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   <news:title>複数タスクに強い強化学習とPopArtの威力（Multi-task Deep Reinforcement Learning with PopArt）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>動きから学ぶStructure-from-Motion（Learning structure-from-motion from motion）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>ランダム特徴量による線形SVMの理論的理解（But How Does It Work in Theory? Linear SVM with Random Features）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>頭頸部放射線治療のための臨床適用可能なセグメンテーションを実現する深層学習（Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>フレームレベル話者埋め込みによるテキスト非依存話者認識の解析（FRAME-LEVEL SPEAKER EMBEDDINGS FOR TEXT-INDEPENDENT SPEAKER RECOGNITION AND ANALYSIS OF END-TO-END MODEL）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>話者方言識別のための教師なし音声表現学習（UNSUPERVISED REPRESENTATION LEARNING OF SPEECH FOR DIALECT IDENTIFICATION）</news:title>
   <news:publication_date>2026-06-12T20:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-12T20:20:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>SU Aurの可視・近赤外での深い減光イベント（SU AUR: A DEEP FADING EVENT IN VISIBLE AND NEAR-INFRARED BANDS）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699969</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>勾配に基づく表現類似性解析とサーチライトによるfMRI全脳解析（Gradient-based Representational Similarity Analysis with Searchlight for Analyzing fMRI Data）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-12T19:29:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>未知の移動行動に対する位置情報プライバシーの再考（Rethinking Location Privacy for Unknown Mobility Behaviors）</news:title>
   <news:publication_date>2026-06-12T19:29:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699965</loc>
  <lastmod>2026-06-12T19:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>実測データから「実在する」量子チャネルを復元する方法（Reconstruction of the Real Quantum Channel via Convex Optimization）</news:title>
   <news:publication_date>2026-06-12T19:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699963</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>グローバルPDFフィットにおける機械学習ツールの活用（Machine Learning tools for global PDF fits）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-12T19:27:54Z</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>大規模動画ラベリングで勝つための“ラベル除噪（Label Denoising）”の実務的教科書（Label Denoising with Large Ensembles of Heterogeneous Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-12T19:27:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>和積ネットワークで拡張する局所ガウス過程の混合モデル（Learning Deep Mixtures of Gaussian Process Experts Using Sum-Product Networks）</news:title>
   <news:publication_date>2026-06-12T19:27:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699957</loc>
  <lastmod>2026-06-12T19:27:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上のベイズ半教師あり学習（Bayesian Semi-supervised Learning with Graph Gaussian Processes）</news:title>
   <news:publication_date>2026-06-12T19:27:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699955</loc>
  <lastmod>2026-06-12T18:36:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調型マルチエージェント強化学習による反ジャミングアルゴリズム（A Collaborative Multi-agent Reinforcement Learning Anti-jamming Algorithm in Wireless Networks）</news:title>
   <news:publication_date>2026-06-12T18:36:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699953</loc>
  <lastmod>2026-06-12T18:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PAUサーベイにおけるフォトメトリック赤方偏移の早期検証（The PAU Survey: Early demonstration of photometric redshift performance in the COSMOS field）</news:title>
   <news:publication_date>2026-06-12T18:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699951</loc>
  <lastmod>2026-06-12T18:25:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期引用データから論文の将来の影響力を予測する（Predicting citation counts based on deep neural network learning techniques）</news:title>
   <news:publication_date>2026-06-12T18:25:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699949</loc>
  <lastmod>2026-06-12T18:25:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質のB因子（柔軟性）を盲検的に予測する手法（Blind prediction of protein B-factor and flexibility）</news:title>
   <news:publication_date>2026-06-12T18:25:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699947</loc>
  <lastmod>2026-06-12T18:25:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データ分類における深層学習の総覧（Deep learning for time series classification: a review）</news:title>
   <news:publication_date>2026-06-12T18:25:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699945</loc>
  <lastmod>2026-06-12T18:24:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心拍変動に基づく睡眠段階判定のためのLSTMと知識転移（LSTM knowledge transfer for HRV-based sleep staging）</news:title>
   <news:publication_date>2026-06-12T18:24:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699943</loc>
  <lastmod>2026-06-12T18:24:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なるデータセットで深層ニューラルネットワークを訓練する手法（Training Deep Neural Networks with Different Datasets In-the-wild: The Emotion Recognition Paradigm）</news:title>
   <news:publication_date>2026-06-12T18:24:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/699941</loc>
  <lastmod>2026-06-12T17:33:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全身アーム操作を用いた人体移動のための位相基盤表現における強化学習（Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation）</news:title>
   <news:publication_date>2026-06-12T17:33:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699939</loc>
  <lastmod>2026-06-12T17:24:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報セキュリティ分野における深層学習の実務的意義（DEEP LEARNING IN INFORMATION SECURITY）</news:title>
   <news:publication_date>2026-06-12T17:24:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699937</loc>
  <lastmod>2026-06-12T17:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UGC 1922 の内部動力学と星形成（A Malin 1 “cousin” with counter-rotation: internal dynamics and stellar content of the giant low surface brightness galaxy UGC 1922）</news:title>
   <news:publication_date>2026-06-12T17:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699935</loc>
  <lastmod>2026-06-12T17:22:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>作業記憶モデルによる中国詩生成（Chinese Poetry Generation with a Working Memory Model）</news:title>
   <news:publication_date>2026-06-12T17:22:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/699933</loc>
  <lastmod>2026-06-12T17:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌詞から自動作曲するニューラル手法（Neural Melody Composition from Lyrics）</news:title>
   <news:publication_date>2026-06-12T17:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699931</loc>
