication_date>2026-06-17T12:26:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701724</loc>
  <lastmod>2026-06-17T12:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの非剛体形状予測を幾何学的に学ぶ（Geometry-Aware Network for Non-Rigid Shape Prediction from a Single View）</news:title>
   <news:publication_date>2026-06-17T12:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701722</loc>
  <lastmod>2026-06-17T12:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメイン表現のためのベクタ学習（Vector Learning for Cross Domain Representations）</news:title>
   <news:publication_date>2026-06-17T12:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701720</loc>
  <lastmod>2026-06-17T12:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向けニューラル言語モデルの適応的プルーニング（ADAPTIVE PRUNING OF NEURAL LANGUAGE MODELS FOR MOBILE DEVICES）</news:title>
   <news:publication_date>2026-06-17T12:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701718</loc>
  <lastmod>2026-06-17T12:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意姿勢での人物画像を教師なしで合成する手法（Unsupervised Person Image Synthesis in Arbitrary Poses）</news:title>
   <news:publication_date>2026-06-17T12:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701716</loc>
  <lastmod>2026-06-17T12:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的に不変なテキスト→画像生成（SEMANTICALLY INVARIANT TEXT-TO-IMAGE GENERATION）</news:title>
   <news:publication_date>2026-06-17T12:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701714</loc>
  <lastmod>2026-06-17T12:25:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化を組み込んだ再帰的ハイウェイネットワークの提案（BATCH-NORMALIZED RECURRENT HIGHWAY NETWORKS）</news:title>
   <news:publication_date>2026-06-17T12:25:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701712</loc>
  <lastmod>2026-06-17T11:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レビューの力が若い書き手を育てる—ファンフィクションに見る分散型メンタリングの効果（Reviews Matter: How Distributed Mentoring Predicts Lexical Diversity on Fanfiction.net）</news:title>
   <news:publication_date>2026-06-17T11:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701710</loc>
  <lastmod>2026-06-17T11:33:41Z</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Q&amp;amp;Aにおける回答者支援としてのフィードバック（Supporting Answerers with Feedback in Social Q&amp;amp;A）</news:title>
   <news:publication_date>2026-06-17T11:33:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701708</loc>
  <lastmod>2026-06-17T11:33:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型地震波形反転が切り拓く高速・頑健な地下像復元（Data-driven Seismic Waveform Inversion: A Study on the Robustness and Generalization）</news:title>
   <news:publication_date>2026-06-17T11:33:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701706</loc>
  <lastmod>2026-06-17T11:32:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列リー群上の前処理子による確率的勾配法の改善（PRECONDITIONER ON MATRIX LIE GROUP FOR SGD）</news:title>
   <news:publication_date>2026-06-17T11:32:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701704</loc>
  <lastmod>2026-06-17T11:32:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット運動計画のための深層情報に基づくサンプリング（Deeply Informed Neural Sampling for Robot Motion Planning）</news:title>
   <news:publication_date>2026-06-17T11:32:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701702</loc>
  <lastmod>2026-06-17T11:32:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量持続ホモロジーのためのカーネル（A Kernel for Multi-Parameter Persistent Homology）</news:title>
   <news:publication_date>2026-06-17T11:32:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701700</loc>
  <lastmod>2026-06-17T11:32:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションから実機への転移を拡大する組成可能なロボットスキルの学習（Scaling simulation-to-real transfer by learning composable robot skills）</news:title>
   <news:publication_date>2026-06-17T11:32:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701698</loc>
  <lastmod>2026-06-17T10:41:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽質量星周りの地球型惑星検出を高速化するマイクロレンズ経路の新しいパラメータ化（Microlensing path parametrization for Earth-like Exoplanet detection around solar mass stars）</news:title>
   <news:publication_date>2026-06-17T10:41:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701696</loc>
  <lastmod>2026-06-17T10:40:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動アノテーションで学ぶCNNによる指紋ポア記述（Automatic Dataset Annotation to Learn CNN Pore Description for Fingerprint Recognition）</news:title>
   <news:publication_date>2026-06-17T10:40:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701694</loc>
  <lastmod>2026-06-17T10:40:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適ノイズ付加機構と(0, δ)-差分プライバシーの実践的意義（Optimal Noise-Adding Mechanism in Additive Differential Privacy）</news:title>
   <news:publication_date>2026-06-17T10:40:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701692</loc>
  <lastmod>2026-06-17T10:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハンズフリーなクエリ最適化の可能性（Towards a Hands-Free Query Optimizer through Deep Learning）</news:title>
   <news:publication_date>2026-06-17T10:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701690</loc>
  <lastmod>2026-06-17T10:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>左心室のセグメンテーションと定量化を同時に学習する手法（Left Ventricle Segmentation and Quantification from Cardiac Cine MR Images via Multi-task Learning）</news:title>
   <news:publication_date>2026-06-17T10:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701688</loc>
  <lastmod>2026-06-17T10:39:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模集団を対象としたデータ解析パイプラインの計算再現性予測（Predicting computational reproducibility of data analysis pipelines in large population studies using collaborative filtering）</news:title>
   <news:publication_date>2026-06-17T10:39:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701686</loc>
  <lastmod>2026-06-17T10:39:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>出荷箱の機械学習による設計最適化（A Machine Learning Approach to Shipping Box Design）</news:title>
   <news:publication_date>2026-06-17T10:39:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701684</loc>
  <lastmod>2026-06-17T09:48:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AlphaSeq: 深層強化学習による配列探索の新パラダイム（AlphaSeq: Sequence Discovery with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-17T09:48:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701682</loc>
  <lastmod>2026-06-17T09:47:55Z</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>2026-06-17T09:47:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701680</loc>
  <lastmod>2026-06-17T09:47:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Monge–Ampère流に基づく生成モデルの実装と示唆（MONGE-AMPÈRE FLOW FOR GENERATIVE MODELING）</news:title>
   <news:publication_date>2026-06-17T09:47:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701678</loc>
  <lastmod>2026-06-17T09:46:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ω-regular目的をモデルフリー強化学習で扱う（Omega-Regular Objectives in Model-Free Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-17T09:46:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701676</loc>
  <lastmod>2026-06-17T09:45:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強く重力レンズ化された超新星の発見と意義（Rates and Properties of Strongly Gravitationally Lensed Supernovae and their Host Galaxies in Time-Domain Imaging Surveys）</news:title>
   <news:publication_date>2026-06-17T09:45:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701674</loc>
  <lastmod>2026-06-17T09:45:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AutoRLによるエンドツーエンド航行学習（Learning Navigation Behaviors End-to-End with AutoRL）</news:title>
   <news:publication_date>2026-06-17T09:45:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701672</loc>
  <lastmod>2026-06-17T09:45:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PCAとMUSICにおける未知信号数のベイズ推定（Bayesian Inference for PCA and MUSIC Algorithms with Unknown Number of Sources）</news:title>
   <news:publication_date>2026-06-17T09:45:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701670</loc>
  <lastmod>2026-06-17T08:53:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き線形二次レギュレータを安全に学習する方法（Safely Learning to Control the Constrained Linear Quadratic Regulator）</news:title>
   <news:publication_date>2026-06-17T08:53:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701668</loc>
  <lastmod>2026-06-17T08:53:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典的ゼロショット学習から一般化ゼロショット学習へ（From Classical to Generalized Zero-Shot Learning: a Simple Adaptation Process）</news:title>
   <news:publication_date>2026-06-17T08:53:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701666</loc>
  <lastmod>2026-06-17T08:52:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画品質評価に畳み込みニューラルネットワークを適用する意義（Convolutional Neural Networks for Video Quality Assessment）</news:title>
   <news:publication_date>2026-06-17T08:52:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701664</loc>
  <lastmod>2026-06-17T08:52:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深サブ波長で生じる複数散乱による左手バンド（Left-handed Band in an Electromagnetic Metamaterial Induced by Sub-wavelength Multiple Scattering）</news:title>
   <news:publication_date>2026-06-17T08:52:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701662</loc>
  <lastmod>2026-06-17T08:52:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冗長な知覚と状態推定による信頼性の向上（Redundant Perception and State Estimation for Reliable Autonomous Racing）</news:title>
   <news:publication_date>2026-06-17T08:52:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701660</loc>
  <lastmod>2026-06-17T08:51:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトメトリック深度超解像（Photometric Depth Super-Resolution）</news:title>
   <news:publication_date>2026-06-17T08:51:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701658</loc>
  <lastmod>2026-06-17T08:51:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意せよ！タスク重視の視覚注意で深層視覚運動ポリシーを頑健化する（Pay attention! - Robustifying a Deep Visuomotor Policy through Task-Focused Visual Attention）</news:title>
   <news:publication_date>2026-06-17T08:51:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701656</loc>
  <lastmod>2026-06-17T08:00:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし敵対的不変性の誘導（Unsupervised Adversarial Invariance）</news:title>
   <news:publication_date>2026-06-17T08:00:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701654</loc>
  <lastmod>2026-06-17T07:59:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタマテリアルの結晶性による局所偏光波の伝搬（Locally Polarized Wave Propagation through Metamaterials’ Crystallinity）</news:title>
   <news:publication_date>2026-06-17T07:59:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701652</loc>
  <lastmod>2026-06-17T07:59:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限状態分布による深層ニューラルネットワークの再発見（Rediscovering Deep Neural Networks Through Finite State Distributions）</news:title>
   <news:publication_date>2026-06-17T07:59:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701650</loc>
  <lastmod>2026-06-17T07:59:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復正則化インクリメンタル部分勾配法によるバイレベル最適化（An Iterative Regularized Incremental Projected Subgradient Method for a Class of Bilevel Optimization Problems）</news:title>
   <news:publication_date>2026-06-17T07:59:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701648</loc>
  <lastmod>2026-06-17T07:59:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースの遅延意識キャッシュ制御（Learning-Based Delay-Aware Caching in Wireless D2D Caching Networks）</news:title>
   <news:publication_date>2026-06-17T07:59:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701646</loc>
  <lastmod>2026-06-17T07:58:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>積グラフ上のグラフ信号に関するサンプリング理論（Sampling Theory for Graph Signals on Product Graphs）</news:title>
   <news:publication_date>2026-06-17T07:58:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701644</loc>
  <lastmod>2026-06-17T07:58:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用宣言的帰納プログラミングによるデータワリング自動化（General-purpose Declarative Inductive Programming with Domain-Specific Background Knowledge for Data Wrangling Automation）</news:title>
   <news:publication_date>2026-06-17T07:58:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701642</loc>
  <lastmod>2026-06-17T07:07:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>励起子の巨大双極子状態の固有エネルギー（Eigenenergies of excitonic giant-dipole states in cuprous oxide）</news:title>
   <news:publication_date>2026-06-17T07:07:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701640</loc>
  <lastmod>2026-06-17T07:07:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤りを生成して誤り検出を強化する（Wronging a Right: Generating Better Errors to Improve Grammatical Error Detection）</news:title>
   <news:publication_date>2026-06-17T07:07:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701638</loc>
  <lastmod>2026-06-17T07:07:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語モデルは翻訳よりも構文を学ぶ（Language Modeling Teaches You More Syntax Than Translation Does: Lessons Learned Through Auxiliary Task Analysis）</news:title>
   <news:publication_date>2026-06-17T07:07:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701636</loc>
  <lastmod>2026-06-17T07:06:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QFlow liteデータセット：量子ドット実験の電荷状態に対する機械学習アプローチ（QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments）</news:title>
   <news:publication_date>2026-06-17T07:06:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701634</loc>
  <lastmod>2026-06-17T07:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルセンサのための情報マップ生成にニューラルネットワークを用いる（Using Neural Networks to Generate Information Maps for Mobile Sensors）</news:title>
   <news:publication_date>2026-06-17T07:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701632</loc>
  <lastmod>2026-06-17T07:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Learning through probing による協調行動の学習（Learning through probing: a decentralized reinforcement learning architecture for social dilemmas）</news:title>
   <news:publication_date>2026-06-17T07:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701630</loc>
  <lastmod>2026-06-17T07:05:48Z</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ための普遍的表現学習（Universal Network Representation for Heterogeneous Information Networks）</news:title>
   <news:publication_date>2026-06-17T07:05:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701628</loc>
  <lastmod>2026-06-17T06:14:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチラベル・データストリーム分類におけるオンライン積み重ねアンサンブルの提案（A Novel Online Stacked Ensemble for Multi-Label Stream Classification）</news:title>
   <news:publication_date>2026-06-17T06:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701626</loc>
  <lastmod>2026-06-17T06:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推定と推論のための深層ニューラルネットワーク（Deep Neural Networks for Estimation and Inference）</news:title>
   <news:publication_date>2026-06-17T06:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701624</loc>
  <lastmod>2026-06-17T06:14:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム遮蔽回復による人物再識別のデータ増強（Random Occlusion-recovery for Person Re-identification）</news:title>
   <news:publication_date>2026-06-17T06:14:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701622</loc>
  <lastmod>2026-06-17T06:13:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層ニューラルネットワークにおけるジャミング現象（Jamming in multilayer supervised learning models）</news:title>
   <news:publication_date>2026-06-17T06:13:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701620</loc>
  <lastmod>2026-06-17T06:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現定理はいつ成立するか（When is there a Representer Theorem?）</news:title>
   <news:publication_date>2026-06-17T06:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701618</loc>
  <lastmod>2026-06-17T06:13:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で読み解くBerezinskii–Kosterlitz–Thouless転移（A machine learning approach to the Berezinskii-Kosterlitz-Thouless transition in classical and quantum models）</news:title>
   <news:publication_date>2026-06-17T06:13:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701616</loc>
  <lastmod>2026-06-17T06:12:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>孤立銀河 CIG 96 の環境と微弱構造の解明（Unveiling the environment and faint features of the isolated galaxy CIG 96 with deep optical and HI observations）</news:title>
   <news:publication_date>2026-06-17T06:12:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701614</loc>
  <lastmod>2026-06-17T05:21:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層に基づく画像埋め込みによるセマンティック画像検索（Hierarchy-based Image Embeddings for Semantic Image Retrieval）</news:title>
   <news:publication_date>2026-06-17T05:21:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701612</loc>
  <lastmod>2026-06-17T05:21:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>すべてのノードが重要になる：自己蒸留型グラフ畳み込みネットワーク（Every Node Counts: Self-Ensembling Graph Convolutional Networks for Semi-Supervised Learning）</news:title>
   <news:publication_date>2026-06-17T05:21:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701610</loc>
  <lastmod>2026-06-17T05:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>hyper-RKHSによるカーネル学習の一般化特性と応用（Generalization Properties of hyper-RKHS and its Applications）</news:title>
   <news:publication_date>2026-06-17T05:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701608</loc>
  <lastmod>2026-06-17T05:20:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CSONに対する敵対的攻撃の脅威と今後の課題 (Adversarial Attacks on Cognitive Self-Organizing Networks: The Challenge and the Way Forward)</news:title>
   <news:publication_date>2026-06-17T05:20:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701606</loc>
  <lastmod>2026-06-17T05:20:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体検出における能動学習の実践的方法（Active Learning for Deep Object Detection）</news:title>
   <news:publication_date>2026-06-17T05:20:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701604</loc>
  <lastmod>2026-06-17T05:20:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何的グラフからランダム点配置を復元する手法（Learning Random Points from Geometric Graphs or Orderings）</news:title>
   <news:publication_date>2026-06-17T05:20:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701602</loc>
  <lastmod>2026-06-17T05:19:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無秩序な高次位相絶縁体の相図：機械学習による検証（Phase diagram of disordered higher-order topological insulator: A machine learning study）</news:title>
   <news:publication_date>2026-06-17T05:19:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701600</loc>
  <lastmod>2026-06-17T04:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続的感情予測における動的難易度認識学習（Dynamic Difficulty Awareness Training for Continuous Emotion Prediction）</news:title>
   <news:publication_date>2026-06-17T04:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701598</loc>
  <lastmod>2026-06-17T04:21:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地理時空重み付きニューラルネットワークによる衛星観測を用いた地上PM2.5推定（Geographically and Temporally Weighted Neural Networks for Satellite-based Mapping of Ground-level PM2.5）</news:title>
   <news:publication_date>2026-06-17T04:21:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701596</loc>
  <lastmod>2026-06-17T04:19:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可視的類似性に基づく転移学習でブラックボックスを発達的に最適化する（Developmental Bayesian Optimization of Black-Box with Visual Similarity-Based Transfer Learning）</news:title>
   <news:publication_date>2026-06-17T04:19:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701594</loc>
  <lastmod>2026-06-17T04:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメインを用いた店舗推薦の新手法（A novel approach for venue recommendation using cross-domain techniques）</news:title>
   <news:publication_date>2026-06-17T04:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701592</loc>
  <lastmod>2026-06-17T04:18:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不正確なヘッセ行列と勾配で動く確率的二次法の実用化（Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient）</news:title>
   <news:publication_date>2026-06-17T04:18:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701590</loc>
