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   <news:title>多峰性を狙い撃ちする探索基準の提案（Infill Criterion for Multimodal Model-Based Optimisation）</news:title>
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   <news:title>モンテカルロ依存性推定（Monte Carlo Dependency Estimation）</news:title>
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   <news:title>Zooming Networkが変える長文理解の効率化（Zooming Network）</news:title>
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   <news:title>胸部X線画像における解剖学的構造のセグメンテーション改善（Improving the Segmentation of Anatomical Structures in Chest Radiographs using U-Net with an ImageNet Pre-trained Encoder）</news:title>
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   <news:title>ドメイン外依存構文解析のための半教師あり手法（SEMI-SUPERVISED METHODS FOR OUT-OF-DOMAIN DEPENDENCY PARSING）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>マルチリンガルSeq2Seq音声認識の転移学習と言語モデルの効果（MULTILINGUAL SEQUENCE-TO-SEQUENCE SPEECH RECOGNITION: ARCHITECTURE, TRANSFER LEARNING, AND LANGUAGE MODELING）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>DeepNISによる非線形電磁逆散乱の新展開（DeepNIS: Deep Neural Network for Nonlinear Electromagnetic Inverse Scattering）</news:title>
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   <news:title>ドメイン間での物理運動転移によるニューラル慣性追跡（Transferring Physical Motion Between Domains for Neural Inertial Tracking）</news:title>
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   <news:title>グラフのグラフに対する二重畳み込みニューラルネットワーク（Dual Convolutional Neural Network for Graph of Graphs Link Prediction）</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>KMTNetによる低表面輝度撮像の最適戦略（KMTNET Nearby Galaxy Survey I: Optimal Strategy for Low Surface Brightness Imaging with KMTNet）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>生成的敵対的プライバシーの解法（Finding Solutions to Generative Adversarial Privacy）</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>FPGA上での高速かつ省電力な二値化ニューラルネットワーク推論（Towards Fast and Energy-Efficient Binarized Neural Network Inference on FPGA）</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>Leave-one-out LSMによるバーミューダンオプション価格の見直し（Leave-one-out least squares Monte Carlo algorithm for pricing Bermudan options）</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>画像→動画人物再識別におけるクロスモーダル埋め込みの再利用（Image-to-Video Person Re-Identification by Reusing Cross-modal Embeddings）</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>弱凸–凹ミンマックス最適化とその応用（Weakly-Convex Concave Min-Max Optimization）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-20T00:51:11Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>過学習ではなく過パラメータ化が最適化を簡単にする（GRADIENT DESCENT PROVABLY OPTIMIZES OVER-PARAMETERIZED NEURAL NETWORKS）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-20T00:50:58Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>双方向LSTMとメッシュ畳み込みによる3Dメッシュアニメーション生成（Learning Bidirectional LSTM Networks for Synthesizing 3D Mesh Animation Sequences）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T23:59:39Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ロバスト推定と敵対的生成ネットワーク（Robust Estimation and Generative Adversarial Nets）</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>層が揃うと学習が進む──深層線形ネットワークにおける勾配法の暗黙の正則化（Gradient descent aligns the layers of deep linear networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T23:58:47Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>偏極座標に基づく深層構造による変調分類とチャネル補償（Polar Feature Based Deep Architectures for Automatic Modulation Classification Considering Channel Fading）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T23:58:18Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>DGAドメイン検出とサイド情報を用いた手法（Detecting DGA domains with recurrent neural networks and side information）</news:title>
   <news:publication_date>2026-06-19T23:58:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>期待値最大化（EM）アルゴリズムの収束解析を離散時間リヤプノフ安定性で捉える（Convergence of the Expectation-Maximization Algorithm Through Discrete-Time Lyapunov Stability Theory）</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>データ拡張を用いた転移増分学習（Transfer Incremental Learning using Data Augmentation）</news:title>
   <news:publication_date>2026-06-19T23:57:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T23:57:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>スレート最適化と再ランキングをRNNで実現するSeq2Slate（Seq2Slate: Re-ranking and Slate Optimization with RNNs）</news:title>
   <news:publication_date>2026-06-19T23:57:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T23:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Soft分類器からHard決定へ：公正性はどこまで達成できるか（From Soft Classifiers to Hard Decisions: How fair can we be?）</news:title>
   <news:publication_date>2026-06-19T23:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T23:06:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン特化近似による物体検出の高速化（Domain-Specific Approximation for Object Detection）</news:title>
   <news:publication_date>2026-06-19T23:06:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/702632</loc>
  <lastmod>2026-06-19T23:06:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四点置換検定による潜在ブロック構造の検出（The Four Point Permutation Test for Latent Block Structure in Incidence Matrices）</news:title>
   <news:publication_date>2026-06-19T23:06:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/702630</loc>
  <lastmod>2026-06-19T23:05:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMを用いた行動モデル獲得（Action Model Acquisition using LSTM）</news:title>
   <news:publication_date>2026-06-19T23:05:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T23:05:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>気候解析のためのエクサスケール深層学習（Exascale Deep Learning for Climate Analytics）</news:title>
   <news:publication_date>2026-06-19T23:05:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T23:05:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習とHybrid Zero Dynamicsの融合──RABBIT事例から学ぶ二足歩行制御（Reinforcement Learning Meets Hybrid Zero Dynamics: A Case Study for RABBIT）</news:title>
   <news:publication_date>2026-06-19T23:05:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-19T23:04:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像と符号化テキストの融合によるマルチモーダル分類（Image and Encoded Text Fusion for Multi-Modal Classification）</news:title>
   <news:publication_date>2026-06-19T23:04:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T22:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T22:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Transfer Learning via Unsupervised Task Discovery for Visual Question Answering（Transfer Learning via Unsupervised Task Discovery for Visual Question Answering）</news:title>
   <news:publication_date>2026-06-19T22:12:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カートポール問題に対する強化学習アルゴリズムの比較（Comparison of Reinforcement Learning Algorithms applied to the Cart-Pole Problem）</news:title>
   <news:publication_date>2026-06-19T22:11:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAWILabトレースから生成するラベル付きフローデータ（Generating Labeled Flow Data from MAWILab Traces for Network Intrusion Detection）</news:title>
   <news:publication_date>2026-06-19T22:11:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ処理クラスタのスケジューリングを学習する（Learning Scheduling Algorithms for Data Processing Clusters）</news:title>
   <news:publication_date>2026-06-19T22:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T21:19:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートグリッドにおける気象データを用いた停電予測のハイブリッド手法（Hybrid integration of multilayer perceptrons and parametric models for reliability forecasting in the smart grid）</news:title>
   <news:publication_date>2026-06-19T21:19:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-19T21:19:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンディット学習が示す競争下の安定性（BANDIT LEARNING IN CONCAVE N-PERSON GAMES）</news:title>
   <news:publication_date>2026-06-19T21:19:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702602</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T21:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法務文書向け感情判定を迅速に構築する手法（Fast Approach to Build an Automatic Sentiment Annotator for Legal Domain using Transfer Learning）</news:title>
   <news:publication_date>2026-06-19T21:17:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702594</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>作業指向の手運動リターゲティングによる巧緻な操作模倣（Task-Oriented Hand Motion Retargeting for Dexterous Manipulation Imitation）</news:title>
   <news:publication_date>2026-06-19T20:26:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前定義した類似度に基づくkクラスタ数の最適決定（Determining Optimal Number of k-Clusters based on Predefined Level-of-Similarity）</news:title>
   <news:publication_date>2026-06-19T20:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702590</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>重み正規化された深層ニューラルネットワークの理解（Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units）</news:title>
   <news:publication_date>2026-06-19T20:25:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702588</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T20:24:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702586</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>重なりを扱うニューラルセグメンタルハイパーグラフ（Neural Segmental Hypergraphs for Overlapping Mention Recognition）</news:title>
   <news:publication_date>2026-06-19T20:24:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702584</loc>
  <lastmod>2026-06-19T20:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像超解像におけるチャネル再校正の威力（An Effective Single-Image Super-Resolution Model Using Squeeze-and-Excitation Networks）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702582</loc>
  <lastmod>2026-06-19T20:24:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間中心の自動運転システム：効果的な共有自律の原則（Human-Centered Autonomous Vehicle Systems: Principles of Effective Shared Autonomy）</news:title>
   <news:publication_date>2026-06-19T20:24:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702580</loc>
  <lastmod>2026-06-19T19:32:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T19:32:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702578</loc>
  <lastmod>2026-06-19T19:32:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ASTに基づく深層学習による悪性PowerShell検出（AST-Based Deep Learning for Detecting Malicious PowerShell）</news:title>
   <news:publication_date>2026-06-19T19:32:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702576</loc>
  <lastmod>2026-06-19T19:32:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルにおける「スプリアス（偽）サンプル」は欠陥か、機能か（Spurious samples in deep generative models: bug or feature?）</news:title>
   <news:publication_date>2026-06-19T19:32:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702574</loc>
  <lastmod>2026-06-19T19:31:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一意的な森の因数分解（Unambiguous Forest Factorization）</news:title>
   <news:publication_date>2026-06-19T19:31:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702572</loc>
  <lastmod>2026-06-19T19:31:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>McTorch：PyTorchのための多様体最適化ライブラリ（McTorch, a manifold optimization library for deep learning）</news:title>
   <news:publication_date>2026-06-19T19:31:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702570</loc>
  <lastmod>2026-06-19T19:31:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネストしたメンション認識の遷移基礎モデル（A Neural Transition-based Model for Nested Mention Recognition）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702568</loc>
  <lastmod>2026-06-19T19:30:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声に基づくアーティスト識別の拡張（Disambiguating Music Artists at Scale with Audio Metric Learning）</news:title>
   <news:publication_date>2026-06-19T19:30:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702566</loc>
  <lastmod>2026-06-19T18:39:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散化ニューラルネットワークのためのRelaxed Quantization（Relaxed Quantization for Discretized Neural Networks）</news:title>
   <news:publication_date>2026-06-19T18:39:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702564</loc>
  <lastmod>2026-06-19T18:39:28Z</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>2026-06-19T18:39:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702562</loc>
  <lastmod>2026-06-19T18:39:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工ニューラルネットワークの位相的探索（Topological exploration of artificial neuronal network dynamics）</news:title>
   <news:publication_date>2026-06-19T18:39:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702560</loc>
