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   <news:title>Generalized PolyDot符号を用いた分散DNN学習の統一的戦略（A Unified Coded Deep Neural Network Training Strategy Based on Generalized PolyDot Codes for Matrix Multiplication）</news:title>
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   <news:title>MATCH-Netによる生存予測の動的化（MATCH-Net: Dynamic Prediction in Survival Analysis using Convolutional Neural Networks）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>fMRIエンコーディングにおける回帰専門家混合モデル（Mixture of Regression Experts in fMRI Encoding）</news:title>
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   <news:title>単眼映像からの車両3D検出と追跡の統合（Joint Monocular 3D Vehicle Detection and Tracking）</news:title>
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   <news:title>カスタムウェイクワード検出を手元で実現する低負荷手法（DONUT: CTC-based Query-by-Example Keyword Spotting）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T06:06:06Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>GANtruthによる合成画像から実写への変換（GANtruth – an unpaired image-to-image translation method for driving scenarios）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ニューラルネットワークによる決定木の自動誘導（Automatic Induction of Neural Network Decision Tree Algorithms）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>動的ネットワークのための埋め込み基盤 DynamicGEM の意義（DynamicGEM: A Library for Dynamic Graph Embedding Methods）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T05:13:21Z</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>生涯学習型強化学習のための環境設計（Environments for Lifelong Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>情報探索対話戦略の最適化（Optimization of Information-Seeking Dialogue Strategy for Argumentation-Based Dialogue System）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>DESによる外縁天体の位置精度と星食予測の改善（ASTROMETRY AND OCCULTATION PREDICTIONS TO TRANSNEPTUNIAN AND CENTAUR OBJECTS OBSERVED WITHIN THE DARK ENERGY SURVEY）</news:title>
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  <lastmod>2026-07-10T05:12:27Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>画像誘導ニューラルオブジェクトレンダリング（Image-Guided Neural Object Rendering）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T05:11:41Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>複数インスタンスを扱う空間変換器（MIST: Multiple Instance Spatial Transformer）</news:title>
   <news:publication_date>2026-07-10T05:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T04:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>単一視点からの3D再構築における視点事前知識の学習 (Learning View Priors for Single-view 3D Reconstruction)</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T04:20:05Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>自動標的認識の堅牢表現学習（Learning Robust Representations for Automatic Target Recognition）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T04:19:14Z</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>生波形とメルスペクトログラムの高次特徴を組み合わせた音声タグ付け（COMBINING HIGH-LEVEL FEATURES OF RAW AUDIO WAVES AND MEL-SPECTROGRAMS FOR AUDIO TAGGING）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T04:19:00Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>時間・視点を意識した映像生成による教師なし表現学習（Time-Aware and View-Aware Video Rendering for Unsupervised Representation Learning）</news:title>
   <news:publication_date>2026-07-10T04:19:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T04:18:48Z</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>遺伝子ゲーティングネットワークが強化学習にもたらす変化（Genetic-Gated Networks for Deep Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T04:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>画像をシーングラフに変換する注意型関係ネットワーク（Attentive Relational Networks for Mapping Images to Scene Graphs）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T04:18:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ディリクレ過程混合モデルによる時系列列の整列（Sequence Alignment with Dirichlet Process Mixtures）</news:title>
   <news:publication_date>2026-07-10T04:18:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710128</loc>
  <lastmod>2026-07-10T03:26:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>顧客対応チャットにおける能動的応答支援（Beyond &amp;quot;How may I help you?&amp;quot;: Assisting Customer Service Agents with Proactive Responses）</news:title>
   <news:publication_date>2026-07-10T03:26:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T03:26:39Z</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>ソフトエッジ検出に導かれた敵対的動画圧縮（Adversarial Video Compression Guided by Soft Edge Detection）</news:title>
   <news:publication_date>2026-07-10T03:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710124</loc>
  <lastmod>2026-07-10T03:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANsfer Learningによるラベル付き・ラベル無しデータの統合的拡張（GANsfer Learning: Combining labelled and unlabelled data for GAN based data augmentation）</news:title>
   <news:publication_date>2026-07-10T03:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T03:25:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>低レベル反復プログラムの帰納的合成への足がかり（Stepping Stones to Inductive Synthesis of Low-Level Looping Programs）</news:title>
   <news:publication_date>2026-07-10T03:25:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T03:25:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>絵画を写真に変える技術—Art2Real（Art2Real: Unfolding the Reality of Artworks）</news:title>
   <news:publication_date>2026-07-10T03:25:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-10T03:25:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>不確実性を埋め込む知識グラフの革新（Embedding Uncertain Knowledge Graphs）</news:title>
   <news:publication_date>2026-07-10T03:25:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710116</loc>
  <lastmod>2026-07-10T03:24:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Bayesian Self-Training入門（Deep Bayesian Self-Training）</news:title>
   <news:publication_date>2026-07-10T03:24:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710114</loc>
  <lastmod>2026-07-10T02:33:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画向け時空間ニューラルアーキテクチャの進化（Evolving Space-Time Neural Architectures for Videos）</news:title>
   <news:publication_date>2026-07-10T02:33:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710112</loc>
  <lastmod>2026-07-10T02:23:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明生成における仮説推論に基づく手法（Abduction-Based Explanations for Machine Learning Models）</news:title>
   <news:publication_date>2026-07-10T02:23:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710110</loc>
  <lastmod>2026-07-10T02:23:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推論時のノイズ計算は有害か有益か（Noisy Computations during Inference: Harmful or Helpful?）</news:title>
   <news:publication_date>2026-07-10T02:23:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710108</loc>
  <lastmod>2026-07-10T02:21:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エリプティカル銀河M86での一過性超高輝度X線源の発見（Discovery of a transient ultraluminous X-ray source in the elliptical galaxy M86）</news:title>
   <news:publication_date>2026-07-10T02:21:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710106</loc>
  <lastmod>2026-07-10T02:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANの内部解剖（GAN Dissection: Visualizing and Understanding Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-10T02:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710104</loc>
  <lastmod>2026-07-10T02:21:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライマンα放射銀河の二点相関とネットワークトポロジーの統計 (STATISTICS OF TWO-POINT CORRELATION AND NETWORK TOPOLOGY FOR LYMAN ALPHA EMITTERS AT Z ≈2.67)</news:title>
   <news:publication_date>2026-07-10T02:21:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/710102</loc>
  <lastmod>2026-07-10T02:21:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的含意タスクと説明可能なEVEモデル（Visual Entailment Task for Visually-Grounded Language Learning）</news:title>
   <news:publication_date>2026-07-10T02:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/710100</loc>
  <lastmod>2026-07-10T01:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HOGWILD!-Gibbsは全変数の期待値を正確に推定できるか（HOGWILD!-Gibbs Can Be PanAccurate）</news:title>
   <news:publication_date>2026-07-10T01:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/710098</loc>
  <lastmod>2026-07-10T01:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響質問応答のための合成データセット CLEAR（CLEAR: A Dataset for Compositional Language and Elementary Acoustic Reasoning）</news:title>
   <news:publication_date>2026-07-10T01:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710096</loc>
  <lastmod>2026-07-10T01:29:38Z</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に対する深層畳み込みニューラルネットワークによるノイズ低減（Low-Dose CT via Deep CNN with Skip Connection and Network in Network）</news:title>
   <news:publication_date>2026-07-10T01:29:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710094</loc>
  <lastmod>2026-07-10T01:28:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィルタ相関に基づく深層モデル圧縮（Leveraging Filter Correlations for Deep Model Compression）</news:title>
   <news:publication_date>2026-07-10T01:28:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710092</loc>
  <lastmod>2026-07-10T01:28:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物再識別のための類似性保持画像間ドメイン適応（Similarity-preserving Image-image Domain Adaptation for Person Re-identification）</news:title>
   <news:publication_date>2026-07-10T01:28:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710090</loc>
  <lastmod>2026-07-10T01:28:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Androidの解除パターン収集方法とデータセット横断比較（A Survey of Collection Methods and Cross-Data Set Comparison of Android Unlock Patterns）</news:title>
   <news:publication_date>2026-07-10T01:28:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710088</loc>
  <lastmod>2026-07-10T01:28:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓の超音波動画から1年死亡率を予測する深層ニューラルネットワーク（A deep neural network to enhance prediction of 1-year mortality using echocardiographic videos of the heart）</news:title>
   <news:publication_date>2026-07-10T01:28:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710086</loc>
  <lastmod>2026-07-10T00:36:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模なマルチマッチングのための高次射影パワー反復法（Higher-order Projected Power Iterations for Scalable Multi-Matching）</news:title>
   <news:publication_date>2026-07-10T00:36:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710084</loc>
  <lastmod>2026-07-10T00:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフベースの大規模個別固有表現同定（Scalable graph-based individual named entity identification）</news:title>
   <news:publication_date>2026-07-10T00:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710082</loc>
  <lastmod>2026-07-10T00:35:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GP-CNASによるCNNアーキテクチャ探索（GP-CNAS: Convolutional Neural Network Architecture Search with Genetic Programming）</news:title>
   <news:publication_date>2026-07-10T00:35:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710080</loc>
  <lastmod>2026-07-10T00:35:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2Dトレースで3D注釈負担を半減する手法（Tracing in 2D to Reduce the Annotation Effort for 3D Deep Delineation）</news:title>
   <news:publication_date>2026-07-10T00:35:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710078</loc>
  <lastmod>2026-07-10T00:35:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳卒中後の言語回復予測における2DスティッチMRIと畳み込みネットワークの有用性（Predicting Language Recovery after Stroke with Convolutional Networks on Stitched MRI）</news:title>
   <news:publication_date>2026-07-10T00:35:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710076</loc>
  <lastmod>2026-07-10T00:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像コレクションからの教師なし3D形状学習（Unsupervised 3D Shape Learning from Image Collections in the Wild）</news:title>
   <news:publication_date>2026-07-10T00:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710074</loc>
  <lastmod>2026-07-10T00:34:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Network Interpolation（Deep Network Interpolation for Continuous Imagery Effect Transition）</news:title>
   <news:publication_date>2026-07-10T00:34:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710072</loc>
  <lastmod>2026-07-09T23:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層アンサンブルテンソル分解による縦断的患者軌跡分類（Deep Ensemble Tensor Factorization for Longitudinal Patient Trajectories Classification）</news:title>
   <news:publication_date>2026-07-09T23:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710070</loc>
  <lastmod>2026-07-09T23:43:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクト畳み込みネットワークの訓練のための線形過剰パラメータ化（ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks）</news:title>
   <news:publication_date>2026-07-09T23:43:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710068</loc>
  <lastmod>2026-07-09T23:43:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>証拠を生成する視点横断歩容認識：Discriminant Gait GAN（DiGGAN）によるアプローチ（Robust Cross-view Gait Recognition with Evidence: A Discriminant Gait GAN (DiGGAN) Approach）</news:title>
   <news:publication_date>2026-07-09T23:43:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710066</loc>
  <lastmod>2026-07-09T23:42:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人配列と参照ゲノムのインターレースで変異検出を最適化する（Interlacing Personal and Reference Genomes for Machine Learning Disease-Variant Detection）</news:title>
   <news:publication_date>2026-07-09T23:42:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710064</loc>
  <lastmod>2026-07-09T23:42:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不足ペナルティを用いた再生可能エネルギー深度統合下の電力オークション（Auctioning Electricity under Deep Renewable Integration using a Penalty for Shortfall）</news:title>
   <news:publication_date>2026-07-09T23:42:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710062</loc>
  <lastmod>2026-07-09T23:42:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造制約付きリレーションネットワークによる文表現（Sentence Encoding with Tree-Constrained Relation Networks）</news:title>
   <news:publication_date>2026-07-09T23:42:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710060</loc>
  <lastmod>2026-07-09T23:41:55Z</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よるCSIベース認証（Deep Neural Networks Meet CSI-Based Authentication）</news:title>
   <news:publication_date>2026-07-09T23:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710058</loc>
  <lastmod>2026-07-09T22:50:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オミクスデータに機械学習を適用するためのフレームワーク（A Framework for Implementing Machine Learning on Omics Data）</news:title>
   <news:publication_date>2026-07-09T22:50:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710056</loc>
  <lastmod>2026-07-09T22:50:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状況認識型群衆カウントの新展開（Context-Aware Crowd Counting）</news:title>
   <news:publication_date>2026-07-09T22:50:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710054</loc>
  <lastmod>2026-07-09T22:50:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼブラフィッシュの群れをニューラルネットで再現する（Modelling zebrafish collective behaviours with multilayer perceptrons optimised by evolutionary algorithms）</news:title>
   <news:publication_date>2026-07-09T22:50:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710052</loc>
  <lastmod>2026-07-09T22:49:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事実要素化された状態・行動空間における計画のためのコンパクトで効率的な符号化（Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models）</news:title>
   <news:publication_date>2026-07-09T22:49:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710050</loc>
  <lastmod>2026-07-09T22:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルと知識ベースの統合によるポーランド語固有表現認識（COMBINING NEURAL AND KNOWLEDGE-BASED APPROACHES TO NAMED ENTITY RECOGNITION IN POLISH）</news:title>
   <news:publication_date>2026-07-09T22:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710048</loc>
  <lastmod>2026-07-09T22:49:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト画像の超解像に特化したDeep Laplacian Pyramid Networks（DEEP LAPLACIAN PYRAMID NETWORK FOR TEXT IMAGES SUPER-RESOLUTION）</news:title>
   <news:publication_date>2026-07-09T22:49:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710046</loc>
  <lastmod>2026-07-09T22:48:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損・汚染観測下でのスパーススペクトル推定（Sparse spectral estimation with missing and corrupted measurements）</news:title>
   <news:publication_date>2026-07-09T22:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710044</loc>
  <lastmod>2026-07-09T21:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深部脳刺激（DBS）手術における術中効果予測を目指す機械学習（Towards Machine Learning Prediction of Deep Brain Stimulation (DBS) Intra-operative Efficacy Maps）</news:title>
   <news:publication_date>2026-07-09T21:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710042</loc>
  <lastmod>2026-07-09T21:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚障害者支援のためのCNNによるライブ物体認識システム（A Convolutional Neural Network based Live Object Recognition System as Blind Aid）</news:title>
   <news:publication_date>2026-07-09T21:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710040</loc>
  <lastmod>2026-07-09T21:57:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病的音声検出におけるチャネル効果への頑健性（Robustness against the channel effect in pathological voice detection）</news:title>
   <news:publication_date>2026-07-09T21:57:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710038</loc>
  <lastmod>2026-07-09T21:57:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照文字列から最適な解析器を推薦するメタラーニングの実装（ParsRec: A Novel Meta-Learning Approach to Recommending Bibliographic Reference Parsers）</news:title>
   <news:publication_date>2026-07-09T21:57:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710036</loc>
  <lastmod>2026-07-09T21:57:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意スタイル転送のための交換可能特徴整列ネットワーク（EFANet: Exchangeable Feature Alignment Network for Arbitrary Style Transfer）</news:title>
   <news:publication_date>2026-07-09T21:57:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710034</loc>
  <lastmod>2026-07-09T21:57:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学術用レコメンダーを手軽に提供する仕組み（The Architecture of Mr. DLib’s Scientific Recommender-System API）</news:title>