  <lastmod>2026-06-12T17:22:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期視覚追跡における回帰と検証ネットワークの統合（Learning regression and verification networks for long-term visual tracking）</news:title>
   <news:publication_date>2026-06-12T17:22:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/699929</loc>
  <lastmod>2026-06-12T17:22:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異結合を持つクラモトモデルにおけるFilippov軌道とクラスタリング（FILIPPOV TRAJECTORIES AND CLUSTERING IN THE KURAMOTO MODEL WITH SINGULAR COUPLINGS）</news:title>
   <news:publication_date>2026-06-12T17:22:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/699927</loc>
  <lastmod>2026-06-12T16:30:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚場面における発話を用いたマルチモーダルな呼びかけ先認識（Deep Learning Based Multi-modal Addressee Recognition in Visual Scenes with Utterances）</news:title>
   <news:publication_date>2026-06-12T16:30:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699925</loc>
  <lastmod>2026-06-12T16:30:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文と意味情報を埋め込みに取り込む方法（Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-06-12T16:30:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699923</loc>
  <lastmod>2026-06-12T16:30:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠測データからの連続時間ベイジアンネットワーク構造学習におけるクラスタ変分近似（Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data）</news:title>
   <news:publication_date>2026-06-12T16:30:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699921</loc>
  <lastmod>2026-06-12T16:29:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識を取り入れた会話型テーブル意味解析 (Knowledge-Aware Conversational Semantic Parsing Over Web Tables)</news:title>
   <news:publication_date>2026-06-12T16:29:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/699919</loc>
  <lastmod>2026-06-12T16:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続変数を離散的に緩和して実用的な変分推論を可能にする方法（Discretely Relaxing Continuous Variables for tractable Variational Inference）</news:title>
   <news:publication_date>2026-06-12T16:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/699917</loc>
  <lastmod>2026-06-12T16:29:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜OCT画像における層分割と不確実性可視化：ベイズ深層学習による信頼度の導入（Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images using Bayesian Deep Learning）</news:title>
   <news:publication_date>2026-06-12T16:29:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/699915</loc>
  <lastmod>2026-06-12T16:29:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Music Transformerによる長期構造を持つ音楽生成（MUSIC TRANSFORMER: GENERATING MUSIC WITH LONG-TERM STRUCTURE）</news:title>
   <news:publication_date>2026-06-12T16:29:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699913</loc>
  <lastmod>2026-06-12T15:37:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-12T15:37:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699911</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>Wasserstein重心を高速に求めるアルゴリズム（A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters）</news:title>
   <news:publication_date>2026-06-12T15:37:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699909</loc>
  <lastmod>2026-06-12T15:37:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分文字列で単語埋め込みを一般化する（Generalizing Word Embeddings using Bag of Subwords）</news:title>
   <news:publication_date>2026-06-12T15:37:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699907</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>脳波(EEG)を用いた視聴映像認識とグラフ畳み込みニューラルネットワーク（EEG-BASED VIDEO IDENTIFICATION USING GRAPH SIGNAL MODELING AND GRAPH CONVOLUTIONAL NEURAL NETWORK）</news:title>
   <news:publication_date>2026-06-12T15:36:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699905</loc>
  <lastmod>2026-06-12T15:36:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-12T15:36:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699903</loc>
  <lastmod>2026-06-12T15:36:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時変安全性を考慮した安全探索：ST-SAFEMDP（Safe Exploration in Markov Decision Processes with Time-Variant Safety using Spatio-Temporal Gaussian Process）</news:title>
   <news:publication_date>2026-06-12T15:36:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699901</loc>
  <lastmod>2026-06-12T15:36:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>洗練された対戦相手に対する効率的検出と最適応答（Towards Efficient Detection and Optimal Response against Sophisticated Opponents）</news:title>
   <news:publication_date>2026-06-12T15:36:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699899</loc>
  <lastmod>2026-06-12T14:44:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市場の共投資関係を自動で学ぶDeepCNL（Deep Co-investment Network Learning for Financial Assets）</news:title>
   <news:publication_date>2026-06-12T14:44:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699897</loc>
  <lastmod>2026-06-12T14:34:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次の関係を捉えるグラフ畳み込み（Higher-order Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-06-12T14:34:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699895</loc>
  <lastmod>2026-06-12T14:33:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意に基づく視覚解析による多指ロボットハンドの高速把持計画（Attention based visual analysis for fast grasp planning with multi-fingered robotic hand）</news:title>
   <news:publication_date>2026-06-12T14:33:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699893</loc>
  <lastmod>2026-06-12T14:32:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動・個人化・柔軟なプレイリスト生成（AUTOMATIC, PERSONALIZED, AND FLEXIBLE PLAYLIST GENERATION USING REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-06-12T14:32:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699891</loc>
  <lastmod>2026-06-12T14:32:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ連鎖上での確率的勾配法の現実的進化（On Markov Chain Gradient Descent）</news:title>
   <news:publication_date>2026-06-12T14:32:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699889</loc>
  <lastmod>2026-06-12T14:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き最適化を生態学的力学として読み解く（Constrained optimization as ecological dynamics with applications to random quadratic programming in high dimensions）</news:title>
   <news:publication_date>2026-06-12T14:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699887</loc>
  <lastmod>2026-06-12T14:32:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Routine Blood Testsで冠動脈疾患を予測する（Prediction of Coronary Heart Disease Using Routine Blood Tests）</news:title>
   <news:publication_date>2026-06-12T14:32:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699885</loc>