  <lastmod>2026-06-19T18:38:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサ運動的不変性から学ぶロボットの空間認識（Learning agent’s spatial configuration from sensorimotor invariants）</news:title>
   <news:publication_date>2026-06-19T18:38:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702558</loc>
  <lastmod>2026-06-19T18:38:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>店舗棚上の商品認識のための深層学習パイプライン（A deep learning pipeline for product recognition on store shelves）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702556</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>視覚野の体験をセンサリーモータの規則性で基礎づける（Grounding the Experience of a Visual Field through Sensorimotor Contingencies）</news:title>
   <news:publication_date>2026-06-19T18:38:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然勾配とヘシアンフリーの統合による系列訓練最適化（Combining Natural Gradient with Hessian Free Methods for Sequence Training）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>オンライン毒性検出の機械学習スイート（Machine Learning Suites for Online Toxicity Detection）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>新領域のNLU向けアクティブラーニング（Active Learning for New Domains in Natural Language Understanding）</news:title>
   <news:publication_date>2026-06-19T17:45:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アグノスティック回帰における有界サンプル圧縮の前進（Agnostic Sample Compression Schemes for Regression）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702534</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実稼働HPCクラスターにおける熱モデル同定の堅牢化とデータ選択（Robust identification of thermal models for in-production High-Performance-Computing clusters with machine learning-based data selection）</news:title>
   <news:publication_date>2026-06-19T16:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースによる完全自動の短軸心臓MRI層間動き補正法（A Comprehensive Approach for Learning-based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T16:44:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>扱いやすい経験的尤度を用いたABC法（An Easy-to-Use Empirical Likelihood ABC Method）</news:title>
   <news:publication_date>2026-06-19T16:44:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T16:44:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepImageSpam: 画像スパム検出における深層学習の実践（DeepImageSpam: Deep Learning based Image Spam Detection）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T15:51:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Inhibited Softmaxによる不確かさ推定の実践的解説（Inhibited Softmax for Uncertainty Estimation in Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極端なデータ拡張：手作業で一例だけラベル付けした医療画像で学習できるか（Extreme Augmentation: Can deep learning based medical image segmentation be trained using a single manually delineated scan?）</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>WARSHIPによる脳インスパイア型画像超解像の統合的枠組み（Towards WARSHIP: Combining Components of Brain-Inspired Computing of RSH for Image Super Resolution）</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>生成深層学習の理論 II：正則化に基づく容量制御で経験誤差の地形を探る（Theory of Generative Deep Learning II: Probe Landscape of Empirical Error via Norm Based Capacity Control）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的多孔弾性媒体の有効特性予測を加速する機械学習手法（Machine learning for accelerating effective property prediction for poroelasticity problem in stochastic media）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>RF電源バックスキャッタ認知無線ネットワークにおける時間割当ての深層強化学習（Deep Reinforcement Learning for Time Scheduling in RF-Powered Backscatter Cognitive Radio Networks）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-19T14:03:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>自動運転車向けディープラーニングベースのキャッシング（Deep Learning Based Caching for Self-Driving Cars in Multi-access Edge Computing）</news:title>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適ドメイン適応のための一般化ニーマン・ピアソン基準（A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation）</news:title>
   <news:publication_date>2026-06-19T13:10:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702478</loc>
  <lastmod>2026-06-19T13:10:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的プログラミング言語による自動化学習（Automated learning with a probabilistic programming language: Birch）</news:title>
   <news:publication_date>2026-06-19T13:10:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702476</loc>
  <lastmod>2026-06-19T13:08:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連結データで正しい推論を行う実用的アプローチ（A Practical Approach to Proper Inference with Linked Data）</news:title>
   <news:publication_date>2026-06-19T13:08:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702474</loc>
  <lastmod>2026-06-19T13:08:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの決定境界を可視化する手法（Geometric Illustration of Neural Networks）</news:title>
   <news:publication_date>2026-06-19T13:08:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702472</loc>
  <lastmod>2026-06-19T13:08:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変ソケット位置での挿入作業に対する現実的アプローチ（A Practical Approach to Insertion with Variable Socket Position）</news:title>
   <news:publication_date>2026-06-19T13:08:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702470</loc>
  <lastmod>2026-06-19T13:08:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デュアルバンドシステムにおけるバンド割当の学習的アプローチ（Band Assignment in Dual Band Systems: A Learning-based Approach）</news:title>
   <news:publication_date>2026-06-19T13:08:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702468</loc>
  <lastmod>2026-06-19T12:16:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンドロメダの巨大南方ストリームに沿った距離と金属量の勾配（Distance and Metallicity Gradients Along Andromeda’s Giant Southern Stream From the Red Clump）</news:title>
   <news:publication_date>2026-06-19T12:16:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702466</loc>
  <lastmod>2026-06-19T12:15:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CINIC-10データセットの意義（CINIC-10 Is Not ImageNet or CIFAR-10）</news:title>
   <news:publication_date>2026-06-19T12:15:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702464</loc>
  <lastmod>2026-06-19T12:15:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動プレイリスト補完の競技的検討──RecSys Challenge 2018の示した実務示唆（An Analysis of Approaches Taken in the ACM RecSys Challenge 2018 for Automatic Music Playlist Continuation）</news:title>
   <news:publication_date>2026-06-19T12:15:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702462</loc>
  <lastmod>2026-06-19T12:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練を要さない簡潔な画像表現としてのDeep Decoder（Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks）</news:title>
   <news:publication_date>2026-06-19T12:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702460</loc>
  <lastmod>2026-06-19T12:14:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブモジュラー最適化のMapReduceモデル（Submodular Optimization in the MapReduce Model）</news:title>
   <news:publication_date>2026-06-19T12:14:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702458</loc>
  <lastmod>2026-06-19T12:14:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的コミュニティ検出の再帰的分割法（Hierarchical community detection by recursive partitioning）</news:title>
   <news:publication_date>2026-06-19T12:14:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702456</loc>
  <lastmod>2026-06-19T12:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果的コンテクスチュアル多腕バンディットによるマーケティング最適化（Contextual Multi-Armed Bandits for Causal Marketing）</news:title>
   <news:publication_date>2026-06-19T12:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702454</loc>
  <lastmod>2026-06-19T11:23:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepCMBによるCMB重力レンズ復元と深層学習の応用（DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-19T11:23:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702452</loc>
  <lastmod>2026-06-19T11:22:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽レコメンドの多様化手法（Diversifying Music Recommendations）</news:title>
   <news:publication_date>2026-06-19T11:22:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702450</loc>
  <lastmod>2026-06-19T11:22:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘキソース結合の生化学的知見を検証する帰納的論理プログラミングの応用（An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge）</news:title>
   <news:publication_date>2026-06-19T11:22:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702448</loc>
  <lastmod>2026-06-19T11:21:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造に基づく多ラベル医療テキストタグ付け（Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding）</news:title>
   <news:publication_date>2026-06-19T11:21:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702446</loc>
  <lastmod>2026-06-19T11:21:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロシア系ツイッター操作の痕跡を無監督学習で解き明かす（Unsupervised Machine Learning of Open Source Russian Twitter Data Reveals Global Scope and Operational Characteristics）</news:title>
   <news:publication_date>2026-06-19T11:21:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702444</loc>
  <lastmod>2026-06-19T11:21:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力分割を学習するNMTが示す文字レベルの優位性（Learning to Segment Inputs for NMT）</news:title>
   <news:publication_date>2026-06-19T11:21:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702442</loc>
  <lastmod>2026-06-19T11:20:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的個別化による視覚的発見の多様化（Adaptive, Personalized Diversity for Visual Discovery）</news:title>
   <news:publication_date>2026-06-19T11:20:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702440</loc>
  <lastmod>2026-06-19T10:29:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動認識のための表現フロー（Representation Flow for Action Recognition）</news:title>
   <news:publication_date>2026-06-19T10:29:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702438</loc>
  <lastmod>2026-06-19T10:28:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き暗黙的最尤推定による超解像（Super-Resolution via Conditional Implicit Maximum Likelihood Estimation）</news:title>
   <news:publication_date>2026-06-19T10:28:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702436</loc>
  <lastmod>2026-06-19T10:28:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算的に実現可能な頑健学習は可能か（Can Adversarially Robust Learning Leverage Computational Hardness?）</news:title>
   <news:publication_date>2026-06-19T10:28:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702434</loc>
  <lastmod>2026-06-19T10:28:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GrAMME：マルチレイヤーグラフ注意モデルを用いた半教師あり学習（GrAMME: Semi-Supervised Learning using Multi-layered Graph Attention Models）</news:title>
   <news:publication_date>2026-06-19T10:28:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702432</loc>
  <lastmod>2026-06-19T10:28:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GLAD: 人間を巻き込むローカル重み付けによる異常検知の実務接続（GLAD: GLocalized Anomaly Detection via Human-in-the-Loop Learning）</news:title>
   <news:publication_date>2026-06-19T10:28:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702430</loc>
  <lastmod>2026-06-19T10:27:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適補完蒸留法（Optimal Completion Distillation）によるシーケンス学習の革新</news:title>
   <news:publication_date>2026-06-19T10:27:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702428</loc>
  <lastmod>2026-06-19T10:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在ディリクレ・カテゴリカルモデルのスケッチ手法 (Sketching for Latent Dirichlet-Categorical Models)</news:title>
   <news:publication_date>2026-06-19T10:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702426</loc>
  <lastmod>2026-06-19T09:36:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルのアンサンブルによる堅牢な異常検知（WAIC, but Why? Generative Ensembles for Robust Anomaly Detection）</news:title>
   <news:publication_date>2026-06-19T09:36:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702424</loc>
  <lastmod>2026-06-19T09:36:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習によるヒトプロモーター予測（PromID: human promoter prediction by deep learning）</news:title>
   <news:publication_date>2026-06-19T09:36:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702422</loc>
  <lastmod>2026-06-19T09:36:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散表現を用いた位相推定で音源分離の天井を押し上げる（Phasebook and Friends: Leveraging discrete representations for source separation）</news:title>
   <news:publication_date>2026-06-19T09:36:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702420</loc>
  <lastmod>2026-06-19T09:34:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポジティブメモリ保持による効率的対話ポリシー学習（EFFICIENT DIALOG POLICY LEARNING VIA POSITIVE MEMORY RETENTION）</news:title>
   <news:publication_date>2026-06-19T09:34:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702418</loc>