   <news:publication_date>2026-07-09T21:57:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710032</loc>
  <lastmod>2026-07-09T21:56:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間・時間にわたるスパース自己符号化器による教師なし学習（Unsupervised learning with sparse space-and-time autoencoders）</news:title>
   <news:publication_date>2026-07-09T21:56:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710030</loc>
  <lastmod>2026-07-09T21:05:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710028</loc>
  <lastmod>2026-07-09T21:05:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>普遍的半教師付きセマンティックセグメンテーション（Universal Semi-Supervised Semantic Segmentation）</news:title>
   <news:publication_date>2026-07-09T21:05:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710026</loc>
  <lastmod>2026-07-09T21:05:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サーフェス再構成から学ぶマッチャブル画像検索（Matchable Image Retrieval by Learning from Surface Reconstruction）</news:title>
   <news:publication_date>2026-07-09T21:05:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710024</loc>
  <lastmod>2026-07-09T21:04:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冠動脈疾患の機械学習分類の実務的インパクト（Machine Learning Classifications of Coronary Artery Disease）</news:title>
   <news:publication_date>2026-07-09T21:04:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710022</loc>
  <lastmod>2026-07-09T21:04:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散かつ安全な機械学習と自己集計による多者集約（Distributed and Secure ML with Self-tallying Multi-party Aggregation）</news:title>
   <news:publication_date>2026-07-09T21:04:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710020</loc>
  <lastmod>2026-07-09T21:04:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分位相から見るフィードフォワードニューラルネットの学習課題（A Differential Topological View of Challenges in Learning with Feedforward Neural Networks）</news:title>
   <news:publication_date>2026-07-09T21:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710018</loc>
  <lastmod>2026-07-09T21:04:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ階層独立相関フィルタによる映像トラッキングの実務的意義（Multi-hierarchical Independent Correlation Filters for Visual Tracking）</news:title>
   <news:publication_date>2026-07-09T21:04:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710016</loc>
  <lastmod>2026-07-09T20:12:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分オートエンコーダを用いたLHCでの新物理探索（Variational Autoencoders for New Physics Mining at the Large Hadron Collider）</news:title>
   <news:publication_date>2026-07-09T20:12:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710014</loc>
  <lastmod>2026-07-09T20:12:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然環境を用いた可変BCI刺激によるヒューマノイドロボットのリアルタイムナビゲーション（Using Variable Natural Environment Brain-Computer Interface Stimuli for Real-time Humanoid Robot Navigation）</news:title>
   <news:publication_date>2026-07-09T20:12:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710012</loc>
  <lastmod>2026-07-09T20:11:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的積分と統計計算の役割に関する再応答（Rejoinder for “Probabilistic Integration: A Role in Statistical Computation?”）</news:title>
   <news:publication_date>2026-07-09T20:11:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710010</loc>
  <lastmod>2026-07-09T20:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集団誘導型ノベルティサーチが変える探索戦略（Population-Guided Novelty Search for Reinforcement Learning in Hard Exploration Environments）</news:title>
   <news:publication_date>2026-07-09T20:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710008</loc>
  <lastmod>2026-07-09T20:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト文書処理のための一般化差分プライバシー（Generalised Differential Privacy for Text Document Processing）</news:title>
   <news:publication_date>2026-07-09T20:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710006</loc>
  <lastmod>2026-07-09T20:10:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮可能かつ学習可能な暗号化によるクラウド活用の安全設計（Compressible and Learnable Encryption for Untrusted Cloud Environments）</news:title>
   <news:publication_date>2026-07-09T20:10:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710004</loc>
  <lastmod>2026-07-09T20:10:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>製品市場予測におけるネットワークと機械学習の統合アプローチ（A combined network and machine learning approaches for product market forecasting）</news:title>
   <news:publication_date>2026-07-09T20:10:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710002</loc>
  <lastmod>2026-07-09T19:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在的信念の学習と認識的推論による効率的かつ有意義な対話管理（Learning Latent Beliefs and Performing Epistemic Reasoning for Efficient and Meaningful Dialog Management）</news:title>
   <news:publication_date>2026-07-09T19:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710000</loc>
  <lastmod>2026-07-09T19:18:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形効果の堅牢な推定と検定（CVEK: Robust Estimation and Testing for Nonlinear Effects using Kernel Machine Ensemble）</news:title>
   <news:publication_date>2026-07-09T19:18:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709998</loc>
  <lastmod>2026-07-09T19:18:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像で物体を3D位置まで特定する技術の実用化可能性（MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization）</news:title>
   <news:publication_date>2026-07-09T19:18:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709996</loc>
  <lastmod>2026-07-09T19:17:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ構造を用いたマルチタスク学習（Multi-task Learning over Graph Structures）</news:title>
   <news:publication_date>2026-07-09T19:17:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709994</loc>
  <lastmod>2026-07-09T19:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像による物体検出と姿勢推定の総覧（A survey on joint object detection and pose estimation using monocular vision）</news:title>
   <news:publication_date>2026-07-09T19:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709992</loc>
  <lastmod>2026-07-09T19:17:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた都市規模道路監査システム（City-Scale Road Audit System using Deep Learning）</news:title>
   <news:publication_date>2026-07-09T19:17:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709990</loc>
  <lastmod>2026-07-09T19:16:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attentioned Convolutional LSTM Inpainting Networkによる映像異常検知の要点と実務インパクト（Attentioned Convolutional LSTM Inpainting Network for Anomaly Detection in Videos）</news:title>
   <news:publication_date>2026-07-09T19:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709988</loc>
  <lastmod>2026-07-09T18:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの3D車線検出の直截的手法（3D-LaneNet: End-to-End 3D Multiple Lane Detection）</news:title>
   <news:publication_date>2026-07-09T18:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709986</loc>
  <lastmod>2026-07-09T18:25:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス認識型ニューラルアーキテクチャ探索（InstaNAS: Instance-aware Neural Architecture Search）</news:title>
   <news:publication_date>2026-07-09T18:25:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709984</loc>
  <lastmod>2026-07-09T18:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非構造化環境における自律走行のためのデータセットIDD (IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained Environments)</news:title>
   <news:publication_date>2026-07-09T18:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709982</loc>
  <lastmod>2026-07-09T18:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TMA画像解析に深層特徴を取り入れる意義（Incorporating Deep Features in the Analysis of Tissue Microarray Images）</news:title>
   <news:publication_date>2026-07-09T18:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709980</loc>
  <lastmod>2026-07-09T18:24:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境シーン認識における単純クラスタリングの実用性（SERVANT: Scene Recognition Through Visual and Acoustic Cues）</news:title>
   <news:publication_date>2026-07-09T18:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709978</loc>
  <lastmod>2026-07-09T18:24:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非公式中国語の大規模コーパスLSICCの意義（LSICC: A LARGE SCALE INFORMAL CHINESE CORPUS）</news:title>
   <news:publication_date>2026-07-09T18:24:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709976</loc>
  <lastmod>2026-07-09T18:24:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像と音声を組み合わせた鳥種分類の新展開（Cross-domain Deep Feature Combination for Bird Species Classification with Audio-visual Data）</news:title>
   <news:publication_date>2026-07-09T18:24:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709974</loc>
  <lastmod>2026-07-09T17:32:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックスモデルの説明をやめて解釈可能なモデルを使うべきだ（Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead）</news:title>
   <news:publication_date>2026-07-09T17:32:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709972</loc>
  <lastmod>2026-07-09T17:24:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像時系列の分類における時間畳み込みニューラルネットワーク（Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series）</news:title>
   <news:publication_date>2026-07-09T17:24:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709970</loc>
  <lastmod>2026-07-09T17:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人化された商品検索のための注意付き長短期嗜好モデリング（Attentive Long Short-Term Preference Modeling for Personalized Product Search）</news:title>
   <news:publication_date>2026-07-09T17:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709968</loc>
  <lastmod>2026-07-09T17:24:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習によるアップリフトモデリングの再定式化（Reinforcement Learning for Uplift Modeling）</news:title>
   <news:publication_date>2026-07-09T17:24:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709966</loc>
  <lastmod>2026-07-09T17:23:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Self-similarity Groupingによる人物再識別の非教師ドメイン適応（Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification）</news:title>
   <news:publication_date>2026-07-09T17:23:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709964</loc>
  <lastmod>2026-07-09T17:22:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的損失関数を持つ深層学習における周波数原理とその応用可能性 (Frequency Principle in Deep Learning with General Loss Functions and Its Potential Application)</news:title>
   <news:publication_date>2026-07-09T17:22:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709962</loc>
  <lastmod>2026-07-09T17:22:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内部表現コラージュによる空間制御可能な画像合成（Spatially Controllable Image Synthesis with Internal Representation Collaging）</news:title>
   <news:publication_date>2026-07-09T17:22:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709960</loc>
  <lastmod>2026-07-09T16:31:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚障害者向けモバイルコンピューティングの概観（A Survey of Mobile Computing for the Visually Impaired）</news:title>
   <news:publication_date>2026-07-09T16:31:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709958</loc>
  <lastmod>2026-07-09T16:31:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hapi: 標準WiFiで実現する疑似3次元キャリブレーションフリー屋内測位（Hapi: A Robust Pseudo-3D Calibration-Free WiFi-based Indoor Localization System）</news:title>
   <news:publication_date>2026-07-09T16:31:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709956</loc>
  <lastmod>2026-07-09T16:31:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Foreground Clusteringによる画像・動画の同時セグメンテーションとローカリゼーション（Foreground Clustering for Joint Segmentation and Localization in Videos and Images）</news:title>
   <news:publication_date>2026-07-09T16:31:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709954</loc>
  <lastmod>2026-07-09T16:30:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>従属データと外れ値からの多項式近似の復元保証 (Recovery Guarantees for Polynomial Approximation from Dependent Data with Outliers)</news:title>
   <news:publication_date>2026-07-09T16:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709952</loc>
  <lastmod>2026-07-09T16:30:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希少疾患診断タスクに対するモデルベース強化学習アプローチ（A MODEL-BASED REINFORCEMENT LEARNING APPROACH FOR A RARE DISEASE DIAGNOSTIC TASK）</news:title>
   <news:publication_date>2026-07-09T16:30:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709950</loc>
  <lastmod>2026-07-09T16:30:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分によるエンドツーエンド航行と自己位置推定（Variational End-to-End Navigation and Localization）</news:title>
   <news:publication_date>2026-07-09T16:30:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709948</loc>
  <lastmod>2026-07-09T16:29:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォン上でリアルタイム睡眠段階判定を行う研究の要点（Real-Time Sleep Staging using Deep Learning on a Smartphone for a Wearable EEG）</news:title>
   <news:publication_date>2026-07-09T16:29:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709946</loc>
  <lastmod>2026-07-09T15:38:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率最適化のための不正確SARAHアルゴリズム（Inexact SARAH Algorithm for Stochastic Optimization）</news:title>
   <news:publication_date>2026-07-09T15:38:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709944</loc>
  <lastmod>2026-07-09T15:38:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース主成分解析をスパース線形回帰から解く（Sparse PCA from Sparse Linear Regression）</news:title>
   <news:publication_date>2026-07-09T15:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709942</loc>
  <lastmod>2026-07-09T15:37:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗号通貨のポンプ・アンド・ダンプの構造解析（The Anatomy of a Cryptocurrency Pump-and-Dump Scheme）</news:title>
   <news:publication_date>2026-07-09T15:37:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709940</loc>
  <lastmod>2026-07-09T15:37:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き自己回帰モデルによる動的環境での計画（Planning in Dynamic Environments with Conditional Autoregressive Models）</news:title>
   <news:publication_date>2026-07-09T15:37:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709938</loc>
  <lastmod>2026-07-09T15:37:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WarpGANによる自動カリカチュア生成（WarpGAN: Automatic Caricature Generation）</news:title>
   <news:publication_date>2026-07-09T15:37:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709936</loc>
  <lastmod>2026-07-09T15:37:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習による逆治療計画の知能化（Intelligent Inverse Treatment Planning via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-09T15:37:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709934</loc>
  <lastmod>2026-07-09T15:37:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テストの（不）公平性から学ぶ教訓（50 Years of Test (Un)fairness: Lessons for Machine Learning）</news:title>
   <news:publication_date>2026-07-09T15:37:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709932</loc>
  <lastmod>2026-07-09T14:45:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データ時代におけるSGLDの光と影（The promises and pitfalls of Stochastic Gradient Langevin Dynamics）</news:title>
   <news:publication_date>2026-07-09T14:45:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709930</loc>
  <lastmod>2026-07-09T14:45:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キャプションから学ぶ開かれた語彙の物体検出（Learning to discover and localize visual objects with open vocabulary）</news:title>
   <news:publication_date>2026-07-09T14:45:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709928</loc>
  <lastmod>2026-07-09T14:44:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚と言語の統合で進化するナビゲーション学習（Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation）</news:title>
   <news:publication_date>2026-07-09T14:44:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709926</loc>
  <lastmod>2026-07-09T14:43:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>虹彩のテクスチャーからの性別推定は思ったより難しい（Predicting Gender From Iris Texture May Be Harder Than It Seems）</news:title>
   <news:publication_date>2026-07-09T14:43:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709924</loc>
  <lastmod>2026-07-09T14:43:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数視点学習による虹彩プレゼンテーション攻撃検出のアンサンブル（Ensemble of Multi-View Learning Classifiers for Cross-Domain Iris Presentation Attack Detection）</news:title>
   <news:publication_date>2026-07-09T14:43:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709922</loc>
  <lastmod>2026-07-09T14:43:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競技推論のアリーナモデル（Arena Model: Inference About Competitions）</news:title>
   <news:publication_date>2026-07-09T14:43:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709920</loc>
  <lastmod>2026-07-09T14:43:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超辺（ハイパーグラフ）上の能動学習：HS2（Active Learning over Hypergraphs）</news:title>
   <news:publication_date>2026-07-09T14:43:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709918</loc>
  <lastmod>2026-07-09T13:51:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像における深層学習の概観（An overview of deep learning in medical imaging focusing on MRI）</news:title>
   <news:publication_date>2026-07-09T13:51:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709916</loc>
  <lastmod>2026-07-09T13:50:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BDLOB: ベイズ的深層畳み込みニューラルネットワークによる限界板データ解析（BDLOB: Bayesian Deep Convolutional Neural Networks for Limit Order Books）</news:title>
   <news:publication_date>2026-07-09T13:50:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709914</loc>
  <lastmod>2026-07-09T13:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知に着想を得たホメオスタシスがロボットの複合的ニーズを両立させる（Cognition-inspired homeostasis can balance conflicting needs in robots）</news:title>
   <news:publication_date>2026-07-09T13:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709912</loc>
  <lastmod>2026-07-09T13:49:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語と視覚注意で導く追跡手法（Describe and Attend to Track: Learning Natural Language guided Structural Representation and Visual Attention for Object Tracking）</news:title>
   <news:publication_date>2026-07-09T13:49:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709910</loc>
  <lastmod>2026-07-09T13:49:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム意味理解を用いた背景差分（Background Subtraction with Real-time Semantic Segmentation）</news:title>
