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   <news:title>マージンに基づく並列コーパス採掘と多言語文埋め込み（Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings）</news:title>
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   <news:title>複数言語の単語埋め込みを無監督で整列させる手法（UNSUPERVISED HYPERALIGNMENT FOR MULTILINGUAL WORD EMBEDDINGS）</news:title>
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   <news:title>VIREL: 強化学習を変える変分推論フレームワーク（VIREL: A Variational Inference Framework for Reinforcement Learning）</news:title>
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   <news:title>属性制御を保ちながら文を変換する手法（Content Preserving Text Generation with Attribute Controls）</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>機械学習におけるセキュリティとプライバシーの全地図（A Marauder’s Map of Security and Privacy in Machine Learning）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>手首軟骨のMRI自動セグメンテーションを深層学習で実現する（Deep learning-based fully automatic segmentation of wrist cartilage in MR images）</news:title>
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  <lastmod>2026-07-01T01:01:22Z</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>トポロジーに基づく深層学習アプローチ（Topological Approaches to Deep Learning）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>複雑な質問応答のためのクエリグラフランキング学習（Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs）</news:title>
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   <news:title>VRローラーコースターにおける酔い予測の機械学習（Machine learning architectures to predict motion sickness using a Virtual Reality rollercoaster simulation tool）</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>Prior Knowledge Integration for Neural Machine Translation using Posterior Regularization（Prior Knowledge Integration for Neural Machine Translation using Posterior Regularization）</news:title>
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   <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>音響シーン認識に必要な聴取時間の研究（Beyond Equal-Length Snippets: How Long is Sufficient to Recognize an Audio Scene?）</news:title>
   <news:publication_date>2026-07-01T00:59:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-01T00:59:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>PBR定理と量子力学の統計解釈（Does the PBR Theorem Rule out a Statistical Understanding of QM?）</news:title>
   <news:publication_date>2026-07-01T00:59:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706742</loc>
  <lastmod>2026-07-01T00:08:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>分離および重複音響イベント検出の統一（Unifying Isolated and Overlapping Audio Event Detection with Multi-Label Multi-Task Convolutional Recurrent Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>言語バリエティへのニューラル機械翻訳（Neural Machine Translation into Language Varieties）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706738</loc>
  <lastmod>2026-07-01T00:07:55Z</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>CT灌流スキャンにおける虚血性脳卒中病変のセグメンテーション（Ischemic Stroke Lesion Segmentation in CT Perfusion Scans using Pyramid Pooling and Focal Loss）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-01T00:06:36Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ニューラルネット距離のミニマックス推定（Minimax Estimation of Neural Net Distance）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-01T00:06:29Z</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>Gradient Graphsによる知識ベース補完の拡張（Augmenting Compositional Models for Knowledge Base Completion Using Gradient Representations）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-01T00:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>皮膚病変分類に使われる深層学習の根拠 (What evidence does deep learning model use to classify Skin Lesions?)</news:title>
   <news:publication_date>2026-07-01T00:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-01T00:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>セミデフィニット緩和による敵対的事例へのロバスト性認証（Semidefinite relaxations for certifying robustness to adversarial examples）</news:title>
   <news:publication_date>2026-07-01T00:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706728</loc>
  <lastmod>2026-06-30T23:14:23Z</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>スケーラブルな深層kサブスペースクラスタリング（Scalable Deep k-Subspace Clustering）</news:title>
   <news:publication_date>2026-06-30T23:14:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T23:13:49Z</lastmod>
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    <news:language>ja</news:language>
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   <news:title>HCI教育におけるサイエンスフィクション活用の論拠（Building an Argument for the Use of Science Fiction in HCI Education）</news:title>
   <news:publication_date>2026-06-30T23:13:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T23:13:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>トレーニングデータを使わない不可視の攻撃手法の衝撃（TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-30T23:13:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706722</loc>
  <lastmod>2026-06-30T23:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>AiDroidによるリアルタイムAndroidマルウェア検出の実務的意義（AiDroid: When Heterogeneous Information Network Marries Deep Neural Network for Real-time Android Malware Detection）</news:title>
   <news:publication_date>2026-06-30T23:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-30T23:13:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェットのエントロピー（The Entropy of a Jet）</news:title>
   <news:publication_date>2026-06-30T23:13:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706718</loc>
  <lastmod>2026-06-30T23:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短文ソーシャル投稿のための単純注意表現学習（Simple Attention-Based Representation Learning for Ranking Short Social Media Posts）</news:title>
   <news:publication_date>2026-06-30T23:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706716</loc>
  <lastmod>2026-06-30T23:12:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な対話モデルを教師なしで学ぶ（An Unsupervised Approach for Learning Interpretable Dialog Models）</news:title>
   <news:publication_date>2026-06-30T23:12:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706714</loc>
  <lastmod>2026-06-30T22:21:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可逆的残差ネットワークの実用的意義（Invertible Residual Networks）</news:title>
   <news:publication_date>2026-06-30T22:21:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706712</loc>
  <lastmod>2026-06-30T22:12:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル言語モデルにおけるドロップアウトと誤差累積の解析 (Analysing Dropout and Compounding Errors in Neural Language Models)</news:title>
   <news:publication_date>2026-06-30T22:12:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706710</loc>
  <lastmod>2026-06-30T22:12:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMの形式言語に対する一般化能力の評価（On Evaluating the Generalization of LSTM Models in Formal Languages）</news:title>
   <news:publication_date>2026-06-30T22:12:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/706708</loc>
  <lastmod>2026-06-30T22:11:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストイフェル多様体上の非滑らか最適化に対する近接勾配法（Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold）</news:title>
   <news:publication_date>2026-06-30T22:11:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/706706</loc>
  <lastmod>2026-06-30T22:10:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デジタルゲーム学習における視線計測でパフォーマンスを評価する方法（EXPLORING GAZE BEHAVIOR TO ASSESS PERFORMANCE IN DIGITAL GAME-BASED LEARNING SYSTEMS）</news:title>
   <news:publication_date>2026-06-30T22:10:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/706704</loc>
  <lastmod>2026-06-30T22:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CapsAccによるCapsuleNet向け専用アクセラレータの提案（CapsAcc: An Efficient Hardware Accelerator for CapsuleNets with Data Reuse）</news:title>
   <news:publication_date>2026-06-30T22:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/706702</loc>
  <lastmod>2026-06-30T22:10:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データに対する深層生成モデルによる異常検知（Anomaly Detection for imbalanced datasets with Deep Generative Models）</news:title>
   <news:publication_date>2026-06-30T22:10:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/706700</loc>
  <lastmod>2026-06-30T21:18:38Z</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>
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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: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: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:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-30T21:07:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-30T21:06:53Z</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>最適近似ノイズ除去行列を用いたDantzig Selectorと強化学習への応用 (Dantzig Selector with an Approximately Optimal Denoising Matrix and its Application to Reinforcement Learning)</news:title>
   <news:publication_date>2026-06-30T21:06:34Z</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>テンソルネットワークに基づくスペクトル手法（Spectral Methods from Tensor Networks）</news:title>
   <news:publication_date>2026-06-30T20:15:38Z</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>高次元特徴ベクトルの高速クラスタリングアルゴリズム（A Fast Algorithm for Clustering of High Dimensional Feature Vectors）</news:title>
   <news:publication_date>2026-06-30T20:15:25Z</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>空間記憶の再生は認知地図の位相変動を抑制する（Replays of spatial memories suppress topological fluctuations in cognitive map）</news:title>
   <news:publication_date>2026-06-30T20:14:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-30T20:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波をそのまま読むCNNによるてんかん発作予測（Convolutional Neural Networks for Epileptic Seizure Prediction）</news:title>
   <news:publication_date>2026-06-30T20:14:26Z</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>比較情報に基づく階層的クラスタリングの基礎（Foundations of Comparison-Based Hierarchical Clustering）</news:title>
   <news:publication_date>2026-06-30T20:14:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-30T20:14:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互注視で音響特徴を融合する多チャネル深層アーキテクチャ（Acoustic Features Fusion using Attentive Multi-channel Deep Architecture）</news:title>
   <news:publication_date>2026-06-30T20:14:05Z</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>2026-06-30T20:13:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/706672</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一モデルでの不確実性評価が変える現場運用（Single-Model Uncertainties for Deep Learning）</news:title>
   <news:publication_date>2026-06-30T19:22:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/706670</loc>
  <lastmod>2026-06-30T19:22:20Z</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>2026-06-30T19:22:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/706668</loc>
  <lastmod>2026-06-30T19:22:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河中心の候補パーセク級ジェットの深堀り（A Deep Chandra View of a Candidate Parsec-Scale Jet from the Galactic Center Super-massive Black Hole）</news:title>
   <news:publication_date>2026-06-30T19:22:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706666</loc>
  <lastmod>2026-06-30T19:21:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SlicStanにおける密度を用いた確率的プログラミング（Probabilistic Programming with Densities in SlicStan: Efficient, Flexible and Deterministic）</news:title>
   <news:publication_date>2026-06-30T19:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/706664</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>2026-06-30T19:21:00Z</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>
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   <news:publication_date>2026-06-30T19:20:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706660</loc>
  <lastmod>2026-06-30T19:20:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療文書におけるテキスト分類の実証比較（Feature Selection and Classifier Comparison for Medical Document Classification）</news:title>
   <news:publication_date>2026-06-30T19:20:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706658</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>2026-06-30T18:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706656</loc>
  <lastmod>2026-06-30T18:29:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多核カーネル回帰とスパース制約（Multi-Kernel Regression with Sparsity Constraint）</news:title>
   <news:publication_date>2026-06-30T18:29:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706654</loc>
  <lastmod>2026-06-30T18:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル環境に強い周囲眼部認証のための異種性配慮深層埋め込み（Heterogeneity Aware Deep Embedding for Mobile Periocular Recognition）</news:title>
   <news:publication_date>2026-06-30T18:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706652</loc>
  <lastmod>2026-06-30T18:28:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直観主義命題論理における自動定理証明（Automated Theorem Proving in Intuitionistic Propositional Logic）</news:title>
   <news:publication_date>2026-06-30T18:28:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706650</loc>
  <lastmod>2026-06-30T18:27:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OrthoNet：多層ネットワークデータのクラスタリング (OrthoNet: Multilayer Network Data Clustering)</news:title>
   <news:publication_date>2026-06-30T18:27:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706648</loc>
  <lastmod>2026-06-30T18:27:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PDFに潜む敵対的マルウェア検出の教訓（Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks）</news:title>
   <news:publication_date>2026-06-30T18:27:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706646</loc>
  <lastmod>2026-06-30T18:27:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>批判的言語モデルを用いたエンドツーエンド音声認識の敵対的訓練 (Adversarial Training of End-to-End Speech Recognition Using a Criticizing Language Model)</news:title>
   <news:publication_date>2026-06-30T18:27:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706644</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>適応的順位付けに基づく制約処理（Adaptive Ranking-based Constraint Handling for Explicitly Constrained Black-Box Optimization）</news:title>
   <news:publication_date>2026-06-30T17:35:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706642</loc>
  <lastmod>2026-06-30T17:27:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層最適化（Deep Optimisation: Solving Combinatorial Optimisation Problems using Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-30T17:27:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706640</loc>
  <lastmod>2026-06-30T17:27:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド注釈での系列タグ付けを改善するベイジアン手法（A Bayesian Approach for Sequence Tagging with Crowds）</news:title>