  <lastmod>2026-06-12T13:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル空間制約に基づくラベルノイズ浄化とランダムラベル伝播（Random Label Propagation with Spectral-Spatial Constraints）</news:title>
   <news:publication_date>2026-06-12T13:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699883</loc>
  <lastmod>2026-06-12T13:40:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGを用いた感情認識における脳結合性と空間情報の活用（CONVOLUTIONAL NEURAL NETWORK APPROACH FOR EEG-BASED EMOTION RECOGNITION USING BRAIN CONNECTIVITY AND ITS SPATIAL INFORMATION）</news:title>
   <news:publication_date>2026-06-12T13:40:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699881</loc>
  <lastmod>2026-06-12T13:40:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>飽和した測定からの高速信号復元（Fast Signal Recovery from Saturated Measurements by Linear Loss and Nonconvex Penalties）</news:title>
   <news:publication_date>2026-06-12T13:40:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699879</loc>
  <lastmod>2026-06-12T13:40:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非微分制約を持つ最適化とその応用（Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals）</news:title>
   <news:publication_date>2026-06-12T13:40:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699877</loc>
  <lastmod>2026-06-12T13:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-12T13:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699875</loc>
  <lastmod>2026-06-12T13:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的概日モデルにおける変化点検出（Change-Point Detection on Hierarchical Circadian Models）</news:title>
   <news:publication_date>2026-06-12T13:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699873</loc>
  <lastmod>2026-06-12T13:39:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zoomに学ぶSSD活用ベクトル検索の実務応用（Zoom: SSD-based Vector Search for Optimizing Accuracy, Latency and Memory）</news:title>
   <news:publication_date>2026-06-12T13:39:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699871</loc>
  <lastmod>2026-06-12T12:48:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DISにおけるハドロン最終状態のNNLO QCDとパートンシャワーの統合（Hadronic Final States in DIS at NNLO QCD with Parton Showers）</news:title>
   <news:publication_date>2026-06-12T12:48:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699869</loc>
  <lastmod>2026-06-12T12:48:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度ネットワークで組込み推論を劇的に効率化する（DISCOVERING LOW-PRECISION NETWORKS CLOSE TO FULL-PRECISION NETWORKS FOR EFFICIENT EMBEDDED INFERENCE）</news:title>
   <news:publication_date>2026-06-12T12:48:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699867</loc>
  <lastmod>2026-06-12T12:47:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードディスクの健康度予測における層別摂動型敵対的訓練（Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction）</news:title>
   <news:publication_date>2026-06-12T12:47:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699865</loc>
  <lastmod>2026-06-12T12:46:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Micro-Dictionary Learning and Coding Network（Deep Micro-Dictionary Learning and Coding Network）</news:title>
   <news:publication_date>2026-06-12T12:46:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699863</loc>
  <lastmod>2026-06-12T12:46:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られた学習データからの反復的セグメンテーション（Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease）</news:title>
   <news:publication_date>2026-06-12T12:46:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699861</loc>
  <lastmod>2026-06-12T12:46:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語学とディープラーニングの相互利益（What can linguistics and deep learning contribute to each other?）</news:title>
   <news:publication_date>2026-06-12T12:46:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699859</loc>
  <lastmod>2026-06-12T12:46:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密な画像予測のための効率的なマルチスケールアーキテクチャ探索（Searching for Efficient Multi-Scale Architectures for Dense Image Prediction）</news:title>
   <news:publication_date>2026-06-12T12:46:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699857</loc>
  <lastmod>2026-06-12T11:54:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相情報を失った状態での動的サブスペース追跡（Phaseless Subspace Tracking）</news:title>
   <news:publication_date>2026-06-12T11:54:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699855</loc>
  <lastmod>2026-06-12T11:54:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Leabra7による生物学的に現実的な再帰ニューラルネット実装（Leabra7: a Python package for modeling recurrent, biologically-realistic neural networks）</news:title>
   <news:publication_date>2026-06-12T11:54:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699853</loc>
  <lastmod>2026-06-12T11:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン講座のクリックログ時系列解析が示す学習行動の見える化（Time Series Analysis of Clickstream Logs from Online Courses）</news:title>
   <news:publication_date>2026-06-12T11:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699851</loc>
  <lastmod>2026-06-12T11:54:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型再生可能電源が増えた配電網における同時確率制約の学習による改良（Joint Chance Constraints in AC Optimal Power Flow: Improving Bounds through Learning）</news:title>
   <news:publication_date>2026-06-12T11:54:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699849</loc>
  <lastmod>2026-06-12T11:53:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトマックス温度を上げることで得られる埋め込みの改善（Heated-Up Softmax Embedding）</news:title>
   <news:publication_date>2026-06-12T11:53:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699847</loc>
  <lastmod>2026-06-12T11:53:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドの画像キャプショニングは分布類似性を利用している（End-to-end Image Captioning Exploits Multimodal Distributional Similarity）</news:title>
   <news:publication_date>2026-06-12T11:53:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699845</loc>
  <lastmod>2026-06-12T11:53:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語ベクトル特化の敵対的伝播とゼロショット跨言語転移（Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization）</news:title>
   <news:publication_date>2026-06-12T11:53:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/699843</loc>
  <lastmod>2026-06-12T11:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化された賭けメカニズムの設計と意義（Randomized Wagering Mechanisms）</news:title>
   <news:publication_date>2026-06-12T11:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699841</loc>
  <lastmod>2026-06-12T10:52:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>断片画像の再構成を深層学習で行うJigsawNet（JigsawNet: Shredded Image Reassembly using Convolutional Neural Network and Loop-based Composition）</news:title>