   <news:publication_date>2026-07-09T13:49:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709908</loc>
  <lastmod>2026-07-09T13:48:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽画像における視覚注意の検証――既存モデルは何を予測しているのか（Visual Attention on the Sun: What Do Existing Models Actually Predict?）</news:title>
   <news:publication_date>2026-07-09T13:48:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709906</loc>
  <lastmod>2026-07-09T13:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を確率的に扱う弱教師あり物体検出の革新（Dissimilarity Coefﬁcient based Weakly Supervised Object Detection）</news:title>
   <news:publication_date>2026-07-09T13:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709904</loc>
  <lastmod>2026-07-09T12:57:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低解像度顔認識を効率化する選択的知識蒸留（Low-resolution Face Recognition via Selective Knowledge Distillation）</news:title>
   <news:publication_date>2026-07-09T12:57:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709902</loc>
  <lastmod>2026-07-09T12:56:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非局所RoIによるクロスオブジェクト認識（Non-local RoI for Cross-Object Perception）</news:title>
   <news:publication_date>2026-07-09T12:56:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709900</loc>
  <lastmod>2026-07-09T12:55:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測アクション認識のための代替観測を用いた条件付きランダムフィールド学習（Learning Conditional Random Fields with Augmented Observations for Partially Observed Action Recognition）</news:title>
   <news:publication_date>2026-07-09T12:55:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709898</loc>
  <lastmod>2026-07-09T12:55:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的環境におけるデータクラスタリングの安全性（Is Data Clustering in Adversarial Settings Secure?）</news:title>
   <news:publication_date>2026-07-09T12:55:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709896</loc>
  <lastmod>2026-07-09T12:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動ベースのマルウェアクラスタリングに対する汚染攻撃（Poisoning Behavioral Malware Clustering）</news:title>
   <news:publication_date>2026-07-09T12:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709894</loc>
  <lastmod>2026-07-09T12:55:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>しきい値を確度高く見つけるための堅牢な領域推定（Robust Super-Level Set Estimation using Gaussian Processes）</news:title>
   <news:publication_date>2026-07-09T12:55:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709892</loc>
  <lastmod>2026-07-09T12:03:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列変分オートエンコーダによる協調フィルタリングの進化（Sequential Variational Autoencoders for Collaborative Filtering）</news:title>
   <news:publication_date>2026-07-09T12:03:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709890</loc>
  <lastmod>2026-07-09T12:03:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graph Learning-Convolutional Networksの要点解説（Graph Learning-Convolutional Networks）</news:title>
   <news:publication_date>2026-07-09T12:03:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709888</loc>
  <lastmod>2026-07-09T12:03:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列双線形ネットワークによるビデオ行動認識 (Temporal Bilinear Networks for Video Action Recognition)</news:title>
   <news:publication_date>2026-07-09T12:03:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709886</loc>
  <lastmod>2026-07-09T12:02:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメインウォールシナプスを用いたオンチップ学習対応FCNN（On-chip learning for domain wall synapse based Fully Connected Neural Network）</news:title>
   <news:publication_date>2026-07-09T12:02:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709884</loc>
  <lastmod>2026-07-09T12:02:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚系列処理のための深層RNNフレームワーク（Deep RNN Framework for Visual Sequential Applications）</news:title>
   <news:publication_date>2026-07-09T12:02:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709882</loc>
  <lastmod>2026-07-09T12:02:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイスループット実験と機械学習で加速する太陽電池材料探索（Accelerating Photovoltaic Materials Development via High-Throughput Experiments and Machine-Learning-Assisted Diagnosis）</news:title>
   <news:publication_date>2026-07-09T12:02:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709880</loc>
  <lastmod>2026-07-09T12:01:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェブのラベル付きデータから学ぶ音響イベント学習 (Learning Sound Events from Webly Labeled Data)</news:title>
   <news:publication_date>2026-07-09T12:01:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709878</loc>
  <lastmod>2026-07-09T11:10:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病的音声信号からの声門閉鎖時刻検出（Glottal Closure Instants Detection From Pathological Acoustic Speech Signal Using Deep Learning）</news:title>
   <news:publication_date>2026-07-09T11:10:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709876</loc>
  <lastmod>2026-07-09T11:10:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Faster CryptoNets：暗号化下での推論を実用秒単位へ（Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted Inference）</news:title>
   <news:publication_date>2026-07-09T11:10:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709874</loc>
  <lastmod>2026-07-09T11:10:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Online Newton Step をバンディット設定で使う意味（Online Newton Step Algorithm with Estimated Gradient）</news:title>
   <news:publication_date>2026-07-09T11:10:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709872</loc>
  <lastmod>2026-07-09T11:09:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテでの完全プライベート深層学習パイプライン（A Fully Private Pipeline for Deep Learning on Electronic Health Records）</news:title>
   <news:publication_date>2026-07-09T11:09:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709870</loc>
  <lastmod>2026-07-09T11:09:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wi‑Fiアクセスへの学習的アプローチ (A Learning Approach to Wi‑Fi Access)</news:title>
   <news:publication_date>2026-07-09T11:09:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709868</loc>
  <lastmod>2026-07-09T11:09:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低解像度深度画像を用いたスマート病院向けプライバシー保護行動認識（Privacy-Preserving Action Recognition for Smart Hospitals using Low-Resolution Depth Images）</news:title>
   <news:publication_date>2026-07-09T11:09:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709866</loc>
  <lastmod>2026-07-09T11:08:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB-D特徴ピラミッドSiameseネットワークによるループクロージャ検出（Loop Closure Detection with RGB-D Feature Pyramid Siamese Networks）</news:title>
   <news:publication_date>2026-07-09T11:08:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709864</loc>
  <lastmod>2026-07-09T10:17:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習の平均情報複雑性（Average-Case Information Complexity of Learning）</news:title>
   <news:publication_date>2026-07-09T10:17:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709862</loc>
  <lastmod>2026-07-09T10:17:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚オドメトリにおける誘導付き特徴選択（Guided Feature Selection for Deep Visual Odometry）</news:title>
   <news:publication_date>2026-07-09T10:17:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709860</loc>
  <lastmod>2026-07-09T10:16:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>業績指標を用いた金融ニュースの感情分析（Sentiment Analysis of Financial News Articles using Performance Indicators）</news:title>
   <news:publication_date>2026-07-09T10:16:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709858</loc>
  <lastmod>2026-07-09T10:16:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統一知能通信モデルの概観（An Unified Intelligence-Communication Model for Multi-Agent System Part-I: Overview）</news:title>
   <news:publication_date>2026-07-09T10:16:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709856</loc>
  <lastmod>2026-07-09T10:16:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話音声からの認知症検出手法の実用性と示唆（A Method for Analysis of Patient Speech in Dialogue for Dementia Detection）</news:title>
   <news:publication_date>2026-07-09T10:16:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709854</loc>
  <lastmod>2026-07-09T10:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国上場企業の信頼性評価へのLDA＋残差CNNの応用（Latent Dirichlet Allocation with Residual Convolutional Neural Network Applied in Evaluating Credibility of Chinese Listed Companies）</news:title>
   <news:publication_date>2026-07-09T10:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709852</loc>
  <lastmod>2026-07-09T10:15:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェア条件付きポリシーによるマルチロボット転移学習（Hardware Conditioned Policies for Multi-Robot Transfer Learning）</news:title>
   <news:publication_date>2026-07-09T10:15:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709850</loc>
  <lastmod>2026-07-09T09:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似マージンを用いた極端多クラス分類の高速化（MEMOIR: Multi-class Extreme Classification with Inexact Margin）</news:title>
   <news:publication_date>2026-07-09T09:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709848</loc>
  <lastmod>2026-07-09T09:23:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期関数を正則化として用いたニューラルネットワークの量子化（ON PERIODIC FUNCTIONS AS REGULARIZERS FOR QUANTIZATION OF NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-07-09T09:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709846</loc>
  <lastmod>2026-07-09T09:23:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>品質認識特徴集約ネットワークによる堅牢なRGBTトラッキング（Quality-aware Feature Aggregation Network for Robust RGBT Tracking）</news:title>
   <news:publication_date>2026-07-09T09:23:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709844</loc>
  <lastmod>2026-07-09T09:22:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OCLEP+ による一クラス異常検知の実務的示唆（OCLEP+: One-class Anomaly and Intrusion Detection Using Minimal Length of Emerging Patterns）</news:title>
   <news:publication_date>2026-07-09T09:22:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709842</loc>
  <lastmod>2026-07-09T09:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的マルチフレームレート解析による効率的ビデオ理解（Efficient Video Understanding via Layered Multi Frame-Rate Analysis）</news:title>
   <news:publication_date>2026-07-09T09:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709840</loc>
  <lastmod>2026-07-09T09:22:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性意識損失を用いた頑健なRGB-D顔認識（Robust RGB-D Face Recognition Using Attribute-Aware Loss）</news:title>
   <news:publication_date>2026-07-09T09:22:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709838</loc>
  <lastmod>2026-07-09T09:22:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移性メラノーマに対する適応的治療推奨と結果予測モデル（An adaptive treatment recommendation and outcome prediction model for metastatic melanoma）</news:title>
   <news:publication_date>2026-07-09T09:22:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709836</loc>
  <lastmod>2026-07-09T08:31:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オブジェクト検出を活用した教師なしディープハッシング（Object Detection based Deep Unsupervised Hashing）</news:title>
   <news:publication_date>2026-07-09T08:31:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709834</loc>
  <lastmod>2026-07-09T08:30:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的ニューラルハイブリッドエージェントによるアーキテクチャ探索（Evolutionary-Neural Hybrid Agents for Architecture Search）</news:title>
   <news:publication_date>2026-07-09T08:30:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709832</loc>
  <lastmod>2026-07-09T08:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強誘電性ペロブスカイトに対するEwald和の体系化（Ewald summation for ferroelectric perovskites with charges and dipoles）</news:title>
   <news:publication_date>2026-07-09T08:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709830</loc>
  <lastmod>2026-07-09T08:30:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースグラフ上の極性復号を深層学習で改善する（Polar Decoding on Sparse Graphs with Deep Learning）</news:title>
   <news:publication_date>2026-07-09T08:30:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709828</loc>
  <lastmod>2026-07-09T08:29:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在特徴摂動による深層ニューラルネットワークの証拠に基づく条件推論の新手法（A Novel Technique for Evidence based Conditional Inference in Deep Neural Networks via Latent Feature Perturbation）</news:title>
   <news:publication_date>2026-07-09T08:29:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709826</loc>
  <lastmod>2026-07-09T08:29:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約充足問題の変分推論の簡素化（Streamlining Variational Inference for Constraint Satisfaction Problems）</news:title>
   <news:publication_date>2026-07-09T08:29:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709824</loc>
  <lastmod>2026-07-09T08:29:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ版QuickNAT：構造別不確かさを用いた脳全体セグメンテーションの品質管理（Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation for Structure-wise Quality Control）</news:title>
   <news:publication_date>2026-07-09T08:29:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709822</loc>
  <lastmod>2026-07-09T07:38:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子の三次元情報を扱うグラフ畳み込みネットワーク（Three-Dimensionally Embedded Graph Convolutional Network (3DGCN) for Molecule Interpretation）</news:title>
   <news:publication_date>2026-07-09T07:38:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709820</loc>
  <lastmod>2026-07-09T07:38:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師あり動画表現学習と時空立方体パズル（Self-Supervised Video Representation Learning with Space-Time Cubic Puzzles）</news:title>
   <news:publication_date>2026-07-09T07:38:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709818</loc>
  <lastmod>2026-07-09T07:37:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし動画要約の識別的特徴学習（Discriminative Feature Learning for Unsupervised Video Summarization）</news:title>
   <news:publication_date>2026-07-09T07:37:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709816</loc>
  <lastmod>2026-07-09T07:37:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>早産予測における交互損失補正（Alternating Loss Correction for Preterm-Birth Prediction from EHR Data with Noisy Labels）</news:title>
   <news:publication_date>2026-07-09T07:37:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709814</loc>
  <lastmod>2026-07-09T07:37:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>A2Netによる単一画像の水滴除去と実務的意義（A2Net: Adjacent Aggregation Networks for Image Raindrop Removal）</news:title>
   <news:publication_date>2026-07-09T07:37:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709812</loc>
  <lastmod>2026-07-09T07:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰で制御する再帰ネットワークが示す新たな系列表現力（Recurrently Controlled Recurrent Networks）</news:title>
   <news:publication_date>2026-07-09T07:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709810</loc>
  <lastmod>2026-07-09T07:36:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情を織り込む画像キャプション手法の提案（SENTI-ATTEND: Image Captioning using Sentiment and Attention）</news:title>
   <news:publication_date>2026-07-09T07:36:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709808</loc>
  <lastmod>2026-07-09T06:45:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DEFactor: 連続的に最適化可能な分子グラフ生成の新手法（DEFactor: Differentiable Edge Factorization-based Probabilistic Graph Generation）</news:title>
   <news:publication_date>2026-07-09T06:45:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709806</loc>
  <lastmod>2026-07-09T06:44:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲームベース学習アプリが学習動機に与える影響の実証（Sewer Rats in Teaching Action）</news:title>
   <news:publication_date>2026-07-09T06:44:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709804</loc>
  <lastmod>2026-07-09T06:44:26Z</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自動塩体解釈（Automatic Seismic Salt Interpretation with Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-09T06:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709802</loc>
  <lastmod>2026-07-09T06:43:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハッシュ検索の評価を見直す指標：Mean Local Group Average Precision（Mean Local Group Average Precision (mLGAP): A New Performance Metric for Hashing-based Retrieval）</news:title>
   <news:publication_date>2026-07-09T06:43:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709800</loc>
  <lastmod>2026-07-09T06:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中継ノードを能動的に制御する学習（Learning To Activate Relay Nodes: Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-07-09T06:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709798</loc>
  <lastmod>2026-07-09T06:43:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情の相互相関を推定する深層ニューラルネットワーク（Estimation of Inter-Sentiment Correlations Employing Deep Neural Network Models）</news:title>
   <news:publication_date>2026-07-09T06:43:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709796</loc>
  <lastmod>2026-07-09T06:42:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理情報を組み込んだCoKriging（Physics-Informed CoKriging: A Gaussian-Process-Regression-Based Multifidelity Method for Data-Model Convergence）</news:title>
   <news:publication_date>2026-07-09T06:42:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709794</loc>
  <lastmod>2026-07-09T05:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネガティブ・トランスファーの定量化と回避（Characterizing and Avoiding Negative Transfer）</news:title>
   <news:publication_date>2026-07-09T05:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709792</loc>
  <lastmod>2026-07-09T05:51:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタリングモデルのための償却化ベイズ推論 (Amortized Bayesian inference for clustering models)</news:title>
   <news:publication_date>2026-07-09T05:51:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709790</loc>
  <lastmod>2026-07-09T05:50:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLEとRLをつなぐ枠組み：系列予測における最尤法と強化学習の接続 (Connecting the Dots Between MLE and RL for Sequence Prediction)</news:title>
   <news:publication_date>2026-07-09T05:50:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709788</loc>