   <news:publication_date>2026-06-30T17:27:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706638</loc>
  <lastmod>2026-06-30T17:26:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗号化データ上で動作する初のGPU対応ホモモルフィックCNN（Towards the AlexNet Moment for Homomorphic Encryption: HCNN, the First Homomorphic CNN on Encrypted Data with GPUs）</news:title>
   <news:publication_date>2026-06-30T17:26:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706636</loc>
  <lastmod>2026-06-30T17:25:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ChemBoost：化学言語で予測するタンパク質–リガンド結合親和性（ChemBoost: A chemical language based approach for protein–ligand binding affinity prediction）</news:title>
   <news:publication_date>2026-06-30T17:25:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706634</loc>
  <lastmod>2026-06-30T17:25:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多忠実度ガウス過程によるベイズ最適化の一般枠組み（A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes）</news:title>
   <news:publication_date>2026-06-30T17:25:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706632</loc>
  <lastmod>2026-06-30T17:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字列カーネルを用いた推移学習によるクロスドメイン文書分類（Transductive Learning with String Kernels for Cross-Domain Text Classification）</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>
   <news:title>臨床長期データからの確率モデルの効果的学習（Effective Learning of Probabilistic Models for Clinical Predictions from Longitudinal Data）</news:title>
   <news:publication_date>2026-06-30T16:33:27Z</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>確信を持った患者リスクの階層化（Risk-Stratify: Confident Stratification Of Patients Based On Risk）</news:title>
   <news:publication_date>2026-06-30T16:32:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706626</loc>
  <lastmod>2026-06-30T16:32:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ汚染攻撃がデータ洗浄防御を破る（Stronger Data Poisoning Attacks Break Data Sanitization Defenses）</news:title>
   <news:publication_date>2026-06-30T16:32:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706624</loc>
  <lastmod>2026-06-30T16:31:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称情報構造下のオンライン二次最適化における学習型制御方針と後悔解析（Learning Based Control Policy and Regret Analysis for Online Quadratic Optimization with Asymmetric Information Structure）</news:title>
   <news:publication_date>2026-06-30T16:31:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706622</loc>
  <lastmod>2026-06-30T16:31:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳ネットワーク解析のための高次グラフ畳み込みを使った類似度学習（Similarity Learning with Higher-Order Graph Convolutions for Brain Network Analysis）</news:title>
   <news:publication_date>2026-06-30T16:31:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706620</loc>
  <lastmod>2026-06-30T16:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市交通をグラフで同時予測する手法（Efficient Metropolitan Traffic Prediction Based on Graph Recurrent Neural Network）</news:title>
   <news:publication_date>2026-06-30T16:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706618</loc>
  <lastmod>2026-06-30T16:30:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル機械翻訳におけるカリキュラム学習の実証的探究 (An Empirical Exploration of Curriculum Learning for Neural Machine Translation)</news:title>
   <news:publication_date>2026-06-30T16:30:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706616</loc>
  <lastmod>2026-06-30T15:39:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック構造学習のためのディリクレ信念ネットワーク（Dirichlet Belief Networks for Topic Structure Learning）</news:title>
   <news:publication_date>2026-06-30T15:39:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706614</loc>
  <lastmod>2026-06-30T15:38:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成音声で学習を拡張する音声認識（Training Neural Speech Recognition Systems with Synthetic Speech Augmentation）</news:title>
   <news:publication_date>2026-06-30T15:38:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706612</loc>
  <lastmod>2026-06-30T15:37:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTにおける現実的なボットネットデータセットの開発（Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset）</news:title>
   <news:publication_date>2026-06-30T15:37:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706610</loc>
  <lastmod>2026-06-30T15:37:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の駆動を伴う潜在分数次力学の学習（Learning Latent Fractional dynamics with Unknown Unknowns）</news:title>
   <news:publication_date>2026-06-30T15:37:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706608</loc>
  <lastmod>2026-06-30T15:37:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似性特徴と深層表現学習を組み合わせたスタンス検出（Combining Similarity Features and Deep Representation Learning for Stance Detection）</news:title>
   <news:publication_date>2026-06-30T15:37:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706606</loc>
  <lastmod>2026-06-30T15:36:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ノイズ付きウェブデータから学ぶ再重み付け（Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification）</news:title>
   <news:publication_date>2026-06-30T15:36:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706604</loc>
  <lastmod>2026-06-30T15:36:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Noise Contrastive Estimationによるスケーラブルな線形推薦（Noise Contrastive Estimation for Scalable Linear Models for One-Class Collaborative Filtering）</news:title>
   <news:publication_date>2026-06-30T15:36:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706602</loc>
  <lastmod>2026-06-30T14:44:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間的変位畳み込みによる映像予測（SDC-Net: Video prediction using spatially-displaced convolution）</news:title>
   <news:publication_date>2026-06-30T14:44:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706600</loc>
  <lastmod>2026-06-30T14:36:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の影響を考慮したニューロン点過程のデータ駆動モデル（Data-driven Perception of Neuron Point Process with Unknown Unknowns）</news:title>
   <news:publication_date>2026-06-30T14:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706598</loc>
  <lastmod>2026-06-30T14:36:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語を問いから答えへ移す力を測るデータセット（Zero-Shot Transfer VQA Dataset）</news:title>
   <news:publication_date>2026-06-30T14:36:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706596</loc>
  <lastmod>2026-06-30T14:36:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガイダーネットワークを用いた系列生成（Sequence Generation with Guider Network）</news:title>
   <news:publication_date>2026-06-30T14:36:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706594</loc>
  <lastmod>2026-06-30T14:35:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的アンサンブル選択におけるプロトタイプ選択手法の評価 (Analyzing different prototype selection techniques for dynamic classifier and ensemble selection)</news:title>
   <news:publication_date>2026-06-30T14:35:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706592</loc>
  <lastmod>2026-06-30T14:35:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的ニューラルネットワークによる多変量分布の準乱数サンプリング（Quasi-random sampling for multivariate distributions via generative neural networks）</news:title>
   <news:publication_date>2026-06-30T14:35:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706590</loc>
  <lastmod>2026-06-30T14:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一隠れ層ベイズニューラルネットワークの閉形式変分目的関数（Closed Form Variational Objectives For Bayesian Neural Networks with a Single Hidden Layer）</news:title>
   <news:publication_date>2026-06-30T14:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706588</loc>
  <lastmod>2026-06-30T13:42:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的アンサンブル選択のメタ学習による枠組み（On Meta-Learning for Dynamic Ensemble Selection）</news:title>
   <news:publication_date>2026-06-30T13:42:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706586</loc>
  <lastmod>2026-06-30T13:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>META-DES.Hに基づく動的アンサンブル選択の要点解説（META-DES.H: a dynamic ensemble selection technique using meta-learning and a dynamic weighting approach）</news:title>
   <news:publication_date>2026-06-30T13:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706584</loc>
  <lastmod>2026-06-30T13:42:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>領域の品質を高める動的アンサンブル選択（A Method For Dynamic Ensemble Selection Based on a Filter and an Adaptive Distance to Improve the Quality of the Regions of Competence）</news:title>
   <news:publication_date>2026-06-30T13:42:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706582</loc>
  <lastmod>2026-06-30T13:40:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習向け浮動小数点の再考（Rethinking floating point for deep learning）</news:title>
   <news:publication_date>2026-06-30T13:40:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706580</loc>
  <lastmod>2026-06-30T13:40:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SGDの暗黙的正則化がNLPで示す意味（Implicit Regularization of Stochastic Gradient Descent in Natural Language Processing: Observations and Implications）</news:title>
   <news:publication_date>2026-06-30T13:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706578</loc>
  <lastmod>2026-06-30T13:40:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VizRecによる安全なデータ可視化の枠組み（VIZREC: A FRAMEWORK FOR SECURE DATA EXPLORATION VIA VISUAL REPRESENTATION）</news:title>
   <news:publication_date>2026-06-30T13:40:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706576</loc>
  <lastmod>2026-06-30T13:39:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティックセグメンテーションにおける予測誤差メタ分類（Prediction Error Meta Classification in Semantic Segmentation）</news:title>
   <news:publication_date>2026-06-30T13:39:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706574</loc>
  <lastmod>2026-06-30T12:47:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トロピカル幾何に基づく適応的プルーニングによるスプーフィング局在化（AN ADAPTIVE PRUNING ALGORITHM FOR SPOOFING LOCALISATION BASED ON TROPICAL GEOMETRY）</news:title>
   <news:publication_date>2026-06-30T12:47:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706572</loc>
  <lastmod>2026-06-30T12:37:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分ドロップアウトと経験ベイズによる自動関連決定（Variational Dropout via Empirical Bayes）</news:title>
   <news:publication_date>2026-06-30T12:37:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706570</loc>
  <lastmod>2026-06-30T12:37:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈と概念を同時に学ぶ多言語埋め込み Co+Co（Multilingual Embeddings Jointly Induced from Contexts and Concepts: Simple, Strong and Scalable）</news:title>
   <news:publication_date>2026-06-30T12:37:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706568</loc>
  <lastmod>2026-06-30T12:37:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホストログのメトリック空間定義と運用的応用（Defining a Metric Space of Host Logs and Operational Use Cases）</news:title>
   <news:publication_date>2026-06-30T12:37:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706566</loc>
  <lastmod>2026-06-30T12:37:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理・数学と深層学習の接点（Connections between physics, mathematics and deep learning）</news:title>
   <news:publication_date>2026-06-30T12:37:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706564</loc>
  <lastmod>2026-06-30T12:36:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続かつ非線形の希薄モデル（Functional Nonlinear Sparse Models）</news:title>
   <news:publication_date>2026-06-30T12:36:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706562</loc>
  <lastmod>2026-06-30T12:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付き有限状態トランスデューサの熱帯代数モデリング (TROPICAL MODELING OF WEIGHTED TRANSDUCER ALGORITHMS ON GRAPHS)</news:title>
   <news:publication_date>2026-06-30T12:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706560</loc>
  <lastmod>2026-06-30T11:45:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語順差がもたらす越境転移の難しさ（On Difficulties of Cross-Lingual Transfer with Order Differences: A Case Study on Dependency Parsing）</news:title>
   <news:publication_date>2026-06-30T11:45:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706558</loc>
  <lastmod>2026-06-30T11:45:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>典型的なLyα放射体のクラスタリング：宿主ハロー質量はLyαおよびUV光度に依存する（The clustering of typical Lyα emitters from z ∼2.5 −6: host halo masses depend on Lyα and UV luminosities）</news:title>
   <news:publication_date>2026-06-30T11:45:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706556</loc>
  <lastmod>2026-06-30T11:44:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数属性を扱うテキスト文体変換（Multiple-Attribute Text Style Transfer）</news:title>
   <news:publication_date>2026-06-30T11:44:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706554</loc>
  <lastmod>2026-06-30T11:43:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的事例の幾何学（On the Geometry of Adversarial Examples）</news:title>
   <news:publication_date>2026-06-30T11:43:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706552</loc>
  <lastmod>2026-06-30T11:43:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接k集約損失の最小化が分類性能を改善する（Minimizing Close-k Aggregate Loss Improves Classification）</news:title>
   <news:publication_date>2026-06-30T11:43:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706550</loc>
  <lastmod>2026-06-30T11:43:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形出力変換を伴う深層構造化予測（Deep Structured Prediction with Nonlinear Output Transformations）</news:title>
   <news:publication_date>2026-06-30T11:43:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706548</loc>
  <lastmod>2026-06-30T11:43:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事実ベースの視覚質問応答におけるグラフ畳み込みによる推論（Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering）</news:title>
   <news:publication_date>2026-06-30T11:43:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706546</loc>
  <lastmod>2026-06-30T10:52:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の注意の流れをモデル化する（Modeling Attention Flow on Graphs）</news:title>
   <news:publication_date>2026-06-30T10:52:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706544</loc>
  <lastmod>2026-06-30T10:44:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビーム探索方策の模倣学習（Learning Beam Search Policies via Imitation Learning）</news:title>
   <news:publication_date>2026-06-30T10:44:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706542</loc>
  <lastmod>2026-06-30T10:44:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩行者の多い環境での模倣によるナビゲーション（Navigation by Imitation in a Pedestrian–Rich Environment）</news:title>
   <news:publication_date>2026-06-30T10:44:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706540</loc>