   <news:publication_date>2026-06-12T10:52:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699839</loc>
  <lastmod>2026-06-12T10:51:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的言語解釈を学ぶ再帰型モデルの可能性と限界（On Learning Interpreted Languages with Recurrent Models）</news:title>
   <news:publication_date>2026-06-12T10:51:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699837</loc>
  <lastmod>2026-06-12T10:50:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフベース推薦システムへの毒物注入攻撃（Poisoning Attacks to Graph-Based Recommender Systems）</news:title>
   <news:publication_date>2026-06-12T10:50:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699835</loc>
  <lastmod>2026-06-12T10:50:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型弾性イメージングのためのCartesian NNCM（Cartesian Neural Network Constitutive Models for Data-driven Elasticity Imaging）</news:title>
   <news:publication_date>2026-06-12T10:50:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699833</loc>
  <lastmod>2026-06-12T10:50:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間は敵対的画像を解読できる（Deciphering Adversarial Images）</news:title>
   <news:publication_date>2026-06-12T10:50:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699831</loc>
  <lastmod>2026-06-12T10:50:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>厚い星盤（スラブ）が示す外縁部の古い星形成停止の痕跡（The imprint of the thick stellar disc in the mid-plane of three early-type edge-on galaxies in the Fornax cluster）</news:title>
   <news:publication_date>2026-06-12T10:50:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699829</loc>
  <lastmod>2026-06-12T09:58:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタグラフとメタパスを同時に埋め込む手法の本質（Joint Embedding of Meta-Path and Meta-Graph for Heterogeneous Information Networks）</news:title>
   <news:publication_date>2026-06-12T09:58:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699827</loc>
  <lastmod>2026-06-12T09:58:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サービスロボットのワンショット話者識別（One-Shot Speaker Identification for a Service Robot using a CNN-based Generic Verifier）</news:title>
   <news:publication_date>2026-06-12T09:58:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699825</loc>
  <lastmod>2026-06-12T09:58:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cas Aの未衝撃放出物の温度と電離状態（The Temperature and Ionization of Unshocked Ejecta in Cas A）</news:title>
   <news:publication_date>2026-06-12T09:58:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699823</loc>
  <lastmod>2026-06-12T09:57:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列分解型3D畳み込みが変える動画・ボリュームデータ解析（Parallel Separable 3D Convolution for Video and Volumetric Data Understanding）</news:title>
   <news:publication_date>2026-06-12T09:57:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699821</loc>
  <lastmod>2026-06-12T09:57:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PUFとAESを組み合わせた新しい不正アクセス耐性（PUF-AES-PUF: a novel PUF architecture against non-invasive attacks）</news:title>
   <news:publication_date>2026-06-12T09:57:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699819</loc>
  <lastmod>2026-06-12T09:57:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子アルゴリズムによる構造化予測の高速化（Quantum Algorithms for Structured Prediction）</news:title>
   <news:publication_date>2026-06-12T09:57:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699817</loc>
  <lastmod>2026-06-12T09:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みネットワークがフーリエ基底に敏感である構造的理由（On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions）</news:title>
   <news:publication_date>2026-06-12T09:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699815</loc>
  <lastmod>2026-06-12T09:05:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移（z∼2）の光学的に暗いAGNを対象としたイオン化ガス星雲のイメージング分光学（IMAGING SPECTROSCOPY OF IONIZED GASEOUS NEBULAE AROUND OPTICALLY FAINT AGN AT REDSHIFT Z ∼2）</news:title>
   <news:publication_date>2026-06-12T09:05:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699813</loc>
  <lastmod>2026-06-12T09:05:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural-Augmented Static Analysis of Android Communication（Neural-Augmented Static Analysis of Android Communication）</news:title>
   <news:publication_date>2026-06-12T09:05:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699811</loc>
  <lastmod>2026-06-12T09:05:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D畳み込みを用いたアンサンブル学習で機能的コネクトーム予測を強化する（Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction）</news:title>
   <news:publication_date>2026-06-12T09:05:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699809</loc>
  <lastmod>2026-06-12T09:04:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一次元系における単粒子移動端を伴う多体局在の観測（Observation of many-body localization in a one-dimensional system with single-particle mobility edge）</news:title>
   <news:publication_date>2026-06-12T09:04:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699807</loc>
  <lastmod>2026-06-12T09:04:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称単語埋め込みによるテキスト含意の改善（AWE: Asymmetric Word Embedding for Textual Entailment）</news:title>
   <news:publication_date>2026-06-12T09:04:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699805</loc>
  <lastmod>2026-06-12T09:03:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepProteomicsによるタンパク質ファミリー分類（DeepProteomics: Protein family classification using Shallow and Deep Networks）</news:title>
   <news:publication_date>2026-06-12T09:03:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699803</loc>
  <lastmod>2026-06-12T09:03:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超距離標準光源による運動学的宇宙論の現状（Status of kinematic cosmology with SN Ia: JLA, Pantheon and future constraints with LSST）</news:title>
   <news:publication_date>2026-06-12T09:03:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699801</loc>
  <lastmod>2026-06-12T08:12:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>史料刻字（グラフィティ）認識に向けたカプセル深層ニューラルネットワークの応用（Capsule Deep Neural Network for Recognition of Historical Graffiti Handwriting）</news:title>
   <news:publication_date>2026-06-12T08:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699799</loc>
  <lastmod>2026-06-12T08:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率ビット（p-bit）による確率的スピン論理の提案（p-Bits for Probabilistic Spin Logic）</news:title>
   <news:publication_date>2026-06-12T08:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699797</loc>
  <lastmod>2026-06-12T08:12:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GitHub上の「保守されていない」プロジェクトを機械学習で見抜く方法（Identifying Unmaintained Projects in GitHub）</news:title>