  <lastmod>2026-07-09T05:50:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TrIMS: 低遅延深層学習推論のための透過的分離モデル共有（Transparent and Isolated Model Sharing for Low Latency Deep Learning Inference in Function as a Service Environments）</news:title>
   <news:publication_date>2026-07-09T05:50:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709786</loc>
  <lastmod>2026-07-09T05:50:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソル・コアを用いたリダクションとスキャンの高速化（Accelerating Reduction and Scan Using Tensor Core Units）</news:title>
   <news:publication_date>2026-07-09T05:50:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709784</loc>
  <lastmod>2026-07-09T05:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ変数積層LSTMによる短期風速予測（A Multi-variable Stacked Long-Short Term Memory Network for Wind Speed Forecasting）</news:title>
   <news:publication_date>2026-07-09T05:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709782</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>共有モデルの再現がうまくいかないと感じたら（Frustrated with Replicating Claims of a Shared Model? A Solution）</news:title>
   <news:publication_date>2026-07-09T05:49:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709780</loc>
  <lastmod>2026-07-09T04:58:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多元素合金の原子ポテンシャルを学習する3Dボクセル深層学習（3D Deep Learning with voxelized atomic configurations for modeling atomistic potentials in complex solid-solution alloys）</news:title>
   <news:publication_date>2026-07-09T04:58:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709778</loc>
  <lastmod>2026-07-09T04:58:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な畳み込みフィルタとSincNet（Interpretable Convolutional Filters with SincNet）</news:title>
   <news:publication_date>2026-07-09T04:58:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709776</loc>
  <lastmod>2026-07-09T04:58:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>皮膚用ダーモスコピー画像における自動病変境界検出（Automatic lesion boundary detection in dermoscopy）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709774</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>信用できない環境でのプライベートなマルチパーティ機械学習（Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709772</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>脳に学ぶ注意の学習――ATTNetによる視覚注意の強化学習的モデル化（Learning to attend in a brain-inspired deep neural network）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709770</loc>
  <lastmod>2026-07-09T04:57:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>曲率正則化によるロバスト性の向上（Robustness via curvature regularization, and vice versa）</news:title>
   <news:publication_date>2026-07-09T04:57:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709768</loc>
  <lastmod>2026-07-09T04:56:45Z</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説明のための代表点選択（Representer Point Selection for Explaining Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-09T04:56:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709766</loc>
  <lastmod>2026-07-09T04:05:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TorchProteinLibrary：高速で微分可能なタンパク質構造表現（TorchProteinLibrary: A computationally efﬁcient, differentiable representation of protein structure）</news:title>
   <news:publication_date>2026-07-09T04:05:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709764</loc>
  <lastmod>2026-07-09T04:05:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしで脳白質病変を自動検出する技術の本質（Unsupervised brain lesion segmentation from MRI using a convolutional autoencoder）</news:title>
   <news:publication_date>2026-07-09T04:05:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709762</loc>
  <lastmod>2026-07-09T04:05:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層特徴とスパース表現を組み合わせたCBIRの比較検討（Detailed Investigation of Deep Features with Sparse Representation and Dimensionality Reduction in CBIR: A Comparative Study）</news:title>
   <news:publication_date>2026-07-09T04:05:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709760</loc>
  <lastmod>2026-07-09T04:04:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>子宮頸部細胞画像のための新しいデータセットと核検出法の提案（A NEW CERVICAL CYTOLOGY DATASET FOR NUCLEUS DETECTION AND IMAGE CLASSIFICATION (CERVIX93)）</news:title>
   <news:publication_date>2026-07-09T04:04:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709758</loc>
  <lastmod>2026-07-09T04:04:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ASASSN-18btの系統解析：非縮退伴星の否定によるIa型超新星論の再整理（No Stripped Companion Material in the Nebular Spectrum of the “Two-Component” Type Ia Supernova ASASSN-18bt）</news:title>
   <news:publication_date>2026-07-09T04:04:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709756</loc>
  <lastmod>2026-07-09T04:04:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意思決定カスケードにおける信念の役割（Beliefs in Decision-Making Cascades）</news:title>
   <news:publication_date>2026-07-09T04:04:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709754</loc>
  <lastmod>2026-07-09T04:04:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽系に取り込まれた恒星間天体の識別法（Identifying Interstellar Objects Trapped in the Solar System through Their Orbital Parameters）</news:title>
   <news:publication_date>2026-07-09T04:04:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709752</loc>
  <lastmod>2026-07-09T03:12:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FLaREONによる高速なLyα放射の予測（FLaREON: a fast computation of Lyα escape fractions and line profiles）</news:title>
   <news:publication_date>2026-07-09T03:12:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709750</loc>
  <lastmod>2026-07-09T03:12:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ギャップ内での惑星による分子線幅拡張の観測的指標（Observational Signatures of Planets in Protoplanetary Disks: Planet-Induced Line Broadening in Gaps）</news:title>
   <news:publication_date>2026-07-09T03:12:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709748</loc>
  <lastmod>2026-07-09T03:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Model-Based Reinforcement Learningを用いた敗血症治療（Model-Based Reinforcement Learning for Sepsis Treatment）</news:title>
   <news:publication_date>2026-07-09T03:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709746</loc>
  <lastmod>2026-07-09T03:11:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子における関係性を発見・統合するスペクトル・マルチグラフネットワーク（Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules）</news:title>
   <news:publication_date>2026-07-09T03:11:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709744</loc>
  <lastmod>2026-07-09T03:11:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長文翻訳に強い階層型ニューラルネットワークの提案（A Hierarchical Neural Network for Sequence-to-Sequences Learning）</news:title>
   <news:publication_date>2026-07-09T03:11:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709742</loc>
  <lastmod>2026-07-09T03:11:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習理論における普遍的推定量の再検討（Note on universal algorithms for learning theory）</news:title>
   <news:publication_date>2026-07-09T03:11:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709740</loc>
  <lastmod>2026-07-09T03:11:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的イノベーションと創造的で持続可能な世界観の進化（Social Innovation and the Evolution of Creative, Sustainable Worldviews）</news:title>
   <news:publication_date>2026-07-09T03:11:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709738</loc>
  <lastmod>2026-07-09T02:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知のガウス過程事前分布を伴うメタベイズ最適化の後悔境界（Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior）</news:title>
   <news:publication_date>2026-07-09T02:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709736</loc>
  <lastmod>2026-07-09T02:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現データの二方向クラスタリングにおけるFCAとアソシエーションルールの活用（Biclustering Gene Expression Data Using FCA and Association Rules）</news:title>
   <news:publication_date>2026-07-09T02:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709734</loc>
  <lastmod>2026-07-09T02:14:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルに基づく生成ネットワークの学習（Kernel-Based Training of Generative Networks）</news:title>
   <news:publication_date>2026-07-09T02:14:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709732</loc>
  <lastmod>2026-07-09T02:14:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lipschitz正則化がGAN訓練に与える影響（How does Lipschitz Regularization Influence GAN Training?）</news:title>
   <news:publication_date>2026-07-09T02:14:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709730</loc>
  <lastmod>2026-07-09T02:13:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超高次元コンピューティングのナノシステム（Hyperdimensional Computing Nanosystem）</news:title>
   <news:publication_date>2026-07-09T02:13:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709728</loc>
  <lastmod>2026-07-09T02:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VGGを用いた自動ぶどう樹フェノタイピングの適応的手法（An Adaptive Approach for Automated Grapevine Phenotyping using VGG-based Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-09T02:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709726</loc>
  <lastmod>2026-07-09T02:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成記憶のためのアトラクタダイナミクス学習（Learning Attractor Dynamics for Generative Memory）</news:title>
   <news:publication_date>2026-07-09T02:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709724</loc>
  <lastmod>2026-07-09T01:21:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダーで見つける慣性多様体の次元（Estimating of the inertial manifold dimension for a chaotic attractor of complex Ginzburg-Landau equation using a neural network）</news:title>
   <news:publication_date>2026-07-09T01:21:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709722</loc>
  <lastmod>2026-07-09T01:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核弾頭認証プロトコルにおけるプライバシーの定量化（Quantifying Privacy in Nuclear Warhead Authentication Protocols）</news:title>
   <news:publication_date>2026-07-09T01:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709720</loc>
  <lastmod>2026-07-09T01:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元分類におけるℓ0ペナルティ付き経験的リスク最小化（High Dimensional Classification through ℓ0-Penalized Empirical Risk Minimization）</news:title>
   <news:publication_date>2026-07-09T01:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709718</loc>
  <lastmod>2026-07-09T01:20:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非ガウス分布データ解析の実務的手法（Selected Methods for non-Gaussian Data Analysis）</news:title>
   <news:publication_date>2026-07-09T01:20:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709716</loc>
  <lastmod>2026-07-09T01:20:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海中ハイドロフォンの特性評価とKM3NeT実験の示唆（Hydrophone characterization for the KM3NeT experiment）</news:title>
   <news:publication_date>2026-07-09T01:20:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709714</loc>
  <lastmod>2026-07-09T01:20:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>惑星探査ローバのグローバル経路計画に関する学習ベースの新手法（A Novel Learning-based Global Path Planning Algorithm for Planetary Rovers）</news:title>
   <news:publication_date>2026-07-09T01:20:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709712</loc>
  <lastmod>2026-07-09T01:20:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜画像における視神経乳頭（Optic Disc）と中心窩（Fovea）の位置推定に関する関係ネットワークの応用（Relation Networks for Optic Disc and Fovea Localization in Retinal Images）</news:title>
   <news:publication_date>2026-07-09T01:20:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709710</loc>
  <lastmod>2026-07-09T00:28:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実データの特徴を合成空間へ写像する手法の実務的意義（Mapping Unlabeled Real Data for Label AUstERity）</news:title>
   <news:publication_date>2026-07-09T00:28:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709708</loc>
  <lastmod>2026-07-09T00:27:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差が特徴となる稲妻予測（The Error is the Feature: How to Forecast Lightning using a Model Prediction Error）</news:title>
   <news:publication_date>2026-07-09T00:27:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709706</loc>
  <lastmod>2026-07-09T00:27:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Privacy-preserving Stackingによる組織間糖尿病予測の秘匿化（Privacy-preserving Stacking with Application to Cross-organizational Diabetes Prediction）</news:title>
   <news:publication_date>2026-07-09T00:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709704</loc>
  <lastmod>2026-07-09T00:27:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列逐次モンテカルロによる非凸確率的最適化（Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization）</news:title>
   <news:publication_date>2026-07-09T00:27:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709702</loc>
  <lastmod>2026-07-09T00:26:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みにおけるフィルタサイズの重要性（On Filter Size in Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-07-09T00:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709700</loc>
  <lastmod>2026-07-09T00:26:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAV画像による欠陥検出とリージョンベースCNNの応用（Defect Detection from UAV Images based on Region-Based CNNs）</news:title>
   <news:publication_date>2026-07-09T00:26:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709698</loc>
  <lastmod>2026-07-09T00:26:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床概念埋め込みを用いた英国EHRにおける心不全予測の応用（Application of Clinical Concept Embeddings for Heart Failure Prediction in UK EHR data）</news:title>
   <news:publication_date>2026-07-09T00:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709696</loc>
  <lastmod>2026-07-08T23:35:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホップフィールド網を使った量子状態準備の地上状態設計（Designing ground states of Hopﬁeld networks for quantum state preparation）</news:title>
   <news:publication_date>2026-07-08T23:35:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709694</loc>
  <lastmod>2026-07-08T23:35:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経架構探索と量子化の共同探索（Joint Neural Architecture Search and Quantization）</news:title>
   <news:publication_date>2026-07-08T23:35:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709692</loc>
  <lastmod>2026-07-08T23:34:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低資源環境における医療分野のタスク指向対話の自然言語理解（Natural language understanding for task oriented dialog in the biomedical domain in a low resources context）</news:title>
   <news:publication_date>2026-07-08T23:34:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709690</loc>
  <lastmod>2026-07-08T23:34:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師あり学習による時系列一貫性の獲得（Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation）</news:title>
   <news:publication_date>2026-07-08T23:34:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709688</loc>
  <lastmod>2026-07-08T23:34:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語レベルの明示的相互作用によるテキスト分類（Explicit Interaction Model towards Text Classification）</news:title>
   <news:publication_date>2026-07-08T23:34:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709686</loc>
  <lastmod>2026-07-08T23:34:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの3D物体再構築に向けた多視点点群回帰（MVPNet: Multi-View Point Regression Networks for 3D Object Reconstruction from A Single Image）</news:title>
   <news:publication_date>2026-07-08T23:34:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709684</loc>
  <lastmod>2026-07-08T23:33:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習アルゴリズムの複数デフォルト学習（Learning Multiple Defaults for Machine Learning Algorithms）</news:title>
   <news:publication_date>2026-07-08T23:33:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709682</loc>
  <lastmod>2026-07-08T22:42:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散系におけるネットワーク制約付き需要応答価格設定のオンライン学習（Online Learning for Network Constrained Demand Response Pricing in Distribution Systems）</news:title>
   <news:publication_date>2026-07-08T22:42:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709680</loc>
  <lastmod>2026-07-08T22:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多チャネル遠隔音声認識における周波数変調特徴量の改善（Improved Frequency Modulation Features for Multichannel Distant Speech Recognition）</news:title>
   <news:publication_date>2026-07-08T22:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709678</loc>
  <lastmod>2026-07-08T22:41:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強力なベースラインの重要性（On the Importance of Strong Baselines in Bayesian Deep Learning）</news:title>
   <news:publication_date>2026-07-08T22:41:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709676</loc>
  <lastmod>2026-07-08T22:41:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>i.i.d. を仮定しない非線形回帰（Nonlinear Regression without i.i.d. Assumption）</news:title>
   <news:publication_date>2026-07-08T22:41:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709674</loc>
  <lastmod>2026-07-08T22:41:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群の回転不変特徴抽出手法（Pointwise Rotation-Invariant Network with Adaptive Sampling and 3D Spherical Voxel Convolution）</news:title>
   <news:publication_date>2026-07-08T22:41:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709672</loc>
  <lastmod>2026-07-08T22:41:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データに強い平均推定をほぼ線形時間で行う方法（High-Dimensional Robust Mean Estimation in Nearly-Linear Time）</news:title>
   <news:publication_date>2026-07-08T22:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709670</loc>
  <lastmod>2026-07-08T22:41:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外国語から発音を学ぶ音声合成ネットワーク（Learning pronunciation from a foreign language in speech synthesis networks）</news:title>
   <news:publication_date>2026-07-08T22:41:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709668</loc>
  <lastmod>2026-07-08T21:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公共データから作る保健脆弱性マップ（Construcción de un Mapa de Vulnerabilidad Sanitaria）</news:title>
   <news:publication_date>2026-07-08T21:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709666</loc>
  <lastmod>2026-07-08T21:49:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AdamとRMSPropの収束を保証する十分条件（A Sufficient Condition for Convergences of Adam and RMSProp）</news:title>