  <lastmod>2026-06-30T10:43:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト生成モデルに対するデータ由来監査（Auditing Data Provenance in Text-Generation Models）</news:title>
   <news:publication_date>2026-06-30T10:43:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706538</loc>
  <lastmod>2026-06-30T10:42:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>付加製造物の構造性能向上手法（Enhancing the Structural Performance of Additively Manufactured Objects）</news:title>
   <news:publication_date>2026-06-30T10:42:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706536</loc>
  <lastmod>2026-06-30T10:42:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超高次元加法部分線形モデルのスパースモデル同定と学習（Sparse Model Identification and Learning for Ultra-high-dimensional Additive Partially Linear Models）</news:title>
   <news:publication_date>2026-06-30T10:42:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706534</loc>
  <lastmod>2026-06-30T10:42:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語非依存の注意ブリッジを用いた多言語ニューラル機械翻訳（Multilingual NMT with a language-independent attention bridge）</news:title>
   <news:publication_date>2026-06-30T10:42:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706532</loc>
  <lastmod>2026-06-30T09:50:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AttentionXMLによる極大多ラベルテキスト分類（AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification）</news:title>
   <news:publication_date>2026-06-30T09:50:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706530</loc>
  <lastmod>2026-06-30T09:50:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己符号化器による教師なし表現学習とドメイン間転移の解析（Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis）</news:title>
   <news:publication_date>2026-06-30T09:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706528</loc>
  <lastmod>2026-06-30T09:49:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス非依存な物体の数え上げ（Class-Agnostic Counting）</news:title>
   <news:publication_date>2026-06-30T09:49:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706526</loc>
  <lastmod>2026-06-30T09:49:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シフト学習で市民科学データのバイアスを補償する（Bias Reduction via End-to-End Shift Learning: Application to Citizen Science）</news:title>
   <news:publication_date>2026-06-30T09:49:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706524</loc>
  <lastmod>2026-06-30T09:48:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号付き決定過程の学習─主小行列割当問題を通して（Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem）</news:title>
   <news:publication_date>2026-06-30T09:48:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706522</loc>
  <lastmod>2026-06-30T09:48:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非ランダムに欠損する電子健康記録を解析する潜在トピックモデル（A latent topic model for mining heterogeneous non-randomly missing electronic health records data）</news:title>
   <news:publication_date>2026-06-30T09:48:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706520</loc>
  <lastmod>2026-06-30T09:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽コロナの性質と太陽風とのつながり (The Properties of the Solar Corona and Its Connection to the Solar Wind)</news:title>
   <news:publication_date>2026-06-30T09:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706518</loc>
  <lastmod>2026-06-30T08:56:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェームズ・ウェッブ望遠鏡で探る高赤方偏移超新星の検出と分類（DETECTION AND CLASSIFICATION OF SUPERNOVAE BEYOND Z ∼2 REDSHIFT WITH THE JAMES WEBB SPACE TELESCOPE）</news:title>
   <news:publication_date>2026-06-30T08:56:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706516</loc>
  <lastmod>2026-06-30T08:56:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照信号を使わない音源分離評価法（REFERENCELESS PERFORMANCE EVALUATION OF AUDIO SOURCE SEPARATION USING DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-30T08:56:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706514</loc>
  <lastmod>2026-06-30T08:56:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RW Aur Aの色・偏光変動の解析（Analysis of colour and polarimetric variability of RW Aur A in 2010–2018）</news:title>
   <news:publication_date>2026-06-30T08:56:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706512</loc>
  <lastmod>2026-06-30T08:55:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可換群作用の強外性とZ安定性の同値性（STRONGLY OUTER ACTIONS OF AMENABLE GROUPS ON Z-STABLE C*-ALGEBRAS）</news:title>
   <news:publication_date>2026-06-30T08:55:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706510</loc>
  <lastmod>2026-06-30T08:55:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>改良された共変性局所特徴検出の学習フレームワーク（An Improved Learning Framework for Covariant Local Feature Detection）</news:title>
   <news:publication_date>2026-06-30T08:55:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706508</loc>
  <lastmod>2026-06-30T08:55:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガンマ線バーストから高速電波バーストへ（From gamma-ray bursts to fast radio bursts）</news:title>
   <news:publication_date>2026-06-30T08:55:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706506</loc>
  <lastmod>2026-06-30T08:54:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔写真から風刺画を自動生成する技術の要諦（CariGAN: Caricature Generation through Weakly Paired Adversarial Learning）</news:title>
   <news:publication_date>2026-06-30T08:54:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706504</loc>
  <lastmod>2026-06-30T08:04:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Query指向型抽出要約を無教師で両段階で学ぶ（Unsupervised Dual-Cascade Learning with Pseudo-Feedback Distillation for Query-based Extractive Summarization）</news:title>
   <news:publication_date>2026-06-30T08:04:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706502</loc>
  <lastmod>2026-06-30T08:03:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ決定過程における時間的正則化（Temporal Regularization in Markov Decision Process）</news:title>
   <news:publication_date>2026-06-30T08:03:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706500</loc>
  <lastmod>2026-06-30T08:03:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Spark上で動く分散型ReliefFによる特徴選択（Distributed ReliefF based Feature Selection in Spark）</news:title>
   <news:publication_date>2026-06-30T08:03:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706498</loc>
  <lastmod>2026-06-30T08:02:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>真に教師なしの音声単語埋め込み――弱いトップダウン制約を用いたエンコーダ・デコーダモデルの提案（TRULY UNSUPERVISED ACOUSTIC WORD EMBEDDINGS USING WEAK TOP-DOWN CONSTRAINTS IN ENCODER-DECODER MODELS）</news:title>
   <news:publication_date>2026-06-30T08:02:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706496</loc>
  <lastmod>2026-06-30T08:02:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HD 95086のデブリ円盤におけるCOガスの深掘り探索（Deep ALMA Search for CO Gas in the HD 95086 Debris Disc）</news:title>
   <news:publication_date>2026-06-30T08:02:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706494</loc>
  <lastmod>2026-06-30T08:02:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dilated DenseNetsによる関係推論の効率化（Dilated DenseNets for Relational Reasoning）</news:title>
   <news:publication_date>2026-06-30T08:02:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706492</loc>
  <lastmod>2026-06-30T08:02:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乗法的潜在力モデルの解説（Multiplicative Latent Force Models）</news:title>
   <news:publication_date>2026-06-30T08:02:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706490</loc>
  <lastmod>2026-06-30T07:11:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>助け合い：顧客間の提案抽出のための枠組み (Helping Each Other: A Framework for Customer-to-Customer Suggestion Mining)</news:title>
   <news:publication_date>2026-06-30T07:11:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706488</loc>
  <lastmod>2026-06-30T07:02:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過剰な不変性がもたらす敵対的脆弱性（Excessive Invariance Causes Adversarial Vulnerability）</news:title>
   <news:publication_date>2026-06-30T07:02:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706486</loc>
  <lastmod>2026-06-30T07:01:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語順の不一致を埋める多言語ニューラル機械翻訳の工夫（Addressing Word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages）</news:title>
   <news:publication_date>2026-06-30T07:01:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706484</loc>
  <lastmod>2026-06-30T07:01:27Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-30T07:01:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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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:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-30T06:08:40Z</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>2026-06-30T06:08:11Z</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>2026-06-30T06:07:35Z</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>液体時定数リカレントニューラルネットワークの普遍近似性（Liquid Time-constant Recurrent Neural Networks as Universal Approximators）</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>
   </news:publication>
   <news:title>核融合研究への深層学習の応用（Applications of Deep Learning to Nuclear Fusion Research）</news:title>
   <news:publication_date>2026-06-30T06:06:38Z</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>局所ブロック座標降下法による畳み込みスパース符号化モデルの効率化（A Local Block Coordinate Descent Algorithm for the Convolutional Sparse Coding Model）</news:title>
   <news:publication_date>2026-06-30T05:15:44Z</news:publication_date>
   <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:publication_date>2026-06-30T05:15:15Z</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>
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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>カプセルネットワークによる線形時間ニューラル機械翻訳（Towards Linear Time Neural Machine Translation with Capsule Networks）</news:title>
   <news:publication_date>2026-06-30T05:14:31Z</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>複数ドメイン辞書学習の効率化（EFFICIENT MULTI-DOMAIN DICTIONARY LEARNING WITH GANS）</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>
   </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>Horizon：Facebookのオープンソース応用強化学習プラットフォーム (Horizon: Facebook’s Open Source Applied Reinforcement Learning Platform)</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>永続ホモロジーに基づく機械学習と応用（Persistent-Homology-based Machine Learning and its Applications – A Survey）</news:title>
   <news:publication_date>2026-06-30T04:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/706438</loc>
  <lastmod>2026-06-30T04:21:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高欠損率に強いLasso（HMLasso: Lasso with High Missing Rate）</news:title>
   <news:publication_date>2026-06-30T04:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706436</loc>
  <lastmod>2026-06-30T04:21:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語非依存リプレゼンタによるニューラル機械翻訳の効率化（Language-Independent Representor for Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-30T04:21:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706434</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>2026-06-30T03:29:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706432</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>自動生成ペアデータによるスケッチ→画像変換の評価（Examining Performance of Sketch-to-Image Translation Models with Multiclass Automatically Generated Paired Training Data）</news:title>
   <news:publication_date>2026-06-30T03:29:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706430</loc>
  <lastmod>2026-06-30T03:29:09Z</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で公正性を達成する（FNNC: Achieving Fairness through Neural Networks）</news:title>
   <news:publication_date>2026-06-30T03:29:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706428</loc>
  <lastmod>2026-06-30T03:28:33Z</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/706426</loc>
  <lastmod>2026-06-30T03:28:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教科書問題へのマルチモーダル文脈グラフによる解法（Textbook Question Answering with Multi-modal Context Graph Understanding and Self-supervised Open-set Comprehension）</news:title>
   <news:publication_date>2026-06-30T03:28:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706424</loc>
  <lastmod>2026-06-30T03:28:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マンダリンと英語のコードスイッチ音声認識に対するエンドツーエンド解法（On the End-to-End Solution to Mandarin-English Code-switching Speech Recognition）</news:title>
   <news:publication_date>2026-06-30T03:28:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706422</loc>
  <lastmod>2026-06-30T03:27:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SARN: 注意機構で効率化した関係推論（SARN: Sequential Attention Relational Network）</news:title>
   <news:publication_date>2026-06-30T03:27:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706420</loc>
  <lastmod>2026-06-30T02:36:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問を用いた社会的学習（Social Learning with Questions）</news:title>
   <news:publication_date>2026-06-30T02:36:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706418</loc>
  <lastmod>2026-06-30T02:36:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>言語モデルの学習ダイナミクスを可視化するSVCCA（Understanding Learning Dynamics Of Language Models with SVCCA）</news:title>
   <news:publication_date>2026-06-30T02:36:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706416</loc>
  <lastmod>2026-06-30T02:36:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-30T02:36:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706414</loc>
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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:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/706412</loc>
  <lastmod>2026-06-30T02:35:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模刺青画像検索のための同時検出とコンパクト表現学習（Tattoo Image Search at Scale: Joint Detection and Compact Representation Learning）</news:title>
   <news:publication_date>2026-06-30T02:35:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706410</loc>
  <lastmod>2026-06-30T02:35:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>META-DES.Oracle：動的アンサンブル選択のメタ学習と特徴選択（META-DES.Oracle: Meta-learning and feature selection for dynamic ensemble selection）</news:title>
   <news:publication_date>2026-06-30T02:35:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706408</loc>
  <lastmod>2026-06-30T02:35:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチラベル頑健因子分解オートエンコーダと薬物相互作用予測への応用 (Multi-Label Robust Factorization Autoencoder and its Application in Predicting Drug-Drug Interactions)</news:title>
   <news:publication_date>2026-06-30T02:35:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706406</loc>