  <lastmod>2026-06-17T04:18:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DBLSTMベース音声変換における誤差低減ネットワーク（Error Reduction Network for DBLSTM-based Voice Conversion）</news:title>
   <news:publication_date>2026-06-17T04:18:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701588</loc>
  <lastmod>2026-06-17T04:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフラプラシアン正則化を組み込んだグラフ畳み込みネットワーク（Graph Laplacian Regularized Graph Convolutional Networks for Semi-supervised Learning）</news:title>
   <news:publication_date>2026-06-17T04:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701586</loc>
  <lastmod>2026-06-17T03:26:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インド・プレミアリーグ（IPL）試合結果予測の機械学習アプローチ（Predicting Outcome of Indian Premier League (IPL) Matches Using Machine Learning）</news:title>
   <news:publication_date>2026-06-17T03:26:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701584</loc>
  <lastmod>2026-06-17T03:25:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>布のピックポイントに関する深層転移学習（Deep Transfer Learning of Pick Points on Fabric for Robot Bed-Making）</news:title>
   <news:publication_date>2026-06-17T03:25:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701582</loc>
  <lastmod>2026-06-17T03:25:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>夜間→昼間画像変換による探索ベースの位置推定の改善（Night-to-Day Image Translation for Retrieval-based Localization）</news:title>
   <news:publication_date>2026-06-17T03:25:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701580</loc>
  <lastmod>2026-06-17T03:25:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習は感覚情報処理の計算モデルをどう進めるか（How can deep learning advance computational modeling of sensory information processing?）</news:title>
   <news:publication_date>2026-06-17T03:25:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701578</loc>
  <lastmod>2026-06-17T03:25:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Relay — 機械学習フレームワークの新しい中間表現（Relay: A New IR for Machine Learning Frameworks）</news:title>
   <news:publication_date>2026-06-17T03:25:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701576</loc>
  <lastmod>2026-06-17T03:25:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ステレオマッチングにおける信頼度推定（Confidence Inference for Focused Learning in Stereo Matching）</news:title>
   <news:publication_date>2026-06-17T03:25:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701574</loc>
  <lastmod>2026-06-17T02:33:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Residualネットワークを用いた模倣（Mimic）アーキテクチャによるスペクトルマッピングの探求（AN EXPLORATION OF MIMIC ARCHITECTURES FOR RESIDUAL NETWORK BASED SPECTRAL MAPPING）</news:title>
   <news:publication_date>2026-06-17T02:33:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701572</loc>
  <lastmod>2026-06-17T02:33:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地図が間違っているときのマップマッチング（Map matching when the map is wrong: Efficient on/off road vehicle tracking and map learning）</news:title>
   <news:publication_date>2026-06-17T02:33:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701570</loc>
  <lastmod>2026-06-17T02:33:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自転車のGPSデータだけで路面を見分ける（Surface Type Estimation from GPS Tracked Bicycle Activities）</news:title>
   <news:publication_date>2026-06-17T02:33:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701568</loc>
  <lastmod>2026-06-17T02:32:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zooniverseによる人間–機械協調の最適化（Optimizing the Human-Machine Partnership with Zooniverse）</news:title>
   <news:publication_date>2026-06-17T02:32:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701566</loc>
  <lastmod>2026-06-17T02:32:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期的記憶の最小表現（Minimal descriptions of cyclic memories）</news:title>
   <news:publication_date>2026-06-17T02:32:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701564</loc>
  <lastmod>2026-06-17T02:32:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>消費者と生産者の埋め込みを学習してユーザ生成コンテンツを推薦する（Learning Consumer and Producer Embeddings for User-Generated Content Recommendation）</news:title>
   <news:publication_date>2026-06-17T02:32:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701562</loc>
  <lastmod>2026-06-17T02:31:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学生のチェックイン行動を活用した注目地点予測の改善（Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction）</news:title>
   <news:publication_date>2026-06-17T02:31:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701560</loc>
  <lastmod>2026-06-17T01:40:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高精度かつ説明可能なモデルツリーの新しい分割基準（A Gradient-Based Split Criterion for Highly Accurate and Transparent Model Trees）</news:title>
   <news:publication_date>2026-06-17T01:40:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701558</loc>
  <lastmod>2026-06-17T01:40:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BANDITSUM：文書切り出し要約を文脈的バンディットとして学習する（BANDITSUM: Extractive Summarization as a Contextual Bandit）</news:title>
   <news:publication_date>2026-06-17T01:40:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701556</loc>
  <lastmod>2026-06-17T01:39:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索的データ分析中の未来行動の学習と予測 (Learning and Anticipating Future Actions During Exploratory Data Analysis)</news:title>
   <news:publication_date>2026-06-17T01:39:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701554</loc>
  <lastmod>2026-06-17T01:38:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的軌跡から力場を学習する手法（Learning force fields from stochastic trajectories）</news:title>
   <news:publication_date>2026-06-17T01:38:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701552</loc>
  <lastmod>2026-06-17T01:38:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非ネイティブの子ども音声認識における転移学習と多言語DNNの応用（NON-NATIVE CHILDREN SPEECH RECOGNITION THROUGH TRANSFER LEARNING）</news:title>
   <news:publication_date>2026-06-17T01:38:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701550</loc>
  <lastmod>2026-06-17T01:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パターン認識のための深層ニューラルネットワーク（Deep Neural Networks for Pattern Recognition）</news:title>
   <news:publication_date>2026-06-17T01:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701548</loc>
  <lastmod>2026-06-17T01:38:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度パノラマSEM画像におけるAIによる損傷分類の新手法（High-resolution Panoramic SEM Damage Classification by AI）</news:title>
   <news:publication_date>2026-06-17T01:38:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701546</loc>
  <lastmod>2026-06-17T01:20:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形圧縮観測からのスパース復元と辞書学習（Sparse Recovery and Dictionary Learning from Nonlinear Compressive Measurements）</news:title>
   <news:publication_date>2026-06-17T01:20:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701544</loc>
  <lastmod>2026-06-17T01:20:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論に基づく最適な縮約変換（Optimal Renormalization Group Transformation from Information Theory）</news:title>
   <news:publication_date>2026-06-17T01:20:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701542</loc>
  <lastmod>2026-06-17T01:20:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>天の川銀河の衛星銀河総数と温かい暗黒物質粒子質量の制約（The Milky Way’s total satellite population and constraining the mass of the warm dark matter particle）</news:title>
   <news:publication_date>2026-06-17T01:20:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701540</loc>
  <lastmod>2026-06-17T01:19:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸最適化と低ランク行列因子分解の概要（Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview）</news:title>
   <news:publication_date>2026-06-17T01:19:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701538</loc>
  <lastmod>2026-06-17T01:19:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自由表面を持つ2次元流体における極の力学：新しい運動量保存量（Dynamics of Poles in 2D Hydrodynamics with Free Surface: New Constants of Motion）</news:title>
   <news:publication_date>2026-06-17T01:19:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701536</loc>
  <lastmod>2026-06-17T01:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の階層分類のためのCNNとRNNの統合（Combined Convolutional and Recurrent Neural Networks for Hierarchical Classification of Images）</news:title>
   <news:publication_date>2026-06-17T01:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701534</loc>
  <lastmod>2026-06-17T01:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈ごとの学習を越える—Contextual Bandits with Cross-Learning（Contextual Bandits with Cross-Learning）</news:title>
   <news:publication_date>2026-06-17T01:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701532</loc>
  <lastmod>2026-06-17T00:28:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソースコード変換による自動微分の実装技法（Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming）</news:title>
   <news:publication_date>2026-06-17T00:28:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701530</loc>
  <lastmod>2026-06-17T00:27:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠隔ロボット操作のためのヒューマンマシンインターフェース（Human-Machine Interface for Remote Training of Robot Tasks）</news:title>
   <news:publication_date>2026-06-17T00:27:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701528</loc>
  <lastmod>2026-06-17T00:27:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンワールド環境における支援ロボットのピック＆プレース（Towards Assistive Robotic Pick and Place in Open World Environments）</news:title>
   <news:publication_date>2026-06-17T00:27:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701526</loc>
  <lastmod>2026-06-17T00:26:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ事後分布近似誤差の実用的上界（PRACTICAL BOUNDS ON THE ERROR OF BAYESIAN POSTERIOR APPROXIMATIONS: A NONASYMPTOTIC APPROACH）</news:title>
   <news:publication_date>2026-06-17T00:26:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701524</loc>
  <lastmod>2026-06-17T00:26:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習におけるAnderson加速法（Anderson Acceleration for Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-17T00:26:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701522</loc>
  <lastmod>2026-06-17T00:26:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダウリング計量空間における多様性最大化（Diversity maximization in doubling metrics）</news:title>
   <news:publication_date>2026-06-17T00:26:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701520</loc>
  <lastmod>2026-06-17T00:26:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波列における周波数低下の比較研究（A Comparison of Frequency Downshift Models of Wave Trains on Deep Water）</news:title>
   <news:publication_date>2026-06-17T00:26:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701518</loc>
  <lastmod>2026-06-16T23:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテゴリレベル敵対学習によるセマンティック整合を重視したドメイン適応（Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation）</news:title>
   <news:publication_date>2026-06-16T23:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701516</loc>
  <lastmod>2026-06-16T23:34:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>横方向運動依存性が明かすスピン非対称性の解像（Role of transverse momentum dependence of unpolarised parton distribution and fragmentation functions in the analysis of azimuthal spin asymmetries）</news:title>
   <news:publication_date>2026-06-16T23:34:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701514</loc>
  <lastmod>2026-06-16T23:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速自動平滑化が変えるGAMの実務適用（Fast Automatic Smoothing for Generalized Additive Models）</news:title>
   <news:publication_date>2026-06-16T23:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701512</loc>
  <lastmod>2026-06-16T23:33:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成音声波形の自然化を実現するWaveCycleGAN（WAVECYCLEGAN: SYNTHETIC-TO-NATURAL SPEECH WAVEFORM CONVERSION USING CYCLE-CONSISTENT ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-06-16T23:33:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701510</loc>
  <lastmod>2026-06-16T23:33:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘッシアン・バリア法による線形制約付き最適化（Hessian Barrier Algorithms for Linearly Constrained Optimization Problems）</news:title>
   <news:publication_date>2026-06-16T23:33:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701508</loc>
  <lastmod>2026-06-16T23:32:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間関係に基づくランキングによる株価予測（Temporal Relational Ranking for Stock Prediction）</news:title>
   <news:publication_date>2026-06-16T23:32:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701506</loc>
  <lastmod>2026-06-16T23:32:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択時のネスト交差検証は実務的には過剰である（Nested cross-validation when selecting classifiers is overzealous for most practical applications）</news:title>
   <news:publication_date>2026-06-16T23:32:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701504</loc>
  <lastmod>2026-06-16T22:41:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分的敵対学習による最適経路計画（Incremental Adversarial Learning for Optimal Path Planning）</news:title>
   <news:publication_date>2026-06-16T22:41:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701502</loc>
  <lastmod>2026-06-16T22:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフニューラルネットワークの概観（Hypergraph Neural Networks）</news:title>
   <news:publication_date>2026-06-16T22:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701500</loc>
  <lastmod>2026-06-16T22:40:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープ畳み込みニューラルネットワークにおける非反復的知識融合（Non-Iterative Knowledge Fusion in Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-16T22:40:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701498</loc>
  <lastmod>2026-06-16T22:39:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分光スペクトルからの赤方偏移推定にCNNを用いる意義（Convolutional Neural Networks for Spectroscopic Redshift Estimation on Euclid Data）</news:title>
   <news:publication_date>2026-06-16T22:39:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701496</loc>
  <lastmod>2026-06-16T22:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ構造を考慮したベイズ的特徴選択と期待伝播（Sparse-Group Bayesian Feature Selection Using Expectation Propagation for Signal Recovery and Network Reconstruction）</news:title>
   <news:publication_date>2026-06-16T22:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701494</loc>
  <lastmod>2026-06-16T22:39:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習における状態表現学習のためのツールボックス（State Representation Learning for Reinforcement Learning Toolbox）</news:title>
   <news:publication_date>2026-06-16T22:39:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701492</loc>
  <lastmod>2026-06-16T22:39:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カゴと閲覧セッションから補完商品を推定する（Inferring Complementary Products from Baskets and Browsing Sessions）</news:title>
   <news:publication_date>2026-06-16T22:39:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701490</loc>
  <lastmod>2026-06-16T21:48:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動学習とSVMによる効率的な地震脆弱性曲線推定（Efficient Seismic fragility curve estimation by Active Learning on Support Vector Machines）</news:title>
   <news:publication_date>2026-06-16T21:48:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701488</loc>
  <lastmod>2026-06-16T21:47:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意サンプリングに基づく加速座標降下法とミニバッチ最適化の最良率（Accelerated Coordinate Descent with Arbitrary Sampling and Best Rates for Minibatches）</news:title>
   <news:publication_date>2026-06-16T21:47:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701486</loc>
  <lastmod>2026-06-16T21:47:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全インプリシットオンライン学習（Fully Implicit Online Learning）</news:title>
   <news:publication_date>2026-06-16T21:47:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701484</loc>
  <lastmod>2026-06-16T21:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有害なソーシャルメディアアカウントの早期検出（Early Identification of Pathogenic Social Media Accounts）</news:title>
   <news:publication_date>2026-06-16T21:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701482</loc>
  <lastmod>2026-06-16T21:46:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データで学ぶ因果推論の概観（A Survey of Learning Causality with Data: Problems and Methods）</news:title>
   <news:publication_date>2026-06-16T21:46:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701480</loc>
  <lastmod>2026-06-16T21:46:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル駆動型深層学習によるMIMO検出 (A Model-Driven Deep Learning Network for MIMO Detection)</news:title>
   <news:publication_date>2026-06-16T21:46:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701478</loc>
  <lastmod>2026-06-16T21:46:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的深層マルチエージェント強化学習と時間抽象（Hierarchical Deep Multiagent Reinforcement Learning with Temporal Abstraction）</news:title>
   <news:publication_date>2026-06-16T21:46:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701476</loc>
  <lastmod>2026-06-16T20:54:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超低ビット非対称ハッシングの協調学習（Collaborative Learning for Extremely Low Bit Asymmetric Hashing）</news:title>
   <news:publication_date>2026-06-16T20:54:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701474</loc>
  <lastmod>2026-06-16T20:54:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所化解析による耐凍結タンパク質予測の堅牢化（RAFP-Pred: Robust Prediction of Antifreeze Proteins using Localized Analysis of n-Peptide Compositions）</news:title>
   <news:publication_date>2026-06-16T20:54:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701472</loc>
  <lastmod>2026-06-16T20:54:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模アップスケールのためのマルチグリッド逆投影（Multigrid Backprojection Super–Resolution and Deep Filter Visualization）</news:title>
   <news:publication_date>2026-06-16T20:54:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701470</loc>
  <lastmod>2026-06-16T20:53:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>C. elegansの逃避行動を自動で予測・解釈するモデル化（Automated, predictive, and interpretable inference of C. elegans escape dynamics）</news:title>
   <news:publication_date>2026-06-16T20:53:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701468</loc>
  <lastmod>2026-06-16T20:53:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Floyd-Warshall Reinforcement Learning が変えるマルチゴール強化学習の考え方（Floyd-Warshall Reinforcement Learning: Learning from Past Experiences to Reach New Goals）</news:title>
   <news:publication_date>2026-06-16T20:53:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701466</loc>
  <lastmod>2026-06-16T20:53:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スピーカー認識における注意機構：深いスピーカー埋め込みは何を学ぶか（ATTENTION MECHANISM IN SPEAKER RECOGNITION: WHAT DOES IT LEARN IN DEEP SPEAKER EMBEDDING?）</news:title>
   <news:publication_date>2026-06-16T20:53:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701464</loc>
  <lastmod>2026-06-16T20:53:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球内部の密度分布がDUNEでの非標準ニュートリノ相互作用検出に与える影響（Impact of Matter Density Profile Shape on NSI at DUNE）</news:title>
   <news:publication_date>2026-06-16T20:53:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701462</loc>
  <lastmod>2026-06-16T20:01:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Scenic: シナリオ記述と言語化によるシーン生成（Scenic: A Language for Scenario Specification and Scene Generation）</news:title>
   <news:publication_date>2026-06-16T20:01:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701460</loc>
  <lastmod>2026-06-16T20:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス情報を用いた表現形成がもたらす差（Utilizing Class Information for Deep Network Representation Shaping）</news:title>
   <news:publication_date>2026-06-16T20:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701458</loc>
  <lastmod>2026-06-16T20:01:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三重監督デコーダネットワークによる結合検出とセグメンテーション（Triply Supervised Decoder Networks for Joint Detection and Segmentation）</news:title>
   <news:publication_date>2026-06-16T20:01:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701456</loc>
  <lastmod>2026-06-16T20:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MedAL：医用画像解析における高精度で頑健な深層アクティブラーニング（MedAL: Accurate and Robust Deep Active Learning for Medical Image Analysis）</news:title>