   <news:publication_date>2026-06-12T08:12:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699795</loc>
  <lastmod>2026-06-12T08:11:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文の意味的合理性の評価（Evaluating Semantic Rationality of a Sentence: A Sememe-Word-Matching Neural Network based on HowNet）</news:title>
   <news:publication_date>2026-06-12T08:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699793</loc>
  <lastmod>2026-06-12T08:11:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ混入した履歴データを用いるテキスト分類の課題（Training and Prediction Data Discrepancies: Challenges of Text Classification with Noisy, Historical Data）</news:title>
   <news:publication_date>2026-06-12T08:11:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699791</loc>
  <lastmod>2026-06-12T08:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMはバスク語の一致を学べるか（Can LSTM Learn to Capture Agreement? The Case of Basque）</news:title>
   <news:publication_date>2026-06-12T08:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699789</loc>
  <lastmod>2026-06-12T08:11:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>看護記録から感染兆候を検出する自動早期敗血症アラートへの道（Toward Automated Early Sepsis Alerting: Identifying Infection Patients from Nursing Notes）</news:title>
   <news:publication_date>2026-06-12T08:11:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699787</loc>
  <lastmod>2026-06-12T07:20:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>切り取られたデータからの効率的推定（Efficient Statistics, in High Dimensions, from Truncated Samples）</news:title>
   <news:publication_date>2026-06-12T07:20:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699785</loc>
  <lastmod>2026-06-12T07:20:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路車線検出に効率化をもたらす深層学習手法（Efficient Road Lane Marking Detection with Deep Learning）</news:title>
   <news:publication_date>2026-06-12T07:20:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699783</loc>
  <lastmod>2026-06-12T07:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外部攪乱からの回復でロボットの長期自律性を高める方法（Endowing Robots with Longer-term Autonomy by Recovering from External Disturbances in Manipulation through Grounded Anomaly Classification and Recovery Policies）</news:title>
   <news:publication_date>2026-06-12T07:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699781</loc>
  <lastmod>2026-06-12T07:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抽象化学習（Abstraction Learning）</news:title>
   <news:publication_date>2026-06-12T07:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699779</loc>
  <lastmod>2026-06-12T07:19:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子位置に依存しない記述子による材料物性の機械学習（Atomic positions independent descriptor for machine learning of material properties）</news:title>
   <news:publication_date>2026-06-12T07:19:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699777</loc>
  <lastmod>2026-06-12T07:19:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空気汚染予測のための深層推論時空間ネットワーク（Deep Inferential Spatial-Temporal Network for Forecasting Air Pollution Concentrations）</news:title>
   <news:publication_date>2026-06-12T07:19:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699775</loc>
  <lastmod>2026-06-12T07:18:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さな神経回路でロボット制御を再発明する（Can a Compact Neuronal Circuit Policy be Re-purposed to Learn Simple Robotic Control?）</news:title>
   <news:publication_date>2026-06-12T07:18:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699773</loc>
  <lastmod>2026-06-12T06:27:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ガウス過程を用いた効率的全域最適化（EFFICIENT GLOBAL OPTIMIZATION USING DEEP GAUSSIAN PROCESSES）</news:title>
   <news:publication_date>2026-06-12T06:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699771</loc>
  <lastmod>2026-06-12T06:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感覚的人工知能が囲碁に示した新しい方針（SAI, a Sensible Artificial Intelligence that plays Go）</news:title>
   <news:publication_date>2026-06-12T06:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699769</loc>
  <lastmod>2026-06-12T06:18:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定量的手法に関する二相研究が示す課題と示唆（A two-phase study examining perspectives and use of quantitative methods in PER）</news:title>
   <news:publication_date>2026-06-12T06:18:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699767</loc>
  <lastmod>2026-06-12T06:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMセルの応答特性による可視化と監査（Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks）</news:title>
   <news:publication_date>2026-06-12T06:18:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699765</loc>
  <lastmod>2026-06-12T06:18:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脆弱な道路利用者の意図検出と協調知能（Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence）</news:title>
   <news:publication_date>2026-06-12T06:18:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699763</loc>
  <lastmod>2026-06-12T06:17:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EXS: ローカルでモデル非依存な解釈性を用いた説明可能な検索（EXS: Explainable Search Using Local Model Agnostic Interpretability）</news:title>
   <news:publication_date>2026-06-12T06:17:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699761</loc>
  <lastmod>2026-06-12T06:17:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンハラ語の算数問題をニューラルネットワークで解く（Solving Sinhala Language Arithmetic Problems using Neural Networks）</news:title>
   <news:publication_date>2026-06-12T06:17:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699759</loc>
  <lastmod>2026-06-12T05:26:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変分類のためのCNN可視化による診断支援の強化（Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification）</news:title>
   <news:publication_date>2026-06-12T05:26:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699757</loc>
  <lastmod>2026-06-12T05:26:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>危険度を見て切り替える自己航行用DRLエージェントの統合手法（Danger-aware Adaptive Composition of DRL Agents for Self-navigation）</news:title>
   <news:publication_date>2026-06-12T05:26:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699755</loc>
  <lastmod>2026-06-12T05:25:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソース誘導差異に基づく教師なしドメイン適応（Unsupervised Domain Adaptation Based on Source-guided Discrepancy）</news:title>
   <news:publication_date>2026-06-12T05:25:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699753</loc>
  <lastmod>2026-06-12T05:25:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習率適応法によるフェデレーテッド／差分プライバシー学習の改善（Learning Rate Adaptation for Federated and Differentially Private Learning）</news:title>