  <lastmod>2026-06-30T01:43:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習を用いた統計的裁定のアルゴリズム（Online Learning Algorithms for Statistical Arbitrage）</news:title>
   <news:publication_date>2026-06-30T01:43:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706404</loc>
  <lastmod>2026-06-30T01:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Balanced SparsityによるGPU上での高速かつ高精度なDNN推論（Balanced Sparsity for Efficient DNN Inference on GPU）</news:title>
   <news:publication_date>2026-06-30T01:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706402</loc>
  <lastmod>2026-06-30T01:43:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COGNI-NET: 脳波に基づく認知特徴学習による視覚知覚の再現（COGNI-NET: COGNITIVE FEATURE LEARNING THROUGH DEEP VISUAL PERCEPTION）</news:title>
   <news:publication_date>2026-06-30T01:43:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706400</loc>
  <lastmod>2026-06-30T01:43:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフに高次ネットワーク効果を注入する手法（MOHONE: Modeling Higher Order Network Effects in Knowledge Graphs via Network Infused Embeddings）</news:title>
   <news:publication_date>2026-06-30T01:43:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706398</loc>
  <lastmod>2026-06-30T01:42:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分クリックで学ぶ多様なランキングのオンライン学習（Online Diverse Learning to Rank from Partial-Click Feedback）</news:title>
   <news:publication_date>2026-06-30T01:42:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706396</loc>
  <lastmod>2026-06-30T01:42:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セッションベース推薦にグラフニューラルネットワークを適用する意義（Session-based Recommendation with Graph Neural Networks）</news:title>
   <news:publication_date>2026-06-30T01:42:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706394</loc>
  <lastmod>2026-06-30T01:42:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能な自然言語処理に向けた生成的説明フレームワーク（Towards Explainable NLP: A Generative Explanation Framework for Text Classification）</news:title>
   <news:publication_date>2026-06-30T01:42:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706392</loc>
  <lastmod>2026-06-30T00:50:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者ダイアライゼーションのための有効なメトリック学習パイプライン設計（DESIGNING AN EFFECTIVE METRIC LEARNING PIPELINE FOR SPEAKER DIARIZATION）</news:title>
   <news:publication_date>2026-06-30T00:50:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706390</loc>
  <lastmod>2026-06-30T00:50:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ注意ネットワークの注意を安定化する正則化手法（A REGULARIZED ATTENTION MECHANISM FOR GRAPH ATTENTION NETWORKS）</news:title>
   <news:publication_date>2026-06-30T00:50:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706388</loc>
  <lastmod>2026-06-30T00:50:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みニューラルネットワークによる少モード光ファイバのモード分解学習 (Learning to decompose the modes in few-mode fibers with deep convolutional neural network)</news:title>
   <news:publication_date>2026-06-30T00:50:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706386</loc>
  <lastmod>2026-06-30T00:49:35Z</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のベイズ的視点（A Bayesian Perspective of Convolutional Neural Networks through a Deconvolutional Generative Model）</news:title>
   <news:publication_date>2026-06-30T00:49:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706384</loc>
  <lastmod>2026-06-30T00:49:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者認証の長さばらつきに強い深層セグメント注意埋め込み（Deep Segment Attentive Embedding for Duration Robust Speaker Verification）</news:title>
   <news:publication_date>2026-06-30T00:49:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706382</loc>
  <lastmod>2026-06-30T00:49:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交通ネットワーク速度予測におけるCapsNetとNLSTMの組合せの実務的意義（Forecasting Transportation Network Speed Using Deep Capsule Networks with Nested LSTM Models）</news:title>
   <news:publication_date>2026-06-30T00:49:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706380</loc>
  <lastmod>2026-06-30T00:49:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fluxによる実践的機械学習環境の革新（Fashionable Modelling with Flux）</news:title>
   <news:publication_date>2026-06-30T00:49:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706378</loc>
  <lastmod>2026-06-29T23:57:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PerceptionNetによる遅延センサーフュージョン（PerceptionNet: A Deep Convolutional Neural Network for Late Sensor Fusion）</news:title>
   <news:publication_date>2026-06-29T23:57:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706376</loc>
  <lastmod>2026-06-29T23:57:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Counterfactual Regret Minimization の意義と実務的インパクト（Deep Counterfactual Regret Minimization）</news:title>
   <news:publication_date>2026-06-29T23:57:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706374</loc>
  <lastmod>2026-06-29T23:56:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重量化文を用いた自然言語推論モデルのストレステスト（Stress-Testing Neural Models of Natural Language Inference with Multiply-Quantified Sentences）</news:title>
   <news:publication_date>2026-06-29T23:56:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706372</loc>
  <lastmod>2026-06-29T23:56:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>評価システムの情報性設計（Designing Informative Rating Systems: Evidence from an Online Labor Market）</news:title>
   <news:publication_date>2026-06-29T23:56:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706370</loc>
  <lastmod>2026-06-29T23:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼度推定と削除予測における双方向再帰ニューラルネットワーク（CONFIDENCE ESTIMATION AND DELETION PREDICTION USING BIDIRECTIONAL RECURRENT NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-29T23:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706368</loc>
  <lastmod>2026-06-29T23:56:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向ラティス再帰型ニューラルネットワークによる信頼度推定（BI-DIRECTIONAL LATTICE RECURRENT NEURAL NETWORKS FOR CONFIDENCE ESTIMATION）</news:title>
   <news:publication_date>2026-06-29T23:56:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706366</loc>
  <lastmod>2026-06-29T23:56:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散台帳設計の解読（Decrypting Distributed Ledger Design - Taxonomy, Classification and Blockchain Community Evaluation）</news:title>
   <news:publication_date>2026-06-29T23:56:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706364</loc>
  <lastmod>2026-06-29T23:05:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆最適化をオンラインで学ぶ手法（An Online-Learning Approach to Inverse Optimization）</news:title>
   <news:publication_date>2026-06-29T23:05:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706362</loc>
  <lastmod>2026-06-29T23:04:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速アップリンク割当のためのスリーピング・マルチアームド・バンディット学習（Sleeping Multi-Armed Bandit Learning for Fast Uplink Grant Allocation in Machine Type Communications）</news:title>
   <news:publication_date>2026-06-29T23:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706360</loc>
  <lastmod>2026-06-29T23:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Word Mover’s Embeddingによる文書表現の刷新（Word Mover’s Embedding: From Word2Vec to Document Embedding）</news:title>
   <news:publication_date>2026-06-29T23:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706358</loc>
  <lastmod>2026-06-29T23:03:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外部惑星の透過スペクトルを網羅するスケール可能な前方モデル格子（Fully scalable forward model grid of exoplanet transmission spectra）</news:title>
   <news:publication_date>2026-06-29T23:03:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706356</loc>
  <lastmod>2026-06-29T23:03:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線の病変検出を高精度化する領域分割融合手法（SDFN: Segmentation-based Deep Fusion Network for Thoracic Disease Classification in Chest X-ray Images）</news:title>
   <news:publication_date>2026-06-29T23:03:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706354</loc>
  <lastmod>2026-06-29T23:03:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンパ腫の自動診断とデジタル病理の可能性（Automated Diagnosis of Lymphoma with Digital Pathology Images Using Deep Learning）</news:title>
   <news:publication_date>2026-06-29T23:03:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706352</loc>
  <lastmod>2026-06-29T23:03:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合信号アーキテクチャによる畳み込みニューラルネットワークの加速（A mixed signal architecture for convolutional neural networks）</news:title>
   <news:publication_date>2026-06-29T23:03:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706350</loc>
  <lastmod>2026-06-29T22:12:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サーブを学習する：ロボットへの示教を効率化する新枠組み（Learning to Serve: an Experimental Study for a new Learning from Demonstrations Framework）</news:title>
   <news:publication_date>2026-06-29T22:12:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706348</loc>
  <lastmod>2026-06-29T22:11:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非構造化されたプロセス観測集合の整理に向けた多様体学習（Manifold Learning for Organizing Unstructured Sets of Process Observations）</news:title>
   <news:publication_date>2026-06-29T22:11:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706346</loc>
  <lastmod>2026-06-29T22:10:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CHEERS結果：NGC 3393の狭線領域におけるChandra X線分光（CHEERS Results from NGC 3393, III: Chandra X-ray Spectroscopy of the Narrow Line Region）</news:title>
   <news:publication_date>2026-06-29T22:10:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706344</loc>
  <lastmod>2026-06-29T22:10:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リコイルフリーなジェット軸とTMD断片化が示す新しいジェット形状の法則性（Phenomenology with a recoil-free jet axis: TMD fragmentation and the jet shape）</news:title>
   <news:publication_date>2026-06-29T22:10:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706342</loc>
  <lastmod>2026-06-29T22:10:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半径方向に分解したセミアナリティック銀河進化モデルと機械学習チューニング（Towards a radially-resolved semi-analytic model for the evolution of disc galaxies tuned with machine learning）</news:title>
   <news:publication_date>2026-06-29T22:10:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706340</loc>
  <lastmod>2026-06-29T22:09:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3色画像から銀河金属量を予測する畳み込みニューラルネットワーク（Using convolutional neural networks to predict galaxy metallicity from three-color images）</news:title>
   <news:publication_date>2026-06-29T22:09:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706338</loc>
  <lastmod>2026-06-29T22:09:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック別感情分析で政治的イデオロギーを見抜く（Topic-Specific Sentiment Analysis Can Help Identify Political Ideology）</news:title>
   <news:publication_date>2026-06-29T22:09:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706336</loc>
  <lastmod>2026-06-29T21:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DropBlockによる畳み込みネットワークの正則化（DropBlock: A regularization method for convolutional networks）</news:title>
   <news:publication_date>2026-06-29T21:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706334</loc>
  <lastmod>2026-06-29T21:17:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ汚染攻撃が暴くノード埋め込みの脆弱性（DATA POISONING ATTACK AGAINST UNSUPERVISED NODE EMBEDDING METHODS）</news:title>
   <news:publication_date>2026-06-29T21:17:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706332</loc>
  <lastmod>2026-06-29T21:17:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムネットワーク蒸留による探索促進（Exploration by Random Network Distillation）</news:title>
   <news:publication_date>2026-06-29T21:17:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706330</loc>
  <lastmod>2026-06-29T21:16:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LUCIDによるTimepix検出器の軌道上初期結果（First results from the LUCID-Timepix spacecraft payload onboard the TechDemoSat-1 satellite in Low Earth Orbit）</news:title>
   <news:publication_date>2026-06-29T21:16:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706328</loc>
  <lastmod>2026-06-29T21:16:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MPNA：畳み込みニューラルネットワーク向けデータフロー最適化を備えた大規模並列ニューラルアレイ（MPNA: A Massively-Parallel Neural Array Accelerator with Dataflow Optimization for Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-29T21:16:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706326</loc>
  <lastmod>2026-06-29T21:16:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スカラー場理論に対する回帰と生成ニューラルネットワーク（Regressive and generative neural networks for scalar field theory）</news:title>
   <news:publication_date>2026-06-29T21:16:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706324</loc>
  <lastmod>2026-06-29T21:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボトムニウムの抑制に関する包括的記述（Global description of bottomonium suppression in proton-nucleus and nucleus-nucleus collisions at LHC energies）</news:title>
   <news:publication_date>2026-06-29T21:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706322</loc>
  <lastmod>2026-06-29T20:23:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然性、ハイパーボリック分岐と荷電ヒッグス検出の展望（Naturalness, the Hyperbolic Branch and Prospects for the Observation of Charged Higgs at High Luminosity LHC and 27 TeV LHC）</news:title>
   <news:publication_date>2026-06-29T20:23:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706320</loc>
  <lastmod>2026-06-29T20:23:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Total Variationを組み合わせた深層画像先験による画像復元（Image Restoration using Total Variation Regularized Deep Image Prior）</news:title>
   <news:publication_date>2026-06-29T20:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706318</loc>
  <lastmod>2026-06-29T20:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Divergence Networkによる発散関数の可視化手法（DIVERGENCE NETWORK: GRAPHICAL CALCULATION METHOD OF DIVERGENCE FUNCTIONS）</news:title>
   <news:publication_date>2026-06-29T20:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706316</loc>
  <lastmod>2026-06-29T20:22:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>資産価格分布と市場効率（Asset Price Distributions and Efficient Markets）</news:title>
   <news:publication_date>2026-06-29T20:22:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706314</loc>
  <lastmod>2026-06-29T20:21:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地下モデルにおける状態とパラメータの対応の発見（Discovering state-parameter mappings in subsurface models using generative adversarial networks）</news:title>
   <news:publication_date>2026-06-29T20:21:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706312</loc>