  <lastmod>2026-06-19T09:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半密度ステレオマッチングを実現する二重CNN（Semi-dense Stereo Matching using Dual CNNs）</news:title>
   <news:publication_date>2026-06-19T09:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702416</loc>
  <lastmod>2026-06-19T09:34:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FFJORD: 自由形式の連続ダイナミクスによるスケーラブルな可逆生成モデル（FFJORD: Free-Form Continuous Dynamics for Scalable Reversible Generative Models）</news:title>
   <news:publication_date>2026-06-19T09:34:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702414</loc>
  <lastmod>2026-06-19T09:34:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール畳み込みと確率的特徴再利用によるDenseNet改良（Multi-scale Convolution Aggregation and Stochastic Feature Reuse for DenseNets）</news:title>
   <news:publication_date>2026-06-19T09:34:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702412</loc>
  <lastmod>2026-06-19T08:43:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギーに基づくヒンドサイト経験優先化（Energy-Based Hindsight Experience Prioritization）</news:title>
   <news:publication_date>2026-06-19T08:43:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702410</loc>
  <lastmod>2026-06-19T08:42:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己変調がもたらすGAN性能向上（ON SELF MODULATION FOR GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-06-19T08:42:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702408</loc>
  <lastmod>2026-06-19T08:42:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分モンテカルロによる高次元偏微分方程式の橋渡し（Variational Monte Carlo — Bridging Concepts of Machine Learning and High Dimensional Partial Differential Equations）</news:title>
   <news:publication_date>2026-06-19T08:42:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702406</loc>
  <lastmod>2026-06-19T08:41:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現場用スペクトル吸収蛍光顕微システムによる藻類の迅速同定（Spectral Absorption-fluorescence Microscopy System for ON-site-imaging of algae）</news:title>
   <news:publication_date>2026-06-19T08:41:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702404</loc>
  <lastmod>2026-06-19T08:41:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FutureGANによる映像フレーム予測の実用性と限界（FutureGAN: Anticipating the Future Frames of Video Sequences using Spatio-Temporal 3d Convolutions in Progressively Growing GANs）</news:title>
   <news:publication_date>2026-06-19T08:41:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702402</loc>
  <lastmod>2026-06-19T08:41:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサーモータ予測から自律的に生まれる空間表現（UNSUPERVISED EMERGENCE OF SPATIAL STRUCTURE FROM SENSORIMOTOR PREDICTION）</news:title>
   <news:publication_date>2026-06-19T08:41:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702400</loc>
  <lastmod>2026-06-19T08:40:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>災害対応ロボットMomaroによる現場作業解決（NimbRo Rescue: Solving Disaster-Response Tasks through Mobile Manipulation Robot Momaro）</news:title>
   <news:publication_date>2026-06-19T08:40:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702398</loc>
  <lastmod>2026-06-19T07:49:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多偏波GPR体積データを用いたオートエンコーダによる地雷検出 (Landmine Detection Using Autoencoders on Multi-polarization GPR Volumetric Data)</news:title>
   <news:publication_date>2026-06-19T07:49:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702396</loc>
  <lastmod>2026-06-19T07:49:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的強化学習におけるほぼ最適な表現学習（Near-Optimal Representation Learning for Hierarchical Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-19T07:49:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702394</loc>
  <lastmod>2026-06-19T07:48:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム学習率による学習（Learning with Random Learning Rates）</news:title>
   <news:publication_date>2026-06-19T07:48:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702392</loc>
  <lastmod>2026-06-19T07:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的手法と勾配ベース手法を組み合わせた方策探索：CEM-RL（CEM-RL: Combining evolutionary and gradient-based methods for policy search）</news:title>
   <news:publication_date>2026-06-19T07:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702390</loc>
  <lastmod>2026-06-19T07:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNAメチル化状態に基づくがんタイプの識別のための深層自己符号化器システム（A Deep Autoencoder System for Differentiation of Cancer Types Based on DNA Methylation State）</news:title>
   <news:publication_date>2026-06-19T07:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702388</loc>
  <lastmod>2026-06-19T07:48:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海洋ロボット航法のためのスパースガウス過程Temporal Difference学習（Sparse Gaussian Process Temporal Difference Learning）</news:title>
   <news:publication_date>2026-06-19T07:48:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702386</loc>
  <lastmod>2026-06-19T07:47:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球より大きな電波干渉計：宇宙VLBIの教訓と展望（Radio Interferometers Larger than Earth: Lessons Learned and Forward Look of Space VLBI）</news:title>
   <news:publication_date>2026-06-19T07:47:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702384</loc>
  <lastmod>2026-06-19T06:56:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトニックニューラルネットにおける全光学的非線形活性化（All-optical Nonlinear Activation Function for Photonic Neural Networks）</news:title>
   <news:publication_date>2026-06-19T06:56:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702382</loc>
  <lastmod>2026-06-19T06:56:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SMCの近赤外VISTA観測（A near-infrared VISTA of the Small Magellanic Cloud）</news:title>
   <news:publication_date>2026-06-19T06:56:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702380</loc>
  <lastmod>2026-06-19T06:56:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラット一次視覚野における視覚オブジェクト表現の特徴付け（Characterization of Visual Object Representations in Rat Primary Visual Cortex）</news:title>
   <news:publication_date>2026-06-19T06:56:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702378</loc>
  <lastmod>2026-06-19T06:55:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的事例の全体像とその含意（Adversarial Examples - A Complete Characterisation of the Phenomenon）</news:title>
   <news:publication_date>2026-06-19T06:55:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702376</loc>
  <lastmod>2026-06-19T06:55:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カスケードバンディットに対するトンプソンサンプリングの設計と意義（Thompson Sampling Algorithms for Cascading Bandits）</news:title>
   <news:publication_date>2026-06-19T06:55:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702374</loc>
  <lastmod>2026-06-19T06:54:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EMIによる探索強化（EMI: Exploration with Mutual Information）</news:title>
   <news:publication_date>2026-06-19T06:54:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702372</loc>
  <lastmod>2026-06-19T06:54:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的プログラミングによるプログラム誘導の推論（Inference Over Programs That Make Predictions）</news:title>
   <news:publication_date>2026-06-19T06:54:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702370</loc>
  <lastmod>2026-06-19T06:03:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粉末X線回折パターン解析に機械学習クラスタリングを適用して合金置換を識別する手法（Machine learning clustering technique applied to powder X-ray diffraction patterns to distinguish alloy substitutions）</news:title>
   <news:publication_date>2026-06-19T06:03:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702368</loc>
  <lastmod>2026-06-19T06:03:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド自然言語生成チャレンジの所見（Findings of the E2E NLG Challenge）</news:title>
   <news:publication_date>2026-06-19T06:03:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702366</loc>
  <lastmod>2026-06-19T06:02:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多項式サイズ回路のための量子準同型暗号（A quantum homomorphic encryption scheme for polynomial-sized circuits）</news:title>
   <news:publication_date>2026-06-19T06:02:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702364</loc>
  <lastmod>2026-06-19T06:01:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>判別器をエネルギーネットワークとして学習する敵対的学習（Learning Discriminators as Energy Networks in Adversarial Learning）</news:title>
   <news:publication_date>2026-06-19T06:01:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702362</loc>
  <lastmod>2026-06-19T06:01:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き生成敵対ネットワークを用いた半教師ありテキスト回帰（Semi-supervised Text Regression with Conditional Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-19T06:01:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702360</loc>
  <lastmod>2026-06-19T06:01:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習に基づく物理層通信によるマルチエージェント協調（Learning-based physical layer communications for multi-agent collaboration）</news:title>
   <news:publication_date>2026-06-19T06:01:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702358</loc>
  <lastmod>2026-06-19T06:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルノイズ下での深層学習におけるエントロピー的最適輸送損失（An Entropic Optimal Transport Loss for Learning Deep Neural Networks under Label Noise in Remote Sensing Images）</news:title>
   <news:publication_date>2026-06-19T06:00:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702356</loc>
  <lastmod>2026-06-19T05:09:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>循環行列を用いた動画分類モデルの圧縮（Training compact deep learning models for video classification using circulant matrices）</news:title>
   <news:publication_date>2026-06-19T05:09:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702354</loc>
  <lastmod>2026-06-19T05:09:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近隣情報を活かす点群の3Dセマンティックセグメンテーション（Know What Your Neighbors Do: 3D Semantic Segmentation of Point Clouds）</news:title>
   <news:publication_date>2026-06-19T05:09:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702352</loc>
  <lastmod>2026-06-19T05:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TRASS: 時間反転を用いた自己教師あり学習によるロボット操作の新展開（TRASS: Time Reversal as Self-Supervision）</news:title>
   <news:publication_date>2026-06-19T05:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702350</loc>
  <lastmod>2026-06-19T05:08:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sinkhorn AutoEncoders（Sinkhorn AutoEncoders）</news:title>
   <news:publication_date>2026-06-19T05:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702348</loc>
  <lastmod>2026-06-19T05:08:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次元分光データの機械学習（Machine Learning of Two-Dimensional Spectroscopic Data）</news:title>
   <news:publication_date>2026-06-19T05:08:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702346</loc>
  <lastmod>2026-06-19T05:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインコメントに対する宛先自動判別の実用可能性（Who is Addressed in this Comment? Automatically Classifying Meta-Comments）</news:title>
   <news:publication_date>2026-06-19T05:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702344</loc>
  <lastmod>2026-06-19T05:07:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>述語学習が示す生成構造の発見（Predicate learning in neural systems: Discovering latent generative structures）</news:title>
   <news:publication_date>2026-06-19T05:07:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702342</loc>
  <lastmod>2026-06-19T04:16:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ターゲット認識型ネットワーク適応による効率的表現学習（Target Aware Network Adaptation for Efficient Representation Learning）</news:title>
   <news:publication_date>2026-06-19T04:16:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702340</loc>
  <lastmod>2026-06-19T04:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>夢見る変分オートエンコーダによる強化学習環境（The Dreaming Variational Autoencoder for Reinforcement Learning Environments）</news:title>
   <news:publication_date>2026-06-19T04:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702338</loc>
  <lastmod>2026-06-19T04:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンク予測に対する敵対的攻撃（Link Prediction Adversarial Attack）</news:title>
   <news:publication_date>2026-06-19T04:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702336</loc>
  <lastmod>2026-06-19T04:08:23Z</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>2026-06-19T04:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T04:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T04:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T04:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T03:15:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Lipschitzかつ凸な損失関数によるロバスト統計学の前進（Robust Statistical learning with Lipschitz and convex loss functions）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702324</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>スマホで回る小型高精度ランドマーク認識モデル（NU-LiteNet: Mobile Landmark Recognition using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-19T03:13:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T03:13:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702320</loc>