   <news:publication_date>2026-06-16T20:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701454</loc>
  <lastmod>2026-06-16T20:00:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的に敵対的攻撃に耐えるニューラルネット（Neural Networks with Structural Resistance to Adversarial Attacks）</news:title>
   <news:publication_date>2026-06-16T20:00:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701452</loc>
  <lastmod>2026-06-16T20:00:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフフィルタによるデータ削減と再構成（GRAPH FILTERING FOR DATA REDUCTION AND RECONSTRUCTION）</news:title>
   <news:publication_date>2026-06-16T20:00:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701450</loc>
  <lastmod>2026-06-16T19:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スクラッチから学ぶ物体検出と深層監督（Object Detection from Scratch with Deep Supervision）</news:title>
   <news:publication_date>2026-06-16T19:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701448</loc>
  <lastmod>2026-06-16T19:08:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度ポリシーディスティレーションとニューロモルフィック応用（Low Precision Policy Distillation with Application to Low-Power, Real-time Sensation-Cognition-Action Loop with Neuromorphic Computing）</news:title>
   <news:publication_date>2026-06-16T19:08:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701446</loc>
  <lastmod>2026-06-16T19:08:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的システム上の強化学習によるレジリエント計算：ソーティングの事例研究（Resilient Computing with Reinforcement Learning on a Dynamical System: Case Study in Sorting）</news:title>
   <news:publication_date>2026-06-16T19:08:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701444</loc>
  <lastmod>2026-06-16T19:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期分散加速確率的勾配降下法（Asynchronous decentralized accelerated stochastic gradient descent）</news:title>
   <news:publication_date>2026-06-16T19:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701442</loc>
  <lastmod>2026-06-16T19:07:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約空間上の柔軟な混合モデル（FLEXIBLE MIXTURE MODELING ON CONSTRAINED SPACES）</news:title>
   <news:publication_date>2026-06-16T19:07:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701440</loc>
  <lastmod>2026-06-16T19:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乗算も浮動小数点演算も不要？省資源推論のためのネットワーク学習（No Multiplication? No Floating Point? No Problem! Training Networks for Efficient Inference）</news:title>
   <news:publication_date>2026-06-16T19:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701438</loc>
  <lastmod>2026-06-16T19:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による多系サロゲート材料予測モデル（Machine-learned multi-system surrogate models for materials prediction）</news:title>
   <news:publication_date>2026-06-16T19:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701436</loc>
  <lastmod>2026-06-16T19:06:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセットバイアス下における公平性指標の評価（Evaluating Fairness Metrics in the Presence of Dataset Bias）</news:title>
   <news:publication_date>2026-06-16T19:06:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701434</loc>
  <lastmod>2026-06-16T18:14:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震直後の点検を自動化する条件認識型モデル（Towards Automated Post-Earthquake Inspections with Deep Learning-based Condition-Aware Models）</news:title>
   <news:publication_date>2026-06-16T18:14:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701432</loc>
  <lastmod>2026-06-16T18:14:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケールでの個別化教育（Personalized Education at Scale）</news:title>
   <news:publication_date>2026-06-16T18:14:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701430</loc>
  <lastmod>2026-06-16T18:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経画像解析における再現可能なデータ解析の計算・情報学的進展（Computational and informatics advances for reproducible data analysis in neuroimaging）</news:title>
   <news:publication_date>2026-06-16T18:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701428</loc>
  <lastmod>2026-06-16T18:13:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Real-Time Monocular Object-Model Aware Sparse SLAM（Real-Time Monocular Object-Model Aware Sparse SLAM）</news:title>
   <news:publication_date>2026-06-16T18:13:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701426</loc>
  <lastmod>2026-06-16T18:13:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データから支配方程式を近似する数値的要点（Numerical Aspects for Approximating Governing Equations Using Data）</news:title>
   <news:publication_date>2026-06-16T18:13:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701424</loc>
  <lastmod>2026-06-16T18:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話なしのローカル差分プライバシー学習はなぜ困難か（Locally Private Learning without Interaction Requires Separation）</news:title>
   <news:publication_date>2026-06-16T18:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701422</loc>
  <lastmod>2026-06-16T18:12:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全志向の強化学習における証拠蓄積法（Better Safe than Sorry: Evidence Accumulation Allows for Safe Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-16T18:12:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701420</loc>
  <lastmod>2026-06-16T17:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EPIRLによるエピスタシス検出の強化学習アプローチ (EPIRL: A REINFORCEMENT LEARNING AGENT TO FACILITATE EPISTASIS DETECTION)</news:title>
   <news:publication_date>2026-06-16T17:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701418</loc>
  <lastmod>2026-06-16T17:21:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最も落ち着いたSPT選抜銀河団の詳細研究：クールコアと中心銀河の性質（A Detailed Study of the Most Relaxed SPT-Selected Galaxy Clusters: Cool Core and Central Galaxy Properties）</news:title>
   <news:publication_date>2026-06-16T17:21:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701416</loc>
  <lastmod>2026-06-16T17:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>円筒変換による3次元腎臓セマンティックセグメンテーション（CYLINDRICAL TRANSFORM: 3D SEMANTIC SEGMENTATION OF KIDNEYS WITH LIMITED ANNOTATED IMAGES）</news:title>
   <news:publication_date>2026-06-16T17:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701414</loc>
  <lastmod>2026-06-16T17:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散逸的量子多体系における直交性カタストロフィー（Orthogonality catastrophe in dissipative quantum many body systems）</news:title>
   <news:publication_date>2026-06-16T17:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701412</loc>
  <lastmod>2026-06-16T17:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>輝度・深度・色を統合する融合型ネットワークによるセマンティックセグメンテーション（INCORPORATING LUMINANCE, DEPTH AND COLOR INFORMATION BY A FUSION-BASED NETWORK FOR SEMANTIC SEGMENTATION）</news:title>
   <news:publication_date>2026-06-16T17:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701410</loc>
  <lastmod>2026-06-16T17:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的最尤推定（Implicit Maximum Likelihood Estimation）</news:title>
   <news:publication_date>2026-06-16T17:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701408</loc>
  <lastmod>2026-06-16T17:19:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化するデータストリーム向け自己組織化ノイズ除去オートエンコーダ（Autonomous Deep Learning: Incremental Learning of Denoising Autoencoder for Evolving Data Streams）</news:title>
   <news:publication_date>2026-06-16T17:19:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701406</loc>
  <lastmod>2026-06-16T16:28:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>占有マップで深度を密にする手法（Sparse-to-Continuous: Enhancing Monocular Depth Estimation using Occupancy Maps）</news:title>
   <news:publication_date>2026-06-16T16:28:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701404</loc>
  <lastmod>2026-06-16T16:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Confidenceによる信頼区間の効率的算出（Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Errors for Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-16T16:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701402</loc>
  <lastmod>2026-06-16T16:26:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>28nm FDSOI CMOSの低温特性とモデリング（Characterization and Modeling of 28-nm FDSOI CMOS Technology down to Cryogenic Temperatures）</news:title>
   <news:publication_date>2026-06-16T16:26:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701400</loc>
  <lastmod>2026-06-16T16:26:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解剖学的ラベルを用いた弱教師ありメトリック集約による変形画像レジストレーション（Weakly-Supervised Learning of Metric Aggregations for Deformable Image Registration）</news:title>
   <news:publication_date>2026-06-16T16:26:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701398</loc>
  <lastmod>2026-06-16T16:26:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SDNにおけるフローエントリ管理を学習で最適化する手法（SDN Flow Entry Management Using Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-16T16:26:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701396</loc>
  <lastmod>2026-06-16T16:26:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一次元周期基板上の二次元液体ダスティプラズマのフォノンスペクトル（Phonon spectra of two-dimensional liquid dusty plasmas on a one-dimensional periodic substrate）</news:title>
   <news:publication_date>2026-06-16T16:26:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701394</loc>
  <lastmod>2026-06-16T16:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Bi-GAN支援遺伝的アルゴリズムによる深層ニューラルネットワークパラメータの自律同時最適化（Autonomously and Simultaneously Refining Deep Neural Network Parameters by a Bi-Generative Adversarial Network Aided Genetic Algorithm）</news:title>
   <news:publication_date>2026-06-16T16:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701392</loc>
  <lastmod>2026-06-16T15:34:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件生成に基づく相互情報量による敵対的部分空間の特徴付け（On the Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial Subspaces）</news:title>
   <news:publication_date>2026-06-16T15:34:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701390</loc>
  <lastmod>2026-06-16T15:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コミュニティ質問応答の共同マルチタスク学習（Joint Multitask Learning for Community Question Answering Using Task-Specific Embeddings）</news:title>
   <news:publication_date>2026-06-16T15:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701388</loc>
  <lastmod>2026-06-16T15:34:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な幾何学的摂動による対抗的顔画像（Fast Geometrically-Perturbed Adversarial Faces）</news:title>
   <news:publication_date>2026-06-16T15:34:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701386</loc>
  <lastmod>2026-06-16T15:33:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的半教師あり手法によるマルチタスク人間行動モデリング（A Probabilistic Semi-Supervised Approach to Multi-Task Human Activity Modeling）</news:title>
   <news:publication_date>2026-06-16T15:33:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701384</loc>
  <lastmod>2026-06-16T15:33:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速で精密なミエリン水量の定量化：DESSとカーネル学習による新手法（Fast, Precise Myelin Water Quantification using DESS MRI and Kernel Learning）</news:title>
   <news:publication_date>2026-06-16T15:33:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701382</loc>
  <lastmod>2026-06-16T15:33:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム干渉識別でIoT端末に共存認識を組み込む（Real-time Interference Identification via Supervised Learning: Embedding Coexistence Awareness in IoT Devices）</news:title>
   <news:publication_date>2026-06-16T15:33:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701380</loc>
  <lastmod>2026-06-16T15:32:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間接近下での四ロータ機の視覚制御（Vision-based Control of a Quadrotor in User Proximity: Mediated vs End-to-End Learning Approaches）</news:title>
   <news:publication_date>2026-06-16T15:32:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701378</loc>
  <lastmod>2026-06-16T14:41:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データから生物学的ネットワークを特徴づける手法（Characterization of Biologically Relevant Network Structures from Time-series Data）</news:title>
   <news:publication_date>2026-06-16T14:41:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701376</loc>
  <lastmod>2026-06-16T14:40:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平面類似変換を用いた半準パラメトリック推定と航空機荷重の高速計算（Semi-Parametric estimation of plane similarities: Application to fast computation of aeronautic loads）</news:title>
   <news:publication_date>2026-06-16T14:40:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701374</loc>
  <lastmod>2026-06-16T14:40:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市建物におけるエネルギー予測のための適応型ファジィ推論システム比較（A Comparative Study: Adaptive Fuzzy Inference Systems for Energy Prediction in Urban Buildings）</news:title>
   <news:publication_date>2026-06-16T14:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701372</loc>
  <lastmod>2026-06-16T14:39:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Residual Networksにおける普遍的な動的等長性の実現（Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function）</news:title>
   <news:publication_date>2026-06-16T14:39:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701370</loc>
  <lastmod>2026-06-16T14:39:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Vis-DSSによる視覚データ要約と選択の実務的利点（Vis-DSS: An Open-Source toolkit for Visual Data Selection and Summarization）</news:title>
   <news:publication_date>2026-06-16T14:39:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701368</loc>
  <lastmod>2026-06-16T14:39:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文木を使った文章圧縮の新手法（Text Summarization as Tree Transduction by Top-Down TreeLSTM）</news:title>
   <news:publication_date>2026-06-16T14:39:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701366</loc>
  <lastmod>2026-06-16T14:39:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン特化型ビデオ要約の枠組み（A Framework towards Domain Specific Video Summarization）</news:title>
   <news:publication_date>2026-06-16T14:39:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701364</loc>
  <lastmod>2026-06-16T13:47:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密結合ニューラルネットワークを疎グラフとして解釈し初期化を変える意義（Dense neural networks as sparse graphs and the lightning initialization）</news:title>
   <news:publication_date>2026-06-16T13:47:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701362</loc>
  <lastmod>2026-06-16T13:44:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル空間モデルにおけるテキスト類似度の比較研究（Text Similarity in Vector Space Models: A Comparative Study）</news:title>
   <news:publication_date>2026-06-16T13:44:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701360</loc>
  <lastmod>2026-06-16T13:43:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆を意識したロボット航行と自己注意を用いた深層強化学習（Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-16T13:43:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701358</loc>
  <lastmod>2026-06-16T13:43:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直交で分離された変分ガウス過程の入門（Orthogonally Decoupled Variational Gaussian Processes）</news:title>
   <news:publication_date>2026-06-16T13:43:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701356</loc>
  <lastmod>2026-06-16T13:43:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wasserstein分布ロバスト・カルマンフィルタ（Wasserstein Distributionally Robust Kalman Filtering）</news:title>
   <news:publication_date>2026-06-16T13:43:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701354</loc>
  <lastmod>2026-06-16T13:42:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Chargridによる2次元文書理解の革新（Chargrid: Towards Understanding 2D Documents）</news:title>
   <news:publication_date>2026-06-16T13:42:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701352</loc>
  <lastmod>2026-06-16T13:42:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報重み付きニューラルキャッシュ言語モデルによるASR改善（INFORMATION-WEIGHTED NEURAL CACHE LANGUAGE MODELS FOR ASR）</news:title>
   <news:publication_date>2026-06-16T13:42:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701350</loc>
  <lastmod>2026-06-16T12:51:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人追従ロボットのための能動的ターゲット探索アーキテクチャ（An Architecture for Person-Following using Active Target Search）</news:title>
   <news:publication_date>2026-06-16T12:51:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701348</loc>
  <lastmod>2026-06-16T12:50:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩行振動を用いた人物識別（Person Identification using Seismic Signals generated from Footfalls）</news:title>
   <news:publication_date>2026-06-16T12:50:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701346</loc>
  <lastmod>2026-06-16T12:49:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>監視映像における人物検索の実務的指針（Person Retrieval in Surveillance Video using Height, Color and Gender）</news:title>
   <news:publication_date>2026-06-16T12:49:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701344</loc>
  <lastmod>2026-06-16T12:49:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAHALO Deep Cluster Survey II — スパイダーネット（Spiderweb）原始クラスターで形成中の巨大銀河を特徴付ける（MAHALO Deep Cluster Survey II. Characterizing massive forming galaxies in the Spiderweb protocluster at z = 2.2）</news:title>
   <news:publication_date>2026-06-16T12:49:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701342</loc>
  <lastmod>2026-06-16T12:49:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>縦断データの行列補完によるモデル化（Modeling longitudinal data using matrix completion）</news:title>
   <news:publication_date>2026-06-16T12:49:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701340</loc>
  <lastmod>2026-06-16T12:49:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノームレンジングLSHによる最大内積探索の改善（Norm-Ranging LSH for Maximum Inner Product Search）</news:title>
   <news:publication_date>2026-06-16T12:49:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701338</loc>
  <lastmod>2026-06-16T12:48:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語の指示を高レベル行動計画へ翻訳する手法（Translating Navigation Instructions in Natural Language to a High-Level Plan for Behavioral Robot Navigation）</news:title>
   <news:publication_date>2026-06-16T12:48:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701336</loc>
  <lastmod>2026-06-16T11:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的に分離されたシステムのための分散Q学習（Distributed Q-Learning for Dynamically Decoupled Systems）</news:title>
   <news:publication_date>2026-06-16T11:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701334</loc>
  <lastmod>2026-06-16T11:57:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野外における偽顔画像検出の学習（Learning to Detect Fake Face Images in the Wild）</news:title>
   <news:publication_date>2026-06-16T11:57:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701332</loc>
  <lastmod>2026-06-16T11:57:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列版線形判別分析（Matrix Linear Discriminant Analysis）</news:title>
   <news:publication_date>2026-06-16T11:57:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701330</loc>
  <lastmod>2026-06-16T11:56:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Horndeski理論におけるダークエネルギーとGW170817後の制約（Dark energy in Horndeski theories after GW170817: A review）</news:title>
   <news:publication_date>2026-06-16T11:56:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701328</loc>
  <lastmod>2026-06-16T11:56:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック進化のスケーラブル推論（Scalable inference of topic evolution via models for latent geometric structures）</news:title>
   <news:publication_date>2026-06-16T11:56:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701326</loc>
  <lastmod>2026-06-16T11:55:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小資源環境での形態論生成とニューラル推移学習（Neural Transductive Learning and Beyond: Morphological Generation in the Minimal-Resource Setting）</news:title>
   <news:publication_date>2026-06-16T11:55:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701324</loc>
  <lastmod>2026-06-16T11:55:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフフィルタ逆畳み込みによる幾何深層学習の強化（ENHANCING GEOMETRIC DEEP LEARNING VIA GRAPH FILTER DECONVOLUTION）</news:title>
   <news:publication_date>2026-06-16T11:55:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701322</loc>