   <news:publication_date>2026-06-12T05:25:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699751</loc>
  <lastmod>2026-06-12T05:24:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シリーズ弾性アクチュエータを用いたBWSのリアルタイム力制御と2-DOF制御構造（Real-Time Force Control of an SEA-based Body Weight Support Unit with the 2-DOF Control Structure）</news:title>
   <news:publication_date>2026-06-12T05:24:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699749</loc>
  <lastmod>2026-06-12T05:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMとBi-LSTMを用いた血糖値予測の実務的意義（Predicting Blood Glucose with an LSTM and Bi-LSTM Based Deep Neural Network）</news:title>
   <news:publication_date>2026-06-12T05:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699747</loc>
  <lastmod>2026-06-12T05:24:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野球ではなくクリケットの「審判ジェスチャー」検出データセットと予備結果（A Dataset and Preliminary Results for Umpire Pose Detection）</news:title>
   <news:publication_date>2026-06-12T05:24:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699745</loc>
  <lastmod>2026-06-12T04:33:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NGC 4388におけるラム圧剥離の詳細解析（The uneven sisters I: NGC 4388 – a strongly constrained ram pressure stripping event）</news:title>
   <news:publication_date>2026-06-12T04:33:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699743</loc>
  <lastmod>2026-06-12T04:33:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークにおけるマルチタスク学習（Multitask Learning on Graph Neural Networks）</news:title>
   <news:publication_date>2026-06-12T04:33:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699741</loc>
  <lastmod>2026-06-12T04:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホログラフィックにおけるエンタングルメントとQNECの数値検証（Holographic Entanglement Entropy and QNEC Numerical Studies）</news:title>
   <news:publication_date>2026-06-12T04:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699739</loc>
  <lastmod>2026-06-12T04:32:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マンモグラフィにおける微小石灰化のセグメンテーションのための畳み込みニューラルネットワーク（Convolutional Neural Networks for the segmentation of microcalcification in Mammography Imaging）</news:title>
   <news:publication_date>2026-06-12T04:32:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699737</loc>
  <lastmod>2026-06-12T04:32:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互作用ネットワークで模倣する複雑な転位ダイナミクス（Mimicking complex dislocation dynamics by Interaction Networks）</news:title>
   <news:publication_date>2026-06-12T04:32:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699735</loc>
  <lastmod>2026-06-12T04:31:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタイルを持つ画像説明を教師なしで生成する仕組み（Unsupervised Stylish Image Description Generation via Domain Layer Norm）</news:title>
   <news:publication_date>2026-06-12T04:31:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699733</loc>
  <lastmod>2026-06-12T04:31:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一機械スケジューリングにおける時間依存処理時間と学習効果を同時扱いする新しい正確アルゴリズム（A new exact algorithm for solving single machine scheduling problems with learning effects and deteriorating jobs）</news:title>
   <news:publication_date>2026-06-12T04:31:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699731</loc>
  <lastmod>2026-06-12T03:40:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期占有グリッド予測と再帰型ニューラルネットワーク（Long-Term Occupancy Grid Prediction Using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-12T03:40:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699729</loc>
  <lastmod>2026-06-12T03:40:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U-Net学習における正規化が2D生体医用セグメンテーションにもたらす変化（Normalization in Training U-Net for 2D Biomedical Semantic Segmentation）</news:title>
   <news:publication_date>2026-06-12T03:40:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699727</loc>
  <lastmod>2026-06-12T03:39:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られた投影データでのCT再構成に対する確率的アプローチ（Probabilistic approach to limited-data computed tomography reconstruction）</news:title>
   <news:publication_date>2026-06-12T03:39:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699725</loc>
  <lastmod>2026-06-12T03:39:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模マルチエージェントの因子化Q学習（Factorized Q-Learning for Large-Scale Multi-Agent Systems）</news:title>
   <news:publication_date>2026-06-12T03:39:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699723</loc>
  <lastmod>2026-06-12T03:38:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元スカラー関数の可視化と主成分パラメータ化（Visualization of High-dimensional Scalar Functions using Principal Parameterizations）</news:title>
   <news:publication_date>2026-06-12T03:38:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699721</loc>
  <lastmod>2026-06-12T03:38:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在特徴モデルの非同定性を解く（Solving Non-identiﬁable Latent Feature Models）</news:title>
   <news:publication_date>2026-06-12T03:38:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699719</loc>
  <lastmod>2026-06-12T03:38:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動詞は問われているか？深層学習QAにおける動詞の重要性の再評価（Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System）</news:title>
   <news:publication_date>2026-06-12T03:38:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699717</loc>
  <lastmod>2026-06-12T02:47:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化・非構造化外れ値の識別によるパラメータフリーなRobust PCA（Structured and Unstructured Outlier Identification for Robust PCA: A Non iterative, Parameter free Algorithm）</news:title>
   <news:publication_date>2026-06-12T02:47:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699715</loc>
  <lastmod>2026-06-12T02:47:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノード単位で感度を変える非対称ネットワーク（Deep Asymmetric Networks with a Set of Node-wise Variant Activation Functions）</news:title>
   <news:publication_date>2026-06-12T02:47:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699713</loc>
  <lastmod>2026-06-12T02:46:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TSARDI: トランジット光度曲線の残差ノイズを自動検出するアルゴリズム（TSARDI: a Machine Learning data rejection algorithm for transiting exoplanet light curves）</news:title>
   <news:publication_date>2026-06-12T02:46:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699711</loc>
  <lastmod>2026-06-12T02:46:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的な「もしも」質問に答える仕組み（Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions）</news:title>