  <lastmod>2026-06-19T03:13:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>コンセンサス最大化による文表現改善（Improving Sentence Representations with Consensus Maximisation）</news:title>
   <news:publication_date>2026-06-19T03:13:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-19T03:13:25Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>超解像ブラインドチャネル・信号推定による大型MIMOの角度解像向上（Super-Resolution Blind Channel-and-Signal Estimation for Massive MIMO with One-Dimensional Antenna Array）</news:title>
   <news:publication_date>2026-06-19T03:13:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T03:13:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702314</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ブロック単位中間表現訓練によるモデル圧縮（Block-wise Intermediate Representation Training）</news:title>
   <news:publication_date>2026-06-19T02:22:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ソフトロボティクス向けリアルタイム微分可能物理シミュレータ（ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics）</news:title>
   <news:publication_date>2026-06-19T02:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T02:21:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>摂動された報酬による強化学習（Reinforcement Learning with Perturbed Rewards）</news:title>
   <news:publication_date>2026-06-19T02:20:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702306</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T02:20:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702302</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T02:20:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702300</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T01:29:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>大規模バッチ学習における敵対的訓練と二次情報の活用 (Large Batch Size Training of Neural Networks with Adversarial Training and Second-Order Information)</news:title>
   <news:publication_date>2026-06-19T01:28:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-19T01:28:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702294</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>ハミング距離ターゲットによるハッシュ符号学習（Learning Hash Codes via Hamming Distance Targets）</news:title>
   <news:publication_date>2026-06-19T01:27:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702292</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T01:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702290</loc>
  <lastmod>2026-06-19T01:27:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>性的暴行に関するTwitter会話の意図検出に対する分散意味論アプローチ（Distributional Semantics Approach to Detect Intent in Twitter Conversations on Sexual Assaults）</news:title>
   <news:publication_date>2026-06-19T01:27:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702288</loc>
  <lastmod>2026-06-19T01:26:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル不確実性に対するベイズ方策最適化（Bayesian Policy Optimization for Model Uncertainty）</news:title>
   <news:publication_date>2026-06-19T01:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702286</loc>
  <lastmod>2026-06-19T00:35:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-19T00:35:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702284</loc>
  <lastmod>2026-06-19T00:35:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小限の局所平滑性仮定下での単純でパラメータ不要かつ適応的な最適化手法 (A simple parameter-free and adaptive approach to optimization under a minimal local smoothness assumption)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702282</loc>
  <lastmod>2026-06-19T00:35:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジャイロを利用した動きブレ除去（Gyroscope-Aided Motion Deblurring with Deep Networks）</news:title>
   <news:publication_date>2026-06-19T00:35:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702280</loc>
  <lastmod>2026-06-19T00:34:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>透明性駆動型環境による信頼できる自動ジャンル分類の実践（Utilizing a Transparency-driven Environment toward Trusted Automatic Genre Classification: A Case Study in Journalism History）</news:title>
   <news:publication_date>2026-06-19T00:34:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702278</loc>
  <lastmod>2026-06-19T00:33:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Regression Trees（Neural Regression Trees）</news:title>
   <news:publication_date>2026-06-19T00:33:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702276</loc>
  <lastmod>2026-06-19T00:33:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワーク向け拡張ビットプレーン圧縮（Extended Bit-Plane Compression for Convolutional Neural Network Accelerators）</news:title>
   <news:publication_date>2026-06-19T00:33:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702274</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>放射線科報告からの効率的かつ高精度な異常抽出（Efficient and Accurate Abnormality Mining from Radiology Reports with Customized False Positive Reduction）</news:title>
   <news:publication_date>2026-06-19T00:33:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702272</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>不完全情報下におけるネットワーク化マイクログリッドの学習ベース電力管理（A Learning-based Power Management for Networked Microgrids Under Incomplete Information）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702270</loc>
  <lastmod>2026-06-18T23:41:19Z</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よる量子暗号の誤り訂正（Error correction in quantum cryptography based on artificial neural networks）</news:title>
   <news:publication_date>2026-06-18T23:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>テキスト分類器を因果推論に使う際の課題と道筋（Challenges of Using Text Classifiers for Causal Inference）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-18T22:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news: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>サンプリングベース探索に深い系列モデルを組み合わせる意義（Deep sequential models for sampling-based planning）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散乱物中での自律把持のためのRGB-D物体検出と意味セグメンテーション（RGB-D Object Detection and Semantic Segmentation for Autonomous Manipulation in Clutter）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BARTの理論的基盤の確立（On Theory for BART）</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>プロファイリング・マシン：知識上の能動的な一般化（The Profiling Machine: Active Generalization over Knowledge）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半適応型ニューラルネットワークによる人間運動予測（Human Motion Prediction using Semi-adaptable Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news: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>グラフで「分類」を再定義する手法—リンク予測で解く分類問題（Classification Using Link Prediction）</news:title>
   <news:publication_date>2026-06-18T19:07:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702190</loc>
  <lastmod>2026-06-18T19:06:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動で見出すサイバーフィジカルシステム（Data-driven Discovery of Cyber-Physical Systems）</news:title>
   <news:publication_date>2026-06-18T19:06:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702188</loc>
  <lastmod>2026-06-18T18:15:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部位レベルの畳み込みニューラルネットワークによる歩行者検出（Part-Level Convolutional Neural Networks for Pedestrian Detection Using Saliency and Boundary Box Alignment）</news:title>
   <news:publication_date>2026-06-18T18:15:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702186</loc>
  <lastmod>2026-06-18T18:14:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Perfect Match を用いた反実仮想推論の簡潔実装（Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks）</news:title>
   <news:publication_date>2026-06-18T18:14:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702184</loc>
  <lastmod>2026-06-18T18:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fusion Hashing：既存ハッシュ法の自己改善フレームワーク（Fusion Hashing: A General Framework for Self-improvement of Hashing）</news:title>
   <news:publication_date>2026-06-18T18:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702182</loc>
  <lastmod>2026-06-18T18:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HST STISによる原始惑星状星雲 HEN 3-1475 の紫外線分光観測（HST STIS UV Spectroscopic Observations of the Protoplanetary Nebula HEN 3-1475）</news:title>
   <news:publication_date>2026-06-18T18:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702180</loc>
  <lastmod>2026-06-18T18:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマホで計測するパーキンソン病診断の可能性（PhoneMD: Learning to Diagnose Parkinson’s Disease from Smartphone Data）</news:title>
   <news:publication_date>2026-06-18T18:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702178</loc>
  <lastmod>2026-06-18T18:13:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SmartChoicesによるプログラミングと機械学習の融合（SmartChoices: Hybridizing Programming and Machine Learning）</news:title>
   <news:publication_date>2026-06-18T18:13:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702176</loc>
  <lastmod>2026-06-18T18:13:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートネットワーク場理論（Smart Network Field Theory: The Technophysics of Blockchain and Deep Learning）</news:title>
   <news:publication_date>2026-06-18T18:13:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702174</loc>
  <lastmod>2026-06-18T17:22:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル外科デモンストレーションの教師なし軌跡分割と促進（Unsupervised Trajectory Segmentation and Promoting of Multi-Modal Surgical Demonstrations）</news:title>
   <news:publication_date>2026-06-18T17:22:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702172</loc>
  <lastmod>2026-06-18T17:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全なDNN推論を実現するPRIVADO（PRIVADO: Practical and Secure DNN Inference with Enclaves）</news:title>
   <news:publication_date>2026-06-18T17:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702170</loc>
  <lastmod>2026-06-18T17:21:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンクリック注釈と誘導付き階層的オブジェクト検出（One-Click Annotation with Guided Hierarchical Object Detection）</news:title>
   <news:publication_date>2026-06-18T17:21:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702168</loc>
  <lastmod>2026-06-18T17:20:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VAEの挙動を制御する手法の提示（Taming VAEs）</news:title>
   <news:publication_date>2026-06-18T17:20:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702166</loc>
  <lastmod>2026-06-18T17:20:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュースに潜む風刺を機械学習で見抜く方法（Detecting Satire in the News with Machine Learning）</news:title>
   <news:publication_date>2026-06-18T17:20:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702164</loc>
  <lastmod>2026-06-18T17:20:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弾力的ニューラルネットワークによる分類（Elastic Neural Networks for Classification）</news:title>
   <news:publication_date>2026-06-18T17:20:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702162</loc>
  <lastmod>2026-06-18T17:20:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cherenkov望遠鏡データからのガンマ線情報抽出（Extracting gamma-ray information from images with convolutional neural network methods on simulated Cherenkov Telescope Array data）</news:title>
   <news:publication_date>2026-06-18T17:20:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702160</loc>
  <lastmod>2026-06-18T16:29:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CdZnTeSe検出器の電気輸送特性に対する深い準位の影響（Influence of deep levels on the electrical transport properties of CdZnTeSe detectors）</news:title>
   <news:publication_date>2026-06-18T16:29:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702158</loc>
  <lastmod>2026-06-18T16:28:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適適応型および加速確率的勾配下降法（Optimal Adaptive and Accelerated Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-06-18T16:28:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702156</loc>
  <lastmod>2026-06-18T16:28:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的メタ表現によるニューラルネットワークの重みモデリング（Probabilistic Meta-Representations Of Neural Networks）</news:title>
   <news:publication_date>2026-06-18T16:28:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702154</loc>
  <lastmod>2026-06-18T16:27:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adv-BNNによる堅牢化—ベイズニューラルネットを用いた対敵防御の実用化 (ADV-BNN: IMPROVED ADVERSARIAL DEFENSE THROUGH ROBUST BAYESIAN NEURAL NETWORK)</news:title>