  <lastmod>2026-06-16T11:04:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>真実ラベル不在下でのマルウェア検出指標の統計的推定（Statistical Estimation of Malware Detection Metrics in the Absence of Ground Truth）</news:title>
   <news:publication_date>2026-06-16T11:04:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701320</loc>
  <lastmod>2026-06-16T11:03:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組合せデータフュージョンと矛盾付き教師あり学習（The Combinatorial Data Fusion Problem in Conflicted-supervised Learning）</news:title>
   <news:publication_date>2026-06-16T11:03:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701318</loc>
  <lastmod>2026-06-16T11:03:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人とロボットの対話によるオンライン物体・タスク学習（Online Object and Task Learning via Human Robot Interaction）</news:title>
   <news:publication_date>2026-06-16T11:03:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701316</loc>
  <lastmod>2026-06-16T11:02:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的学生分類を組み込んだDeep Knowledge Tracing（Deep Knowledge Tracing with Dynamic Student Classification）</news:title>
   <news:publication_date>2026-06-16T11:02:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701314</loc>
  <lastmod>2026-06-16T11:02:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒントをください！人間のフィードバックで画像データベースを探索する方法（Give me a hint! Navigating Image Databases using Human-in-the-loop Feedback）</news:title>
   <news:publication_date>2026-06-16T11:02:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701312</loc>
  <lastmod>2026-06-16T11:02:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中央銀行の情報発信が利回り曲線に与える影響（Central Bank Communication and the Yield Curve: A Semi-Automatic Approach using Non-Negative Matrix Factorization）</news:title>
   <news:publication_date>2026-06-16T11:02:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701310</loc>
  <lastmod>2026-06-16T11:02:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様な特徴タイプに対応する統一再帰型ニューラルネットワーク（UNIFIED RECURRENT NEURAL NETWORK FOR MANY FEATURE TYPES）</news:title>
   <news:publication_date>2026-06-16T11:02:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701308</loc>
  <lastmod>2026-06-16T10:10:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポッドキャストで映画タイトルを認識する方法（Recognizing Film Entities in Podcasts）</news:title>
   <news:publication_date>2026-06-16T10:10:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701306</loc>
  <lastmod>2026-06-16T10:10:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイヤレスネットワークにおける機械学習の応用と課題（Application of Machine Learning in Wireless Networks: Key Techniques and Open Issues）</news:title>
   <news:publication_date>2026-06-16T10:10:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701304</loc>
  <lastmod>2026-06-16T10:09:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OWL正則化回帰の敵対的耐性の検証（IS ORDERED WEIGHTED ℓ1 REGULARIZED REGRESSION ROBUST TO ADVERSARIAL PERTURBATION? A CASE STUDY ON OSCAR）</news:title>
   <news:publication_date>2026-06-16T10:09:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701302</loc>
  <lastmod>2026-06-16T10:09:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ除去における教師なしパラメータ選択（Unsupervised parameter selection for denoising with the elastic net）</news:title>
   <news:publication_date>2026-06-16T10:09:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701300</loc>
  <lastmod>2026-06-16T10:09:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>嫉妬のない分類（Envy-Free Classification）</news:title>
   <news:publication_date>2026-06-16T10:09:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701298</loc>
  <lastmod>2026-06-16T10:09:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合モデルに対するExpectation-Maximizationアルゴリズムの振る舞い（On the Behavior of the Expectation-Maximization Algorithm for Mixture Models）</news:title>
   <news:publication_date>2026-06-16T10:09:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701296</loc>
  <lastmod>2026-06-16T10:08:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚質問応答にテキストを加える新手法（Textually Enriched Neural Module Networks for Visual Question Answering）</news:title>
   <news:publication_date>2026-06-16T10:08:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701294</loc>
  <lastmod>2026-06-16T09:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitter上のヘイトスピーチと攻撃的発言の自動検出（Detecting Hate Speech and Offensive Language on Twitter using Machine Learning: An N-gram and TFIDF based Approach）</news:title>
   <news:publication_date>2026-06-16T09:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701292</loc>
  <lastmod>2026-06-16T09:09:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペリングで学ぶ文字認識（Learning to Read by Spelling: Towards Unsupervised Text Recognition）</news:title>
   <news:publication_date>2026-06-16T09:09:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701290</loc>
  <lastmod>2026-06-16T09:09:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動による構造設計の新展開（Data-Driven Design: Exploring new Structural Forms using Machine Learning and Graphic Statics）</news:title>
   <news:publication_date>2026-06-16T09:09:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701288</loc>
  <lastmod>2026-06-16T09:08:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカル流入に起因する陸上流の“ほぼ瞬時”モデリング（Modelling overland flow from local inflows in “almost no-time” using Self-Organizing Maps）</news:title>
   <news:publication_date>2026-06-16T09:08:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701286</loc>
  <lastmod>2026-06-16T09:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語に注意を払え：コードスイッチ言語の虐待・侮辱検出（Mind Your Language: Abuse and Offense Detection for Code-Switched Languages）</news:title>
   <news:publication_date>2026-06-16T09:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701284</loc>
  <lastmod>2026-06-16T09:07:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ヘビーボール法による加速ギャシップ（Accelerated Gossip via Stochastic Heavy Ball Method）</news:title>
   <news:publication_date>2026-06-16T09:07:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701282</loc>
  <lastmod>2026-06-16T09:07:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンジニアリング・メソッドの牢獄からの脱出をゲーミフィケーションで学ぶ（Gamifying the Escape from the Engineering Method Prison）</news:title>
   <news:publication_date>2026-06-16T09:07:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701280</loc>
  <lastmod>2026-06-16T08:16:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変とその属性のセグメンテーション（Segmentation of Skin Lesions and their Attributes Using Multi-Scale Convolutional Neural Networks and Domain Specific Augmentations）</news:title>
   <news:publication_date>2026-06-16T08:16:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701278</loc>
  <lastmod>2026-06-16T08:15:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>saprEMo: 天文サーベイにおける電磁トランジェント検出予測のための簡易アルゴリズム（saprEMo: a simplified algorithm for predicting detections of electromagnetic transients in surveys）</news:title>
   <news:publication_date>2026-06-16T08:15:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701276</loc>
  <lastmod>2026-06-16T08:15:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳ネットによるマルチパーソン脳間インターフェース（BrainNet: A Multi-Person Brain-to-Brain Interface for Direct Collaboration Between Brains）</news:title>
   <news:publication_date>2026-06-16T08:15:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701274</loc>
  <lastmod>2026-06-16T08:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効果から道具・対象・動作を検出するロボット学習（Detecting Features of Tools, Objects, and Actions from Effects in a Robot using Deep Learning）</news:title>
   <news:publication_date>2026-06-16T08:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701272</loc>
  <lastmod>2026-06-16T08:14:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能なスパース文センテンス埋め込みの学習と評価（Learning and Evaluating Sparse Interpretable Sentence Embeddings）</news:title>
   <news:publication_date>2026-06-16T08:14:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701270</loc>
  <lastmod>2026-06-16T08:14:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット予知保全のためのドメイン適応（Domain Adaptation for Robot Predictive Maintenance Systems）</news:title>
   <news:publication_date>2026-06-16T08:14:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701268</loc>
  <lastmod>2026-06-16T08:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疎イベントデータからの密な深度・光学フロー・エゴモーションの無監督学習（Unsupervised Learning of Dense Optical Flow, Depth and Egomotion from Sparse Event Data）</news:title>
   <news:publication_date>2026-06-16T08:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701266</loc>
  <lastmod>2026-06-16T07:22:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い線形ニューラルネットワークにおける勾配降下の指数的収束時間（Exponential Convergence Time of Gradient Descent for One-Dimensional Deep Linear Neural Networks）</news:title>
   <news:publication_date>2026-06-16T07:22:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701264</loc>
  <lastmod>2026-06-16T07:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学際研究と教育を強化する仮想現実の活用（The use of Virtual Reality in Enhancing Interdisciplinary Research and Education）</news:title>
   <news:publication_date>2026-06-16T07:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701262</loc>
  <lastmod>2026-06-16T07:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>数式計算を純ニューラルで解く方法（Neural Arithmetic Expression Calculator）</news:title>
   <news:publication_date>2026-06-16T07:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701260</loc>
  <lastmod>2026-06-16T07:21:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ANM混合モデルの因果推論と機構クラスタリング（Causal Inference and Mechanism Clustering of a Mixture of Additive Noise Models）</news:title>
   <news:publication_date>2026-06-16T07:21:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701258</loc>
  <lastmod>2026-06-16T07:21:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度光学フロー推定による動画超解像学習（Learning for Video Super-Resolution through HR Optical Flow Estimation）</news:title>
   <news:publication_date>2026-06-16T07:21:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701256</loc>
  <lastmod>2026-06-16T07:21:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ理解におけるエンティティ属性同定（Query Understanding via Entity Attribute Identification）</news:title>
   <news:publication_date>2026-06-16T07:21:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701254</loc>
  <lastmod>2026-06-16T07:21:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>糖尿病網膜症診断における深層学習分類器が用いる独立原因の同定と可視化（Identification and Visualization of the Underlying Independent Causes of the Diagnostic of Diabetic Retinopathy made by a Deep Learning Classifier）</news:title>
   <news:publication_date>2026-06-16T07:21:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701252</loc>
  <lastmod>2026-06-16T06:29:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常性を利用した因果推論の新展開（A KERNEL EMBEDDING-BASED APPROACH FOR NONSTATIONARY CAUSAL MODEL INFERENCE）</news:title>
   <news:publication_date>2026-06-16T06:29:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701250</loc>
  <lastmod>2026-06-16T06:29:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Self Attention Gridによる人物再識別の改善（Self Attention Grid for Person Re-Identification）</news:title>
   <news:publication_date>2026-06-16T06:29:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701248</loc>
  <lastmod>2026-06-16T06:29:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高精度産業組立の学習フレームワーク（A Learning Framework for High Precision Industrial Assembly）</news:title>
   <news:publication_date>2026-06-16T06:29:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701246</loc>
  <lastmod>2026-06-16T06:28:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>どこから転移するかを探る深層転移学習（Deep Transfer Learning by Exploring Where to Transfer）</news:title>
   <news:publication_date>2026-06-16T06:28:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701244</loc>
  <lastmod>2026-06-16T06:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>がん組織におけるCD8陽性T細胞とがん島の位置情報から予後を予測する機械学習アプローチ（Predicting patient outcomes (TNBC) based on positions of cancer islands and CD8+ T cells using machine learning approach）</news:title>
   <news:publication_date>2026-06-16T06:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701242</loc>
  <lastmod>2026-06-16T06:27:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カスタマイズグリッパによる堅牢なビンピッキングの学習フレームワーク（A Learning Framework for Robust Bin Picking by Customized Grippers）</news:title>
   <news:publication_date>2026-06-16T06:27:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701240</loc>
  <lastmod>2026-06-16T06:27:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を用いたバウンディングボックス回帰（Bounding Box Regression with Uncertainty for Accurate Object Detection）</news:title>
   <news:publication_date>2026-06-16T06:27:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701238</loc>
  <lastmod>2026-06-16T05:36:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識表現学習における負例サンプリングへのGAN導入（Incorporating GAN for Negative Sampling in Knowledge Representation Learning）</news:title>
   <news:publication_date>2026-06-16T05:36:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701236</loc>
  <lastmod>2026-06-16T05:36:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ依存活性化関数・全変差最小化・敵対的訓練による敵対的防御 (Adversarial Defense via the Data-Dependent Activation, Total Variation Minimization, and Adversarial Training)</news:title>
   <news:publication_date>2026-06-16T05:36:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701234</loc>
  <lastmod>2026-06-16T05:35:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動サブ微分の証明付き手法（Provably Correct Automatic Subdifferentiation for Qualified Programs）</news:title>
   <news:publication_date>2026-06-16T05:35:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701232</loc>
  <lastmod>2026-06-16T05:34:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インド鉄道向け列車状況アシスタント（A Train Status Assistant for Indian Railways）</news:title>
   <news:publication_date>2026-06-16T05:34:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701230</loc>
  <lastmod>2026-06-16T05:34:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LiDAR点群の実用精度を高めるSqueezeSegV2（SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud）</news:title>
   <news:publication_date>2026-06-16T05:34:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701228</loc>
  <lastmod>2026-06-16T05:34:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語に依存しない普遍表現の構築（TOWARDS LANGUAGE AGNOSTIC UNIVERSAL REPRESENTATIONS）</news:title>
   <news:publication_date>2026-06-16T05:34:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701226</loc>
  <lastmod>2026-06-16T05:34:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SelfKinによる親族関係推定（SelfKin: Self Adjusted Deep Model For Kinship Verification）</news:title>
   <news:publication_date>2026-06-16T05:34:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701224</loc>
  <lastmod>2026-06-16T04:42:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動画像注釈による訓練バイアスの是正（Addressing Training Bias via Automated Image Annotation）</news:title>
   <news:publication_date>2026-06-16T04:42:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701222</loc>
  <lastmod>2026-06-16T04:42:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepOriginによる未知マルウェア検出の実用性（DeepOrigin: End-to-End Deep Learning for Detection of New Malware Families）</news:title>
   <news:publication_date>2026-06-16T04:42:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701220</loc>
  <lastmod>2026-06-16T04:41:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル認知に基づく人的社会行動モデルの定常状態解析（Steady-state Analysis of a Neural-cognition Based Human-social Behavior Model）</news:title>
   <news:publication_date>2026-06-16T04:41:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701218</loc>
  <lastmod>2026-06-16T04:41:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無条件に安全かつ普遍的に合成可能な内積プロトコルの安全性（On the Security of an Unconditionally Secure, Universally Composable Inner Product Protocol）</news:title>
   <news:publication_date>2026-06-16T04:41:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701216</loc>
  <lastmod>2026-06-16T04:40:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>姿勢誘導マルチ粒度注意ネットワークによる文章ベース人物検索（Pose-Guided Multi-Granularity Attention Network for Text-Based Person Search）</news:title>
   <news:publication_date>2026-06-16T04:40:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701214</loc>
  <lastmod>2026-06-16T04:40:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Shift-based Primitivesによる効率的な畳み込みニューラルネットワーク（Shift-based Primitives for Efficient Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-16T04:40:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701212</loc>
  <lastmod>2026-06-16T04:40:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マウスの睡眠ステージ自動分類とアーティファクト検出を深層学習で実現する手法（Automated Classification of Sleep Stages and EEG Artifacts in Mice with Deep Learning）</news:title>
   <news:publication_date>2026-06-16T04:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701210</loc>
  <lastmod>2026-06-16T03:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パチンコ予測：ソーシャルメディアデータからの事象予測のベイズ法 (Pachinko Prediction: A Bayesian method for event prediction from social media data)</news:title>
   <news:publication_date>2026-06-16T03:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701208</loc>
  <lastmod>2026-06-16T03:49:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できるマルチパーティ計算と検証可能なシミュレーション（Trusted Multi-Party Computation and Verifiable Simulations: A Scalable Blockchain Approach）</news:title>
   <news:publication_date>2026-06-16T03:49:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701206</loc>
  <lastmod>2026-06-16T03:48:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小規模データ下での浅頑丈基礎の許容支持力予測に最適なANNモデル（The Optimal ANN Model for Predicting Bearing Capacity of Shallow Foundations Trained on Scarce Data）</news:title>
   <news:publication_date>2026-06-16T03:48:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701204</loc>
  <lastmod>2026-06-16T03:48:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生理信号に基づくエントロピー支援型マルチモーダル感情認識フレームワーク（Entropy-Assisted Multi-Modal Emotion Recognition Framework Based on Physiological Signals）</news:title>
   <news:publication_date>2026-06-16T03:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701202</loc>
  <lastmod>2026-06-16T03:47:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療知識埋め込みと再帰型ニューラルネットワークによる多疾患診断（Medical Knowledge Embedding Based on Recursive Neural Network for Multi-Disease Diagnosis）</news:title>
   <news:publication_date>2026-06-16T03:47:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701200</loc>
  <lastmod>2026-06-16T03:47:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファジィC平均法と可能性的C平均法によるクラスタリング傾向分析と検証（Implementation of Fuzzy C-Means and Possibilistic C-Means Clustering Algorithms, Cluster Tendency Analysis and Cluster Validation）</news:title>
   <news:publication_date>2026-06-16T03:47:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701198</loc>
  <lastmod>2026-06-16T03:47:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分可能で偏りのないオンライン学習ランキング（Differentiable Unbiased Online Learning to Rank）</news:title>
   <news:publication_date>2026-06-16T03:47:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701196</loc>
  <lastmod>2026-06-16T02:56:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乏しい指示文に対する細粒度行動の位置特定と整合学習（Learning to Localize and Align Fine-Grained Actions to Sparse Instructions）</news:title>
   <news:publication_date>2026-06-16T02:56:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701194</loc>
  <lastmod>2026-06-16T02:52:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習のための組合せデザイン（Combinatorial Designs for Deep Learning）</news:title>
   <news:publication_date>2026-06-16T02:52:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701192</loc>
  <lastmod>2026-06-16T02:52:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的画像復元（Active image restoration）</news:title>
   <news:publication_date>2026-06-16T02:52:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701190</loc>