  <lastmod>2026-06-29T20:21:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用音声タグ付けにおけるCNNと統計特徴のアンサンブル（GENERAL AUDIO TAGGING WITH ENSEMBLING CONVOLUTIONAL NEURAL NETWORKS AND STATISTICAL FEATURES）</news:title>
   <news:publication_date>2026-06-29T20:21:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706310</loc>
  <lastmod>2026-06-29T20:21:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスリンガル文センテンス表現の学習（Learning Cross-Lingual Sentence Representations via a Multi-task Dual-Encoder Model）</news:title>
   <news:publication_date>2026-06-29T20:21:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706308</loc>
  <lastmod>2026-06-29T19:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク上の疫学プロセスの確率的最適制御（Stochastic Optimal Control of Epidemic Processes in Networks）</news:title>
   <news:publication_date>2026-06-29T19:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706306</loc>
  <lastmod>2026-06-29T19:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB-D物体検出のためのクロスモーダル注意文脈学習（Cross-Modal Attentional Context Learning for RGB-D Object Detection）</news:title>
   <news:publication_date>2026-06-29T19:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706304</loc>
  <lastmod>2026-06-29T19:29:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepTwistによるモデル圧縮の実務的インパクト（DEEPTWIST: LEARNING MODEL COMPRESSION VIA OCCASIONAL WEIGHT DISTORTION）</news:title>
   <news:publication_date>2026-06-29T19:29:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706302</loc>
  <lastmod>2026-06-29T19:28:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CLEASE：クラスター展開法の汎用的で使いやすい実装（CLEASE: A versatile and user-friendly implementation of Cluster Expansion method）</news:title>
   <news:publication_date>2026-06-29T19:28:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706300</loc>
  <lastmod>2026-06-29T19:28:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度航空画像の意味セグメンテーションのための文脈的アワーグラスネットワーク (Contextual Hourglass Network for Semantic Segmentation of High Resolution Aerial Imagery)</news:title>
   <news:publication_date>2026-06-29T19:28:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706298</loc>
  <lastmod>2026-06-29T19:28:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模有機結晶のバンドギャップ予測を機械学習で行う（Band gap prediction for large organic crystal structures with machine learning）</news:title>
   <news:publication_date>2026-06-29T19:28:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706296</loc>
  <lastmod>2026-06-29T19:28:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動認識における未知検知を投票で解く（Informed Democracy: Voting-based Novelty Detection for Action Recognition）</news:title>
   <news:publication_date>2026-06-29T19:28:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706294</loc>
  <lastmod>2026-06-29T18:36:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>急性骨髄性白血病の予後予測に対する深層学習の応用（Application of Deep Learning on Predicting Prognosis of Acute Myeloid Leukemia with Cytogenetics, Age, and Mutations）</news:title>
   <news:publication_date>2026-06-29T18:36:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706292</loc>
  <lastmod>2026-06-29T18:35:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移可能な正負感情の音声認識を目指すクラス別敵対的ドメイン適応（TRANSFERABLE POSITIVE/NEGATIVE SPEECH EMOTION RECOGNITION VIA CLASS-WISE ADVERSARIAL DOMAIN ADAPTATION）</news:title>
   <news:publication_date>2026-06-29T18:35:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706290</loc>
  <lastmod>2026-06-29T18:34:47Z</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部分的強凸性が示す学習安定化の可能性（Piecewise Strong Convexity of Neural Networks）</news:title>
   <news:publication_date>2026-06-29T18:34:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706288</loc>
  <lastmod>2026-06-29T18:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚ベースの車線制御における深層学習と強化学習の統合（Reinforcement Learning and Deep Learning based Lateral Control for Autonomous Driving）</news:title>
   <news:publication_date>2026-06-29T18:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706286</loc>
  <lastmod>2026-06-29T18:34:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を内蔵した再帰ユニットがもたらす変化（Recurrent Attention Unit）</news:title>
   <news:publication_date>2026-06-29T18:34:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706284</loc>
  <lastmod>2026-06-29T18:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療文献におけるPICO要素検出の高精度化（Advancing PICO Element Detection in Biomedical Text via Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-29T18:34:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706282</loc>
  <lastmod>2026-06-29T18:33:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチプレックス位相復元のスペクトル法（SPECTRAL METHOD FOR MULTIPLEXED PHASE RETRIEVAL AND APPLICATION IN OPTICAL IMAGING IN COMPLEX MEDIA）</news:title>
   <news:publication_date>2026-06-29T18:33:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706272</loc>
  <lastmod>2026-06-29T17:42:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>区間境界伝播（IBP）による検証可能な頑健モデルの訓練法（On the Effectiveness of Interval Bound Propagation for Training Veriﬁably Robust Models）</news:title>
   <news:publication_date>2026-06-29T17:42:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706270</loc>
  <lastmod>2026-06-29T17:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長短期注意（Long Short-Term Attention）</news:title>
   <news:publication_date>2026-06-29T17:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706268</loc>
  <lastmod>2026-06-29T17:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HTTPトラフィックの異常検知を言語モデルで実現するDeepHTTP（DeepHTTP: Semantics-Structure Model with Attention for Anomalous HTTP Traffic Detection and Pattern Mining）</news:title>
   <news:publication_date>2026-06-29T17:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706266</loc>
  <lastmod>2026-06-29T17:33:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程による条件付き確率密度推定（Gaussian Process Conditional Density Estimation）</news:title>
   <news:publication_date>2026-06-29T17:33:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706264</loc>
  <lastmod>2026-06-29T17:32:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタサイズ管理による多段階凝集型階層的クラスタリングの実務的改善（CLUSTER SIZE MANAGEMENT IN MULTI-STAGE AGGLOMERATIVE HIERARCHICAL CLUSTERING OF ACOUSTIC SPEECH SEGMENTS）</news:title>
   <news:publication_date>2026-06-29T17:32:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706262</loc>
  <lastmod>2026-06-29T17:32:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声セグメントクラスタリングのための特徴軌跡ダイナミックタイムワーピング（FEATURE TRAJECTORY DYNAMIC TIME WARPING FOR CLUSTERING OF SPEECH SEGMENTS）</news:title>
   <news:publication_date>2026-06-29T17:32:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706260</loc>
  <lastmod>2026-06-29T17:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジで動く音声理解の現実（Spoken Language Understanding on the Edge）</news:title>
   <news:publication_date>2026-06-29T17:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706258</loc>
  <lastmod>2026-06-29T16:40:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語質問応答における解釈可能性のための構成的注意ネットワーク（Compositional Attention Networks for Interpretability in Natural Language Question Answering）</news:title>
   <news:publication_date>2026-06-29T16:40:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706256</loc>
  <lastmod>2026-06-29T16:30:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハバードモデルの密度汎関数を機械学習で再構築する（Machine learning density functional theory for the Hubbard model）</news:title>
   <news:publication_date>2026-06-29T16:30:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706254</loc>
  <lastmod>2026-06-29T16:30:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人のスマートフォン行動ルールを採掘する研究課題（Research Issues in Mining User Behavioral Rules for Context-Aware Intelligent Mobile Applications）</news:title>
   <news:publication_date>2026-06-29T16:30:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706252</loc>
  <lastmod>2026-06-29T16:28:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルの再解釈と疑似ベイズ学習による特徴学習（Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior）</news:title>
   <news:publication_date>2026-06-29T16:28:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706250</loc>
  <lastmod>2026-06-29T16:28:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間領域におけるスペクトル事前知識を用いたスパースガウス過程音声源分離（SPARSE GAUSSIAN PROCESS AUDIO SOURCE SEPARATION USING SPECTRUM PRIORS IN THE TIME-DOMAIN）</news:title>
   <news:publication_date>2026-06-29T16:28:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706248</loc>
  <lastmod>2026-06-29T16:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込み辞書正則化によるトモグラフィー再構成（CONVOLUTIONAL DICTIONARY REGULARIZERS FOR TOMOGRAPHIC INVERSION）</news:title>
   <news:publication_date>2026-06-29T16:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706246</loc>
  <lastmod>2026-06-29T16:28:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パルサー風星雲 HESS J1825–137 内の粒子輸送（Particle transport within the pulsar wind nebula HESS J1825–137）</news:title>
   <news:publication_date>2026-06-29T16:28:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706244</loc>
  <lastmod>2026-06-29T15:36:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>障害のある発話のための非並列音声変換に関するGAN研究（Generative Adversarial Networks for Unpaired Voice Transformation on Impaired Speech）</news:title>
   <news:publication_date>2026-06-29T15:36:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706242</loc>
  <lastmod>2026-06-29T15:36:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス・ワイヤータップチャネルに対する深層学習の応用（Deep Learning for the Gaussian Wiretap Channel）</news:title>
   <news:publication_date>2026-06-29T15:36:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706240</loc>
  <lastmod>2026-06-29T15:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線科と機械の協働を可能にするMAMMO（MAMMO: A Deep Learning Solution for Facilitating Radiologist-Machine Collaboration in Breast Cancer Diagnosis）</news:title>
   <news:publication_date>2026-06-29T15:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706238</loc>
  <lastmod>2026-06-29T15:35:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地域間・タスク間の知識移転による適応的転移学習（Adaptive Transfer Learning in Deep Neural Networks: Wind Power Prediction using Knowledge Transfer from Region to Region and Between Different Task Domains）</news:title>
   <news:publication_date>2026-06-29T15:35:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706236</loc>
  <lastmod>2026-06-29T15:35:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア製品の機能選定における利害関係者の価値命題（Key Stakeholders’ Value Propositions for Feature Selection in Software-intensive Products）</news:title>
   <news:publication_date>2026-06-29T15:35:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706234</loc>
  <lastmod>2026-06-29T15:34:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピッチ同期マルチスケールGANによる音声波形生成（WAVEFORM GENERATION FOR TEXT-TO-SPEECH SYNTHESIS USING PITCH-SYNCHRONOUS MULTI-SCALE GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-06-29T15:34:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706232</loc>
  <lastmod>2026-06-29T15:34:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SubSpectralNet：周波数帯ごとの特徴抽出で音環境を識別する新手法（SubSpectralNet – Using Sub-spectrogram Based Convolutional Neural Networks for Acoustic Scene Classification）</news:title>
   <news:publication_date>2026-06-29T15:34:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706230</loc>
  <lastmod>2026-06-29T14:43:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大西洋サケの深潜行動（Deep-diving of Atlantic Salmon）</news:title>
   <news:publication_date>2026-06-29T14:43:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706228</loc>
  <lastmod>2026-06-29T14:43:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次的深層モデルによる知識グラフ補完（DSKG: A Deep Sequential Model for Knowledge Graph Completion）</news:title>
   <news:publication_date>2026-06-29T14:43:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706226</loc>
  <lastmod>2026-06-29T14:43:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースの予測制御の統一的アプローチ（Learning-based predictive control for linear systems: a unitary approach）</news:title>
   <news:publication_date>2026-06-29T14:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706224</loc>
  <lastmod>2026-06-29T14:42:12Z</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>2026-06-29T14:42:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706222</loc>
  <lastmod>2026-06-29T14:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-29T14:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706220</loc>
  <lastmod>2026-06-29T14:41:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対者批評者を用いたネットワークのロバスト性向上（Improved Network Robustness with Adversary Critic）</news:title>
   <news:publication_date>2026-06-29T14:41:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706218</loc>
  <lastmod>2026-06-29T14:41:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル近傍ネットワーク（Neural Nearest Neighbors Networks）</news:title>
   <news:publication_date>2026-06-29T14:41:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706216</loc>
  <lastmod>2026-06-29T13:50:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ADEPOSによる予知保全向け省電力異常検知（ADEPOS: Anomaly Detection Based Power Saving for Predictive Maintenance using Edge Computing）</news:title>
   <news:publication_date>2026-06-29T13:50:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706214</loc>
  <lastmod>2026-06-29T13:30:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極少データでほぼ教師なし音声認識を実現する方法（ALMOST-UNSUPERVISED SPEECH RECOGNITION WITH CLOSE-TO-ZERO RESOURCE）</news:title>
   <news:publication_date>2026-06-29T13:30:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706212</loc>
  <lastmod>2026-06-29T13:29:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短縮空間・スペクトルRNNと並列GRUによるハイパースペクトル画像分類（Shorten Spatial-spectral RNN with Parallel-GRU for Hyperspectral Image Classification）</news:title>
   <news:publication_date>2026-06-29T13:29:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706210</loc>
  <lastmod>2026-06-29T13:29:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英越間ニューラル機械翻訳の実証研究（NEURAL MACHINE TRANSLATION BETWEEN VIETNAMESE AND ENGLISH: AN EMPIRICAL STUDY）</news:title>
   <news:publication_date>2026-06-29T13:29:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706208</loc>
  <lastmod>2026-06-29T13:28:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数箇所のプログラム修復戦略の学習（Multi-Location Program Repair Strategies Learned from Past Successful Experience）</news:title>