   <news:publication_date>2026-06-18T16:27:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702152</loc>
  <lastmod>2026-06-18T16:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォルナクス深部サーベイによる矮小銀河カタログ（The Fornax Deep Survey (FDS) with the VST. IV. A size and magnitude limited catalog of dwarf galaxies in the area of the Fornax cluster）</news:title>
   <news:publication_date>2026-06-18T16:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702150</loc>
  <lastmod>2026-06-18T16:27:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像向け生成敵対ネットワークの実践的意義（Generative Adversarial Network for Medical Images）</news:title>
   <news:publication_date>2026-06-18T16:27:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702148</loc>
  <lastmod>2026-06-18T16:26:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Z∼4における星形成が抑制された大型銀河の休止光学サイズ（THE REST-FRAME OPTICAL SIZES OF MASSIVE GALAXIES WITH SUPPRESSED STAR FORMATION AT Z ∼4）</news:title>
   <news:publication_date>2026-06-18T16:26:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702146</loc>
  <lastmod>2026-06-18T15:35:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多階層で把持候補を統合する実用的ロボット把持検出（Densely Supervised Grasp Detector）</news:title>
   <news:publication_date>2026-06-18T15:35:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702144</loc>
  <lastmod>2026-06-18T15:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチキャリア通信における信号悪用攻撃の耐性評価（How Secure are Multicarrier Communication Systems Against Signal Exploitation Attacks?）</news:title>
   <news:publication_date>2026-06-18T15:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702142</loc>
  <lastmod>2026-06-18T15:34:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な時空間注意による動画行動認識（Interpretable Spatio-temporal Attention for Video Action Recognition）</news:title>
   <news:publication_date>2026-06-18T15:34:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702140</loc>
  <lastmod>2026-06-18T15:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドで挑むアルツハイマー病診断とバイオマーカー特定（End-To-End Alzheimer’s Disease Diagnosis and Biomarker Identification）</news:title>
   <news:publication_date>2026-06-18T15:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702138</loc>
  <lastmod>2026-06-18T15:33:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FIRE-DES++: 動的アンサンブル選択のためのオンライン剪定強化（FIRE-DES++: Enhanced Online Pruning of Base Classifiers for Dynamic Ensemble Selection）</news:title>
   <news:publication_date>2026-06-18T15:33:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702136</loc>
  <lastmod>2026-06-18T15:33:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動アプローチは常識推論に足りるか（A Simple Method for Commonsense Reasoning）</news:title>
   <news:publication_date>2026-06-18T15:33:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702134</loc>
  <lastmod>2026-06-18T15:33:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープファクターモデル（Deep Factor Model –Explaining Deep Learning Decisions for Forecasting Stock Returns with Layer-wise Relevance Propagation–）</news:title>
   <news:publication_date>2026-06-18T15:33:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702132</loc>
  <lastmod>2026-06-18T14:41:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層補償プルーニングによる資源制約型畳み込みニューラルネットワークの最適化（Layer-compensated Pruning for Resource-constrained Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-18T14:41:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702130</loc>
  <lastmod>2026-06-18T14:41:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム反例による対話型学習の高速アルゴリズム（Simple and Fast Algorithms for Interactive Machine Learning with Random Counter-examples）</news:title>
   <news:publication_date>2026-06-18T14:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702128</loc>
  <lastmod>2026-06-18T14:41:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互作用で学ぶエージェントモデル化（Interactive Agent Modeling by Learning to Probe）</news:title>
   <news:publication_date>2026-06-18T14:41:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702126</loc>
  <lastmod>2026-06-18T14:40:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝・文化・道徳の進化研究における類似点と有望な方向性 (Parallels and promising directions in the study of genetic, cultural, and moral evolution)</news:title>
   <news:publication_date>2026-06-18T14:40:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702124</loc>
  <lastmod>2026-06-18T14:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペクトル画像における混合ノイズ除去のための空間・スペクトル勾配ネットワーク（Hybrid Noise Removal in Hyperspectral Imagery with a Spatial-Spectral Gradient Network）</news:title>
   <news:publication_date>2026-06-18T14:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702122</loc>
  <lastmod>2026-06-18T14:40:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/702120</loc>
  <lastmod>2026-06-18T14:40:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハドロン衝突を含むグローバル解析によるトランスヴァーシティの初抽出（First extraction of transversity from data on lepton-hadron scattering and hadronic collisions）</news:title>
   <news:publication_date>2026-06-18T14:40:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702118</loc>
  <lastmod>2026-06-18T13:48:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床データから深い潜在表現を学ぶ（Learning Deep Representations from Clinical Data for Chronic Kidney Disease）</news:title>
   <news:publication_date>2026-06-18T13:48:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702116</loc>
  <lastmod>2026-06-18T13:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MultiWOZが示した対話AI研究の地殻変動（MultiWOZ – A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling）</news:title>
   <news:publication_date>2026-06-18T13:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702114</loc>
  <lastmod>2026-06-18T13:47:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段落ランク付けによるオープンドメインQAの想定改善（Ranking Paragraphs for Improving Answer Recall in Open-Domain Question Answering）</news:title>
   <news:publication_date>2026-06-18T13:47:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702112</loc>
  <lastmod>2026-06-18T13:47:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未分割実演からサブタスクを自動発見し階層方策を学ぶ手法（DIRECTED-INFO GAIL: LEARNING HIERARCHICAL POLICIES FROM UNSEGMENTED DEMONSTRATIONS USING DIRECTED INFORMATION）</news:title>
   <news:publication_date>2026-06-18T13:47:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702110</loc>
  <lastmod>2026-06-18T13:47:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模確率的最適化のための高速準ニュートン法（A fast quasi-Newton-type method for large-scale stochastic optimisation）</news:title>
   <news:publication_date>2026-06-18T13:47:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702108</loc>
  <lastmod>2026-06-18T13:47:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー嗜好の変化検出と順序型推薦への応用（Detecting Changes in User Preferences using Hidden Markov Models for Sequential Recommendation Tasks）</news:title>
   <news:publication_date>2026-06-18T13:47:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702106</loc>
  <lastmod>2026-06-18T13:47:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移可能な敵対的例の生成（CAAD 2018: Generating Transferable Adversarial Examples）</news:title>
   <news:publication_date>2026-06-18T13:47:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702104</loc>
  <lastmod>2026-06-18T12:55:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rでの強化学習入門と実装の要点（Reinforcement Learning in R）</news:title>
   <news:publication_date>2026-06-18T12:55:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702102</loc>
  <lastmod>2026-06-18T12:55:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コマ銀河団コアにおける矮小銀河の構造と分類（Dwarf Galaxies in the Core of Coma Cluster）</news:title>
   <news:publication_date>2026-06-18T12:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702100</loc>
  <lastmod>2026-06-18T12:55:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明を正則化して学習する機械学習モデル（Training Machine Learning Models by Regularizing their Explanations）</news:title>
   <news:publication_date>2026-06-18T12:55:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702098</loc>
  <lastmod>2026-06-18T12:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音色（ティンバー）を多対多で変換する新手法：Modulated Variational auto-Encoders（MODULATED VARIATIONAL AUTO-ENCODERS FOR MANY-TO-MANY MUSICAL TIMBRE TRANSFER）</news:title>
   <news:publication_date>2026-06-18T12:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702096</loc>
  <lastmod>2026-06-18T12:54:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化マルチチャンネル変分オートエンコーダによる過未決定音源分離（GENERALIZED MULTICHANNEL VARIATIONAL AUTOENCODER FOR UNDERDETERMINED SOURCE SEPARATION）</news:title>
   <news:publication_date>2026-06-18T12:54:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702094</loc>
  <lastmod>2026-06-18T12:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多臓器組織像における核セグメンテーションの深層敵対的訓練（Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images）</news:title>
   <news:publication_date>2026-06-18T12:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702092</loc>
  <lastmod>2026-06-18T12:53:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dynamic Ensemble Active Learning（Dynamic Ensemble Active Learning: A Non-Stationary Bandit with Expert Advice）</news:title>
   <news:publication_date>2026-06-18T12:53:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702090</loc>
  <lastmod>2026-06-18T12:02:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PHY層鍵抽出に対する統計的推論攻撃と対策（Statistical Inference Attack Against PHY-layer Key Extraction and Countermeasures）</news:title>
   <news:publication_date>2026-06-18T12:02:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702088</loc>
  <lastmod>2026-06-18T12:01:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮して使うべきか否か：敵対的攻撃とニューラルネットワーク圧縮の相互作用を理解する (TO COMPRESS OR NOT TO COMPRESS: UNDERSTANDING THE INTERACTIONS BETWEEN ADVERSARIAL ATTACKS AND NEURAL NETWORK COMPRESSION)</news:title>
   <news:publication_date>2026-06-18T12:01:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702086</loc>
  <lastmod>2026-06-18T12:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈依存処理を継続的に学習するニューラルネット（Continual Learning of Context-dependent Processing in Neural Networks）</news:title>
   <news:publication_date>2026-06-18T12:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702084</loc>
  <lastmod>2026-06-18T12:01:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒトのデモ映像から学ぶロボットの眼手協調（Robot eye-hand coordination learning by watching human demonstrations: a task function approximation approach）</news:title>
   <news:publication_date>2026-06-18T12:01:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702082</loc>
  <lastmod>2026-06-18T12:01:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造学習による量化子消去（Quantifier Elimination With Structural Learning）</news:title>
   <news:publication_date>2026-06-18T12:01:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702080</loc>
  <lastmod>2026-06-18T12:00:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手作業で作った記号地上化と上位計画の自動改善（Refining Manually-Designed Symbol Grounding and High-Level Planning by Policy Gradients）</news:title>
   <news:publication_date>2026-06-18T12:00:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702078</loc>
  <lastmod>2026-06-18T12:00:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NICE：ノイズ注入とクランピング推定によるニューラルネットワーク量子化（NICE: Noise Injection and Clamping Estimation for Neural Network Quantization）</news:title>
   <news:publication_date>2026-06-18T12:00:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702076</loc>
  <lastmod>2026-06-18T11:09:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配降下法における方向性解析（Directional Analysis of Stochastic Gradient Descent via von Mises-Fisher Distributions in Deep Learning）</news:title>
   <news:publication_date>2026-06-18T11:09:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702074</loc>
  <lastmod>2026-06-18T11:09:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>労働者の「こころ」を読む管理者学習：M3RL（M3RL: Mind-aware Multi-agent Management Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-18T11:09:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702072</loc>
  <lastmod>2026-06-18T11:09:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数デモから一般化するロボット技能の学習（Auto-conditioned Recurrent Mixture Density Networks for Learning Generalizable Robot Skills）</news:title>
   <news:publication_date>2026-06-18T11:09:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702070</loc>
  <lastmod>2026-06-18T11:08:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒトの操作デモから幾何学的制約を推定する方法（Inferring geometric constraints in human demonstrations）</news:title>