  <lastmod>2026-06-16T02:52:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相対カメラ姿勢推定をエンドツーエンドで行う手法（RPNet: an End-to-End Network for Relative Camera Pose Estimation）</news:title>
   <news:publication_date>2026-06-16T02:52:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701188</loc>
  <lastmod>2026-06-16T02:51:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>STEAMメイカースペースによる幾何学学習の活性化（Implementing a STEAM Makerspace for Geometry Education）</news:title>
   <news:publication_date>2026-06-16T02:51:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701186</loc>
  <lastmod>2026-06-16T02:51:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何学的マルチモデルフィッティングを深層強化学習で解く（Geometric Multi-Model Fitting by Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-16T02:51:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701184</loc>
  <lastmod>2026-06-16T02:50:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分協調学習によるユーザー確率表現（Variational Collaborative Learning for User Probabilistic Representation）</news:title>
   <news:publication_date>2026-06-16T02:50:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701182</loc>
  <lastmod>2026-06-16T01:59:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全光学的機械学習と回折ディープニューラルネットワーク（All-optical machine learning using diffractive deep neural networks）</news:title>
   <news:publication_date>2026-06-16T01:59:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701180</loc>
  <lastmod>2026-06-16T01:57:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cross-View Trainingによる半教師あり系列モデリング（Semi-Supervised Sequence Modeling with Cross-View Training）</news:title>
   <news:publication_date>2026-06-16T01:57:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701178</loc>
  <lastmod>2026-06-16T01:57:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河の形態分類におけるカプセルネットワーク（Galaxy morphology prediction using capsule networks）</news:title>
   <news:publication_date>2026-06-16T01:57:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701176</loc>
  <lastmod>2026-06-16T01:56:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結合グラフとテンソル分解によるレコメンデーションとコミュニティ検出（Coupled Graphs and Tensor Factorization for Recommender Systems and Community Detection）</news:title>
   <news:publication_date>2026-06-16T01:56:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701174</loc>
  <lastmod>2026-06-16T01:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制限なしの敵対的例（Unrestricted Adversarial Examples）</news:title>
   <news:publication_date>2026-06-16T01:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701172</loc>
  <lastmod>2026-06-16T01:56:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CPMETRIC: 構造化された選好のための深層シアミスネットワークによる距離学習（CPMETRIC: Deep Siamese Networks for Metric Learning on Structured Preferences）</news:title>
   <news:publication_date>2026-06-16T01:56:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701170</loc>
  <lastmod>2026-06-16T01:55:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ転移学習によるカスタムモデル訓練（A Meta-Learning Approach for Custom Model Training）</news:title>
   <news:publication_date>2026-06-16T01:55:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701168</loc>
  <lastmod>2026-06-16T01:04:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタープリタブルな多目的強化学習とポリシーオーケストレーション（Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration）</news:title>
   <news:publication_date>2026-06-16T01:04:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701166</loc>
  <lastmod>2026-06-16T01:04:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習された偽ユーザーによる攻撃と対策（Adversarial Recommendation: Attack of the Learned Fake Users）</news:title>
   <news:publication_date>2026-06-16T01:04:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701164</loc>
  <lastmod>2026-06-16T01:03:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチロボット箱押しにおける強化学習手法の比較（A Comparison of Various Approaches to Reinforcement Learning Algorithms for Multi-robot Box Pushing）</news:title>
   <news:publication_date>2026-06-16T01:03:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701162</loc>
  <lastmod>2026-06-16T01:03:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列補間を用いた光学フロー推定の教師なし事前学習（Temporal Interpolation as an Unsupervised Pretraining Task for Optical Flow Estimation）</news:title>
   <news:publication_date>2026-06-16T01:03:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701157</loc>
  <lastmod>2026-06-16T01:03:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイナリの作者特定を撹乱する攻撃手法（Adversarial Binaries for Authorship Identification）</news:title>
   <news:publication_date>2026-06-16T01:03:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701150</loc>
  <lastmod>2026-06-16T01:03:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Certificate Transparencyの台頭とインターネット生態系への影響 (The Rise of Certificate Transparency and Its Implications)</news:title>
   <news:publication_date>2026-06-16T01:03:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701148</loc>
  <lastmod>2026-06-16T01:02:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理情報ニューラルネットワークにおける総合的不確かさの定量化（Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems）</news:title>
   <news:publication_date>2026-06-16T01:02:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701146</loc>
  <lastmod>2026-06-16T00:11:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>miniTimeCubeにおけるMCP-PMT研究の実務的示唆（Studies of MCP-PMTs in the miniTimeCube neutrino detector）</news:title>
   <news:publication_date>2026-06-16T00:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701144</loc>
  <lastmod>2026-06-16T00:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代謝モデリングにおける手法の“森林”と実務への示唆（Seeing the wood for the trees: a forest of methods for optimisation and omic-network integration in metabolic modelling）</news:title>
   <news:publication_date>2026-06-16T00:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701142</loc>
  <lastmod>2026-06-16T00:10:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランオン文（Run-on sentence）を機械で直す――不揃いエラーに挑む新手法（How do you correct run-on sentences it’s not as easy as it seems）</news:title>
   <news:publication_date>2026-06-16T00:10:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701140</loc>
  <lastmod>2026-06-16T00:10:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシーを意識したインデックス符号化：k-Limited-Accessスキーム（Privacy in Index Coding: k-Limited-Access Schemes）</news:title>
   <news:publication_date>2026-06-16T00:10:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701138</loc>
  <lastmod>2026-06-16T00:10:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問の不透明さと希少性が示す問いの幾何学 (Opacity, Obscurity, and the Geometry of Question-Asking)</news:title>
   <news:publication_date>2026-06-16T00:10:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701136</loc>
  <lastmod>2026-06-16T00:09:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球の岩石寄生生命と火星探査の戦略（Paleo‑Rock‑Hosted Life on Earth and the Search on Mars: a Review and Strategy for Exploration）</news:title>
   <news:publication_date>2026-06-16T00:09:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701134</loc>
  <lastmod>2026-06-16T00:09:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットの汎化可能な接近行動学習（GAPLE: Generalizable Approaching Policy LEarning for Robotic Object Searching in Indoor Environment）</news:title>
   <news:publication_date>2026-06-16T00:09:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701132</loc>
  <lastmod>2026-06-15T23:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高自由度ロボットの高速運動計画と階層的システム同定（Fast Motion Planning for High-DOF Robot Systems Using Hierarchical System Identification）</news:title>
   <news:publication_date>2026-06-15T23:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701130</loc>
  <lastmod>2026-06-15T23:18:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>青色水平分枝星でたどる銀河ハローの外縁（A-type stars in the Canada-France Imaging Survey I. The stellar halo of the Milky Way traced to large radius by blue horizontal branch stars）</news:title>
   <news:publication_date>2026-06-15T23:18:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701128</loc>
  <lastmod>2026-06-15T23:17:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有機太陽電池のC-V特性の解析と数値モデル化（Analytical and numerical modeling of capacitance voltage characteristics of organic solar cells）</news:title>
   <news:publication_date>2026-06-15T23:17:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701126</loc>
  <lastmod>2026-06-15T23:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Abell 133周辺のフィラメント検出と光学的検証（Filaments around Abell 133）</news:title>
   <news:publication_date>2026-06-15T23:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701124</loc>
  <lastmod>2026-06-15T23:17:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>X-UDS：UKIDSS Ultra Deep Survey フィールドのChandraレガシー調査（X-UDS: THE CHANDRA LEGACY SURVEY OF THE UKIDSS ULTRA DEEP SURVEY FIELD）</news:title>
   <news:publication_date>2026-06-15T23:17:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701122</loc>
  <lastmod>2026-06-15T23:16:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPT-3G二次鏡の幾何学（SPT-3G secondary mirror geometry）</news:title>
   <news:publication_date>2026-06-15T23:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701120</loc>
  <lastmod>2026-06-15T23:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の超解像とノイズ除去を同時に解く一手法（Image Denoising and Super-Resolution Using Residual Learning of Deep Convolutional Network）</news:title>
   <news:publication_date>2026-06-15T23:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701118</loc>
  <lastmod>2026-06-15T22:25:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高温強磁性体における構造検出（High-Temperature Structure Detection in Ferromagnets）</news:title>
   <news:publication_date>2026-06-15T22:25:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701116</loc>
  <lastmod>2026-06-15T22:25:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>背景知識を活用した会話システム構築への挑戦（Towards Exploiting Background Knowledge for Building Conversation Systems）</news:title>
   <news:publication_date>2026-06-15T22:25:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701114</loc>
  <lastmod>2026-06-15T22:24:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数ネットワーク整列のための低ランク手法 (Low Rank Methods for Multiple Network Alignment)</news:title>
   <news:publication_date>2026-06-15T22:24:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701112</loc>
  <lastmod>2026-06-15T22:24:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレータ較正における共変量シフト対策とカーネル手法（Simulator Calibration under Covariate Shift with Kernels）</news:title>
   <news:publication_date>2026-06-15T22:24:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701110</loc>
  <lastmod>2026-06-15T22:23:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数行動を学習する推薦モデルの設計（Learning to Recommend with Multiple Cascading Behaviors）</news:title>
   <news:publication_date>2026-06-15T22:23:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701108</loc>
  <lastmod>2026-06-15T22:23:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビュー情報を活用したBPRのサンプラー設計（Sampler Design for Bayesian Personalized Ranking by Leveraging View Data）</news:title>
   <news:publication_date>2026-06-15T22:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701106</loc>
  <lastmod>2026-06-15T22:23:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Exclusive Independent Probability Estimationを用いた深層3D Fully Convolutional DenseNets（Exclusive Independent Probability Estimation using Deep 3D Fully Convolutional DenseNets: Application to IsoIntense Infant Brain MRI Segmentation）</news:title>
   <news:publication_date>2026-06-15T22:23:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701104</loc>
  <lastmod>2026-06-15T21:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>科学館来館者の動機を測る心理計測器の妥当性検証（Psychometric properties of an instrument to investigate the motivation of visitors to a science museum: The combination of methods）</news:title>
   <news:publication_date>2026-06-15T21:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701102</loc>
  <lastmod>2026-06-15T21:31:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同期と衝突で情報を共有する仕組み——SIC‑MMABの要点と経営への示唆 (Synchronisation Involves Communication in Multiplayer Multi‑Armed Bandits)</news:title>
   <news:publication_date>2026-06-15T21:31:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701100</loc>
  <lastmod>2026-06-15T21:30:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BEOムサラ観測に基づく雲凝結核サイズ分布から分かること（What One Can Learn From the Cloud Condensation Nuclei Size Distributions as Monitored by the BEO Moussala?）</news:title>
   <news:publication_date>2026-06-15T21:30:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701098</loc>
  <lastmod>2026-06-15T21:30:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>L1回帰による疎な敵対的ノイズ下の圧縮センシング（Compressed Sensing with Adversarial Sparse Noise via L1 Regression）</news:title>
   <news:publication_date>2026-06-15T21:30:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701096</loc>
  <lastmod>2026-06-15T21:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極低金属量銀河における分子ガスと星形成の関係（Star Formation and Molecular Gas in Extremely Metal-poor Galaxies: Insights from the Thermal Balance in the Neutral Gas）</news:title>
   <news:publication_date>2026-06-15T21:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701094</loc>
  <lastmod>2026-06-15T21:29:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形属性付きグラフのクラスタリング（Non-linear Attributed Graph Clustering by Symmetric NMF with PU Learning）</news:title>
   <news:publication_date>2026-06-15T21:29:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701092</loc>
  <lastmod>2026-06-15T21:29:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散データ下における木構造ガウスグラフィカルモデルの学習（Learning of Tree-Structured Gaussian Graphical Models on Distributed Data under Communication Constraints）</news:title>
   <news:publication_date>2026-06-15T21:29:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701090</loc>
  <lastmod>2026-06-15T20:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stochasticity from function – why the Bayesian brain may need no noise（Stochasticity from function – why the Bayesian brain may need no noise）</news:title>
   <news:publication_date>2026-06-15T20:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701088</loc>
  <lastmod>2026-06-15T20:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッセイのレベル推定における語彙バイアス（Lexical Bias In Essay Level Prediction）</news:title>
   <news:publication_date>2026-06-15T20:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701086</loc>
  <lastmod>2026-06-15T20:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>読者識別と読解度推定のための識別モデル（A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements）</news:title>
   <news:publication_date>2026-06-15T20:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701084</loc>
  <lastmod>2026-06-15T20:36:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M31の北部円盤に対する深宇宙X線観測がもたらす変化（Deep XMM-Newton Observations of the Northern Disc of M31）</news:title>
   <news:publication_date>2026-06-15T20:36:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701082</loc>
  <lastmod>2026-06-15T20:36:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多次元・多層・非線形・動的HITS（Multi-Dimensional, Multilayer, Nonlinear and Dynamic HITS）</news:title>
   <news:publication_date>2026-06-15T20:36:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701080</loc>
  <lastmod>2026-06-15T20:35:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOOCにおける学習者行動に基づく情報に基づくアクション（Taking Informed Action on Student Activity in MOOCs）</news:title>
   <news:publication_date>2026-06-15T20:35:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701078</loc>
  <lastmod>2026-06-15T20:35:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競技場での選手負荷と膝損傷リスクの現場監視（On-field player workload exposure and knee injury risk monitoring via deep learning）</news:title>
   <news:publication_date>2026-06-15T20:35:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701076</loc>
  <lastmod>2026-06-15T19:44:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星レーザー測距（SLR）による一般相対性理論の検証とLARASEの進展（Satellite Laser Ranging and General Relativity measurements in the field of the Earth: state of the art and perspectives）</news:title>
   <news:publication_date>2026-06-15T19:44:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701074</loc>
  <lastmod>2026-06-15T19:36:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラミング課題における自動介入の効果（Effects of Automated Interventions in Programming Assignments: Evidence from a Field Experiment）</news:title>
   <news:publication_date>2026-06-15T19:36:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701072</loc>
  <lastmod>2026-06-15T19:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完璧な一致：音声-映像同期のための改良されたクロスモーダル埋め込み（PERFECT MATCH: IMPROVED CROSS-MODAL EMBEDDINGS FOR AUDIO-VISUAL SYNCHRONISATION）</news:title>
   <news:publication_date>2026-06-15T19:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701070</loc>
  <lastmod>2026-06-15T19:35:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画ストーリーの問いに答えるための多層注意メモリ（Multimodal Dual Attention Memory for Video Story Question Answering）</news:title>
   <news:publication_date>2026-06-15T19:35:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701068</loc>
  <lastmod>2026-06-15T19:34:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動きと記憶で動画の注目点を検出する仕組み（SG-FCN: Motion and Memory-Based Deep Learning Model for Video Saliency Detection）</news:title>
   <news:publication_date>2026-06-15T19:34:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701066</loc>
  <lastmod>2026-06-15T19:34:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮的敵対的プライバシーの理解（Understanding Compressive Adversarial Privacy）</news:title>
   <news:publication_date>2026-06-15T19:34:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701064</loc>
  <lastmod>2026-06-15T19:34:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FeO2における電子スピン遷移とFeの酸化状態の解明（Electronic Spin transition in FeO2: evidence for Fe(II) with peroxide O2−2）</news:title>
   <news:publication_date>2026-06-15T19:34:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701062</loc>
  <lastmod>2026-06-15T18:42:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳房密度の自動分類に残差学習を使う意義（Classifying Mammographic Breast Density by Residual Learning）</news:title>
   <news:publication_date>2026-06-15T18:42:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701060</loc>
  <lastmod>2026-06-15T18:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ環境におけるGTD方策評価の有限サンプル解析 (Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting)</news:title>
   <news:publication_date>2026-06-15T18:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701058</loc>
  <lastmod>2026-06-15T18:41:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験に基づく探索制約と回復（Constrained Exploration and Recovery from Experience Shaping）</news:title>
   <news:publication_date>2026-06-15T18:41:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701056</loc>
  <lastmod>2026-06-15T18:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粗い空間データの精緻化（Refining Coarse-grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities）</news:title>
   <news:publication_date>2026-06-15T18:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701054</loc>
  <lastmod>2026-06-15T18:40:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数モデルの協調で生物医療文献から正確に固有表現を抜き出す（CollaboNet: collaboration of deep neural networks for biomedical named entity recognition）</news:title>
   <news:publication_date>2026-06-15T18:40:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701052</loc>
  <lastmod>2026-06-15T18:40:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stack Overflow質問のプログラミング言語予測（Predicting the Programming Language of Questions and Snippets of StackOverflow Using Natural Language Processing）</news:title>
   <news:publication_date>2026-06-15T18:40:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701050</loc>
  <lastmod>2026-06-15T18:40:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ターゲット転移Q学習と収束解析 (Target Transfer Q-Learning and Its Convergence Analysis)</news:title>