   <news:publication_date>2026-07-08T21:49:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709664</loc>
  <lastmod>2026-07-08T21:48:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雑音に強い話者埋め込みを学習するマルチタスク敵対的ネットワーク（TRAINING MULTI-TASK ADVERSARIAL NETWORK FOR EXTRACTING NOISE-ROBUST SPEAKER EMBEDDING）</news:title>
   <news:publication_date>2026-07-08T21:48:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709662</loc>
  <lastmod>2026-07-08T21:48:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非i.i.d.サンプリングによる効率的学習と汎化の向上（A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better Generalization）</news:title>
   <news:publication_date>2026-07-08T21:48:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709660</loc>
  <lastmod>2026-07-08T21:48:00Z</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よる無線多重経路フェージング・シナリオ識別（Deep Neural Network Aided Scenario Identification in Wireless Multi-path Fading Channels）</news:title>
   <news:publication_date>2026-07-08T21:48:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709658</loc>
  <lastmod>2026-07-08T21:47:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語を発見し、接地し、利用する学習（Learning to Discover, Ground and Use Words with Segmental Neural Language Models）</news:title>
   <news:publication_date>2026-07-08T21:47:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709656</loc>
  <lastmod>2026-07-08T21:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>財務記録と自己注意型循環ニューラルネットワークによる糖尿病進展予測（Predicting Diabetes Disease Evolution Using Financial Records and Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-08T21:47:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709654</loc>
  <lastmod>2026-07-08T20:56:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イールドカーブの特徴抽出に機械学習を使う（MACHINE LEARNING FOR YIELD CURVE FEATURE EXTRACTION: APPLICATION TO ILLIQUID CORPORATE BONDS）</news:title>
   <news:publication_date>2026-07-08T20:56:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709652</loc>
  <lastmod>2026-07-08T20:46:27Z</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構造的プルーニングと予算意識正則化（Structured Pruning of Neural Networks with Budget-Aware Regularization）</news:title>
   <news:publication_date>2026-07-08T20:46:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709650</loc>
  <lastmod>2026-07-08T20:45:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共鳴電荷交換衝突における量子力学的ポテンシャルと非活性電子の影響 (Quantum Mechanical Potentials and Inactive Electron Effects in Resonant Charge Exchange Collisions)</news:title>
   <news:publication_date>2026-07-08T20:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709648</loc>
  <lastmod>2026-07-08T20:45:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多数は力になる：敵対的学習で強化するアンサンブルの有効性（STRENGTH IN NUMBERS: TRADING-OFF ROBUSTNESS AND COMPUTATION VIA ADVERSARIALLY-TRAINED ENSEMBLES）</news:title>
   <news:publication_date>2026-07-08T20:45:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709646</loc>
  <lastmod>2026-07-08T20:45:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生存解析における特徴選択とDeep Learningの改善（Feature Selection for Survival Analysis with Competing Risks using Deep Learning）</news:title>
   <news:publication_date>2026-07-08T20:45:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709644</loc>
  <lastmod>2026-07-08T20:44:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメトリックノイズ注入によるDNNの頑健化（Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack）</news:title>
   <news:publication_date>2026-07-08T20:44:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709642</loc>
  <lastmod>2026-07-08T20:44:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MR-GANによる生成モデルの幾何学的正則化（MR-GAN: Manifold Regularized Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-08T20:44:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709640</loc>
  <lastmod>2026-07-08T19:53:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一望遠鏡で揃えた超新星サーベイの意義（The Foundation Supernova Survey: Measuring Cosmological Parameters with Supernovae from a Single Telescope）</news:title>
   <news:publication_date>2026-07-08T19:53:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709638</loc>
  <lastmod>2026-07-08T19:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>傾斜Ni(111)表面上の六方窒化ホウ素単層成長の系統的研究（Boron nitride monolayer growth on vicinal Ni(111) surfaces systematically studied with a curved crystal）</news:title>
   <news:publication_date>2026-07-08T19:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709636</loc>
  <lastmod>2026-07-08T19:53:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M31の元素組成に関する知見（Elemental Abundances in M31: Alpha and Iron Element Abundances from Low-Resolution Resolved Stellar Spectroscopy in the Stellar Halo）</news:title>
   <news:publication_date>2026-07-08T19:53:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709634</loc>
  <lastmod>2026-07-08T19:52:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zastavnyi演算子と正定値放射関数の意義（Zastavnyi Operators and Positive Definite Radial Functions）</news:title>
   <news:publication_date>2026-07-08T19:52:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709632</loc>
  <lastmod>2026-07-08T19:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境での部分勾配の符号化計算（DISTRIBUTED GRADIENT DESCENT WITH CODED PARTIAL GRADIENT COMPUTATIONS）</news:title>
   <news:publication_date>2026-07-08T19:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709630</loc>
  <lastmod>2026-07-08T19:51:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次力定数抽出のためのhiphiveパッケージ (The hiphive package for the extraction of high-order force constants by machine learning)</news:title>
   <news:publication_date>2026-07-08T19:51:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709628</loc>
  <lastmod>2026-07-08T19:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元量子エンコーディングと光子減算を用いた符号化手法（High-dimensional quantum encoding via photon-subtracted squeezed states）</news:title>
   <news:publication_date>2026-07-08T19:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709626</loc>
  <lastmod>2026-07-08T19:00:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Legendre級数畳み込みによるオプション価格付けとヘッジ（Hedging and Pricing European-type, Early-Exercise and Discrete Barrier Options using an Algorithm for the Convolution of Legendre Series）</news:title>
   <news:publication_date>2026-07-08T19:00:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709624</loc>
  <lastmod>2026-07-08T19:00:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TimbreTron：CQT＋CycleGAN＋WaveNetによる音色転送パイプライン（TIMBRETRON: A WAVENET(CYCLEGAN(CQT(AUDIO))) PIPELINE FOR MUSICAL TIMBRE TRANSFER）</news:title>
   <news:publication_date>2026-07-08T19:00:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709622</loc>
  <lastmod>2026-07-08T18:59:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GuacaMolによる新しい分子設計の評価フレームワーク（GuacaMol: Benchmarking Models for De Novo Molecular Design）</news:title>
   <news:publication_date>2026-07-08T18:59:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709620</loc>
  <lastmod>2026-07-08T18:58:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FAIM：3次元医用画像レジストレーションの高速・折り畳み抑制手法（FAIM – A ConvNet Method for Unsupervised 3D Medical Image Registration）</news:title>
   <news:publication_date>2026-07-08T18:58:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709618</loc>
  <lastmod>2026-07-08T18:58:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不安全なシステムの監督と動的安全エンベロープ（Oversight of Unsafe Systems via Dynamic Safety Envelopes）</news:title>
   <news:publication_date>2026-07-08T18:58:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709616</loc>
  <lastmod>2026-07-08T18:58:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語義誘導の自動化モデルが変える意味の捉え方（AutoSense Model for Word Sense Induction）</news:title>
   <news:publication_date>2026-07-08T18:58:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709614</loc>
  <lastmod>2026-07-08T18:57:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低メモリで高解像度映像を学習する時系列GANの手法 (Train Sparsely, Generate Densely: Memory-efficient Unsupervised Training of High-resolution Temporal GAN)</news:title>
   <news:publication_date>2026-07-08T18:57:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709612</loc>
  <lastmod>2026-07-08T18:06:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学校のバリュー・アッド指標で生徒背景を調整すべきか（Should we adjust for pupil background in school value-added models?）</news:title>
   <news:publication_date>2026-07-08T18:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709610</loc>
  <lastmod>2026-07-08T18:06:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガンマ線パルサー：ab-initio運動論的シミュレーションから何を学んだか（Gamma-ray pulsars: What have we learned from ab-initio kinetic simulations?）</news:title>
   <news:publication_date>2026-07-08T18:06:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709608</loc>
  <lastmod>2026-07-08T18:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三次元クロマチン構造とその時間的挙動の推定 (Inference of the three-dimensional chromatin structure and its temporal behavior)</news:title>
   <news:publication_date>2026-07-08T18:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709606</loc>
  <lastmod>2026-07-08T18:05:07Z</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とデータ前処理による多クラス不均衡学習の実証的分析（On dynamic ensemble selection and data preprocessing for multi-class imbalance learning）</news:title>
   <news:publication_date>2026-07-08T18:05:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709604</loc>
  <lastmod>2026-07-08T18:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮動画の画質を向上させる多帧注視ネットワーク（MGANet: A Robust Model for Quality Enhancement of Compressed Video）</news:title>
   <news:publication_date>2026-07-08T18:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709602</loc>
  <lastmod>2026-07-08T18:04:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己進度型敵対的訓練によるマルチモーダル少数ショット学習（Self Paced Adversarial Training for Multimodal Few-shot Learning）</news:title>
   <news:publication_date>2026-07-08T18:04:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709600</loc>
  <lastmod>2026-07-08T18:04:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トレーニングデータ無しで学ぶ方法 — 銀河応用のベイズ的アプローチ (Learning in the Absence of Training Data – a Galactic Application)</news:title>
   <news:publication_date>2026-07-08T18:04:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709598</loc>
  <lastmod>2026-07-08T17:12:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理によるセルビア語の比喩（直喩）コーパス構築（Creating a contemporary corpus of similes in Serbian by using natural language processing）</news:title>
   <news:publication_date>2026-07-08T17:12:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709596</loc>
  <lastmod>2026-07-08T17:12:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブスレッショルドスイングの改訂理論限界（Revised Theoretical Limit of Subthreshold Swing in Field-Effect Transistors）</news:title>
   <news:publication_date>2026-07-08T17:12:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709594</loc>
  <lastmod>2026-07-08T17:11:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再電離シミュレーションのパワースペクトルを高速予測する機械学習の実用性（Evaluating machine learning techniques for predicting power spectra from reionization simulations）</news:title>
   <news:publication_date>2026-07-08T17:11:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709592</loc>
  <lastmod>2026-07-08T17:11:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑材料のBRDF推定とネスト学習（BRDF Estimation of Complex Materials with Nested Learning）</news:title>
   <news:publication_date>2026-07-08T17:11:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709590</loc>
  <lastmod>2026-07-08T17:11:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>座位における褥瘡予防のためのリアルタイム個別化モデリング（Personalized modeling for real-time pressure ulcer prevention in sitting posture）</news:title>
   <news:publication_date>2026-07-08T17:11:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709588</loc>
  <lastmod>2026-07-08T17:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で長時間の分子光動力学が可能に（Machine learning enables long time scale molecular photodynamics）</news:title>
   <news:publication_date>2026-07-08T17:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709586</loc>
  <lastmod>2026-07-08T17:09:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドライバー行動認識のための多入力インターウーブンCNN（Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets with Multi-stream Inputs）</news:title>
   <news:publication_date>2026-07-08T17:09:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709584</loc>
  <lastmod>2026-07-08T16:18:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ELMの条件数最適化：マルチタスクビートル触角群最適化法（Conditioning Optimization of Extreme Learning Machine by Multitask Beetle Antennae Swarm Algorithm）</news:title>
   <news:publication_date>2026-07-08T16:18:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709582</loc>
  <lastmod>2026-07-08T16:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己対戦で学ぶ目標埋め込みと階層型強化学習（Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-08T16:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709580</loc>
  <lastmod>2026-07-08T16:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Multi-Task GANで臨床画像の不均衡を扱う（Multi-Task Generative Adversarial Network for Handling Imbalanced Clinical Data）</news:title>
   <news:publication_date>2026-07-08T16:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709578</loc>
  <lastmod>2026-07-08T16:17:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DCE-MRIでの腫瘍追跡を自動化するCNN種点生成と制約付き体積増殖（Response monitoring of breast cancer on DCE-MRI using convolutional neural network-generated seed points and constrained volume growing）</news:title>
   <news:publication_date>2026-07-08T16:17:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709576</loc>
  <lastmod>2026-07-08T16:17:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム射影によるニューラルネットワークの表現力強化と高速学習（Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections）</news:title>
   <news:publication_date>2026-07-08T16:17:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709574</loc>
  <lastmod>2026-07-08T16:17:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PSICA：カテゴリカル処置に対する確率的サブグループ同定（PSICA: decision trees for probabilistic subgroup identification with categorical treatments）</news:title>
   <news:publication_date>2026-07-08T16:17:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709572</loc>
  <lastmod>2026-07-08T16:17:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集団動物移動活動のオンライン認識（Online Collective Animal Movement Activity Recognition）</news:title>
   <news:publication_date>2026-07-08T16:17:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709570</loc>
  <lastmod>2026-07-08T15:25:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化空間における空間的振る舞いで敵対的摂動を検出する（Detecting Adversarial Perturbations Through Spatial Behavior in Activation Spaces）</news:title>
   <news:publication_date>2026-07-08T15:25:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709568</loc>
  <lastmod>2026-07-08T15:25:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スーパーディフュージョンによる顕著領域検出（Super Diffusion for Salient Object Detection）</news:title>
   <news:publication_date>2026-07-08T15:25:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709566</loc>
  <lastmod>2026-07-08T15:24:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KekuleScopeによる化合物画像からの活性予測（KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images）</news:title>
   <news:publication_date>2026-07-08T15:24:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709564</loc>
  <lastmod>2026-07-08T15:24:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間的確率制約を持つバンディット問題 (Bandits with Temporal Stochastic Constraints)</news:title>
   <news:publication_date>2026-07-08T15:24:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709562</loc>
  <lastmod>2026-07-08T15:24:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OCT画像のノイズ除去を変える多入力全畳み込みネットワーク（Three-dimensional Optical Coherence Tomography Image Denoising through Multi-input Fully-Convolutional Networks）</news:title>
   <news:publication_date>2026-07-08T15:24:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709560</loc>
  <lastmod>2026-07-08T15:23:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像データ拡張の新手法：ランダム画像クロップとパッチング（Random Image Cropping and Patching）</news:title>
   <news:publication_date>2026-07-08T15:23:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709558</loc>
  <lastmod>2026-07-08T15:23:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化されたバイナリニューラルネットワークがもたらす変化（Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation）</news:title>
   <news:publication_date>2026-07-08T15:23:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709556</loc>
  <lastmod>2026-07-08T14:32:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚的距離に基づくタスク汎用的な敵対的攻撃（Task-generalizable Adversarial Attack based on Perceptual Metric）</news:title>
   <news:publication_date>2026-07-08T14:32:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709554</loc>
  <lastmod>2026-07-08T14:32:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイト単位の多言語音声認識と合成が切り拓く実務応用（BYTES ARE ALL YOU NEED: END-TO-END MULTILINGUAL SPEECH RECOGNITION AND SYNTHESIS WITH BYTES）</news:title>
   <news:publication_date>2026-07-08T14:32:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709552</loc>
  <lastmod>2026-07-08T14:32:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造生成とディテール強調による顔の高解像化と復元（Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement）</news:title>
   <news:publication_date>2026-07-08T14:32:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709550</loc>
  <lastmod>2026-07-08T14:30:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースなショートカットトポロジーがもたらす表現力の飛躍（On a Sparse Shortcut Topology of Artificial Neural Networks）</news:title>
   <news:publication_date>2026-07-08T14:30:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709548</loc>
  <lastmod>2026-07-08T14:30:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lipschitz連続性を用いた頑健なニューラルネットワークの訓練法（Towards Robust Neural Networks with Lipschitz Continuity）</news:title>
   <news:publication_date>2026-07-08T14:30:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709546</loc>