   <news:publication_date>2026-06-18T11:08:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702068</loc>
  <lastmod>2026-06-18T11:08:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力空間の決定面から読み解く敵対的ロバスト性（INTERPRETING ADVERSARIAL ROBUSTNESS: A VIEW FROM DECISION SURFACE IN INPUT SPACE）</news:title>
   <news:publication_date>2026-06-18T11:08:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702066</loc>
  <lastmod>2026-06-18T11:07:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識指導型セマンティックコンピューティングネットワーク（Knowledge-guided Semantic Computing Network）</news:title>
   <news:publication_date>2026-06-18T11:07:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702064</loc>
  <lastmod>2026-06-18T11:07:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AdaShiftが示した「適応学習率の再考」—Adamの非収束問題を時間ずらしで解く（ADASHIFT: DECORRELATION AND CONVERGENCE OF ADAPTIVE LEARNING RATE METHODS）</news:title>
   <news:publication_date>2026-06-18T11:07:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702062</loc>
  <lastmod>2026-06-18T10:16:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FusedLSTMによる動画関連性予測（FusedLSTM at ACMMM-2018 CBVRP Challenge: Fusing frame-level and video-level features for Content-based Video Relevance Prediction）</news:title>
   <news:publication_date>2026-06-18T10:16:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702060</loc>
  <lastmod>2026-06-18T10:16:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>X線透視撮影システムにおける誤差モデリングとデータ駆動型自己較正（MODELLING ERRORS IN X-RAY FLUOROSCOPIC IMAGING SYSTEMS USING PHOTOGRAMMETRIC BUNDLE ADJUSTMENT WITH A DATA-DRIVEN SELF-CALIBRATION APPROACH）</news:title>
   <news:publication_date>2026-06-18T10:16:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702058</loc>
  <lastmod>2026-06-18T10:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイドアングルレンズカメラの自動較正法（ROBOT VISION: CALIBRATION OF WIDE-ANGLE LENS CAMERAS USING COLLINEARITY CONDITION AND K-NEAREST NEIGHBOUR REGRESSION）</news:title>
   <news:publication_date>2026-06-18T10:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702056</loc>
  <lastmod>2026-06-18T10:15:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化が勾配降下法にもたらす定量的効果（A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent）</news:title>
   <news:publication_date>2026-06-18T10:15:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702054</loc>
  <lastmod>2026-06-18T10:15:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散分布上の勾配最適化改善（IMPROVED GRADIENT-BASED OPTIMIZATION OVER DISCRETE DISTRIBUTIONS）</news:title>
   <news:publication_date>2026-06-18T10:15:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702052</loc>
  <lastmod>2026-06-18T10:15:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DQNにおける汎化と正則化の考察（Generalization and Regularization in DQN）</news:title>
   <news:publication_date>2026-06-18T10:15:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702050</loc>
  <lastmod>2026-06-18T10:14:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変量情報に基づくランダム分割モデルによる相互作用の発見 (Discovering Interactions Using Covariate Informed Random Partition Models)</news:title>
   <news:publication_date>2026-06-18T10:14:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702048</loc>
  <lastmod>2026-06-18T09:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン対抗マルチタスクフレームワークによる化合物の新規治療特性予測（Domain-Adversarial Multi-Task Framework for Novel Therapeutic Property Prediction of Compounds）</news:title>
   <news:publication_date>2026-06-18T09:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702046</loc>
  <lastmod>2026-06-18T09:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マージン分布による深層ネットワークの汎化ギャップ予測 (Predicting the Generalization Gap in Deep Networks with Margin Distributions)</news:title>
   <news:publication_date>2026-06-18T09:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702044</loc>
  <lastmod>2026-06-18T09:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSSMによる原画像からの統計形状モデリング（DeepSSM: A Deep Learning Framework for Statistical Shape Modeling from Raw Images）</news:title>
   <news:publication_date>2026-06-18T09:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702042</loc>
  <lastmod>2026-06-18T09:22:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>保証付きマシンティーチングのためのバリア証明（Barrier Certificates for Assured Machine Teaching）</news:title>
   <news:publication_date>2026-06-18T09:22:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702040</loc>
  <lastmod>2026-06-18T09:22:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小児体部MRAを短時間化する深層残差ネットワークによるオフレゾナンス補正（Deep Residual Network for Off-Resonance Artifact Correction with Application to Pediatric Body Magnetic Resonance Angiography with 3D Cones）</news:title>
   <news:publication_date>2026-06-18T09:22:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702038</loc>
  <lastmod>2026-06-18T09:22:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタイルとコンテンツの切り分けで「未知の組合せ」を作る技術（Open-Ended Content-Style Recombination via Leakage Filtering）</news:title>
   <news:publication_date>2026-06-18T09:22:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702036</loc>
  <lastmod>2026-06-18T09:21:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子核パートン分布の最近の進展 (Recent progress in Nuclear Parton Distributions)</news:title>
   <news:publication_date>2026-06-18T09:21:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702034</loc>
  <lastmod>2026-06-18T08:30:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的攻撃と防御の総説（Adversarial Attacks and Defences: A Survey）</news:title>
   <news:publication_date>2026-06-18T08:30:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702032</loc>
  <lastmod>2026-06-18T08:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシー下の文脈付き線形バンディット（Differentially Private Contextual Linear Bandits）</news:title>
   <news:publication_date>2026-06-18T08:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702030</loc>
  <lastmod>2026-06-18T08:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定した脳–機械インターフェースのための敵対的ドメイン適応（Adversarial Domain Adaptation for Stable Brain-Machine Interfaces）</news:title>
   <news:publication_date>2026-06-18T08:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702028</loc>
  <lastmod>2026-06-18T08:28:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きジニ不純度最小化とk平均問題の接続（Minimization of Gini impurity via connections with the k-means problem）</news:title>
   <news:publication_date>2026-06-18T08:28:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702026</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>能動的公平性――情報取得を変えることで達成するアルゴリズム公正性（Active Fairness in Algorithmic Decision Making）</news:title>
   <news:publication_date>2026-06-18T08:28:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702024</loc>
  <lastmod>2026-06-18T08:28:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生体内で動作する超音波スイッチ型蛍光イメージング（In vivo ultrasound-switchable fluorescence imaging）</news:title>
   <news:publication_date>2026-06-18T08:28:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702022</loc>
  <lastmod>2026-06-18T08:28:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>I-DLVグラウンダーとASPソルバーの効率的な連携（Efficiently Coupling the I-DLV Grounder with ASP Solvers）</news:title>
   <news:publication_date>2026-06-18T08:28:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702020</loc>
  <lastmod>2026-06-18T07:36:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOSFIREによる休止銀河のスペクトル解析が示す星形成履歴と消光メカニズム（MOSFIRE Spectroscopy of Quiescent Galaxies at 1.5 &amp;lt; z &amp;lt; 2.5: Star Formation Histories and Galaxy Quenching）</news:title>
   <news:publication_date>2026-06-18T07:36:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702018</loc>
  <lastmod>2026-06-18T07:36:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NuSTARによる外宇宙調査が暴いた埋もれたAGNの実像（THE NuSTAR EXTRAGALACTIC SURVEYS: UNVEILING RARE, BURIED AGNS AND DETECTING THE CONTRIBUTORS TO THE PEAK OF THE COSMIC X-RAY BACKGROUND）</news:title>
   <news:publication_date>2026-06-18T07:36:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702016</loc>
  <lastmod>2026-06-18T07:35:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群れの「まとまり度」から感情影響を予測する手法（Data-Driven Modeling of Group Entitativity in Virtual Environments）</news:title>
   <news:publication_date>2026-06-18T07:35:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702014</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配降下法の揺らぎ–散逸関係（Fluctuation-Dissipation Relations for Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-06-18T07:34:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702012</loc>
  <lastmod>2026-06-18T07:34:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPyTorchによるGPU高速化ガウス過程推論（GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration）</news:title>
   <news:publication_date>2026-06-18T07:34:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702010</loc>
  <lastmod>2026-06-18T07:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測下でのモデルベース制御のためのPropagation Networks（Propagation Networks for Model-Based Control Under Partial Observation）</news:title>
   <news:publication_date>2026-06-18T07:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702008</loc>
  <lastmod>2026-06-18T07:34:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハッブル超深度場の失われた光（The missing light of the Hubble Ultra Deep Field）</news:title>
   <news:publication_date>2026-06-18T07:34:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702006</loc>
  <lastmod>2026-06-18T06:42:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動で新物理を探す手法の実務的意義（Learning New Physics from a Machine）</news:title>
   <news:publication_date>2026-06-18T06:42:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702004</loc>
  <lastmod>2026-06-18T06:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dirichlet分布による形式的コンテキストの生成（Formal Context Generation using Dirichlet Distributions）</news:title>
   <news:publication_date>2026-06-18T06:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702002</loc>
  <lastmod>2026-06-18T06:41:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGA上でのDNN推論のスループット最適化（Throughput Optimizations for FPGA-based Deep Neural Network Inference）</news:title>
   <news:publication_date>2026-06-18T06:41:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/702000</loc>
  <lastmod>2026-06-18T06:41:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノード重み付きスペクトル埋め込み（Weighted Spectral Embedding of Graphs）</news:title>
   <news:publication_date>2026-06-18T06:41:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701998</loc>
  <lastmod>2026-06-18T06:40:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャネル方向と空間特徴の変調ネットワークによる単一画像超解像（Channel-wise and Spatial Feature Modulation Network for Single Image Super-Resolution）</news:title>
   <news:publication_date>2026-06-18T06:40:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701996</loc>
  <lastmod>2026-06-18T06:40:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XXL-S電波源の多波長同定（Identifications of 2.1 GHz radio sources in the XXL-S field）</news:title>
   <news:publication_date>2026-06-18T06:40:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701994</loc>
  <lastmod>2026-06-18T06:39:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EDDIによる効率的な情報取得（Efficient Dynamic Discovery of High-Value Information with Partial VAE）</news:title>
   <news:publication_date>2026-06-18T06:39:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701992</loc>
  <lastmod>2026-06-18T05:48:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転の再考（RETHINKING SELF-DRIVING: MULTI-TASK KNOWLEDGE FOR BETTER GENERALIZATION AND ACCIDENT EXPLANATION ABILITY）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701990</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-18T05:48:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701988</loc>
  <lastmod>2026-06-18T05:47:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子構造の解析におけるカーネルベース手法（A kernel-based approach to molecular conformation analysis）</news:title>
   <news:publication_date>2026-06-18T05:47:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-18T05:47:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701984</loc>
  <lastmod>2026-06-18T05:47:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701982</loc>
  <lastmod>2026-06-18T05:47:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-18T05:47:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-18T05:47:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同期ネットワークの最適化ランドスケープ（On the Landscape of Synchronization Networks: A Perspective from Nonconvex Optimization）</news:title>