   <news:publication_date>2026-06-15T18:40:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701048</loc>
  <lastmod>2026-06-15T17:49:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中ロボットの「身ぶり」コミュニケーション（Robot Communication Via Motion: Closing the Underwater Human-Robot Interaction Loop）</news:title>
   <news:publication_date>2026-06-15T17:49:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701046</loc>
  <lastmod>2026-06-15T17:48:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コードスニペットの自動分類（SCC: Automatic Classification of Code Snippets）</news:title>
   <news:publication_date>2026-06-15T17:48:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701044</loc>
  <lastmod>2026-06-15T17:48:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LIDARとカメラの融合による道路検出（LIDAR-Camera Fusion for Road Detection）</news:title>
   <news:publication_date>2026-06-15T17:48:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701042</loc>
  <lastmod>2026-06-15T17:47:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル深度監督による敵対的3D人体姿勢推定（Adversarial 3D Human Pose Estimation via Multimodal Depth Supervision）</news:title>
   <news:publication_date>2026-06-15T17:47:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701040</loc>
  <lastmod>2026-06-15T17:47:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序性を考慮した文脈対応型推薦（Context-Aware Systems for Sequential Item Recommendation）</news:title>
   <news:publication_date>2026-06-15T17:47:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701038</loc>
  <lastmod>2026-06-15T17:47:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adaptive O-CNNによる高効率3D形状表現（Adaptive O-CNN: A Patch-based Deep Representation of 3D Shapes）</news:title>
   <news:publication_date>2026-06-15T17:47:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701036</loc>
  <lastmod>2026-06-15T17:46:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カシオペヤAの深い近赤外線[Fe II]+[Si I]イメージ（A Deep Near-Infrared [Fe II]+[Si I] Emission Line Image of the Supernova Remnant Cassiopeia A）</news:title>
   <news:publication_date>2026-06-15T17:46:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701034</loc>
  <lastmod>2026-06-15T16:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化パッケージによるサブグループ同定 (Subgroup Identification Using the personalized Package)</news:title>
   <news:publication_date>2026-06-15T16:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701032</loc>
  <lastmod>2026-06-15T16:55:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗号化データのインテリジェント処理のための安全なフレーズ検索（Secure Phrase Search for Intelligent Processing of Encrypted Data in Cloud-Based IoT）</news:title>
   <news:publication_date>2026-06-15T16:55:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701030</loc>
  <lastmod>2026-06-15T16:54:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転のための自動規則学習（Automatic Rule Learning for Autonomous Driving Using Semantic Memory）</news:title>
   <news:publication_date>2026-06-15T16:54:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701028</loc>
  <lastmod>2026-06-15T16:53:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化されたニューラル設計に向けて（Towards automated neural design: An open source, distributed neural architecture research framework）</news:title>
   <news:publication_date>2026-06-15T16:53:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701026</loc>
  <lastmod>2026-06-15T16:53:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LaSOT: 大規模単一対象トラッキングの高品質ベンチマーク（LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking）</news:title>
   <news:publication_date>2026-06-15T16:53:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701024</loc>
  <lastmod>2026-06-15T16:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KMTNet DEEP-South による新規時間変動検出向け光度パイプラインの構築（NEW PHOTOMETRIC PIPELINE TO EXPLORE TEMPORAL AND SPATIAL VARIABILITY WITH KMTNET DEEP-SOUTH OBSERVATIONS）</news:title>
   <news:publication_date>2026-06-15T16:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701022</loc>
  <lastmod>2026-06-15T16:52:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モジュール式メタラーニングで素早く計画を学ぶ（Learning Quickly to Plan Quickly Using Modular Meta-Learning）</news:title>
   <news:publication_date>2026-06-15T16:52:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701020</loc>
  <lastmod>2026-06-15T16:01:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IntelligentCrowdによるモバイルクラウドセンシング（IntelligentCrowd: Mobile Crowdsensing via Multi-Agent Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-15T16:01:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701018</loc>
  <lastmod>2026-06-15T16:01:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMを用いたささやき音声検出の実用化（LSTM-BASED WHISPER DETECTION）</news:title>
   <news:publication_date>2026-06-15T16:01:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701016</loc>
  <lastmod>2026-06-15T16:00:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活動データを用いたRNNによる肥満状態予測（Recurrent Neural Networks based Obesity Status Prediction Using Activity Data）</news:title>
   <news:publication_date>2026-06-15T16:00:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701014</loc>
  <lastmod>2026-06-15T16:00:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>論理制約付きニューラルFitted Q反復法（Logically-Constrained Neural Fitted Q-iteration）</news:title>
   <news:publication_date>2026-06-15T16:00:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701012</loc>
  <lastmod>2026-06-15T15:59:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層ネットワークに対する改良型ディープ埋め込みによる推論（Improved Deep Embeddings for Inferencing with Multi-Layered Networks）</news:title>
   <news:publication_date>2026-06-15T15:59:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701010</loc>
  <lastmod>2026-06-15T15:59:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音素知覚のための距離学習（Metric learning for phoneme perception）</news:title>
   <news:publication_date>2026-06-15T15:59:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701008</loc>
  <lastmod>2026-06-15T15:59:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動で流体の「小さなモデル」を作る新手法（Non-intrusive inference reduced order model for fluids using linear multistep neural network）</news:title>
   <news:publication_date>2026-06-15T15:59:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701006</loc>
  <lastmod>2026-06-15T15:07:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォルナクス矮小楕円銀河の構造解析（THE MORPHOLOGY AND STRUCTURE OF STELLAR POPULATIONS IN THE FORNAX DWARF SPHEROIDAL GALAXY FROM DARK ENERGY SURVEY DATA）</news:title>
   <news:publication_date>2026-06-15T15:07:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701004</loc>
  <lastmod>2026-06-15T14:57:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的深層強化学習における動的重み（Dynamic Weights in Multi-Objective Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-15T14:57:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701002</loc>
  <lastmod>2026-06-15T14:57:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>普遍的敵対的摂動のゲーム的学習（Playing the Game of Universal Adversarial Perturbations）</news:title>
   <news:publication_date>2026-06-15T14:57:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701000</loc>
  <lastmod>2026-06-15T14:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応分離畳み込みを用いた映像フレーム補間の実装（Implementing Adaptive Separable Convolution for Video Frame Interpolation）</news:title>
   <news:publication_date>2026-06-15T14:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700998</loc>
  <lastmod>2026-06-15T14:56:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スプラインに基づく確率キャリブレーション（Spline-Based Probability Calibration）</news:title>
   <news:publication_date>2026-06-15T14:56:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700996</loc>
  <lastmod>2026-06-15T14:56:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PriPeARL: プライバシー保護型アナリティクスの実務フレームワーク（PriPeARL: A Framework for Privacy-Preserving Analytics and Reporting at LinkedIn）</news:title>
   <news:publication_date>2026-06-15T14:56:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700994</loc>
  <lastmod>2026-06-15T14:56:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点別に分類して学習する脳腫瘍セグメンテーション（Brain Tumor Segmentation Using Deep Learning by Type Specific Sorting of Images）</news:title>
   <news:publication_date>2026-06-15T14:56:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700992</loc>
  <lastmod>2026-06-15T14:05:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抽出例に基づく地質画像合成とカーネル差異を用いた生成ニューラルネットワーク（Exemplar-based synthesis of geology using kernel discrepancies and generative neural networks）</news:title>
   <news:publication_date>2026-06-15T14:05:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700990</loc>
  <lastmod>2026-06-15T14:04:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実ロボットでの強化学習ベンチマーク（Benchmarking Reinforcement Learning Algorithms on Real-World Robots）</news:title>
   <news:publication_date>2026-06-15T14:04:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700988</loc>
  <lastmod>2026-06-15T14:04:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元偏微分方程式に対する深層ニューラルネットワークの表現率解析（DNN Expression Rate Analysis of High-dimensional PDEs: Application to Option Pricing）</news:title>
   <news:publication_date>2026-06-15T14:04:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700986</loc>
  <lastmod>2026-06-15T14:04:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語に基づく視覚言語学習で得られた教訓（Lessons learned in multilingual grounded language learning）</news:title>
   <news:publication_date>2026-06-15T14:04:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700984</loc>
  <lastmod>2026-06-15T14:03:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元脳における小さな神経アンサンブルの驚異的有効性（The unreasonable effectiveness of small neural ensembles in high-dimensional brain）</news:title>
   <news:publication_date>2026-06-15T14:03:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700982</loc>
  <lastmod>2026-06-15T14:03:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>化学機械学習における高速かつ高精度な不確かさ推定（Fast and Accurate Uncertainty Estimation in Chemical Machine Learning）</news:title>
   <news:publication_date>2026-06-15T14:03:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700980</loc>
  <lastmod>2026-06-15T14:03:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン評価で「危険な回答」を検出するニューラルネットワーク手法（Neural network approach to classifying alarming student responses to online assessment）</news:title>
   <news:publication_date>2026-06-15T14:03:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700978</loc>
  <lastmod>2026-06-15T13:12:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ConvPathが変える病理画像の定量化と予後予測（ConvPath: A Software Tool for Lung Adenocarcinoma Digital Pathological Image Analysis Aided by Convolutional Neural Network）</news:title>
   <news:publication_date>2026-06-15T13:12:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700976</loc>
  <lastmod>2026-06-15T13:12:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半線形偏微分方程式に対する機械学習（Machine Learning for Semi-Linear PDEs）</news:title>
   <news:publication_date>2026-06-15T13:12:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700974</loc>
  <lastmod>2026-06-15T13:11:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明るい高赤方偏移銀河候補の発見—79視線にわたるBoRG[z9]調査の要点（The bright-end galaxy candidates at z ∼9 from 79 independent HST fields）</news:title>
   <news:publication_date>2026-06-15T13:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700972</loc>
  <lastmod>2026-06-15T13:10:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル不足下の深層ドメイン適応（Deep Domain Adaptation under Deep Label Scarcity）</news:title>
   <news:publication_date>2026-06-15T13:10:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700970</loc>
  <lastmod>2026-06-15T13:10:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリを併用した勾配の疎化によるSGD高速化（Sparsified SGD with Memory）</news:title>
   <news:publication_date>2026-06-15T13:10:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700968</loc>
  <lastmod>2026-06-15T13:10:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像時系列分類のためのデュアルビュー深層学習（DuPLO: A DUal view Point deep Learning architecture for time series classiﬁcatiOn）</news:title>
   <news:publication_date>2026-06-15T13:10:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700966</loc>
  <lastmod>2026-06-15T13:10:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MIDI-VAEによる音楽の様式転送とダイナミクス制御（MIDI-VAE: Modeling Dynamics and Instrumentation of Music with Applications to Style Transfer）</news:title>
   <news:publication_date>2026-06-15T13:10:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700964</loc>
  <lastmod>2026-06-15T12:18:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列に対するU‑Netを用いた人間行動認識（Human activity recognition based on time series analysis using U‑Net）</news:title>
   <news:publication_date>2026-06-15T12:18:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700962</loc>
  <lastmod>2026-06-15T12:10:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボリック音楽のジャンル変換を実現するCycleGANの応用（Symbolic Music Genre Transfer with CycleGAN）</news:title>
   <news:publication_date>2026-06-15T12:10:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700960</loc>
  <lastmod>2026-06-15T12:10:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速かつ高精度な顔検出・識別・照合の統合パイプライン（A Fast and Accurate System for Face Detection, Identification, and Verification）</news:title>
   <news:publication_date>2026-06-15T12:10:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700958</loc>
  <lastmod>2026-06-15T12:09:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有毒コメント分類における課題と誤分類分析（Challenges for Toxic Comment Classification: An In-Depth Error Analysis）</news:title>
   <news:publication_date>2026-06-15T12:09:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700956</loc>
  <lastmod>2026-06-15T12:09:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的物体を除去して静的な風景を再構築する技術（Empty Cities: Image Inpainting for a Dynamic-Object-Invariant Space）</news:title>
   <news:publication_date>2026-06-15T12:09:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700954</loc>
  <lastmod>2026-06-15T12:08:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習のための効率的かつ安全なデータ配送手法（Towards Efficient and Secure Delivery of Data for Deep Learning with Privacy-Preserving）</news:title>
   <news:publication_date>2026-06-15T12:08:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700952</loc>
  <lastmod>2026-06-15T12:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の記述から一枚の高品質画像を作る技術（C4Synth: Cross-Caption Cycle-Consistent Text-to-Image Synthesis）</news:title>
   <news:publication_date>2026-06-15T12:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700950</loc>
  <lastmod>2026-06-15T11:17:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>支配的前景オブジェクトのモデル非依存検出（MASON: A Model AgnoStic ObjectNess Framework）</news:title>
   <news:publication_date>2026-06-15T11:17:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700948</loc>
  <lastmod>2026-06-15T11:16:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>工業用時系列データにおける機械学習ベース侵入検知（Time is of the Essence: Machine Learning-based Intrusion Detection in Industrial Time Series Data）</news:title>
   <news:publication_date>2026-06-15T11:16:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700946</loc>
  <lastmod>2026-06-15T11:16:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D LiDARスキャンの局所特徴記述子の学習（Learning a Local Feature Descriptor for 3D LiDAR Scans）</news:title>
   <news:publication_date>2026-06-15T11:16:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700944</loc>
  <lastmod>2026-06-15T11:15:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OxIOD: 深層慣性オドメトリのためのデータセット (OxIOD: The Dataset for Deep Inertial Odometry)</news:title>
   <news:publication_date>2026-06-15T11:15:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700942</loc>
  <lastmod>2026-06-15T11:15:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を取りこむ節（clause）表現で状況実体（Situation Entity）型を識別する手法（Building Context-aware Clause Representations for Situation Entity Type Classification）</news:title>
   <news:publication_date>2026-06-15T11:15:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700940</loc>
  <lastmod>2026-06-15T11:15:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遮蔽に強い混合パーティクルフィルタによる汎用車両追跡フレームワーク（Generic Vehicle Tracking Framework Capable of Handling Occlusions Based on Modified Mixture Particle Filter）</news:title>
   <news:publication_date>2026-06-15T11:15:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700938</loc>
  <lastmod>2026-06-15T11:14:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変長入力を扱うロボット学習のシムトゥリアル転移（Sim-to-Real Transfer of Robot Learning with Variable Length Inputs）</news:title>
   <news:publication_date>2026-06-15T11:14:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700936</loc>
  <lastmod>2026-06-15T10:23:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元における局所密度推定の効率化（Local Density Estimation in High Dimensions）</news:title>
   <news:publication_date>2026-06-15T10:23:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700934</loc>
  <lastmod>2026-06-15T10:23:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冪（べき）を通じて見る単項式イデアルと組合せ論の接点（Powers of Monomial Ideals and Combinatorics）</news:title>
   <news:publication_date>2026-06-15T10:23:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700932</loc>
  <lastmod>2026-06-15T10:22:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイヤレス分散コンピューティングにおけるデータシャッフルを低ランク最適化で解く（Data Shufﬂing in Wireless Distributed Computing via Low-Rank Optimization）</news:title>
   <news:publication_date>2026-06-15T10:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700930</loc>
  <lastmod>2026-06-15T10:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック画像セグメンテーションの最近の進展（Recent progress in semantic image segmentation）</news:title>
   <news:publication_date>2026-06-15T10:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700928</loc>
  <lastmod>2026-06-15T10:22:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Conv-TasNetによる時間領域スピーチ分離の革新（Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation）</news:title>
   <news:publication_date>2026-06-15T10:22:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700926</loc>
  <lastmod>2026-06-15T10:22:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリオーバーヘッドゼロの高性能直接畳み込み（High Performance Zero-Memory Overhead Direct Convolutions）</news:title>
   <news:publication_date>2026-06-15T10:22:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700924</loc>
  <lastmod>2026-06-15T10:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>年齢推定のための結合進化ネットワーク（A Coupled Evolutionary Network for Age Estimation）</news:title>
   <news:publication_date>2026-06-15T10:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700922</loc>
  <lastmod>2026-06-15T09:30:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像による胸部疾患診断のための深層生成分類器（Deep Generative Classifiers for Thoracic Disease Diagnosis with Chest X-ray Images）</news:title>
   <news:publication_date>2026-06-15T09:30:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700920</loc>
  <lastmod>2026-06-15T09:29:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Distribution Networks for Open Set Learning（Distribution Networks for Open Set Learning）</news:title>
   <news:publication_date>2026-06-15T09:29:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700918</loc>
  <lastmod>2026-06-15T09:29:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間差学習による周期性予測（Predicting Periodicity with Temporal Difference Learning）</news:title>
   <news:publication_date>2026-06-15T09:29:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700916</loc>
  <lastmod>2026-06-15T09:29:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形状ペアから学ぶ可動部の自動推定（Deep Part Induction from Articulated Object Pairs）</news:title>
   <news:publication_date>2026-06-15T09:29:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700914</loc>
  <lastmod>2026-06-15T09:29:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>矮小銀河を通じた宇宙論の検証（Dwarf Galaxies as Cosmological Probes）</news:title>