   <news:publication_date>2026-06-29T13:28:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706206</loc>
  <lastmod>2026-06-29T13:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフポリシーActor‑Criticにおける相対重要度サンプリング（Relative Importance Sampling for off-Policy Actor-Critic in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-29T13:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706204</loc>
  <lastmod>2026-06-29T13:28:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UnityとPythonによる自動運転車の3D交通シミュレーション (3D Traffic Simulation for Autonomous Vehicles in Unity and Python)</news:title>
   <news:publication_date>2026-06-29T13:28:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706202</loc>
  <lastmod>2026-06-29T12:36:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次元を越える位相の接続：1D Zak相から2D チェルン数へ（The Connection of Topology between Systems with Different Dimensions: 1D Zak Phases to 2D Chern Number, Weyl Point as the Jumping Channel for One Singularity and Nodal Line to Merge All Singularities）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706200</loc>
  <lastmod>2026-06-29T12:36:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情目標を組み込むソフトウェア設計の体系化（Emotionalism within People-Oriented Software Design）</news:title>
   <news:publication_date>2026-06-29T12:36:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706198</loc>
  <lastmod>2026-06-29T12:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタ間類似度の高速伝播による強化型アンサンブルクラスタリング（Enhanced Ensemble Clustering via Fast Propagation of Cluster-wise Similarities）</news:title>
   <news:publication_date>2026-06-29T12:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/706196</loc>
  <lastmod>2026-06-29T12:35:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマノイドロボットの共同行為ジェスチャ生成（Co-Speech Gesture Generation for Humanoid Robots）</news:title>
   <news:publication_date>2026-06-29T12:35:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-29T12:35:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-29T12:35:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/706192</loc>
  <lastmod>2026-06-29T12:34:59Z</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>2026-06-29T12:34:59Z</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>機能選択で転移学習を変える：Gated Transfer Network（Gated Transfer Network for Transfer Learning）</news:title>
   <news:publication_date>2026-06-29T11:43:24Z</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>
   <news:title>DeepGRU：軽量で実運用向けのジェスチャ認識ユーティリティ（DeepGRU: Deep Gesture Recognition Utility）</news:title>
   <news:publication_date>2026-06-29T11:43:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/706186</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス不均衡下における弱監視での深層表現学習（Weak-supervision for Deep Representation Learning under Class Imbalance）</news:title>
   <news:publication_date>2026-06-29T11:42:56Z</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>2026-06-29T11:42:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706182</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>2026-06-29T11:42:06Z</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>継続学習評価の再検討 — 強力なベースラインの重要性（Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong Baselines）</news:title>
   <news:publication_date>2026-06-29T11:41:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706178</loc>
  <lastmod>2026-06-29T11:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的汎用交通シーン予測の枠組み（A Framework for Probabilistic Generic Traffic Scene Prediction）</news:title>
   <news:publication_date>2026-06-29T11:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706176</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>周波数領域/画像領域を組み合わせたMRI再構成のハイブリッド深層ネットワーク（A Hybrid Frequency-domain/Image-domain Deep Network for Magnetic Resonance Image Reconstruction）</news:title>
   <news:publication_date>2026-06-29T10:50:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-29T10:50:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴マップフィルタリングによる視覚的場所認識の改善（Feature Map Filtering: Improving Visual Place Recognition with Convolutional Calibration）</news:title>
   <news:publication_date>2026-06-29T10:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706172</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>貪欲法を微分可能にするネットワーク：Differentiable Greedy Networks（Differentiable Greedy Networks）</news:title>
   <news:publication_date>2026-06-29T10:49:16Z</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>
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   <news:publication_date>2026-06-29T10:49:02Z</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>
   </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>シンプルな繰り返しユニットと縮約テンソル積表現（A SIMPLE RECURRENT UNIT WITH REDUCED TENSOR PRODUCT REPRESENTATIONS）</news:title>
   <news:publication_date>2026-06-29T10:48:22Z</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>ダンスを教えるロボットが示した「身体と認知の融合」—学習支援における適応的インピーダンス制御の提案（Dance Teaching by a Robot: Combining Cognitive and Physical Human–Robot Interaction for Supporting the Skill Learning Process）</news:title>
   <news:publication_date>2026-06-29T10:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706162</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>大規模n・pベイズスパース回帰における事前条件付き共役勾配法によるギブスサンプリング加速（Prior-preconditioned Conjugate Gradient Method for Accelerated Gibbs Sampling in &amp;#039;Large n &amp;amp; Large p&amp;#039; Bayesian Sparse Regression）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706160</loc>
  <lastmod>2026-06-29T09:49:12Z</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>2026-06-29T09:49:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706158</loc>
  <lastmod>2026-06-29T09:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語内部構造のより良い学習法（Learning Better Internal Structure of Words for Sequence Labeling）</news:title>
   <news:publication_date>2026-06-29T09:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706156</loc>
  <lastmod>2026-06-29T09:47:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模リモートセンシングデータのセマンティックセグメンテーションに対する増分学習（Incremental Learning for Semantic Segmentation of Large-Scale Remote Sensing Data）</news:title>
   <news:publication_date>2026-06-29T09:47:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706154</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>地平の呪いを破る：無限ホライズンでのオフポリシー推定（Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation）</news:title>
   <news:publication_date>2026-06-29T09:47:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706152</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>並列注意機構によるニューラル機械翻訳の高速化と精度向上（Parallel Attention Mechanisms in Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-29T09:47:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706150</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>2026-06-29T08:55:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-29T08:55:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビッグデータとサイバーフィジカルシステムの全景（Big Data Meet Cyber-Physical Systems: A Panoramic Survey）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-29T08:55:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-29T08:55:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706142</loc>
  <lastmod>2026-06-29T08:54:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>準同型暗号における条件分岐と機械学習応用（Conditionals in Homomorphic Encryption, and Machine Learning Applications）</news:title>
   <news:publication_date>2026-06-29T08:54:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-29T08:54:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒルベルト空間での学習と推論：量子グラフィカルモデルの再解釈（Learning and Inference in Hilbert Space with Quantum Graphical Models）</news:title>
   <news:publication_date>2026-06-29T08:54:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-29T08:53:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-29T08:53:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動コード化のためのマルチラベル・マルチタスク深層学習（Multi-label Multi-task Deep Learning for Behavioral Coding）</news:title>
   <news:publication_date>2026-06-29T08:02:08Z</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:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news: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>
  <loc>https://aibr.jp/archives/706122</loc>
  <lastmod>2026-06-29T07:51:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>要約モデルにおける内容選択の理解（Content Selection in Deep Learning Models of Summarization）</news:title>
   <news:publication_date>2026-06-29T07:51:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706120</loc>
  <lastmod>2026-06-29T07:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>導関数を含むガウス過程回帰の大規模化（Scaling Gaussian Process Regression with Derivatives）</news:title>
   <news:publication_date>2026-06-29T07:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706118</loc>
  <lastmod>2026-06-29T06:59:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み減衰による正則化の三つの仕組み（THREE MECHANISMS OF WEIGHT DECAY REGULARIZATION）</news:title>
   <news:publication_date>2026-06-29T06:59:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706116</loc>
  <lastmod>2026-06-29T06:59:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習における汎化の評価（Assessing Generalization in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-29T06:59:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706114</loc>
  <lastmod>2026-06-29T06:58:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークにおける不確実性推定の原理的アプローチ（Towards Principled Uncertainty Estimation for Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-29T06:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706112</loc>
  <lastmod>2026-06-29T06:58:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー生成データを活用したコメント生成の学習 (Learning Comment Generation by Leveraging User-Generated Data)</news:title>
   <news:publication_date>2026-06-29T06:58:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706110</loc>
  <lastmod>2026-06-29T06:58:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一様分布下での敵対的リスクと堅牢性の定義と含意（Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution）</news:title>
   <news:publication_date>2026-06-29T06:58:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706108</loc>
  <lastmod>2026-06-29T06:58:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カルマン勾配降下法（Kalman Gradient Descent: Adaptive Variance Reduction in Stochastic Optimization）</news:title>
   <news:publication_date>2026-06-29T06:58:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706106</loc>
  <lastmod>2026-06-29T06:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PAC-Bayesian境界を最小化して学習するガウス過程（Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds）</news:title>
   <news:publication_date>2026-06-29T06:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706104</loc>
  <lastmod>2026-06-29T06:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低線量CT再構成を変える「画像マニフォールド」手法（Low dose CT reconstruction assisted by an image manifold prior）</news:title>
   <news:publication_date>2026-06-29T06:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706102</loc>
  <lastmod>2026-06-29T06:05:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAESTROデータセットによるピアノ音楽生成の革新（Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset）</news:title>
   <news:publication_date>2026-06-29T06:05:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706100</loc>
  <lastmod>2026-06-29T06:05:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショットで挑む3D多モーダル医用画像分割（Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning）</news:title>
   <news:publication_date>2026-06-29T06:05:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706098</loc>
  <lastmod>2026-06-29T06:05:05Z</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GMsFEM離散化の予測（Prediction of Discretization of GMsFEM using Deep Learning）</news:title>
   <news:publication_date>2026-06-29T06:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706096</loc>
  <lastmod>2026-06-29T06:04:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類と適応提案を組み合わせた近似ベイズ推論（Approximate Bayesian Computation via Population Monte Carlo and Classification）</news:title>
   <news:publication_date>2026-06-29T06:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706094</loc>
  <lastmod>2026-06-29T06:04:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ支援型構造故障同定（Data-assisted structural fault identification）</news:title>
   <news:publication_date>2026-06-29T06:04:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706092</loc>
  <lastmod>2026-06-29T05:13:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習ハイパーヒューリスティックによるマルチ目的最適化の単点探索応用（A Reinforcement Learning Hyper‑Heuristic in Multi‑Objective Single Point Search）</news:title>
   <news:publication_date>2026-06-29T05:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706090</loc>
  <lastmod>2026-06-29T05:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>夢を見るニューラルネットワーク：不要な記憶の忘却と重要な記憶の強化（Dreaming neural networks: forgetting spurious memories and reinforcing pure ones）</news:title>
   <news:publication_date>2026-06-29T05:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706088</loc>
  <lastmod>2026-06-29T05:13:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習が明かす宇宙の新情報（Machine learning uncovers new cosmological information）</news:title>
   <news:publication_date>2026-06-29T05:13:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706086</loc>
  <lastmod>2026-06-29T05:12:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Learning as a Serviceフレームワーク比較測定研究（A Comparative Measurement Study of Deep Learning as a Service Framework）</news:title>
   <news:publication_date>2026-06-29T05:12:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706084</loc>
  <lastmod>2026-06-29T05:12:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的バンディットに対する報酬操作攻撃（Adversarial Attacks on Stochastic Bandits）</news:title>
   <news:publication_date>2026-06-29T05:12:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706082</loc>
  <lastmod>2026-06-29T05:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReviewQA—関係性に基づくアスペクト別意見読解データセット (ReviewQA: a relational aspect-based opinion reading dataset)</news:title>
   <news:publication_date>2026-06-29T05:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706080</loc>
  <lastmod>2026-06-29T05:12:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピラミッド型Person Re-IDと動的マルチロス学習（Pyramidal Person Re-Identification via Multi-Loss Dynamic Training）</news:title>
   <news:publication_date>2026-06-29T05:12:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706078</loc>