   <news:publication_date>2026-06-18T04:55:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701976</loc>
  <lastmod>2026-06-18T04:55:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習から得た知識でロボットの表現と推論を統合する（Robot Representation and Reasoning with Knowledge from Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-18T04:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701974</loc>
  <lastmod>2026-06-18T04:55:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転倒を防ぐ「一歩」を学習する技術 — Learning to Improve Capture Steps for Disturbance Rejection in Humanoid Soccer（Learning to Improve Capture Steps for Disturbance Rejection in Humanoid Soccer）</news:title>
   <news:publication_date>2026-06-18T04:55:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701972</loc>
  <lastmod>2026-06-18T04:54:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係性を学ぶ予測モデルが変えるマルチエージェント学習（Relational Forward Models for Multi-Agent Learning）</news:title>
   <news:publication_date>2026-06-18T04:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701970</loc>
  <lastmod>2026-06-18T04:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限記憶を伴う場面横断的語彙学習（Cross-situational learning of large lexicons with finite memory）</news:title>
   <news:publication_date>2026-06-18T04:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701968</loc>
  <lastmod>2026-06-18T04:54:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話し言葉パスフレーズ検証とi-vector空間の応用（Spoken Pass-Phrase Verification in the i-vector Space）</news:title>
   <news:publication_date>2026-06-18T04:54:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701966</loc>
  <lastmod>2026-06-18T04:53:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SConE: キーポイントの「隣人関係」を埋め込む新しい特徴量（SConE: Siamese Constellation Embedding Descriptor for Image Matching）</news:title>
   <news:publication_date>2026-06-18T04:53:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701964</loc>
  <lastmod>2026-06-18T04:02:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な線形バンディットと行列スケッチ（Efficient Linear Bandits through Matrix Sketching）</news:title>
   <news:publication_date>2026-06-18T04:02:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701962</loc>
  <lastmod>2026-06-18T04:02:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ApolloScapeデータセット上の注目点検出器安定性評価（Interest point detectors stability evaluation on ApolloScape dataset）</news:title>
   <news:publication_date>2026-06-18T04:02:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701960</loc>
  <lastmod>2026-06-18T04:01:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SIGUA: ラベルノイズ下の学習で「忘れる」ことが有効である理由（SIGUA: Forgetting May Make Learning with Noisy Labels More Robust）</news:title>
   <news:publication_date>2026-06-18T04:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701958</loc>
  <lastmod>2026-06-18T04:01:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空撮画像における建物検出のCNN融合（CNNs Fusion for Building Detection in Aerial Images）</news:title>
   <news:publication_date>2026-06-18T04:01:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701956</loc>
  <lastmod>2026-06-18T04:01:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>保守予測におけるコスト感度学習（Cost-Sensitive Learning for Predictive Maintenance）</news:title>
   <news:publication_date>2026-06-18T04:01:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701954</loc>
  <lastmod>2026-06-18T04:01:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移銀河におけるHeIIλ1640放射の性質と意味（Exploring Heiiλ1640 emission line properties at z = 2 −4）</news:title>
   <news:publication_date>2026-06-18T04:01:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701952</loc>
  <lastmod>2026-06-18T04:00:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>準備された実験データが示す ― カイオン断片化関数とSIDISにおける成果（Hadron Multiplicity and Fragmentation in SIDIS）</news:title>
   <news:publication_date>2026-06-18T04:00:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701950</loc>
  <lastmod>2026-06-18T03:09:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン固有集約モジュールによるドメイン一般化（Domain Generalization with Domain-Specific Aggregation Modules）</news:title>
   <news:publication_date>2026-06-18T03:09:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701948</loc>
  <lastmod>2026-06-18T03:09:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フードジャーナリングアプリの良し悪しを読み解く（The Good, The Bad &amp;amp; The Ugly Features: A Meta-analysis on User Review About Food Journaling Apps）</news:title>
   <news:publication_date>2026-06-18T03:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701946</loc>
  <lastmod>2026-06-18T03:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声・映像を統合した複数話者トラッキングの変分ベイズ推論（Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers）</news:title>
   <news:publication_date>2026-06-18T03:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701944</loc>
  <lastmod>2026-06-18T03:08:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語画像から筆者を特定する深層適応学習（Deep Adaptive Learning for Writer Identification based on Single Handwritten Word Images）</news:title>
   <news:publication_date>2026-06-18T03:08:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701942</loc>
  <lastmod>2026-06-18T03:08:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化する学習可能なダイナミカルネットワーク（Self-organizing dynamical networks able to learn autonomously）</news:title>
   <news:publication_date>2026-06-18T03:08:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701940</loc>
  <lastmod>2026-06-18T03:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>子どものオンラインプライバシー支援は十分か（Are Children Well-Supported by Their Parents Concerning Online Privacy Risks, and Who Supports the Parents?）</news:title>
   <news:publication_date>2026-06-18T03:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701938</loc>
  <lastmod>2026-06-18T03:07:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピックトロープス：映画トロープのデータセットの概要（Overview of PicTropes, a film trope dataset）</news:title>
   <news:publication_date>2026-06-18T03:07:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701936</loc>
  <lastmod>2026-06-18T02:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SeqSleepNet: シーケンス対シーケンス自動睡眠ステージ分類の階層型RNN（SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging）</news:title>
   <news:publication_date>2026-06-18T02:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701934</loc>
  <lastmod>2026-06-18T02:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑ネットワークとしての深層学習（Deep learning systems as complex networks）</news:title>
   <news:publication_date>2026-06-18T02:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701932</loc>
  <lastmod>2026-06-18T02:15:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半透明物体の深度復元技術（Depth Reconstruction of Translucent Objects from a Single Time-of-Flight Camera using Deep Residual Networks）</news:title>
   <news:publication_date>2026-06-18T02:15:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701930</loc>
  <lastmod>2026-06-18T02:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wikistat 2.0：人工知能教育のための教材群 (Wikistat 2.0: Educational Resources for Artificial Intelligence)</news:title>
   <news:publication_date>2026-06-18T02:15:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701928</loc>
  <lastmod>2026-06-18T02:14:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単発推論で信頼度を較正する手法の意義（Learning for Single-Shot Confidence Calibration in Deep Neural Networks through Stochastic Inferences）</news:title>
   <news:publication_date>2026-06-18T02:14:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701926</loc>
  <lastmod>2026-06-18T02:14:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声に対する敵対的事例の特徴付け：時間的依存性の活用 (CHARACTERIZING AUDIO ADVERSARIAL EXAMPLES USING TEMPORAL DEPENDENCY)</news:title>
   <news:publication_date>2026-06-18T02:14:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701924</loc>
  <lastmod>2026-06-18T02:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HyperST-Netによる時空間予測の新展開 (HyperST-Net: Hypernetworks for Spatio-Temporal Forecasting)</news:title>
   <news:publication_date>2026-06-18T02:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701922</loc>
  <lastmod>2026-06-18T01:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>H∞ノルム推定の最小最大下界（Minimax Lower Bounds for H∞-Norm Estimation）</news:title>
   <news:publication_date>2026-06-18T01:22:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701920</loc>
  <lastmod>2026-06-18T01:14:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移可能で頑健な文表現の学習（LEARNING ROBUST, TRANSFERABLE SENTENCE REPRESENTATIONS FOR TEXT CLASSIFICATION）</news:title>
   <news:publication_date>2026-06-18T01:14:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701918</loc>
  <lastmod>2026-06-18T01:14:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市計画図に対するU-Netベースのセマンティックセグメンテーション（SEMANTIC SEGMENTATION FOR URBAN PLANNING MAPS BASED ON U-NET）</news:title>
   <news:publication_date>2026-06-18T01:14:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701916</loc>
  <lastmod>2026-06-18T01:14:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トポロジーを考慮したドープグラフェンのバンドギャップ予測に深層学習を適用する意義（Deep Learning Bandgaps of Topologically Doped Graphene）</news:title>
   <news:publication_date>2026-06-18T01:14:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701914</loc>
  <lastmod>2026-06-18T01:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUネットワークにおける局所最適性検査と鞍点回避の効率的手法（EFFICIENTLY TESTING LOCAL OPTIMALITY AND ESCAPING SADDLES FOR RELU NETWORKS）</news:title>
   <news:publication_date>2026-06-18T01:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701912</loc>
  <lastmod>2026-06-18T01:12:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>作業記憶課題を解くためのマルチタスクと転移学習の活用（Using Multi-task and Transfer Learning to Solve Working Memory Tasks）</news:title>
   <news:publication_date>2026-06-18T01:12:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701910</loc>
  <lastmod>2026-06-18T01:12:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ生成のための頑健な表現符号化（Encoding robust representation for graph generation）</news:title>
   <news:publication_date>2026-06-18T01:12:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701908</loc>
  <lastmod>2026-06-18T00:20:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図を学習して不整脈を自動診断する手法（Computer-Aided Arrhythmia Diagnosis by Learning ECG Signal）</news:title>
   <news:publication_date>2026-06-18T00:20:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701906</loc>
  <lastmod>2026-06-18T00:20:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-18T00:19:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SVMで学ぶ信頼度セットの構築（Learning Confidence Sets using Support Vector Machines）</news:title>
   <news:publication_date>2026-06-18T00:19:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/701900</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆輸送ネットワークによる物理知覚の学習（Inverse Transport Networks）</news:title>
   <news:publication_date>2026-06-18T00:19:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/701898</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い検出の限界と線形スペクトル統計に基づく検定（Weak detection in the spiked Wigner model）</news:title>
   <news:publication_date>2026-06-18T00:19:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/701896</loc>
  <lastmod>2026-06-18T00:19:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界誘導特徴集約ネットワークによる顕著物体検出（Boundary-guided Feature Aggregation Network for Salient Object Detection）</news:title>
   <news:publication_date>2026-06-18T00:19:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/701894</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>長期個人メモリを用いた検索型パーソナル質問応答のF1直接最適化（Direct Optimization of F-measure for Retrieval-based Personal Question Answering）</news:title>
   <news:publication_date>2026-06-17T23:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/701892</loc>
  <lastmod>2026-06-17T23:27:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ATRIAS二足歩行ロボットにおける深層強化学習で学ぶ高次方策（Using Deep Reinforcement Learning to Learn High-Level Policies on the ATRIAS Biped）</news:title>
   <news:publication_date>2026-06-17T23:27:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701890</loc>
  <lastmod>2026-06-17T23:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的敵対的能動学習による教師なし外れ値検出（Generative Adversarial Active Learning for Unsupervised Outlier Detection）</news:title>
   <news:publication_date>2026-06-17T23:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701888</loc>