   <news:publication_date>2026-06-15T09:29:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700912</loc>
  <lastmod>2026-06-15T09:28:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ranking Distillation：推薦システム向け高性能な小型ランキングモデルの学習（Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System）</news:title>
   <news:publication_date>2026-06-15T09:28:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700910</loc>
  <lastmod>2026-06-15T09:28:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人化Top-N時系列推薦のための畳み込み系列埋め込み（Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding）</news:title>
   <news:publication_date>2026-06-15T09:28:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700908</loc>
  <lastmod>2026-06-15T08:37:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WiFi信号で室内の「つながり」を描く技術（Distances for WiFi Based Topological Indoor Mapping）</news:title>
   <news:publication_date>2026-06-15T08:37:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700906</loc>
  <lastmod>2026-06-15T08:36:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wikipediaと衛星画像で学ぶ衛星画像解釈（Learning to Interpret Satellite Images Using Wikipedia）</news:title>
   <news:publication_date>2026-06-15T08:36:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700904</loc>
  <lastmod>2026-06-15T08:36:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一統合型ニューラル事象推論アーキテクチャにおける学習・計画・制御（Learning, Planning, and Control in a Monolithic Neural Event Inference Architecture）</news:title>
   <news:publication_date>2026-06-15T08:36:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700902</loc>
  <lastmod>2026-06-15T08:35:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>西部米国におけるサブシーズナル予測の改善と機械学習の活用（Improving Subseasonal Forecasting in the Western U.S. with Machine Learning）</news:title>
   <news:publication_date>2026-06-15T08:35:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700900</loc>
  <lastmod>2026-06-15T08:35:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの形式安全性解析を急速に実現する技術（Efficient Formal Safety Analysis of Neural Networks）</news:title>
   <news:publication_date>2026-06-15T08:35:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700898</loc>
  <lastmod>2026-06-15T08:35:15Z</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汎化特性の解析（Identifying Generalization Properties in Neural Networks）</news:title>
   <news:publication_date>2026-06-15T08:35:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700896</loc>
  <lastmod>2026-06-15T08:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散ナッシュ均衡探索の収束理論と加速手法（Geometric Convergence of Gradient Play Algorithms for Distributed Nash Equilibrium Seeking）</news:title>
   <news:publication_date>2026-06-15T08:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700894</loc>
  <lastmod>2026-06-15T07:42:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>盲（ブラインド）音声減響におけるダイバージェンス切り替え（Switching divergences for spectral learning in blind speech dereverberation）</news:title>
   <news:publication_date>2026-06-15T07:42:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700892</loc>
  <lastmod>2026-06-15T07:42:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>auditorパッケージによるモデル非依存の可視化検証 (auditor: an R Package for Model-Agnostic Visual Validation and Diagnostics)</news:title>
   <news:publication_date>2026-06-15T07:42:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700890</loc>
  <lastmod>2026-06-15T07:42:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>消費者向け単一チャネルEEGでのSSVEPとその振幅変調の検出強化（A Single-Channel Consumer-Grade EEG Device for Brain-Computer Interface: Enhancing Detection of SSVEP and Its Amplitude Modulation）</news:title>
   <news:publication_date>2026-06-15T07:42:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700888</loc>
  <lastmod>2026-06-15T07:41:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ビデオからの物体マイニング（Towards Large-Scale Video Object Mining）</news:title>
   <news:publication_date>2026-06-15T07:41:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700886</loc>
  <lastmod>2026-06-15T07:41:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習で加速するフラッシュ計算（Accelerating Flash Calculation through Deep Learning Methods）</news:title>
   <news:publication_date>2026-06-15T07:41:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700884</loc>
  <lastmod>2026-06-15T07:41:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元偏微分方程式をニューラルネットが現実的に解く（A proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant diffusion and nonlinear drift coefficients）</news:title>
   <news:publication_date>2026-06-15T07:41:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700882</loc>
  <lastmod>2026-06-15T07:41:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒルベルト空間値関数の一般化リプレゼンター定理 (A Generalized Representer Theorem for Hilbert Space-Valued Functions)</news:title>
   <news:publication_date>2026-06-15T07:41:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700880</loc>
  <lastmod>2026-06-15T06:50:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>γ-Ψ次元に関する組合せ的・構造的結果（Combinatorial and Structural Results for γ-Ψ-dimensions）</news:title>
   <news:publication_date>2026-06-15T06:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700878</loc>
  <lastmod>2026-06-15T06:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像における生成敵対ネットワークの総覧（Generative Adversarial Network in Medical Imaging: A Review）</news:title>
   <news:publication_date>2026-06-15T06:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700876</loc>
  <lastmod>2026-06-15T06:49:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CPU負荷の高い反応移流モデルのエミュレーション比較（Emulation of CPU-demanding reactive transport models: comparison of Gaussian processes, polynomial chaos expansion and deep neural networks）</news:title>
   <news:publication_date>2026-06-15T06:49:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700874</loc>
  <lastmod>2026-06-15T06:48:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声と歌詞に基づく音楽ムード検出（Music mood detection based on audio and lyrics with Deep Neural Net）</news:title>
   <news:publication_date>2026-06-15T06:48:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700872</loc>
  <lastmod>2026-06-15T06:48:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストニューロンの解釈可能な表現法（Interpretable Textual Neuron Representations for NLP）</news:title>
   <news:publication_date>2026-06-15T06:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700870</loc>
  <lastmod>2026-06-15T06:48:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スレッド構造を利用した分散トピックモデル（Modeling Online Discourse with Coupled Distributed Topics）</news:title>
   <news:publication_date>2026-06-15T06:48:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700868</loc>
  <lastmod>2026-06-15T06:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク割当問題へのゲーム理論的アプローチ（A game theoretic approach to a network allocation problem）</news:title>
   <news:publication_date>2026-06-15T06:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700866</loc>
  <lastmod>2026-06-15T05:57:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数最適化に形状事前情報を組み込むベイズ最適化（Bayesian functional optimisation with shape prior）</news:title>
   <news:publication_date>2026-06-15T05:57:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700864</loc>
  <lastmod>2026-06-15T05:47:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>倉庫におけるマルチロボット自動化と効率的経路計画の改良（A Novel Warehouse Multi-Robot Automation System with Semi-Complete and Computationally Efficient Path Planning and Adaptive Genetic Task Allocation Algorithms）</news:title>
   <news:publication_date>2026-06-15T05:47:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700862</loc>
  <lastmod>2026-06-15T05:46:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DPPy: Pythonで扱う多様性サンプリングの実用ツール（DPPy: Sampling DPPs with Python）</news:title>
   <news:publication_date>2026-06-15T05:46:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700860</loc>
  <lastmod>2026-06-15T05:46:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ統計を知らなくても使えるロバスト回帰法の提案（Noise Statistics Oblivious GARD For Robust Regression With Sparse Outliers）</news:title>
   <news:publication_date>2026-06-15T05:46:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700858</loc>
  <lastmod>2026-06-15T05:45:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MTLE: マルチタスク学習による動画表現エンコーダの提案（MTLE: A Multitask Learning Encoder of Visual Feature Representations for Video and Movie Description）</news:title>
   <news:publication_date>2026-06-15T05:45:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700856</loc>
  <lastmod>2026-06-15T05:45:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列差分（Temporal Difference）強化学習の決定論的極限と多状態マルチエージェント環境への適用（Deterministic limit of temporal difference reinforcement learning for stochastic games）</news:title>
   <news:publication_date>2026-06-15T05:45:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700854</loc>
  <lastmod>2026-06-15T05:45:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声に基づく音楽ジャンルタグの曖昧性解消（Audio Based Disambiguation of Music Genre Tags）</news:title>
   <news:publication_date>2026-06-15T05:45:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700852</loc>
  <lastmod>2026-06-15T04:54:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタベースの自己学習フィードバック制御による乱流性ポストストール分離流の制御（Cluster-based feedback control of turbulent post-stall separated flows）</news:title>
   <news:publication_date>2026-06-15T04:54:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700850</loc>
  <lastmod>2026-06-15T04:53:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シアミーズ等変埋め込みによる単眼3D人間姿勢推定（3D Human Pose Estimation with Siamese Equivariant Embedding）</news:title>
   <news:publication_date>2026-06-15T04:53:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700848</loc>
  <lastmod>2026-06-15T04:53:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビットコインブロックチェーンから短期ボラティリティ指標を推定する（Inferring short-term volatility indicators from the Bitcoin blockchain）</news:title>
   <news:publication_date>2026-06-15T04:53:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700846</loc>
  <lastmod>2026-06-15T04:53:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リソース制約環境向けCNNの全段階最適化（Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-15T04:53:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700844</loc>
  <lastmod>2026-06-15T04:52:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>C4における形式的同値性の論点整理（Formal Equivalences in C4）</news:title>
   <news:publication_date>2026-06-15T04:52:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700842</loc>
  <lastmod>2026-06-15T04:52:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>爆発的核合成の現在地（Explosive Nucleosynthesis: What we learned and what we still do not understand）</news:title>
   <news:publication_date>2026-06-15T04:52:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700840</loc>
  <lastmod>2026-06-15T04:52:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短距離センサとオドメトリから自己教師ありで長距離認識を学ぶ（Learning Long-Range Perception Using Self-Supervision from Short-Range Sensors and Odometry）</news:title>
   <news:publication_date>2026-06-15T04:52:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/700838</loc>
  <lastmod>2026-06-15T04:01:36Z</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>2026-06-15T04:01:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700836</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>基底経路ノルムによるReLUニューラルネットワークの容量制御 (Capacity Control of ReLU Neural Networks by Basis-path Norm)</news:title>
   <news:publication_date>2026-06-15T04:00:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700834</loc>
  <lastmod>2026-06-15T04:00:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ハイブリッド散乱画像学の実験的示唆（Deep Hybrid Scattering Image Learning）</news:title>
   <news:publication_date>2026-06-15T04:00:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700832</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>InfoSSM: 多モード動力学を解釈可能に学習する非パラメトリック状態空間モデル（InfoSSM: Interpretable Unsupervised Learning of Nonparametric State-Space Model for Multi-modal Dynamics）</news:title>
   <news:publication_date>2026-06-15T03:59:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700830</loc>
  <lastmod>2026-06-15T03:59:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>早産児の脳年齢を直接推定する統一的ベイズ手法（A unifying Bayesian approach for preterm ‘brain-age’ prediction that models EEG sleep transitions over age）</news:title>
   <news:publication_date>2026-06-15T03:59:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700828</loc>
  <lastmod>2026-06-15T03:59:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配感受性損失を用いた二方向再構成ネットワークによる画像超解像（Dual Reconstruction Nets for Image Super-Resolution with Gradient Sensitive Loss）</news:title>
   <news:publication_date>2026-06-15T03:59:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700826</loc>
  <lastmod>2026-06-15T03:58:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限月オーダーブックで中間価格を予測する機械学習手法（Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data）</news:title>
   <news:publication_date>2026-06-15T03:58:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700824</loc>
  <lastmod>2026-06-15T03:07:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Novelty-Organizing Team of Classifiersの実践的意義（Novelty-Organizing Team of Classifiers in Noisy and Dynamic Environments）</news:title>
   <news:publication_date>2026-06-15T03:07:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700822</loc>
  <lastmod>2026-06-15T03:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル以下の対象を数える技術が変える現場（Counting the uncountable: Deep semantic density estimation from space）</news:title>
   <news:publication_date>2026-06-15T03:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700820</loc>
  <lastmod>2026-06-15T03:06:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肋骨のセンターライン抽出とラベリング（Deep Learning Based Rib Centerline Extraction and Labeling）</news:title>
   <news:publication_date>2026-06-15T03:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700818</loc>
  <lastmod>2026-06-15T03:05:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マスクR-CNNの学習高速化をもたらす境界重視の工夫（Faster Training of Mask R-CNN by Focusing on Instance Boundaries）</news:title>
   <news:publication_date>2026-06-15T03:05:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700816</loc>
  <lastmod>2026-06-15T03:05:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>積み重なった物体の自律把持のためのマルチタスクCNN（A Multi-task Convolutional Neural Network for Autonomous Robotic Grasping in Object Stacking Scenes）</news:title>
   <news:publication_date>2026-06-15T03:05:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700814</loc>
  <lastmod>2026-06-15T03:05:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-15T03:05:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700812</loc>
  <lastmod>2026-06-15T03:04:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>耐性のあるマルチメディア推薦のための敵対的訓練（Adversarial Training Towards Robust Multimedia Recommender System）</news:title>
   <news:publication_date>2026-06-15T03:04:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700810</loc>
  <lastmod>2026-06-15T02:13:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アイテム類似性に注意を払うニューラル推薦モデル（NAIS: Neural Attentive Item Similarity Model for Recommendation）</news:title>
   <news:publication_date>2026-06-15T02:13:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700808</loc>
  <lastmod>2026-06-15T02:13:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓左心室の多スケール全畳み込みネットワークによるセグメンテーション（Multi-Scale Fully Convolutional Network for Cardiac Left Ventricle Segmentation）</news:title>
   <news:publication_date>2026-06-15T02:13:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700806</loc>
  <lastmod>2026-06-15T02:12:57Z</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>2026-06-15T02:12:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700804</loc>
  <lastmod>2026-06-15T02:12:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乱流混合層の多重スケール予測に向けた深層学習（Deep learning approach in multi-scale prediction of turbulent mixing-layer）</news:title>
   <news:publication_date>2026-06-15T02:12:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700802</loc>
  <lastmod>2026-06-15T02:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乗法的ノイズによる特徴相関効果の除去（Removing the Feature Correlation Effect of Multiplicative Noise）</news:title>
   <news:publication_date>2026-06-15T02:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700800</loc>
  <lastmod>2026-06-15T02:11:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群に対する敵対的生成の手法（Generating 3D Adversarial Point Clouds）</news:title>
   <news:publication_date>2026-06-15T02:11:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700798</loc>
  <lastmod>2026-06-15T02:11:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-15T02:11:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700796</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>混合変数データからの確率推定における固有中心性の応用（Using Eigencentrality to Estimate Joint, Conditional and Marginal Probabilities from Mixed-Variable Data: Method and Applications）</news:title>
   <news:publication_date>2026-06-15T01:20:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700794</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>Positive-Unlabeled分類における事前確率シフトと非対称誤り（Positive-Unlabeled Classification under Class Prior Shift and Asymmetric Error）</news:title>
   <news:publication_date>2026-06-15T01:20:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700792</loc>
  <lastmod>2026-06-15T01:19:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接触力を活かした把持学習（Leveraging Contact Forces for Learning to Grasp）</news:title>
   <news:publication_date>2026-06-15T01:19:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700790</loc>
  <lastmod>2026-06-15T01:19:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GwardarによるSDN保護の新視点（Gwardar: Towards Protecting a Software-Defined Network from Malicious Network Operating Systems）</news:title>
   <news:publication_date>2026-06-15T01:19:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700788</loc>
  <lastmod>2026-06-15T01:19:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な強化学習とアンサンブル手法（Interpretable Reinforcement Learning with Ensemble Methods）</news:title>
   <news:publication_date>2026-06-15T01:19:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700786</loc>
  <lastmod>2026-06-15T01:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ下における二重振り子ダイナミクスのマニフォールド整合（Aligning Manifolds of Double Pendulum Dynamics Under the Influence of Noise）</news:title>
   <news:publication_date>2026-06-15T01:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700784</loc>
  <lastmod>2026-06-15T01:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胎児先天性心疾患検出におけるディープラーニングの臨床的意義（Deep-learning models improve on community-level diagnosis for common congenital heart disease lesions）</news:title>
   <news:publication_date>2026-06-15T01:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700781</loc>
  <lastmod>2026-06-15T00:27:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベガ周辺の内側15AUにおける深い惑星探索（A Deep Search for Planets in the Inner 15 AU Around Vega）</news:title>
   <news:publication_date>2026-06-15T00:27:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700779</loc>
  <lastmod>2026-06-15T00:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型クラスタリングとパラメータ化されたLloyd族（Data-Driven Clustering via Parameterized Lloyd’s Families）</news:title>
   <news:publication_date>2026-06-15T00:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700777</loc>
  <lastmod>2026-06-15T00:18:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>距離行列の部分線形時間低ランク近似（Sublinear Time Low-Rank Approximation of Distance Matrices）</news:title>
   <news:publication_date>2026-06-15T00:18:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700775</loc>
  <lastmod>2026-06-15T00:18:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FastDeepIoTによるモバイル向けニューラルネット実行時間最適化（FastDeepIoT: Towards Understanding and Optimizing Neural Network Execution Time on Mobile and Embedded Devices）</news:title>