  <lastmod>2026-07-08T14:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相再構成に基づく話者分離の新視点（DEEP LEARNING BASED PHASE RECONSTRUCTION FOR SPEAKER SEPARATION: A TRIGONOMETRIC PERSPECTIVE）</news:title>
   <news:publication_date>2026-07-08T14:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709544</loc>
  <lastmod>2026-07-08T14:30:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフポリシー方策勾配定理とエンファティック重み付け（An Off-policy Policy Gradient Theorem Using Emphatic Weightings）</news:title>
   <news:publication_date>2026-07-08T14:30:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709542</loc>
  <lastmod>2026-07-08T13:38:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全観測下でのロバストな近視制御（ROBUST MYOPIC CONTROL FOR SYSTEMS WITH IMPERFECT OBSERVATIONS）</news:title>
   <news:publication_date>2026-07-08T13:38:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709540</loc>
  <lastmod>2026-07-08T13:38:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HyperAdam：タスク適応型学習可能Adam（HyperAdam: A Learnable Task-Adaptive Adam for Network Training）</news:title>
   <news:publication_date>2026-07-08T13:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709538</loc>
  <lastmod>2026-07-08T13:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一次元系におけるソリトンとBCS–BECクロスオーバー（Solitons in One Dimensional Systems at BCS-BEC Crossover）</news:title>
   <news:publication_date>2026-07-08T13:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709536</loc>
  <lastmod>2026-07-08T13:37:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グレイボックス・ファジングを効率化するプログラム挙動のモデリング（Improving Grey-Box Fuzzing by Modeling Program Behavior）</news:title>
   <news:publication_date>2026-07-08T13:37:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709534</loc>
  <lastmod>2026-07-08T13:36:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多モーダルデータから情報的特徴を効率的に抽出する手法（An Efficient Approach to Informative Feature Extraction from Multimodal Data）</news:title>
   <news:publication_date>2026-07-08T13:36:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709532</loc>
  <lastmod>2026-07-08T13:36:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポラリティ損失によるゼロショット物体検出の改良（Polarity Loss for Zero-shot Object Detection）</news:title>
   <news:publication_date>2026-07-08T13:36:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709530</loc>
  <lastmod>2026-07-08T13:36:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ連鎖に基づくブロック座標降下法（Markov Chain Block Coordinate Descent）</news:title>
   <news:publication_date>2026-07-08T13:36:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709527</loc>
  <lastmod>2026-07-08T12:44:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布の重なりを作ることで定義できる差異指標 ― Spread Divergence（Spread Divergence）</news:title>
   <news:publication_date>2026-07-08T12:44:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709525</loc>
  <lastmod>2026-07-08T12:44:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低解像度顔認識の挑戦と解決（Low-Resolution Face Recognition）</news:title>
   <news:publication_date>2026-07-08T12:44:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709523</loc>
  <lastmod>2026-07-08T12:44:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原油スポット価格の多変量予測におけるニューラルネットワークの実証（Multivariate Forecasting of Crude Oil Spot Prices using Neural Networks）</news:title>
   <news:publication_date>2026-07-08T12:44:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709521</loc>
  <lastmod>2026-07-08T12:43:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線における肺炎検出の自動化（Pneumonia Detection in Chest Radiographs）</news:title>
   <news:publication_date>2026-07-08T12:43:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709519</loc>
  <lastmod>2026-07-08T12:43:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在交絡因子モデルにおける個別処置効果推定の敵対学習（Estimation of Individual Treatment Effect in Latent Confounder Models via Adversarial Learning）</news:title>
   <news:publication_date>2026-07-08T12:43:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709517</loc>
  <lastmod>2026-07-08T12:43:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力と電磁気の幾何学的統一（Geometrical Unification of Gravitation and Electromagnetism）</news:title>
   <news:publication_date>2026-07-08T12:43:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709515</loc>
  <lastmod>2026-07-08T12:42:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク・モーション計画と強化学習を統合したロバスト意思決定（Integrating Task-Motion Planning with Reinforcement Learning for Robust Decision Making in Mobile Robots）</news:title>
   <news:publication_date>2026-07-08T12:42:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709513</loc>
  <lastmod>2026-07-08T11:51:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己敵対学習によるベイズサンプリング（Self-Adversarially Learned Bayesian Sampling）</news:title>
   <news:publication_date>2026-07-08T11:51:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709511</loc>
  <lastmod>2026-07-08T11:51:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的でロバストなフィルタ生成のための教師なし学習フレームワーク（Generating adaptive and robust filter sets using an unsupervised learning framework）</news:title>
   <news:publication_date>2026-07-08T11:51:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709509</loc>
  <lastmod>2026-07-08T11:51:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Learningと密度汎関数理論の融合（Deep Learning and Density Functional Theory）</news:title>
   <news:publication_date>2026-07-08T11:51:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709507</loc>
  <lastmod>2026-07-08T11:50:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語に基づく動画の時間局所化のための活動概念抽出（MAC: Mining Activity Concepts for Language-based Temporal Localization）</news:title>
   <news:publication_date>2026-07-08T11:50:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709505</loc>
  <lastmod>2026-07-08T11:50:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>開かれたドメイン動画におけるマルチビュー相関からの学習（LEARNING FROM MULTIVIEW CORRELATIONS IN OPEN-DOMAIN VIDEOS）</news:title>
   <news:publication_date>2026-07-08T11:50:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709503</loc>
  <lastmod>2026-07-08T11:50:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力定数が変わる世界の力学（Gravitational Potential and Nonrelativistic Lagrangian in Modified Gravity with Varying G）</news:title>
   <news:publication_date>2026-07-08T11:50:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709501</loc>
  <lastmod>2026-07-08T11:49:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図信号分類のためのロバストな能動学習（Robust Active Learning for Electrocardiographic Signal Classification）</news:title>
   <news:publication_date>2026-07-08T11:49:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709499</loc>
  <lastmod>2026-07-08T10:59:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NuSTARによるX線パルサーIGR J19294+1816の研究（Study of the X-ray pulsar IGR J19294+1816 with NuSTAR: detection of cyclotron line and transition to accretion from the cold disc）</news:title>
   <news:publication_date>2026-07-08T10:59:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709497</loc>
  <lastmod>2026-07-08T10:58:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックホール内部とモジュラー包含（Comments on black hole interiors and modular inclusions）</news:title>
   <news:publication_date>2026-07-08T10:58:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709495</loc>
  <lastmod>2026-07-08T10:58:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過剰パラメータ化したDeep ReLUネットワークをSGDが最適化する（Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks）</news:title>
   <news:publication_date>2026-07-08T10:58:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709493</loc>
  <lastmod>2026-07-08T10:57:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理的外挿を可能にするガウス過程の一般化（Physical extrapolation of quantum observables by generalization with Gaussian Processes）</news:title>
   <news:publication_date>2026-07-08T10:57:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709491</loc>
  <lastmod>2026-07-08T10:57:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェア意識混合精度自動量子化（Hardware-Aware Automated Quantization with Mixed Precision）</news:title>
   <news:publication_date>2026-07-08T10:57:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709489</loc>
  <lastmod>2026-07-08T10:57:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な非近視的アクティブサーチ（Efficient Nonmyopic Active Search）</news:title>
   <news:publication_date>2026-07-08T10:57:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709487</loc>
  <lastmod>2026-07-08T10:57:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン逆強化学習の非線形系への拡張（Online inverse reinforcement learning for nonlinear systems）</news:title>
   <news:publication_date>2026-07-08T10:57:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709485</loc>
  <lastmod>2026-07-08T10:05:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOOCフォーラムにおけるリソース言及抽出（Resource Mention Extraction for MOOC Discussion Forums）</news:title>
   <news:publication_date>2026-07-08T10:05:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709483</loc>
  <lastmod>2026-07-08T10:05:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可視化可能なシーングラフ生成モデルが変える視覚理解（An Interpretable Model for Scene Graph Generation）</news:title>
   <news:publication_date>2026-07-08T10:05:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709481</loc>
  <lastmod>2026-07-08T10:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習を取り入れた自己学習による胸部X線肺結節セグメンテーション（Integrating Reinforcement Learning to Self Training for Pulmonary Nodule Segmentation in Chest X-rays）</news:title>
   <news:publication_date>2026-07-08T10:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709479</loc>
  <lastmod>2026-07-08T10:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な階層分類を用いる音の手動アノテーション支援（Facilitating the Manual Annotation of Sounds When Using Large Taxonomies）</news:title>
   <news:publication_date>2026-07-08T10:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709477</loc>
  <lastmod>2026-07-08T10:04:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標を早期に視覚に組み込むロボット視覚（EARLY FUSION for Goal Directed Robotic Vision）</news:title>
   <news:publication_date>2026-07-08T10:04:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709475</loc>
  <lastmod>2026-07-08T10:03:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速化MRIのための大規模データセットとベンチマーク（fastMRI: An Open Dataset and Benchmarks for Accelerated MRI）</news:title>
   <news:publication_date>2026-07-08T10:03:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709473</loc>
  <lastmod>2026-07-08T10:03:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチメソッドで画像品質評価を高める発想（Boosting in Image Quality Assessment）</news:title>
   <news:publication_date>2026-07-08T10:03:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709471</loc>
  <lastmod>2026-07-08T09:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴空間における運動学習：局所一貫性を持つ変形畳み込みネットワークによる微細動作検出（Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection）</news:title>
   <news:publication_date>2026-07-08T09:12:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709469</loc>
  <lastmod>2026-07-08T09:11:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低資源言語間の単語トランスダクション機構（NMT word transduction mechanisms for LRL）</news:title>
   <news:publication_date>2026-07-08T09:11:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709467</loc>
  <lastmod>2026-07-08T09:10:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データ分類のための敵対的再重み付け（Adversarial Classifier for Imbalanced Problems）</news:title>
   <news:publication_date>2026-07-08T09:10:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709465</loc>
  <lastmod>2026-07-08T09:10:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マージナル加重最尤法による効率的学習（Marginal Weighted Maximum Log-likelihood for Efficient Learning of Perturb-and-Map models）</news:title>
   <news:publication_date>2026-07-08T09:10:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709463</loc>
  <lastmod>2026-07-08T09:10:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>尤度非計算型推論の逐次ニューラル手法（Sequential Neural Methods for Likelihood-free Inference）</news:title>
   <news:publication_date>2026-07-08T09:10:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709461</loc>
  <lastmod>2026-07-08T09:10:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層グラフに対する半教師あり分類のGCN拡張（MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-07-08T09:10:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709459</loc>
  <lastmod>2026-07-08T09:09:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関と因果を見分ける：ゲノムワイド関連解析からの示唆（Distinguishing correlation from causation using genome-wide association studies）</news:title>
   <news:publication_date>2026-07-08T09:09:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709457</loc>
  <lastmod>2026-07-08T08:18:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン生成アルゴリズムのインライン検知（Inline Detection of Domain Generation Algorithms with Context-Sensitive Word Embeddings）</news:title>
   <news:publication_date>2026-07-08T08:18:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709455</loc>
  <lastmod>2026-07-08T08:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復的グローバル探索とカオス理論に基づくPSO特徴選択の改良（Improving PSO Global Method for Feature Selection According to Iterations Global Search and Chaotic Theory）</news:title>
   <news:publication_date>2026-07-08T08:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709453</loc>
  <lastmod>2026-07-08T08:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造ベースのネットワークによる薬物検証（Structure-Based Networks for Drug Validation）</news:title>
   <news:publication_date>2026-07-08T08:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709451</loc>
  <lastmod>2026-07-08T08:16:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー保護された協調予測とランダムフォレスト（Privacy-Preserving Collaborative Prediction using Random Forests）</news:title>
   <news:publication_date>2026-07-08T08:16:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709449</loc>
  <lastmod>2026-07-08T08:16:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動塩層分割：深層学習アプローチ（Automatic salt deposits segmentation: A deep learning approach）</news:title>
   <news:publication_date>2026-07-08T08:16:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709447</loc>
  <lastmod>2026-07-08T08:16:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代理モデル支援パラレルテンパリングによるベイズニューラル学習（Surrogate-assisted parallel tempering for Bayesian neural learning）</news:title>
   <news:publication_date>2026-07-08T08:16:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709445</loc>
  <lastmod>2026-07-08T08:16:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態空間に基づく疎な動的ネットワーク再構築（A state-space approach to sparse dynamic network reconstruction）</news:title>
   <news:publication_date>2026-07-08T08:16:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709443</loc>
  <lastmod>2026-07-08T07:24:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボリュームCT画像からの気道抽出のグラフ洗練法（Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks）</news:title>
   <news:publication_date>2026-07-08T07:24:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709441</loc>
  <lastmod>2026-07-08T07:23:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ誘導グラフィカルラッソによる分子パスウェイ間相互作用の発見（Group induced graphical lasso allows for discovery of molecular pathways-pathways interactions）</news:title>
   <news:publication_date>2026-07-08T07:23:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709439</loc>
  <lastmod>2026-07-08T07:22:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子強化学習の進展（Advances in Quantum Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-08T07:22:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709437</loc>
  <lastmod>2026-07-08T07:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字レベルCNNによる悪意あるWebリクエスト検知（Malicious Web Request Detection Using Character-level CNN）</news:title>
   <news:publication_date>2026-07-08T07:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709435</loc>
  <lastmod>2026-07-08T07:22:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声認識における四元数ニューラルネットワーク（Speech Recognition with Quaternion Neural Networks）</news:title>
   <news:publication_date>2026-07-08T07:22:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709433</loc>
  <lastmod>2026-07-08T07:22:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何相位顕微鏡による定量位相イメージング（GEOMETRIC-PHASE MICROSCOPY FOR QUANTITATIVE PHASE IMAGING）</news:title>
   <news:publication_date>2026-07-08T07:22:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709431</loc>
  <lastmod>2026-07-08T07:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PersEmoN：外見的パーソナリティと感情を同時解析する深層ネットワーク（PersEmoN: A Deep Network for Joint Analysis of Apparent Personality, Emotion and Their Relationship）</news:title>
   <news:publication_date>2026-07-08T07:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709429</loc>
  <lastmod>2026-07-08T06:30:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補償付き統合勾配によるEEG分類の信頼できる解釈（Compensated Integrated Gradients to Reliably Interpret EEG Classification）</news:title>
   <news:publication_date>2026-07-08T06:30:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709427</loc>
  <lastmod>2026-07-08T06:29:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像の雨粒除去を木構造で達成する（A Deep Tree-Structured Fusion Model for Single Image Deraining）</news:title>
   <news:publication_date>2026-07-08T06:29:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709425</loc>
  <lastmod>2026-07-08T06:29:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>第一原理に基づく水の熱力学――液体と氷の安定性を機械学習で定量化する（Ab initio thermodynamics of liquid and solid water）</news:title>
   <news:publication_date>2026-07-08T06:29:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709423</loc>
  <lastmod>2026-07-08T06:28:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重障害ポテンシャルを伴う腫瘍成長モデルの最適性条件（Optimality conditions for an extended tumor growth model with double obstacle potential via deep quench approach）</news:title>
   <news:publication_date>2026-07-08T06:28:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709421</loc>