   <news:publication_date>2026-06-12T02:46:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699709</loc>
  <lastmod>2026-06-12T02:45:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Visual QAにおける細部の罠（The Visual QA Devil in the Details: The Impact of Early Fusion and Batch Norm on CLEVR）</news:title>
   <news:publication_date>2026-06-12T02:45:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699707</loc>
  <lastmod>2026-06-12T02:45:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Bio-LSTM：歩行者の3D姿勢と歩容を予測する生体力学に基づくリカレントニューラルネットワーク（Bio-LSTM: A Biomechanically Inspired Recurrent Neural Network for 3D Pedestrian Pose and Gait Prediction）</news:title>
   <news:publication_date>2026-06-12T02:45:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699705</loc>
  <lastmod>2026-06-12T02:45:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AFM画像の解像度を深層学習で高める方法（General Resolution Enhancement Method in Atomic Force Microscopy (AFM) Using Deep Learning）</news:title>
   <news:publication_date>2026-06-12T02:45:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699703</loc>
  <lastmod>2026-06-12T01:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リマインドによる長期時系列のクレジット配分を実現する手法（Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding）</news:title>
   <news:publication_date>2026-06-12T01:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699701</loc>
  <lastmod>2026-06-12T01:54:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話文脈と潜在トピックの共同モデル（A Joint Model of Conversational Discourse and Latent Topics on Microblogs）</news:title>
   <news:publication_date>2026-06-12T01:54:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/699699</loc>
  <lastmod>2026-06-12T01:53:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロモルフィック・スパイキングニューラルネットワークによる時間学習（Tutorial: Neuromorphic spiking neural networks for temporal learning）</news:title>
   <news:publication_date>2026-06-12T01:53:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699697</loc>
  <lastmod>2026-06-12T01:52:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バンド線形システムのためのCNNベース信号検出（CNN-Based Signal Detection for Banded Linear Systems）</news:title>
   <news:publication_date>2026-06-12T01:52:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699695</loc>
  <lastmod>2026-06-12T01:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スクリプト学習を隠れマルコフモデルとして捉える（Learning Scripts as Hidden Markov Models）</news:title>
   <news:publication_date>2026-06-12T01:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699693</loc>
  <lastmod>2026-06-12T01:52:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声認識に対する敵対的攻撃検出における音声前処理とアンサンブルの有効性（Isolated and Ensemble Audio Preprocessing Methods for Detecting Adversarial Examples against Automatic Speech Recognition）</news:title>
   <news:publication_date>2026-06-12T01:52:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699691</loc>
  <lastmod>2026-06-12T01:52:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスセクショナル株式リターン予測のための視覚的注意モデルとエンドツーエンドマルチモーダル市場表現学習 (Visual Attention Model for Cross-sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning)</news:title>
   <news:publication_date>2026-06-12T01:52:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699689</loc>
  <lastmod>2026-06-12T01:00:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー興味の時間的進化を捉えるDIEN（Deep Interest Evolution Network for Click-Through Rate Prediction）</news:title>
   <news:publication_date>2026-06-12T01:00:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699687</loc>
  <lastmod>2026-06-12T01:00:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データでロボットの視覚を偏りなく強化する方法（Unbiasing Semantic Segmentation For Robot Perception using Synthetic Data）</news:title>
   <news:publication_date>2026-06-12T01:00:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699685</loc>
  <lastmod>2026-06-12T00:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間空間マッピングによる行動認識（Temporal-Spatial Mapping for Action Recognition）</news:title>
   <news:publication_date>2026-06-12T00:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699683</loc>
  <lastmod>2026-06-12T00:59:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボリックデータ解析の新しい枠組み（New models for symbolic data analysis）</news:title>
   <news:publication_date>2026-06-12T00:59:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699681</loc>
  <lastmod>2026-06-12T00:59:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈依存拡散ネットワークによる視覚関係検出（Context-Dependent Diffusion Network for Visual Relationship Detection）</news:title>
   <news:publication_date>2026-06-12T00:59:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699679</loc>
  <lastmod>2026-06-12T00:59:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間俳優映像のニューラルレンダリングと再演（Neural Rendering and Reenactment of Human Actor Videos）</news:title>
   <news:publication_date>2026-06-12T00:59:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699677</loc>
  <lastmod>2026-06-12T00:58:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマノイドロボットでの深層学習向け計算プラットフォーム比較 (Comparing Computing Platforms for Deep Learning on a Humanoid Robot)</news:title>
   <news:publication_date>2026-06-12T00:58:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699675</loc>
  <lastmod>2026-06-12T00:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸正則化サポートベクターマシンに対する効率的なADMMベースのアルゴリズム（An Efficient ADMM-Based Algorithm to Nonconvex Penalized Support Vector Machines）</news:title>
   <news:publication_date>2026-06-12T00:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699673</loc>
  <lastmod>2026-06-12T00:07:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク行列復元における構造の有効かつ効率的な活用（Exploiting the structure effectively and efficiently in low rank matrix recovery）</news:title>
   <news:publication_date>2026-06-12T00:07:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699671</loc>
  <lastmod>2026-06-12T00:06:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波で嗜好を読み取る――CNNによるマルチメディア嗜好評価の進展（Evaluation of preference of multimedia content using deep neural networks for electroencephalography）</news:title>
   <news:publication_date>2026-06-12T00:06:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699669</loc>
  <lastmod>2026-06-12T00:06:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースの効率的グラフ類似度計算（Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching）</news:title>
   <news:publication_date>2026-06-12T00:06:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699667</loc>
  <lastmod>2026-06-12T00:06:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込み空間の教師なしクロスリンガルトランスファー（Unsupervised Cross-lingual Transfer of Word Embedding Spaces）</news:title>