   <news:publication_date>2026-06-15T00:18:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700773</loc>
  <lastmod>2026-06-15T00:17:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ依存の暗黙的正則化による分散SGD（Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent）</news:title>
   <news:publication_date>2026-06-15T00:17:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700771</loc>
  <lastmod>2026-06-15T00:17:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>思春期の骨年齢評価に深層学習で挑む：エルボーX線とSauvegrain法の自動化（A Study on Deep Learning Based Sauvegrain Method for Measurement of Puberty Bone Age）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプル再重み付けを用いたマルチタスク学習による機械読解の改善（Multi-task Learning with Sample Re-weighting for Machine Reading Comprehension）</news:title>
   <news:publication_date>2026-06-15T00:16:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700767</loc>
  <lastmod>2026-06-14T23:25:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポリマーナノピラーにおけるせん断帯形成の構造的指標の同定（Identifying structural signatures of shear banding in polymer nanopillars）</news:title>
   <news:publication_date>2026-06-14T23:25:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700765</loc>
  <lastmod>2026-06-14T23:16:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チーム編成における探索と活用のトレードオフ（Exploration vs. Exploitation in Team Formation for Collaborative Work）</news:title>
   <news:publication_date>2026-06-14T23:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700763</loc>
  <lastmod>2026-06-14T23:15:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ba1−xNaxFe2As2における出現秩序の分光学的証拠（Spectral Evidence for Emergent Order in Ba1−xNaxFe2As2）</news:title>
   <news:publication_date>2026-06-14T23:15:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700761</loc>
  <lastmod>2026-06-14T23:15:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測的集合変数発見と深層ベイズモデル（Predictive Collective Variable Discovery with Deep Bayesian Models）</news:title>
   <news:publication_date>2026-06-14T23:15:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700759</loc>
  <lastmod>2026-06-14T23:14:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粘塑性流のモデリングへの機械学習の応用（Application of machine learning to viscoplastic flow modeling）</news:title>
   <news:publication_date>2026-06-14T23:14:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700757</loc>
  <lastmod>2026-06-14T23:14:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電力市場価格予測における深層学習（Power Market Price Forecasting via Deep Learning）</news:title>
   <news:publication_date>2026-06-14T23:14:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700755</loc>
  <lastmod>2026-06-14T23:14:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短発話に対する深層ボトルネック特徴を用いた言語識別（Language Identification with Deep Bottleneck Features）</news:title>
   <news:publication_date>2026-06-14T23:14:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700753</loc>
  <lastmod>2026-06-14T22:23:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダイバー追従アルゴリズムの効率と頑健性の両立（Towards a Generic Diver-Following Algorithm: Balancing Robustness and Efficiency in Deep Visual Detection）</news:title>
   <news:publication_date>2026-06-14T22:23:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700751</loc>
  <lastmod>2026-06-14T22:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの学習ダイナミクス（On the Learning Dynamics of Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-14T22:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700749</loc>
  <lastmod>2026-06-14T22:22:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-NNとスライディングウィンドウによるMNIST分類（MNIST Dataset Classification Utilizing k-NN Classifier with Modified Sliding-window Metric）</news:title>
   <news:publication_date>2026-06-14T22:22:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700747</loc>
  <lastmod>2026-06-14T22:21:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Labyrinth: 命令型制御フローを並列データフローへ編纂する技術（Labyrinth: Compiling Imperative Control Flow to Parallel Dataflows）</news:title>
   <news:publication_date>2026-06-14T22:21:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700745</loc>
  <lastmod>2026-06-14T22:21:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングモーメントの伝搬を解析する線形ホークスネットワーク（Propagation of spiking moments in linear Hawkes networks）</news:title>
   <news:publication_date>2026-06-14T22:21:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700743</loc>
  <lastmod>2026-06-14T22:21:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチアクセント音声認識を進化させる生徒–教師学習（ADVANCING MULTI-ACCENTED LSTM-CTC SPEECH RECOGNITION USING A DOMAIN SPECIFIC STUDENT-TEACHER LEARNING PARADIGM）</news:title>
   <news:publication_date>2026-06-14T22:21:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700741</loc>
  <lastmod>2026-06-14T22:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Albumentations：高速で柔軟な画像拡張（Albumentations: fast and flexible image augmentations）</news:title>
   <news:publication_date>2026-06-14T22:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700739</loc>
  <lastmod>2026-06-14T21:29:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張可能なNoCベースのニューロモルフィックハードウェアによる学習と推論（Scalable NoC-based Neuromorphic Hardware Learning and Inference）</news:title>
   <news:publication_date>2026-06-14T21:29:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700737</loc>
  <lastmod>2026-06-14T21:28:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的因果構造を推定するベイズ手法（A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks）</news:title>
   <news:publication_date>2026-06-14T21:28:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700735</loc>
  <lastmod>2026-06-14T21:28:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込みで冗長性とモデル劣化に立ち向かう（Fighting Redundancy and Model Decay with Embeddings）</news:title>
   <news:publication_date>2026-06-14T21:28:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700733</loc>
  <lastmod>2026-06-14T21:27:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸な論理断片による学習と推論の設計（On a Convex Logic Fragment for Learning and Reasoning）</news:title>
   <news:publication_date>2026-06-14T21:27:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700731</loc>
  <lastmod>2026-06-14T21:27:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BOPからBOSSへ、そしてその先へ：辞書ベース時系列分類の再考（From BOP to BOSS and Beyond: Time Series Classification with Dictionary Based Classifiers）</news:title>
   <news:publication_date>2026-06-14T21:27:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700729</loc>
  <lastmod>2026-06-14T21:27:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TeV–PeV帯ニュートリノ–核子断面積の測定（TeV-PeV neutrino-nucleon cross section measurement with 5 years of IceCube data）</news:title>
   <news:publication_date>2026-06-14T21:27:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700727</loc>
  <lastmod>2026-06-14T21:26:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二乗項測定からの非凸デミキシング（Nonconvex Demixing from Bilinear Measurements）</news:title>
   <news:publication_date>2026-06-14T21:26:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700725</loc>
  <lastmod>2026-06-14T20:35:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>製造プロセスの再構成可能な適応最適制御のための多目的強化学習（Multiobjective Reinforcement Learning for Reconfigurable Adaptive Optimal Control of Manufacturing Processes）</news:title>
   <news:publication_date>2026-06-14T20:35:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700723</loc>
  <lastmod>2026-06-14T20:35:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>名詞–名詞複合語の解釈における転移学習とマルチタスク学習（Transfer and Multi-Task Learning for Noun–Noun Compound Interpretation）</news:title>
   <news:publication_date>2026-06-14T20:35:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700721</loc>
  <lastmod>2026-06-14T20:35:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>区間に連続的に到達するよう条件付けされた安定過程（STABLE PROCESSES CONDITIONED TO HIT AN INTERVAL CONTINUOUSLY FROM THE OUTSIDE）</news:title>
   <news:publication_date>2026-06-14T20:35:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700719</loc>
  <lastmod>2026-06-14T20:34:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頻度非依存型単語表現（FRAGE: Frequency-Agnostic Word Representation）</news:title>
   <news:publication_date>2026-06-14T20:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700717</loc>
  <lastmod>2026-06-14T20:34:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノ光学における5つの全方位最適化手法の比較（Benchmarking five global optimization approaches for nano-optical shape optimization and parameter reconstruction）</news:title>
   <news:publication_date>2026-06-14T20:34:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700715</loc>
  <lastmod>2026-06-14T20:33:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値転帰に対するベイズ最適治療規程の推定（Estimating Bayesian Optimal Treatment Regimes for Dichotomous Outcomes using Observational Data）</news:title>
   <news:publication_date>2026-06-14T20:33:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700713</loc>
  <lastmod>2026-06-14T20:33:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続特徴量に強い回転フォレストの有効性（Is rotation forest the best classifier for problems with continuous features?）</news:title>
   <news:publication_date>2026-06-14T20:33:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700711</loc>
  <lastmod>2026-06-14T19:41:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復視覚刺激を用いた多尺度相対固有ファジーエントロピーによる片頭痛前兆検出（SSVEP-based multi-scale relative inherent fuzzy entropy for migraine detection）</news:title>
   <news:publication_date>2026-06-14T19:41:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700709</loc>
  <lastmod>2026-06-14T19:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非構造3Dメッシュ上での内在的対応学習の単純な手法（A Simple Approach to Intrinsic Correspondence Learning on Unstructured 3D Meshes）</news:title>
   <news:publication_date>2026-06-14T19:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700707</loc>
  <lastmod>2026-06-14T19:41:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性認識を組み込んだ顔老化とWavelet GAN（Attribute-aware Face Aging with Wavelet-based Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-14T19:41:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700705</loc>
  <lastmod>2026-06-14T19:40:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エピソディック固定ホライズン製造プロセスのモデルフリー最適制御（Model-Free Adaptive Optimal Control of Episodic Fixed-Horizon Manufacturing Processes using Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-14T19:40:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700703</loc>
  <lastmod>2026-06-14T19:40:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Additive Bayesian Networksにおける適切な事前分布の比較（Comparison between Suitable Priors for Additive Bayesian Networks）</news:title>
   <news:publication_date>2026-06-14T19:40:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700701</loc>
  <lastmod>2026-06-14T19:39:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きな横方向運動量でのトップ生成の精度向上（Top production at large pt at NLO+NLL accuracy）</news:title>
   <news:publication_date>2026-06-14T19:39:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700699</loc>
  <lastmod>2026-06-14T19:39:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模2次元トーリック符号に対するニューラルネットワークデコーダ（Neural Network Decoders for Large-Distance 2D Toric Codes）</news:title>
   <news:publication_date>2026-06-14T19:39:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700697</loc>
  <lastmod>2026-06-14T18:48:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実行時ニューロン活性パターンの監視（Runtime Monitoring Neuron Activation Patterns）</news:title>
   <news:publication_date>2026-06-14T18:48:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700695</loc>
  <lastmod>2026-06-14T18:43:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>改良型3DTV正則化とハイパースペクトル画像応用（Enhanced 3DTV Regularization and Its Applications on Hyper-spectral Image Denoising and Compressed Sensing）</news:title>
   <news:publication_date>2026-06-14T18:43:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/700693</loc>
  <lastmod>2026-06-14T18:43:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均-最大注意オートエンコーダによる普遍的な文表現学習 (Learning Universal Sentence Representations with Mean-Max Attention Autoencoder)</news:title>
   <news:publication_date>2026-06-14T18:43:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/700691</loc>
  <lastmod>2026-06-14T18:43:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SCC-rFMQによる連続行動協調学習（SCC-rFMQ Learning in Cooperative Markov Games with Continuous Actions）</news:title>
   <news:publication_date>2026-06-14T18:43:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/700689</loc>
  <lastmod>2026-06-14T18:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ空間ノイズによる等方性・方向性探索の切替（Switching Isotropic and Directional Exploration with Parameter Space Noise in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-14T18:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700687</loc>
  <lastmod>2026-06-14T18:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Macroblock ScalingによるCNNモデル圧縮の実務的インパクト（MBS: Macroblock Scaling for CNN Model Reduction）</news:title>
   <news:publication_date>2026-06-14T18:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700685</loc>
  <lastmod>2026-06-14T18:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAVによる水圧管検査のためのU-Net：多クラスセグメンテーションにおけるフォーカル損失の検討 (U-Net for MAV-based Penstock Inspection: an Investigation of Focal Loss in Multi-class Segmentation for Corrosion Identification)</news:title>
   <news:publication_date>2026-06-14T18:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700683</loc>
  <lastmod>2026-06-14T17:50:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像超解像の新アプローチ：決定論的–確率的合成と局所統計補正（Image Super-Resolution via Deterministic-Stochastic Synthesis and Local Statistical Rectification）</news:title>
   <news:publication_date>2026-06-14T17:50:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700681</loc>
  <lastmod>2026-06-14T17:49:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー情報を活用する意味フレーム解析の高速化と少データ化（User Information Augmented Semantic Frame Parsing using Coarse-to-Fine Neural Networks）</news:title>
   <news:publication_date>2026-06-14T17:49:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700679</loc>
  <lastmod>2026-06-14T17:48:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡な多相配電網のトポロジ推定とバス相同定（Unbalanced Multi-Phase Distribution Grid Topology Estimation and Bus Phase Identification）</news:title>
   <news:publication_date>2026-06-14T17:48:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700677</loc>
  <lastmod>2026-06-14T17:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人体のテクスチャ付き3D再構成（Deep Textured 3D Reconstruction of Human Bodies）</news:title>
   <news:publication_date>2026-06-14T17:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700675</loc>
  <lastmod>2026-06-14T17:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動計量フォワード・バックワード分割アルゴリズムの収束解析（Convergence analysis of a variable metric forward-backward splitting algorithm with applications）</news:title>
   <news:publication_date>2026-06-14T17:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700673</loc>
  <lastmod>2026-06-14T17:48:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転のためのマルチモーダル軌道予測（Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks）</news:title>
   <news:publication_date>2026-06-14T17:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700671</loc>
  <lastmod>2026-06-14T17:47:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル保護型マルチタスク学習の要点（Model-Protected Multi-Task Learning）</news:title>
   <news:publication_date>2026-06-14T17:47:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700669</loc>
  <lastmod>2026-06-14T16:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形分類における実行可能な救済手段（Actionable Recourse in Linear Classification）</news:title>
   <news:publication_date>2026-06-14T16:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700667</loc>
  <lastmod>2026-06-14T16:56:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータレス確率的自然勾配法による離散最適化とニューラルネットワークのハイパーパラメータ最適化（Parameterless Stochastic Natural Gradient Method for Discrete Optimization）</news:title>
   <news:publication_date>2026-06-14T16:56:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700665</loc>
  <lastmod>2026-06-14T16:56:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大の光学応答を求めて：2次元材料の可能性（In Pursuit of 2D Materials for Maximum Optical Response）</news:title>
   <news:publication_date>2026-06-14T16:56:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700663</loc>
  <lastmod>2026-06-14T16:55:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HashTran‑DNNによるマルウェア検出の堅牢化（HashTran‑DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples）</news:title>
   <news:publication_date>2026-06-14T16:55:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700661</loc>
  <lastmod>2026-06-14T16:55:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無熱ゆがみをPCAで読む：非晶質材料のせん断変形に潜む主成分（Correlations in the shear flow of athermal amorphous solids: A principal component analysis）</news:title>
   <news:publication_date>2026-06-14T16:55:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700659</loc>
  <lastmod>2026-06-14T16:54:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セッション内での個人化による人材検索の最前線（In-Session Personalization for Talent Search）</news:title>
   <news:publication_date>2026-06-14T16:54:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700657</loc>
  <lastmod>2026-06-14T16:54:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層化乱流の“二つの原子”から学ぶ深層学習による混合効率予測（Deep learning of mixing by two ‘atoms’ of stratified turbulence）</news:title>
   <news:publication_date>2026-06-14T16:54:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700655</loc>
  <lastmod>2026-06-14T16:03:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LinkedInにおけるタレント検索と推薦の実務課題（Talent Search and Recommendation Systems at LinkedIn: Practical Challenges and Lessons Learned）</news:title>
   <news:publication_date>2026-06-14T16:03:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700653</loc>
  <lastmod>2026-06-14T16:02:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロ次元非凸確率的最適化の扱い（Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality and Saddle-Points）</news:title>
   <news:publication_date>2026-06-14T16:02:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700651</loc>
  <lastmod>2026-06-14T16:02:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンサンブルによる能動異常検知の実務的意義（Active Anomaly Detection via Ensembles）</news:title>
   <news:publication_date>2026-06-14T16:02:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700649</loc>
  <lastmod>2026-06-14T16:01:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タレントサーチにおける深層表現学習の実装と示唆（Towards Deep and Representation Learning for Talent Search at LinkedIn）</news:title>
   <news:publication_date>2026-06-14T16:01:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700647</loc>
  <lastmod>2026-06-14T16:01:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ推論とガウス過程の堅牢性保証（Robustness Guarantees for Bayesian Inference with Gaussian Processes）</news:title>
   <news:publication_date>2026-06-14T16:01:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700645</loc>
  <lastmod>2026-06-14T16:01:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己構成による機械学習の層別訓練法（Self-Configuration in Machine Learning）</news:title>
   <news:publication_date>2026-06-14T16:01:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700643</loc>
  <lastmod>2026-06-14T16:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mask Editor：不規則形状のための画像マスク編集ツール（Mask Editor : an Image Annotation Tool for Image Segmentation Tasks）</news:title>
   <news:publication_date>2026-06-14T16:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700641</loc>
  <lastmod>2026-06-14T15:08:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラフレーズによる堅牢な音声言語理解（Robust Spoken Language Understanding via Paraphrasing）</news:title>
   <news:publication_date>2026-06-14T15:08:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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