  <lastmod>2026-07-08T06:28:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク深層形態素解析器（Multi Task Deep Morphological Analyzer: Context Aware Neural Joint Morphological Tagging and Lemma Prediction）</news:title>
   <news:publication_date>2026-07-08T06:28:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709419</loc>
  <lastmod>2026-07-08T06:28:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化ネットワークを備えたニューラルネットワーク（Neural Networks with Activation Networks）</news:title>
   <news:publication_date>2026-07-08T06:28:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709417</loc>
  <lastmod>2026-07-08T06:27:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>角度ベースの距離学習で3D形状検索を改善する手法（Angular Triplet-Center Loss for Multi-view 3D Shape Retrieval）</news:title>
   <news:publication_date>2026-07-08T06:27:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709415</loc>
  <lastmod>2026-07-08T05:36:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医用画像とレポートの教師なしマルチモーダル表現学習 (Unsupervised Multimodal Representation Learning across Medical Images and Reports)</news:title>
   <news:publication_date>2026-07-08T05:36:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709413</loc>
  <lastmod>2026-07-08T05:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト検出と認識を統合する新しい枠組み（A Novel Integrated Framework for Learning both Text Detection and Recognition）</news:title>
   <news:publication_date>2026-07-08T05:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709411</loc>
  <lastmod>2026-07-08T05:35:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理を取り込んだ深層生成モデルによるマイクロ構造合成（Physics-aware Deep Generative Models for Creating Synthetic Microstructures）</news:title>
   <news:publication_date>2026-07-08T05:35:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709409</loc>
  <lastmod>2026-07-08T05:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による高精度ポリマーのクラウドポイント逆設計（Machine learning enables polymer cloud-point engineering via inverse design）</news:title>
   <news:publication_date>2026-07-08T05:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709407</loc>
  <lastmod>2026-07-08T05:35:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Joint Mapping and Calibration via Differentiable Sensor Fusion（Joint Mapping and Calibration via Differentiable Sensor Fusion）</news:title>
   <news:publication_date>2026-07-08T05:35:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709405</loc>
  <lastmod>2026-07-08T05:35:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>場面文字検出の文脈強化手法がもたらす実務的インパクト（Scene Text Detection with Supervised Pyramid Context Network）</news:title>
   <news:publication_date>2026-07-08T05:35:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709403</loc>
  <lastmod>2026-07-08T05:35:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間帯フィルターを用いたz∼5の微光クエーサー発見（Discovery of Faint Quasars at z ∼5 with a Medium-band-based Approach）</news:title>
   <news:publication_date>2026-07-08T05:35:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709401</loc>
  <lastmod>2026-07-08T04:44:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルから誰でも試着可能にする技術（M2E-Try On Net: Fashion from Model to Everyone）</news:title>
   <news:publication_date>2026-07-08T04:44:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709399</loc>
  <lastmod>2026-07-08T04:43:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈化された非ローカルニューラルネットワークによる系列学習の革新（Contextualized Non-local Neural Networks for Sequence Learning）</news:title>
   <news:publication_date>2026-07-08T04:43:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709397</loc>
  <lastmod>2026-07-08T04:43:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FFTによる勾配スパース化で分散学習を効率化する手法（FFT-based Gradient Sparsification for the Distributed Training of Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-08T04:43:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709395</loc>
  <lastmod>2026-07-08T04:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graph-Adaptive PruningによるCNN推論高速化（Graph-Adaptive Pruning for Efficient Inference of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-08T04:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709393</loc>
  <lastmod>2026-07-08T04:43:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市部走行における多目的深層強化学習（Urban Driving with Multi-Objective Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-08T04:43:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709391</loc>
  <lastmod>2026-07-08T04:42:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的特徴整合による非教師ありドメイン適応（Progressive Feature Alignment for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-07-08T04:42:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709389</loc>
  <lastmod>2026-07-08T04:42:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話し言葉と3D顔表情から抑うつ症状の重症度を測る（Measuring Depression Symptom Severity from Spoken Language and 3D Facial Expressions）</news:title>
   <news:publication_date>2026-07-08T04:42:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709387</loc>
  <lastmod>2026-07-08T03:51:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンセット認識の最近の進展（Recent Advances in Open Set Recognition: A Survey）</news:title>
   <news:publication_date>2026-07-08T03:51:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709385</loc>
  <lastmod>2026-07-08T03:51:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人口属性を考慮した階層ベイズ型ドメイン適応（Population-aware Hierarchical Bayesian Domain Adaptation）</news:title>
   <news:publication_date>2026-07-08T03:51:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709383</loc>
  <lastmod>2026-07-08T03:50:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運動学習は「動かずに」起きるか：受動的訓練での手位置推定の再考（Motor Learning Without Moving: Hand Localization after Passive Training）</news:title>
   <news:publication_date>2026-07-08T03:50:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709381</loc>
  <lastmod>2026-07-08T03:50:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非教師単一画像の雨除去を自己監督制約で解く（Unsupervised Single Image Deraining with Self-supervised Constraints）</news:title>
   <news:publication_date>2026-07-08T03:50:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709379</loc>
  <lastmod>2026-07-08T03:50:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物再識別のための深層特徴の適応的再ランキング（Adaptive Re-ranking of Deep Features for Person Re-identification）</news:title>
   <news:publication_date>2026-07-08T03:50:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709377</loc>
  <lastmod>2026-07-08T03:49:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測下における高水準戦略選択（High-Level Strategy Selection under Partial Observability in StarCraft: Brood War）</news:title>
   <news:publication_date>2026-07-08T03:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709375</loc>
  <lastmod>2026-07-08T03:49:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Softmax出力は敵対的例の強度評価を誤らせる（How the Softmax Output is Misleading for Evaluating the Strength of Adversarial Examples）</news:title>
   <news:publication_date>2026-07-08T03:49:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709373</loc>
  <lastmod>2026-07-08T02:58:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>翻訳の「抜け」を減らす学習法（Neural Machine Translation with Adequacy-Oriented Learning）</news:title>
   <news:publication_date>2026-07-08T02:58:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709371</loc>
  <lastmod>2026-07-08T02:58:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットで高速に予測する電子衝突イオン化質量分析（Rapid Prediction of Electron-Ionization Mass Spectrometry using Neural Networks）</news:title>
   <news:publication_date>2026-07-08T02:58:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709369</loc>
  <lastmod>2026-07-08T02:58:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース強化学習が示すサンプル効率の飛躍（Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches）</news:title>
   <news:publication_date>2026-07-08T02:58:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709367</loc>
  <lastmod>2026-07-08T02:57:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>食道組織のがん・前がん病変検出に対する注意機構型深層ニューラルネットワーク（Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides）</news:title>
   <news:publication_date>2026-07-08T02:57:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709365</loc>
  <lastmod>2026-07-08T02:56:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗所での視覚を改善する再帰型畳み込みニューラルネットワーク（Seeing in the dark with recurrent convolutional neural networks）</news:title>
   <news:publication_date>2026-07-08T02:56:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709363</loc>
  <lastmod>2026-07-08T02:56:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中でのCNNベース密な3Dシーン再構築（CNN based dense underwater 3D scene reconstruction by transfer learning using bubble database）</news:title>
   <news:publication_date>2026-07-08T02:56:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709361</loc>
  <lastmod>2026-07-08T02:56:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層音声強調のための微分可能な整合性制約（Differentiable Consistency Constraints for Improved Deep Speech Enhancement）</news:title>
   <news:publication_date>2026-07-08T02:56:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709359</loc>
  <lastmod>2026-07-08T02:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小規模X線回折データの高速で解釈可能な分類（Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks）</news:title>
   <news:publication_date>2026-07-08T02:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709357</loc>
  <lastmod>2026-07-08T01:55:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多視点データの結合的関連と分類解析（Joint association and classification analysis of multi-view data）</news:title>
   <news:publication_date>2026-07-08T01:55:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709355</loc>
  <lastmod>2026-07-08T01:55:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バランスの取れたデータセットでは不十分（Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations）</news:title>
   <news:publication_date>2026-07-08T01:55:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709353</loc>
  <lastmod>2026-07-08T01:54:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライマル・デュアルQ学習フレームワークによるLQR設計（Primal-Dual Q-Learning Framework for LQR Design）</news:title>
   <news:publication_date>2026-07-08T01:54:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709351</loc>
  <lastmod>2026-07-08T01:54:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定的な相手の影響を利用する学習（Stable Opponent Shaping in Differentiable Games）</news:title>
   <news:publication_date>2026-07-08T01:54:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709349</loc>
  <lastmod>2026-07-08T01:53:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MimicGANによる盲点補正と敵対的防御の実務的意義（MimicGAN: Corruption-Mimicking for Blind Image Recovery &amp;amp; Adversarial Defense）</news:title>
   <news:publication_date>2026-07-08T01:53:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709347</loc>
  <lastmod>2026-07-08T01:53:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イタリア上院における政治的DNAの学習（Learning Political DNA in the Italian Senate）</news:title>
   <news:publication_date>2026-07-08T01:53:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709338</loc>
  <lastmod>2026-07-08T01:02:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動フローワークフレームによる機械学習を用いた材料探索（MACHINE LEARNING, PHASE STABILITY, AND DISORDER WITH THE AUTOMATIC FLOW FRAMEWORK FOR MATERIALS DISCOVERY）</news:title>
   <news:publication_date>2026-07-08T01:02:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709336</loc>
  <lastmod>2026-07-08T01:01:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間層に着目した敵対的攻撃の転移性向上（Intermediate Level Adversarial Attack for Enhanced Transferability）</news:title>
   <news:publication_date>2026-07-08T01:01:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709334</loc>
  <lastmod>2026-07-08T01:01:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>色の恒常性を学習するCNNと角度損失（Artificial Color Constancy via GoogLeNet with Angular Loss Function）</news:title>
   <news:publication_date>2026-07-08T01:01:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709332</loc>
  <lastmod>2026-07-08T01:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ波長観測を用いた電波トランジェント分類（Multiwavelength Classification of Radio Transients）</news:title>
   <news:publication_date>2026-07-08T01:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709330</loc>
  <lastmod>2026-07-08T01:00:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチラベル画像分類における強力なベースライン（A BASELINE FOR MULTI-LABEL IMAGE CLASSIFICATION USING AN ENSEMBLE OF DEEP CONVOLUTIONAL NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-07-08T01:00:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709328</loc>
  <lastmod>2026-07-08T01:00:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプリングは最適化よりも速いことがある（Sampling Can Be Faster Than Optimization）</news:title>
   <news:publication_date>2026-07-08T01:00:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709326</loc>
  <lastmod>2026-07-08T01:00:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込みと出力層の圧縮を実現するWEST（Word Encoded Sequence Transducers）</news:title>
   <news:publication_date>2026-07-08T01:00:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709324</loc>
  <lastmod>2026-07-08T00:08:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gen-Oja：ストリーミングCCAの二段階技法（Gen-Oja: A Two-time-scale approach for Streaming CCA）</news:title>
   <news:publication_date>2026-07-08T00:08:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709322</loc>
  <lastmod>2026-07-08T00:08:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>植物苗の画像を深層学習で識別する意義（Deep Convolutional Neural Network for Plant Seedlings Classification）</news:title>
   <news:publication_date>2026-07-08T00:08:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709320</loc>
  <lastmod>2026-07-08T00:08:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一ラベル多クラス画像分類における深層ロジスティック回帰（Single-Label Multi-Class Image Classification by Deep Logistic Regression）</news:title>
   <news:publication_date>2026-07-08T00:08:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709318</loc>
  <lastmod>2026-07-08T00:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>刺激アーティファクトを拡張的に取り除く拡散幾何学アプローチ（Diffusion geometry approach to efficiently remove electrical stimulation artifacts in intracranial electroencephalography）</news:title>
   <news:publication_date>2026-07-08T00:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709316</loc>
  <lastmod>2026-07-08T00:07:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカル差分プライバシー下でのガウス分布平均推定（Locally Private Gaussian Estimation）</news:title>
   <news:publication_date>2026-07-08T00:07:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709314</loc>
  <lastmod>2026-07-08T00:06:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的プルーニングによる効率的なConvNet（Structured Pruning for Efficient ConvNets via Incremental Regularization）</news:title>
   <news:publication_date>2026-07-08T00:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709312</loc>
  <lastmod>2026-07-08T00:06:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボリック音楽生成における深層ニューラルネットワークの明示的構造符号化の効果 (The Effect of Explicit Structure Encoding of Deep Neural Networks for Symbolic Music Generation)</news:title>
   <news:publication_date>2026-07-08T00:06:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709310</loc>
  <lastmod>2026-07-07T23:15:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列グラフのオフセット再構成による時間的に頑健な表現学習（Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation Learning）</news:title>
   <news:publication_date>2026-07-07T23:15:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709308</loc>
  <lastmod>2026-07-07T23:14:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオ行動認識における汎化可能な表現のマルチタスク学習（MULTI-TASK LEARNING OF GENERALIZABLE REPRESENTATIONS FOR VIDEO ACTION RECOGNITION）</news:title>
   <news:publication_date>2026-07-07T23:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709306</loc>
  <lastmod>2026-07-07T23:14:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層系列学習モデルのグレイボックス可視化とデバッグ手法（A Gray Box Interpretable Visual Debugging Approach for Deep Sequence Learning Model）</news:title>
   <news:publication_date>2026-07-07T23:14:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709304</loc>
  <lastmod>2026-07-07T23:14:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層カーネルによる指数族密度の学習（Learning Deep Kernels for Exponential Family Densities）</news:title>
   <news:publication_date>2026-07-07T23:14:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709302</loc>
  <lastmod>2026-07-07T23:13:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pepperのための近リアルタイム物体認識（Near Real-Time Object Recognition for Pepper based on Deep Neural Networks Running on a Backpack）</news:title>
   <news:publication_date>2026-07-07T23:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709300</loc>
  <lastmod>2026-07-07T23:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練済みニューラルネットワークのための強い混合整数計画法の定式化（Strong mixed-integer programming formulations for trained neural networks）</news:title>
   <news:publication_date>2026-07-07T23:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709298</loc>
  <lastmod>2026-07-07T23:13:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様化したマイクロドップラーで学ぶDNN転移学習（DNN Transfer Learning from Diversified Micro-Doppler for Motion Classification）</news:title>
   <news:publication_date>2026-07-07T23:13:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709296</loc>
  <lastmod>2026-07-07T22:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テクスチャに基づく顔認識の新しい一手法：LGLG-WPCA（LGLG-WPCA: An Effective Texture-based Method for Face Recognition）</news:title>
   <news:publication_date>2026-07-07T22:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709294</loc>
  <lastmod>2026-07-07T22:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字図式による因果推論の図式手術（Causal Inference by String Diagram Surgery）</news:title>
   <news:publication_date>2026-07-07T22:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709292</loc>