  <lastmod>2026-06-29T04:21:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSphere：HEALPixサンプリングを用いた効率的球面畳み込みニューラルネットワーク（DeepSphere: Efficient spherical Convolutional Neural Network with HEALPix sampling for cosmological applications）</news:title>
   <news:publication_date>2026-06-29T04:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706076</loc>
  <lastmod>2026-06-29T04:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形ドメインでのエンドツーエンド音楽源分離は可能か（End-to-end music source separation: is it possible in the waveform domain?）</news:title>
   <news:publication_date>2026-06-29T04:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706074</loc>
  <lastmod>2026-06-29T04:21:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRIの動きによるアーチファクトを自動検出するCNN手法（Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning）</news:title>
   <news:publication_date>2026-06-29T04:21:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706072</loc>
  <lastmod>2026-06-29T04:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声と表情を同時に変換する技術の要点（Audiovisual Speaker Conversion: Jointly and Simultaneously Transforming Facial Expression and Acoustic Characteristics）</news:title>
   <news:publication_date>2026-06-29T04:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706070</loc>
  <lastmod>2026-06-29T04:19:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆問題のためのマルチスケール畳み込みニューラルネットワーク (Multi-scale Convolutional Neural Networks for Inverse Problems)</news:title>
   <news:publication_date>2026-06-29T04:19:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706068</loc>
  <lastmod>2026-06-29T04:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師なし学習による人間行動推定（Semi-unsupervised Learning of Human Activity using Deep Generative Models）</news:title>
   <news:publication_date>2026-06-29T04:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706066</loc>
  <lastmod>2026-06-29T04:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンピュータモデルの変分較正（Variational Calibration of Computer Models）</news:title>
   <news:publication_date>2026-06-29T04:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706064</loc>
  <lastmod>2026-06-29T03:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を意識した音声認識における『難しいネガティブ例』を使った学習（Contextual Speech Recognition with Difficult Negative Training Examples）</news:title>
   <news:publication_date>2026-06-29T03:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706062</loc>
  <lastmod>2026-06-29T03:27:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲノムとメタゲノムの相互作用を高速に解析する手法（Fast Computation of Genome-Metagenome Interaction Effects）</news:title>
   <news:publication_date>2026-06-29T03:27:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706060</loc>
  <lastmod>2026-06-29T03:27:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークにおける中央値活性化関数（MEDIAN ACTIVATION FUNCTIONS FOR GRAPH NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-29T03:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706058</loc>
  <lastmod>2026-06-29T03:26:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース能動探索（Model-Based Active eXploration）</news:title>
   <news:publication_date>2026-06-29T03:26:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706056</loc>
  <lastmod>2026-06-29T03:26:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低複雑度RNNを用いた極性符号デコーダと重み量子化の実践的解説（LOW-COMPLEXITY RECURRENT NEURAL NETWORK-BASED POLAR DECODER WITH WEIGHT QUANTIZATION MECHANISM）</news:title>
   <news:publication_date>2026-06-29T03:26:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706054</loc>
  <lastmod>2026-06-29T03:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波ネットワークによる無向グラフでの長距離情報学習（Deep learning long-range information in undirected graphs with wave networks）</news:title>
   <news:publication_date>2026-06-29T03:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706052</loc>
  <lastmod>2026-06-29T03:26:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化付き最尤推定による混合エキスパートモデルの変革（Regularized Maximum Likelihood Estimation and Feature Selection in Mixtures-of-Experts Models）</news:title>
   <news:publication_date>2026-06-29T03:26:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706050</loc>
  <lastmod>2026-06-29T02:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時ワイヤレス情報・電力伝送を学習で設計する（A Learning Approach to Wireless Information and Power Transfer）</news:title>
   <news:publication_date>2026-06-29T02:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/706048</loc>
  <lastmod>2026-06-29T02:34:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イメージに基づくサンプル構築によるゼロショット学習（Imagination Based Sample Construction for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-06-29T02:34:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706046</loc>
  <lastmod>2026-06-29T02:34:36Z</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音楽のオーディオ・インペインティング（AUDIO INPAINTING OF MUSIC BY MEANS OF NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-29T02:34:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706044</loc>
  <lastmod>2026-06-29T02:34:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子層堆積による高アスペクト比イリジウムX線回折格子の作製（Towards Sub-micrometer High Aspect Ratio X-ray Gratings by Atomic Layer Deposition of Iridium）</news:title>
   <news:publication_date>2026-06-29T02:34:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706042</loc>
  <lastmod>2026-06-29T02:33:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的機械学習によるエンティティ解決（Gradual Machine Learning for Entity Resolution）</news:title>
   <news:publication_date>2026-06-29T02:33:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706040</loc>
  <lastmod>2026-06-29T02:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相ハーモニック相関と畳み込みニューラルネットワーク（Phase Harmonic Correlations and Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-29T02:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706038</loc>
  <lastmod>2026-06-29T02:33:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バースト画像の自動選別で画質を最大化する手法（Burst ranking for blind multi-image deblurring）</news:title>
   <news:publication_date>2026-06-29T02:33:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706036</loc>
  <lastmod>2026-06-29T01:41:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現から薬物応答を予測する協調フィルタリング手法（FROM GENE EXPRESSION TO DRUG RESPONSE: A COLLABORATIVE FILTERING APPROACH）</news:title>
   <news:publication_date>2026-06-29T01:41:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706034</loc>
  <lastmod>2026-06-29T01:40:09Z</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>2026-06-29T01:40:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706032</loc>
  <lastmod>2026-06-29T01:32:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理学研究の進化を予測する機械学習（Using Machine Learning to Predict the Evolution of Physics Research）</news:title>
   <news:publication_date>2026-06-29T01:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706030</loc>
  <lastmod>2026-06-29T01:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的損失関数で学ぶ「教えること」の自動化（Learning to Teach with Dynamic Loss Functions）</news:title>
   <news:publication_date>2026-06-29T01:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706028</loc>
  <lastmod>2026-06-29T01:31:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型ニューラルネットワークの訓練収束率に関する理論的進展（On the Convergence Rate of Training Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-29T01:31:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706026</loc>
  <lastmod>2026-06-29T01:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構付きSeq2Seqモデルによる音声合成の話し方スタイル適応（SPEAKING STYLE ADAPTATION IN TEXT-TO-SPEECH SYNTHESIS USING SEQUENCE-TO-SEQUENCE MODELS WITH ATTENTION）</news:title>
   <news:publication_date>2026-06-29T01:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706024</loc>
  <lastmod>2026-06-29T01:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習における「条件付きリプレイ」と「周辺（マージナル）リプレイ」の比較（Marginal Replay vs Conditional Replay for Continual Learning）</news:title>
   <news:publication_date>2026-06-29T01:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706022</loc>
  <lastmod>2026-06-29T00:39:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチベースのスパース表現による細菌検出（PATCH-BASED SPARSE REPRESENTATION FOR BACTERIAL DETECTION）</news:title>
   <news:publication_date>2026-06-29T00:39:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706020</loc>
  <lastmod>2026-06-29T00:39:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的再ランク付けによるテキストスポッティングの改善（Visual Re-ranking with Natural Language Understanding for Text Spotting）</news:title>
   <news:publication_date>2026-06-29T00:39:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706018</loc>
  <lastmod>2026-06-29T00:38:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジットペアリング手法は勾配ベース攻撃を欺ける（Logit Pairing Methods Can Fool Gradient-Based Attacks）</news:title>
   <news:publication_date>2026-06-29T00:38:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706016</loc>
  <lastmod>2026-06-29T00:37:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習におけるソフトウェア工学上の課題（Software Engineering Challenges of Deep Learning）</news:title>
   <news:publication_date>2026-06-29T00:37:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706014</loc>
  <lastmod>2026-06-29T00:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的なユーザー・アイテム相互作用を組み込んだ深層強化学習による推薦（Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling）</news:title>
   <news:publication_date>2026-06-29T00:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706012</loc>
  <lastmod>2026-06-29T00:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カスケード型CNN-resBiLSTM-CTC：音声認識のためのエンドツーエンド音響モデル (CASCADED CNN-resBiLSTM-CTC: AN END-TO-END ACOUSTIC MODEL FOR SPEECH RECOGNITION)</news:title>
   <news:publication_date>2026-06-29T00:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706010</loc>
  <lastmod>2026-06-29T00:37:03Z</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>2026-06-29T00:37:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706008</loc>
  <lastmod>2026-06-28T23:46:12Z</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>2026-06-28T23:46:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706006</loc>
  <lastmod>2026-06-28T23:45:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型とデータ同化を組み合わせた物理過程の同定（Identification of physical processes via combined data-driven and data-assimilation methods）</news:title>
   <news:publication_date>2026-06-28T23:45:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706004</loc>
  <lastmod>2026-06-28T23:45:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GOT-10k：大規模高多様性トラッキングベンチマーク（GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild）</news:title>
   <news:publication_date>2026-06-28T23:45:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706002</loc>
  <lastmod>2026-06-28T23:45:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴量バギングによるステガノグラファー識別（Feature Bagging for Steganographer Identification）</news:title>
   <news:publication_date>2026-06-28T23:45:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/706000</loc>
  <lastmod>2026-06-28T23:45:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半クラウドソース型深層生成モデルによるクラスタリング（Semi-crowdsourced Clustering with Deep Generative Models）</news:title>
   <news:publication_date>2026-06-28T23:45:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705998</loc>
  <lastmod>2026-06-28T23:44:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Softmaxに替わる制御可能なスパースな代替手法（On Controllable Sparse Alternatives to Softmax）</news:title>
   <news:publication_date>2026-06-28T23:44:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705996</loc>
  <lastmod>2026-06-28T23:44:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的フィードバックと暗黙的フィードバックの統合による推薦システム（Explicit Feedbacks Meet with Implicit Feedbacks: A Combined Approach for Recommendation System）</news:title>
   <news:publication_date>2026-06-28T23:44:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705994</loc>
  <lastmod>2026-06-28T22:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典と量子機械学習の融合による肺がんサブタイプ分類（An Amalgamation of Classical and Quantum Machine Learning For the Classification of Adenocarcinoma and Squamous Cell Carcinoma Patients）</news:title>
   <news:publication_date>2026-06-28T22:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705992</loc>
  <lastmod>2026-06-28T22:52:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピッチアクセント言語のための自己注意を用いたTacotron音声合成システムの検討 (INVESTIGATION OF ENHANCED TACOTRON TEXT-TO-SPEECH SYNTHESIS SYSTEMS WITH SELF-ATTENTION FOR PITCH ACCENT LANGUAGE)</news:title>
   <news:publication_date>2026-06-28T22:52:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705990</loc>
  <lastmod>2026-06-28T22:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化する自己表現モデルによる部分空間クラスタリング（Evolutionary Self-Expressive Models for Subspace Clustering）</news:title>
   <news:publication_date>2026-06-28T22:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705988</loc>
  <lastmod>2026-06-28T22:52:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T22:52:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705986</loc>
  <lastmod>2026-06-28T22:52:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビットコイン上の実体（エンティティ）識別の実務的インパクト（Characterizing Entities in the Bitcoin Blockchain）</news:title>
   <news:publication_date>2026-06-28T22:52:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705984</loc>
  <lastmod>2026-06-28T22:51:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会車両スウォームの視点と実装課題（Social Vehicle Swarms: Agent-based Model for Social-aware Internet of Vehicles）</news:title>
   <news:publication_date>2026-06-28T22:51:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705982</loc>
  <lastmod>2026-06-28T22:51:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構に基づく車両追跡手法（Attention-Mechanism-based Tracking Method for Intelligent Internet of Vehicles）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-28T22:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-28T22:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-28T22:00:25Z</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>2026-06-28T22:00:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705976</loc>
  <lastmod>2026-06-28T21:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>裾適応fダイバージェンスを用いた変分推論（Variational Inference with Tail-adaptive f-Divergence）</news:title>
   <news:publication_date>2026-06-28T21:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705974</loc>