  <lastmod>2026-06-17T23:26:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FanStoreによる分散Deep Learning向けI/O最適化（FanStore: Enabling Efficient and Scalable I/O for Distributed Deep Learning）</news:title>
   <news:publication_date>2026-06-17T23:26:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701886</loc>
  <lastmod>2026-06-17T23:26:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協働ロボットのデモからの学習：隠れマルコフモデルによる状態分布学習（Collaborative Robot Learning from Demonstrations using Hidden Markov Model State Distribution）</news:title>
   <news:publication_date>2026-06-17T23:26:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701884</loc>
  <lastmod>2026-06-17T23:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッドニューラルネットワークによるレーダー自動目標認識（A HYBRID NEURAL NETWORK FRAMEWORK AND APPLICATION TO RADAR AUTOMATIC TARGET RECOGNITION）</news:title>
   <news:publication_date>2026-06-17T23:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701882</loc>
  <lastmod>2026-06-17T23:26:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者リスク評価と警告症状検出の実運用（Patient Risk Assessment and Warning Symptom Detection Using Deep Attention-Based Neural Networks）</news:title>
   <news:publication_date>2026-06-17T23:26:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701880</loc>
  <lastmod>2026-06-17T22:34:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルを壊さずに変える感度解析（Model-Preserving Sensitivity Analysis for Families of Gaussian Distributions）</news:title>
   <news:publication_date>2026-06-17T22:34:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701878</loc>
  <lastmod>2026-06-17T22:34:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>筆記体風景文字の解析と深層畳み込み線形ピラミッド（Cursive Scene Text Analysis by Deep Convolutional Linear Pyramids）</news:title>
   <news:publication_date>2026-06-17T22:34:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701876</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>因果経路に紐づく個別効果の推定（Estimation of Personalized Effects Associated With Causal Pathways）</news:title>
   <news:publication_date>2026-06-17T22:33:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701874</loc>
  <lastmod>2026-06-17T22:33:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUニューラルネットワーク学習の計算複雑性 (Complexity of Training ReLU Neural Network)</news:title>
   <news:publication_date>2026-06-17T22:33:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701872</loc>
  <lastmod>2026-06-17T22:33:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カリキュラム学習におけるシラバス比較（An Empirical Comparison of Syllabuses for Curriculum Learning）</news:title>
   <news:publication_date>2026-06-17T22:33:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701870</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-17T22:33:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701868</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>身近な空間で学び動く：到達と把持の学習（Learning and Acting in Peripersonal Space: Moving, Reaching, and Grasping）</news:title>
   <news:publication_date>2026-06-17T22:32:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701866</loc>
  <lastmod>2026-06-17T21:41:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索的モデル解析のためのユーザベースの可視分析ワークフロー（A User-based Visual Analytics Workflow for Exploratory Model Analysis）</news:title>
   <news:publication_date>2026-06-17T21:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701864</loc>
  <lastmod>2026-06-17T21:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ推論のための適応型ガウス過程代理モデル（Adaptive Gaussian process surrogates for Bayesian inference）</news:title>
   <news:publication_date>2026-06-17T21:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701862</loc>
  <lastmod>2026-06-17T21:31:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Morpho-MNISTによる表現学習の定量評価（Morpho‑MNIST: Quantitative Assessment and Diagnostics for Representation Learning）</news:title>
   <news:publication_date>2026-06-17T21:31:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701860</loc>
  <lastmod>2026-06-17T21:30:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的プログラミング入門（An Introduction to Probabilistic Programming）</news:title>
   <news:publication_date>2026-06-17T21:30:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701858</loc>
  <lastmod>2026-06-17T21:30:05Z</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>2026-06-17T21:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701856</loc>
  <lastmod>2026-06-17T21:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己注意型オートエンコーダと近傍影響を用いたPOI推薦（Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence）</news:title>
   <news:publication_date>2026-06-17T21:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701854</loc>
  <lastmod>2026-06-17T21:29:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己符号化ノックオフ生成器によるFDR制御変数選択（Auto-Encoding Knockoff Generator for FDR Controlled Variable Selection）</news:title>
   <news:publication_date>2026-06-17T21:29:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701852</loc>
  <lastmod>2026-06-17T20:37:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密集群衆のインタラクティブ監視技術（Interactive Surveillance Technologies for Dense Crowds）</news:title>
   <news:publication_date>2026-06-17T20:37:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701850</loc>
  <lastmod>2026-06-17T20:37:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>あるクラスの深層ニューラルネットワークの損失地形に関する知見（ON THE LOSS LANDSCAPE OF A CLASS OF DEEP NEURAL NETWORKS WITH NO BAD LOCAL VALLEYS）</news:title>
   <news:publication_date>2026-06-17T20:37:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701848</loc>
  <lastmod>2026-06-17T20:36:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェア難読化に対する機械学習を用いた構造解析攻撃（SAIL: Machine Learning Guided Structural Analysis Attack on Hardware Obfuscation）</news:title>
   <news:publication_date>2026-06-17T20:36:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701846</loc>
  <lastmod>2026-06-17T20:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顧客対応音声理解のための自動データ拡張（AUTOMATIC DATA EXPANSION FOR CUSTOMER-CARE SPOKEN LANGUAGE UNDERSTANDING）</news:title>
   <news:publication_date>2026-06-17T20:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701844</loc>
  <lastmod>2026-06-17T20:35:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量時系列における希少事象分類（Rare Event Classification in Multivariate Time Series）</news:title>
   <news:publication_date>2026-06-17T20:35:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701842</loc>
  <lastmod>2026-06-17T20:34:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T20:34:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701840</loc>
  <lastmod>2026-06-17T20:34:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール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>
   <news:publication_date>2026-06-17T20:34:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701838</loc>
  <lastmod>2026-06-17T19:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T19:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701836</loc>
  <lastmod>2026-06-17T19:43:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T19:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701834</loc>
  <lastmod>2026-06-17T19:42:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T19:42:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701832</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-17T19:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701830</loc>
  <lastmod>2026-06-17T19:41:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバストな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>
   <news:publication_date>2026-06-17T19:41:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701828</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>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>
   <news:publication_date>2026-06-17T19:41:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701826</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>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>
   <news:publication_date>2026-06-17T19:41:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701824</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>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>
   <news:publication_date>2026-06-17T18:48:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701822</loc>
  <lastmod>2026-06-17T18:47:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きWaveGAN（Conditional WaveGAN）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701820</loc>
  <lastmod>2026-06-17T18:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T18:47:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701818</loc>
  <lastmod>2026-06-17T18:47:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T18:47:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701816</loc>
  <lastmod>2026-06-17T18:46:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T18:46:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701814</loc>
  <lastmod>2026-06-17T18:46:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類における反事実的公平性と頑健性（Counterfactual Fairness in Text Classification through Robustness）</news:title>
   <news:publication_date>2026-06-17T18:46:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701812</loc>
  <lastmod>2026-06-17T18:46:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T18:46:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701810</loc>
  <lastmod>2026-06-17T17:55:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T17:55:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701808</loc>
  <lastmod>2026-06-17T17:47:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T17:47:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701806</loc>
  <lastmod>2026-06-17T17:47:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル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>
   <news:publication_date>2026-06-17T17:47:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701804</loc>
  <lastmod>2026-06-17T17:46:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T17:46:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701802</loc>
  <lastmod>2026-06-17T17:46:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T17:46:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701800</loc>
  <lastmod>2026-06-17T17:46:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T17:46:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701798</loc>
  <lastmod>2026-06-17T17:46:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-17T17:46:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701796</loc>
  <lastmod>2026-06-17T16:54:59Z</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>
   <news:publication_date>2026-06-17T16:54:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701794</loc>
  <lastmod>2026-06-17T16:54:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T16:54:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701792</loc>
  <lastmod>2026-06-17T16:53:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングとホログラフィックQCD (Deep Learning and Holographic QCD)</news:title>
   <news:publication_date>2026-06-17T16:53:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701790</loc>
  <lastmod>2026-06-17T16:52:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース化された勾配法の収束性（The Convergence of Sparsified Gradient Methods）</news:title>
   <news:publication_date>2026-06-17T16:52:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701788</loc>
  <lastmod>2026-06-17T16:52:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T16:52:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701786</loc>
  <lastmod>2026-06-17T16:52:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Kernel Neural Ranking Modelの一貫性と変動（Consistency and Variation in Kernel Neural Ranking Model）</news:title>
   <news:publication_date>2026-06-17T16:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/701784</loc>
  <lastmod>2026-06-17T16:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-06-17T16:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <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>
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   <news:publication_date>2026-06-17T15:06:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/701758</loc>
  <lastmod>2026-06-17T15:06:06Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
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  <loc>https://aibr.jp/archives/701756</loc>
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