  <lastmod>2026-07-07T22:22:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックス自己回帰密度推定による状態空間モデルの近似ベイズ推定（Black-Box Autoregressive Density Estimation for State-Space Models）</news:title>
   <news:publication_date>2026-07-07T22:22:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709290</loc>
  <lastmod>2026-07-07T22:21:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定性に基づくフィルタ剪定による深層CNN高速化（Stability Based Filter Pruning for Accelerating Deep CNNs）</news:title>
   <news:publication_date>2026-07-07T22:21:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709288</loc>
  <lastmod>2026-07-07T22:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存テストを自動で“強化”する技術の実務的意義（Automatic Test Improvement with DSpot）</news:title>
   <news:publication_date>2026-07-07T22:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709286</loc>
  <lastmod>2026-07-07T22:20:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒト-物体相互作用検出のための転移可能な相互作用性知識（Transferable Interactiveness Knowledge for Human-Object Interaction Detection）</news:title>
   <news:publication_date>2026-07-07T22:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709284</loc>
  <lastmod>2026-07-07T22:20:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不規則サンプリング時系列のデータ拡張手法 T-CGAN（T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling）</news:title>
   <news:publication_date>2026-07-07T22:20:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709282</loc>
  <lastmod>2026-07-07T21:29:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FALCON: 高速かつプライバシー保護されたCNN推論の実装（FALCON: A Fourier Transform Based Approach for Fast and Secure Convolutional Neural Network Predictions）</news:title>
   <news:publication_date>2026-07-07T21:29:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709280</loc>
  <lastmod>2026-07-07T21:29:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fristonの能動推論の幾何学（Geometry of Friston’s active inference）</news:title>
   <news:publication_date>2026-07-07T21:29:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709278</loc>
  <lastmod>2026-07-07T21:29:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Unfolded Robust PCAによる超音波クラッタ除去の実務的意義（Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound）</news:title>
   <news:publication_date>2026-07-07T21:29:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709276</loc>
  <lastmod>2026-07-07T21:28:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化分類器の第一歩（Self Organizing Classifiers: First Steps in Structured Evolutionary Machine Learning）</news:title>
   <news:publication_date>2026-07-07T21:28:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709274</loc>
  <lastmod>2026-07-07T21:28:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化分類器とニッチ化された適応（Self Organizing Classifiers and Niched Fitness）</news:title>
   <news:publication_date>2026-07-07T21:28:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709272</loc>
  <lastmod>2026-07-07T21:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり空間・スペクトル正則化マニフォールド局所スケーリングカットによるハイパースペクトル画像の次元削減（A Semi-supervised Spatial Spectral Regularized Manifold Local Scaling Cut With HGF for Dimensionality Reduction of Hyperspectral Images）</news:title>
   <news:publication_date>2026-07-07T21:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709270</loc>
  <lastmod>2026-07-07T21:27:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分析的ネットワーク学習（Analytic Network Learning）</news:title>
   <news:publication_date>2026-07-07T21:27:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709268</loc>
  <lastmod>2026-07-07T20:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正射影特徴変換による単眼3D物体検出（Orthographic Feature Transform for Monocular 3D Object Detection）</news:title>
   <news:publication_date>2026-07-07T20:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709266</loc>
  <lastmod>2026-07-07T20:28:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Contingency Training：不要変数に強い学習を作る訓練法（Contingency Training）</news:title>
   <news:publication_date>2026-07-07T20:28:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709264</loc>
  <lastmod>2026-07-07T20:27:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳に学ぶスティグメルギー学習（Brain-Inspired Stigmergy Learning）</news:title>
   <news:publication_date>2026-07-07T20:27:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709262</loc>
  <lastmod>2026-07-07T20:27:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相情報のマルチスケール集約によるCNNベースDOA推定の計算コスト削減（MULTI-SCALE AGGREGATION OF PHASE INFORMATION FOR REDUCING COMPUTATIONAL COST OF CNN BASED DOA ESTIMATION）</news:title>
   <news:publication_date>2026-07-07T20:27:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709260</loc>
  <lastmod>2026-07-07T20:26:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>曲特徴を取り込む注意機構付きニューラル構造による音楽レコメンド（Attentive Neural Architecture Incorporating Song Features For Music Recommendation）</news:title>
   <news:publication_date>2026-07-07T20:26:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709258</loc>
  <lastmod>2026-07-07T20:26:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平な機械学習の最前線（State of the Art in Fair Machine Learning）</news:title>
   <news:publication_date>2026-07-07T20:26:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709256</loc>
  <lastmod>2026-07-07T20:25:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CGNet: 軽量コンテキストガイドネットワークによるセマンティックセグメンテーション（CGNet: A Light-weight Context Guided Network for Semantic Segmentation）</news:title>
   <news:publication_date>2026-07-07T20:25:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709254</loc>
  <lastmod>2026-07-07T19:34:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN生成画像の起源特定とフィンガープリント解析（Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints）</news:title>
   <news:publication_date>2026-07-07T19:34:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709252</loc>
  <lastmod>2026-07-07T19:34:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古い文献が示す洞察と現代物理学の接点（Coffee stains, cell receptors, and time crystals: Lessons from the old literature）</news:title>
   <news:publication_date>2026-07-07T19:34:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709250</loc>
  <lastmod>2026-07-07T19:34:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換入力とロバストなテンソル分解に基づく畳み込みニューラルネットワーク（Convolutional Neural Networks with Transformed Input based on Robust Tensor Network Decomposition）</news:title>
   <news:publication_date>2026-07-07T19:34:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709248</loc>
  <lastmod>2026-07-07T19:33:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胎児超音波画像における影領域信頼度マップの弱教師あり推定（Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging）</news:title>
   <news:publication_date>2026-07-07T19:33:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709246</loc>
  <lastmod>2026-07-07T19:33:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクタースケッチ認識のための注意型ネットワーク（Sketch-R2CNN: An Attentive Network for Vector Sketch Recognition）</news:title>
   <news:publication_date>2026-07-07T19:33:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709244</loc>
  <lastmod>2026-07-07T19:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形の概念を機械が自ら学ぶ方法（Unsupervised Learning of Shape Concepts – From Real-World Objects to Mental Simulation）</news:title>
   <news:publication_date>2026-07-07T19:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709242</loc>
  <lastmod>2026-07-07T19:33:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hedge手法を巡る攻防：適応的意思決定と最悪ケースの解析（Playing with and against Hedge）</news:title>
   <news:publication_date>2026-07-07T19:33:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709240</loc>
  <lastmod>2026-07-07T18:41:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>De Sitterの地平線とホログラフィック流体（De Sitter Horizons &amp;amp; Holographic Liquids）</news:title>
   <news:publication_date>2026-07-07T18:41:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709238</loc>
  <lastmod>2026-07-07T18:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNを用いた可逆データ圧縮（DeepZip: Lossless Data Compression using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-07T18:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709236</loc>
  <lastmod>2026-07-07T18:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による脳外科スキル判定（Machine Learning Distinguishes Neurosurgical Skill Levels in a Virtual Reality Tumor Resection Task）</news:title>
   <news:publication_date>2026-07-07T18:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709234</loc>
  <lastmod>2026-07-07T18:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的学習による点群整合（Adversarial point set registration）</news:title>
   <news:publication_date>2026-07-07T18:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709232</loc>
  <lastmod>2026-07-07T18:40:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深さと幅が局所最小値に与える影響（Effect of Depth and Width on Local Minima in Deep Learning）</news:title>
   <news:publication_date>2026-07-07T18:40:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709230</loc>
  <lastmod>2026-07-07T18:40:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNが画像をどう見るか（How you see me）</news:title>
   <news:publication_date>2026-07-07T18:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709228</loc>
  <lastmod>2026-07-07T18:40:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>即時変化検出の学習：遡及畳み込みと静的サンプル合成 (Learning to Detect Instantaneous Changes with Retrospective Convolution and Static Sample Synthesis)</news:title>
   <news:publication_date>2026-07-07T18:40:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709226</loc>
  <lastmod>2026-07-07T17:48:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的フィードバックループによる生成画像の品質改善（Adversarial Feedback Loop）</news:title>
   <news:publication_date>2026-07-07T17:48:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709224</loc>
  <lastmod>2026-07-07T17:48:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DarwinML: グラフベースの進化的AutoML（DarwinML: A Graph-based Evolutionary Algorithm for Automated Machine Learning）</news:title>
   <news:publication_date>2026-07-07T17:48:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709222</loc>
  <lastmod>2026-07-07T17:48:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Auto-Set: ウェアラブルを用いた活動認識のための深層オートエンコーダセット（Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables）</news:title>
   <news:publication_date>2026-07-07T17:48:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709220</loc>
  <lastmod>2026-07-07T17:47:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルノイズ下で主要パターンを最大限学習する方法（Limited Gradient Descent: Learning With Noisy Labels）</news:title>
   <news:publication_date>2026-07-07T17:47:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709218</loc>
  <lastmod>2026-07-07T17:47:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーケンス基盤の人物属性認識とJoint CTC-Attentionモデル（Sequence-based Person Attribute Recognition with Joint CTC-Attention Model）</news:title>
   <news:publication_date>2026-07-07T17:47:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709216</loc>
  <lastmod>2026-07-07T17:47:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トラフィックを考慮したNFVスケーリングの閾値調整（Traffic-aware Threshold Adjustment for NFV Scaling using DRL）</news:title>
   <news:publication_date>2026-07-07T17:47:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/709214</loc>
  <lastmod>2026-07-07T17:47:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在因子モデルの説明可能化と影響関数（Explaining Latent Factor Models for Recommendation with Influence Functions）</news:title>
   <news:publication_date>2026-07-07T17:47:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/709212</loc>
  <lastmod>2026-07-07T16:55:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動フォント生成におけるマルチスケール埋め込みと生成的敵対学習の意義（Pyramid Embedded Generative Adversarial Network for Automated Font Generation）</news:title>
   <news:publication_date>2026-07-07T16:55:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709210</loc>
  <lastmod>2026-07-07T16:55:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト監督を付与したSeq2Seq音声変換の改善（IMPROVING SEQUENCE-TO-SEQUENCE VOICE CONVERSION BY ADDING TEXT-SUPERVISION）</news:title>
   <news:publication_date>2026-07-07T16:55:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709208</loc>
  <lastmod>2026-07-07T16:54:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔検出のための特徴融合とセグメンテーション監督による学習（Learning Better Features for Face Detection with Feature Fusion and Segmentation Supervision）</news:title>
   <news:publication_date>2026-07-07T16:54:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709206</loc>
  <lastmod>2026-07-07T16:54:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話生成の多様性を高める新しい目的関数（Another Diversity-Promoting Objective Function for Neural Dialogue Generation）</news:title>
   <news:publication_date>2026-07-07T16:54:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/709204</loc>
  <lastmod>2026-07-07T16:54:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>先読み探索による連続制御の学習革新（Model Learning for Look-ahead Exploration in Continuous Control）</news:title>
   <news:publication_date>2026-07-07T16:54:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709202</loc>
  <lastmod>2026-07-07T16:54:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能なマルチプル・カーネル学習による統合的がんサブタイプの発見（An interpretable multiple kernel learning approach for the discovery of integrative cancer subtypes）</news:title>
   <news:publication_date>2026-07-07T16:54:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/709200</loc>
  <lastmod>2026-07-07T16:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向敵対的オートエンコーダによるゼロショット学習（Bi-Adversarial Auto-Encoder for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-07-07T16:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709198</loc>
  <lastmod>2026-07-07T16:02:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Multiple-Instance Learning を無限のシェイプレットで拡張する手法（Multiple-Instance Learning by Boosting Infinitely Many Shapelet-based Classifiers）</news:title>
   <news:publication_date>2026-07-07T16:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709196</loc>
  <lastmod>2026-07-07T16:02:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ChainGAN: 逐次的編集で生成を安定化させるアプローチ（CHAINGAN: A SEQUENTIAL APPROACH TO GANS）</news:title>
   <news:publication_date>2026-07-07T16:02:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709194</loc>
  <lastmod>2026-07-07T16:01:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量リプシッツ・マージン学習による証明済み防御の実装可能性（Lightweight Lipschitz Margin Training for Certified Defense against Adversarial Examples）</news:title>
   <news:publication_date>2026-07-07T16:01:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709192</loc>
  <lastmod>2026-07-07T16:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩行者軌跡の表現学習――Actor–Critic Sequence-to-Sequence Autoencoderによる新展開（Representation Learning of Pedestrian Trajectories Using Actor-Critic Sequence-to-Sequence Autoencoder）</news:title>
   <news:publication_date>2026-07-07T16:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/709190</loc>
  <lastmod>2026-07-07T16:01:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列ニューラルネットワークから学ぶ異種音声特徴の頑健学習（Learning Robust Heterogeneous Signal Features from Parallel Neural Network for Audio Sentiment Analysis）</news:title>
   <news:publication_date>2026-07-07T16:01:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/709188</loc>
  <lastmod>2026-07-07T16:01:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遮蔽下で手と目を協調させる強化学習（Reinforcement Learning of Active Vision for Manipulating Objects under Occlusions）</news:title>
   <news:publication_date>2026-07-07T16:01:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709186</loc>
  <lastmod>2026-07-07T16:00:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Factorized DistillationによるHolistic Person Re-identificationの効率化（Factorized Distillation: Training Holistic Person Re-identiﬁcation Model by Distilling an Ensemble of Partial ReID Models）</news:title>
   <news:publication_date>2026-07-07T16:00:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709184</loc>
  <lastmod>2026-07-07T15:09:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外観変化下の視覚的自己位置推定：フィルタリング手法の可能性（Visual Localization Under Appearance Change: Filtering Approaches）</news:title>
   <news:publication_date>2026-07-07T15:09:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709182</loc>
  <lastmod>2026-07-07T15:09:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配整合型強正則化による深層学習の安定化（Gradient-Coherent Strong Regularization for Deep Neural Networks with Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-07-07T15:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709180</loc>
  <lastmod>2026-07-07T15:09:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模行列の対数行列式を並列で速く計算する方法（Parallel Matrix Condensation for Calculating Log-Determinant of Large Matrix）</news:title>
   <news:publication_date>2026-07-07T15:09:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/709178</loc>
  <lastmod>2026-07-07T15:08:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量時系列データにおける教師なし異常検知と診断の深層ニューラルネットワーク（A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data）</news:title>
   <news:publication_date>2026-07-07T15:08:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709176</loc>
  <lastmod>2026-07-07T15:08:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多声音楽作曲のための結合リカレントモデル (Coupled Recurrent Models for Polyphonic Music Composition)</news:title>
   <news:publication_date>2026-07-07T15:08:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/709174</loc>
  <lastmod>2026-07-07T15:08:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率粒子最適化サンプリングにおける分散削減（Variance Reduced Stochastic Particle-Optimization Sampling）</news:title>
   <news:publication_date>2026-07-07T15:08:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709172</loc>
  <lastmod>2026-07-07T15:07:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶を保存せずに継続学習する手法の要点解説（Learning without Memorizing）</news:title>
   <news:publication_date>2026-07-07T15:07:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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