  <lastmod>2026-06-28T21:59:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三次元自然対流における不確かさ定量化と代理モデル（Uncertainty Quantification in Three Dimensional Natural Convection using Polynomial Chaos Expansion and Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T21:59:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705972</loc>
  <lastmod>2026-06-28T21:59:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T21:59:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705970</loc>
  <lastmod>2026-06-28T21:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要なクラウドインフラを予測的に守る確率モデル（An approach to predictively securing critical cloud infrastructures through probabilistic modeling）</news:title>
   <news:publication_date>2026-06-28T21:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705968</loc>
  <lastmod>2026-06-28T21:58:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>聞き方を学ぶ：時間・周波数注意モデルによる音響イベント検出（LEARNING HOW TO LISTEN: A TEMPORAL-FREQUENTIAL ATTENTION MODEL FOR SOUND EVENT DETECTION）</news:title>
   <news:publication_date>2026-06-28T21:58:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705966</loc>
  <lastmod>2026-06-28T21:07:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>赤方偏移7.02で発見された朗明なBALクエーサーの発見（The Discovery of A Luminous Broad Absorption Line Quasar at A Redshift of 7.02）</news:title>
   <news:publication_date>2026-06-28T21:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705964</loc>
  <lastmod>2026-06-28T21:07:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Parameterized Quantum Circuitsの表現力（The Expressive Power of Parameterized Quantum Circuits）</news:title>
   <news:publication_date>2026-06-28T21:07:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705962</loc>
  <lastmod>2026-06-28T21:07:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AutoIntによる特徴相互作用の自動学習（AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks）</news:title>
   <news:publication_date>2026-06-28T21:07:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705960</loc>
  <lastmod>2026-06-28T21:06:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的事例に対する一般化の理論的理解（Rademacher Complexity for Adversarially Robust Generalization）</news:title>
   <news:publication_date>2026-06-28T21:06:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705958</loc>
  <lastmod>2026-06-28T21:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト適応型生成対抗ネットワークによる自然言語での画像操作（Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language）</news:title>
   <news:publication_date>2026-06-28T21:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705956</loc>
  <lastmod>2026-06-28T21:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>システムログ処理の高速化と半教師あり学習（Accelerating System Log Processing by Semi-supervised Learning）</news:title>
   <news:publication_date>2026-06-28T21:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705954</loc>
  <lastmod>2026-06-28T21:05:42Z</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>2026-06-28T21:05:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705952</loc>
  <lastmod>2026-06-28T20:14:25Z</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>2026-06-28T20:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705950</loc>
  <lastmod>2026-06-28T20:14:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>忘れずに学ぶ学習法（Learning to Learn Without Forgetting by Maximizing Transfer and Minimizing Interference）</news:title>
   <news:publication_date>2026-06-28T20:14:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705948</loc>
  <lastmod>2026-06-28T20:13:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークの平均場理論による分割性能の解明（Mean-field theory of graph neural networks in graph partitioning）</news:title>
   <news:publication_date>2026-06-28T20:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705946</loc>
  <lastmod>2026-06-28T20:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースロジスティック回帰による離散対向グラフモデルの学習（Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models）</news:title>
   <news:publication_date>2026-06-28T20:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705944</loc>
  <lastmod>2026-06-28T20:12:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MMDネットワークによる半教師付き翻訳（Semi-Supervised Translation with MMD Networks）</news:title>
   <news:publication_date>2026-06-28T20:12:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705942</loc>
  <lastmod>2026-06-28T20:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模グラフを効率的に学習する仕組み（Accurate, Efficient and Scalable Graph Embedding）</news:title>
   <news:publication_date>2026-06-28T20:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705940</loc>
  <lastmod>2026-06-28T20:11:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散テンソル分解のスムーズ解析（Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons）</news:title>
   <news:publication_date>2026-06-28T20:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705938</loc>
  <lastmod>2026-06-28T19:21:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非並列テキスト転換の教師なし評価指標と学習基準（Unsupervised Evaluation Metrics and Learning Criteria for Non-Parallel Textual Transfer）</news:title>
   <news:publication_date>2026-06-28T19:21:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705936</loc>
  <lastmod>2026-06-28T19:20:53Z</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>2026-06-28T19:20:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705934</loc>
  <lastmod>2026-06-28T19:20:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>材料シミュレーションのための均一に高精度な原子間ポテンシャルの能動学習（Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation）</news:title>
   <news:publication_date>2026-06-28T19:20:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705932</loc>
  <lastmod>2026-06-28T19:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T19:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705930</loc>
  <lastmod>2026-06-28T19:19:39Z</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>2026-06-28T19:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705928</loc>
  <lastmod>2026-06-28T19:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コスト意識的因果グラフ学習の実験デザイン（Experimental Design for Cost-Aware Learning of Causal Graphs）</news:title>
   <news:publication_date>2026-06-28T19:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705926</loc>
  <lastmod>2026-06-28T19:19:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汚れた訓練データから学ぶ反復トリム損失最小化（Learning with Bad Training Data via Iterative Trimmed Loss Minimization）</news:title>
   <news:publication_date>2026-06-28T19:19:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705924</loc>
  <lastmod>2026-06-28T18:28:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T18:28:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705922</loc>
  <lastmod>2026-06-28T18:27:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙の夜明けにおける21cm信号の解析的定式化（Analytic Formulation of 21 cm Signal from Cosmic Dawn: Lyα Fluctuations）</news:title>
   <news:publication_date>2026-06-28T18:27:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705920</loc>
  <lastmod>2026-06-28T18:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LPCNetによる低コスト音声合成（LPCNet: IMPROVING NEURAL SPEECH SYNTHESIS THROUGH LINEAR PREDICTION）</news:title>
   <news:publication_date>2026-06-28T18:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705918</loc>
  <lastmod>2026-06-28T18:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>資源制約下で「最大値」を狙うオンライン学習フレームワーク（MaxHedge: Maximising a Maximum Online）</news:title>
   <news:publication_date>2026-06-28T18:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705916</loc>
  <lastmod>2026-06-28T18:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模視覚データを機械学習向けに高速に扱う仕組み（VDMS: Efficient Big-Visual-Data Access for Machine Learning Workloads）</news:title>
   <news:publication_date>2026-06-28T18:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705914</loc>
  <lastmod>2026-06-28T18:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像ノイズ除去のための強化畳み込みニューラルネットワーク（Enhanced CNN for image denoising）</news:title>
   <news:publication_date>2026-06-28T18:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705912</loc>
  <lastmod>2026-06-28T18:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雲を「ノイズ」と見なす衛星画像の頑健なセグメンテーション（Convolutional LSTMs for Cloud-Robust Segmentation of Remote Sensing Imagery）</news:title>
   <news:publication_date>2026-06-28T18:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705910</loc>
  <lastmod>2026-06-28T17:34:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門家助言の統合による差別保持の問題（On preserving non-discrimination when combining expert advice）</news:title>
   <news:publication_date>2026-06-28T17:34:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705908</loc>
  <lastmod>2026-06-28T17:34:17Z</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動画における物体追跡の新手法（Object Tracking in Hyperspectral Videos with Convolutional Features and Kernelized Correlation Filter）</news:title>
   <news:publication_date>2026-06-28T17:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705906</loc>
  <lastmod>2026-06-28T17:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフに基づく半教師あり学習アルゴリズムの音声認識への適用（Hypergraph Based Semi-Supervised Learning Algorithms Applied to Speech Recognition Problem）</news:title>
   <news:publication_date>2026-06-28T17:34:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705904</loc>
  <lastmod>2026-06-28T17:33:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別力を重視したチャネル削減（Discrimination-aware Channel Pruning for Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T17:33:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705902</loc>
  <lastmod>2026-06-28T17:33:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TV事前情報を用いた画像超解像の実用的意味（Image Super-Resolution Using TV Priori Guided Convolutional Network）</news:title>
   <news:publication_date>2026-06-28T17:33:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705900</loc>
  <lastmod>2026-06-28T17:33:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットが「ノー」を学ぶ――否定語獲得における禁止と拒否のメカニズム（Robots Learning to Say ‘No’: Prohibition and Rejective Mechanisms in Acquisition of Linguistic Negation）</news:title>
   <news:publication_date>2026-06-28T17:33:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705898</loc>
  <lastmod>2026-06-28T17:32:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>四次元におけるボソン—フェルミオン双対性（Boson-fermion duality in four dimensions）</news:title>
   <news:publication_date>2026-06-28T17:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705896</loc>
  <lastmod>2026-06-28T16:41:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽子スピンの深い混合（Proton Spin in Deep Inelastic Scattering）</news:title>
   <news:publication_date>2026-06-28T16:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705894</loc>
  <lastmod>2026-06-28T16:41:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの分散学習ガイド（A Hitchhiker’s Guide On Distributed Training of Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T16:41:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705892</loc>
  <lastmod>2026-06-28T16:41:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理世界で機能する音声の敵対的事例の生成（Robust Audio Adversarial Example for a Physical Attack）</news:title>
   <news:publication_date>2026-06-28T16:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705890</loc>
  <lastmod>2026-06-28T16:41:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的ヤコビアン境界アルゴリズム RecurJac（RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications）</news:title>
   <news:publication_date>2026-06-28T16:41:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705888</loc>
  <lastmod>2026-06-28T16:40:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Affinity Network による複数物体追跡の再設計（Deep Affinity Network for Multiple Object Tracking）</news:title>
   <news:publication_date>2026-06-28T16:40:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705886</loc>
  <lastmod>2026-06-28T16:40:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パリティ奇数のニュートリノトルク検出（Parity-odd neutrino torque detection）</news:title>
   <news:publication_date>2026-06-28T16:40:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705884</loc>
  <lastmod>2026-06-28T16:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的系における安定で予測可能な構造の学習（Learning stable and predictive structures in kinetic systems: Benefits of a causal approach）</news:title>
   <news:publication_date>2026-06-28T16:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705882</loc>
  <lastmod>2026-06-28T15:49:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解析モデルと機械学習の融合による性能予測（Learning with Analytical Models）</news:title>
   <news:publication_date>2026-06-28T15:49:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705880</loc>
  <lastmod>2026-06-28T15:49:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シナプスから空間記憶地図へ（Through synapses to spatial memory maps: a topological model）</news:title>
   <news:publication_date>2026-06-28T15:49:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705878</loc>
  <lastmod>2026-06-28T15:48:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感度駆動型正則化によるスパースニューラルネット学習（Learning Sparse Neural Networks via Sensitivity-Driven Regularization）</news:title>
   <news:publication_date>2026-06-28T15:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705876</loc>
  <lastmod>2026-06-28T15:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ネットワークの中心性を学習で高速化する研究（Computing Vertex Centrality Measures in Massive Real Networks with a Neural Learning Model）</news:title>
   <news:publication_date>2026-06-28T15:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705874</loc>
  <lastmod>2026-06-28T15:48:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習とリザバーコンピューティングによる分散型動的スペクトラムアクセス（Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach）</news:title>
   <news:publication_date>2026-06-28T15:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705872</loc>
  <lastmod>2026-06-28T15:47:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察されていないものを見る：並列化されたモンテカルロ木探索の単純なアプローチ（WATCH THE UNOBSERVED: A SIMPLE APPROACH TO PARALLELIZING MONTE CARLO TREE SEARCH）</news:title>
   <news:publication_date>2026-06-28T15:47:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705870</loc>
  <lastmod>2026-06-28T15:47:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク中心性指標における機械学習による近似手法（Machine Learning in Network Centrality Measures: Tutorial and Outlook）</news:title>
   <news:publication_date>2026-06-28T15:47:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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