   <news:publication_date>2026-06-12T00:06:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699665</loc>
  <lastmod>2026-06-12T00:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ManifoldNet——多様体値データのための深層ネットワークフレームワーク（ManifoldNet: A Deep Network Framework for Manifold-valued Data）</news:title>
   <news:publication_date>2026-06-12T00:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699663</loc>
  <lastmod>2026-06-12T00:05:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ClusterGANによる潜在空間クラスタリング（ClusterGAN: Latent Space Clustering in Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-12T00:05:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699661</loc>
  <lastmod>2026-06-11T23:14:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河の固有配向が波長で変わるという発見（The dependence of intrinsic alignment of galaxies on wavelength using KiDS and GAMA）</news:title>
   <news:publication_date>2026-06-11T23:14:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699659</loc>
  <lastmod>2026-06-11T23:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全なインデックス符号化の容量領域について（On the Capacity Region for Secure Index Coding）</news:title>
   <news:publication_date>2026-06-11T23:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699657</loc>
  <lastmod>2026-06-11T23:13:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書のみで学ぶ固有表現タグ付け（Learning Named Entity Tagger using Domain-Specific Dictionary）</news:title>
   <news:publication_date>2026-06-11T23:13:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699655</loc>
  <lastmod>2026-06-11T23:12:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリックベイズ群因子解析のための効率的な崩壊変分推論（Collapsed Variational Inference for Nonparametric Bayesian Group Factor Analysis）</news:title>
   <news:publication_date>2026-06-11T23:12:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699653</loc>
  <lastmod>2026-06-11T23:12:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像公平性を組み込んだ多様性再ランキング（Using Image Fairness Representations in Diversity-Based Re-ranking for Recommendations）</news:title>
   <news:publication_date>2026-06-11T23:12:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699651</loc>
  <lastmod>2026-06-11T23:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PCGMLの根本的緊張に対処する識別学習（Addressing the Fundamental Tension of PCGML with Discriminative Learning）</news:title>
   <news:publication_date>2026-06-11T23:12:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699649</loc>
  <lastmod>2026-06-11T23:11:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GEFCom2017の確率的負荷予測における分位点回帰（Quantile Regression for Qualifying Match of GEFCom2017 Probabilistic Load Forecasting）</news:title>
   <news:publication_date>2026-06-11T23:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699647</loc>
  <lastmod>2026-06-11T22:20:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層時系列辞書学習によるエネルギー分解（Energy Disaggregation via Deep Temporal Dictionary Learning）</news:title>
   <news:publication_date>2026-06-11T22:20:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699645</loc>
  <lastmod>2026-06-11T22:11:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向け深層学習（Deep Learning Towards Mobile Applications）</news:title>
   <news:publication_date>2026-06-11T22:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699643</loc>
  <lastmod>2026-06-11T22:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ケースベース推論をベイズ的に組み立てる手法の実務的解説（Bayesian Patchworks: An Approach to Case-Based Reasoning）</news:title>
   <news:publication_date>2026-06-11T22:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699641</loc>
  <lastmod>2026-06-11T22:11:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Policy Embeddingによる転移強化学習の要点（Variational Policy Embedding for Transfer Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-11T22:11:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699639</loc>
  <lastmod>2026-06-11T21:18:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PRIMAL: 分散学習による実用的なマルチエージェント経路探索（PRIMAL: Pathfinding via Reinforcement and Imitation）</news:title>
   <news:publication_date>2026-06-11T21:18:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699637</loc>
  <lastmod>2026-06-11T21:18:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュース記事の政治的イデオロギー検出の多視点モデル（Multi-view Models for Political Ideology Detection of News Articles）</news:title>
   <news:publication_date>2026-06-11T21:18:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699635</loc>
  <lastmod>2026-06-11T21:17:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師データ不要で「形式化」を制御する文章変換（Unsupervised Controllable Text Formalization）</news:title>
   <news:publication_date>2026-06-11T21:17:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699633</loc>
  <lastmod>2026-06-11T21:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SpRRAMによる事前定義スパースメムリスタ回路で実現する低電力ニューラル推論（SpRRAM: A Predefined Sparsity Based Memristive Neuromorphic Circuit for Low Power Application）</news:title>
   <news:publication_date>2026-06-11T21:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699631</loc>
  <lastmod>2026-06-11T20:25:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理情報支援型クリギング（Physics-Information-Aided Kriging: Constructing Covariance Functions using Stochastic Simulation Models）</news:title>
   <news:publication_date>2026-06-11T20:25:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699629</loc>
  <lastmod>2026-06-11T20:25:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データベース運用の産業的手法と最適化アプローチ（A collection of database industrial techniques and optimization approaches of database operations）</news:title>
   <news:publication_date>2026-06-11T20:25:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699627</loc>
  <lastmod>2026-06-11T20:24:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エキスパート強化型アクタークリティックの実用的インパクト（Expert-augmented actor-critic for ViZDoom and Montezuma’s Revenge）</news:title>
   <news:publication_date>2026-06-11T20:24:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699625</loc>
  <lastmod>2026-06-11T20:23:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆整合性を持つ深層ネットワークによる教師なし変形画像レジストレーション（Inverse-Consistent Deep Networks for Unsupervised Deformable Image Registration）</news:title>
   <news:publication_date>2026-06-11T20:23:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699623</loc>
  <lastmod>2026-06-11T20:23:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠落する経路を補う：語彙意味関係検出のための単語対と依存パスの共起モデル化（Filling Missing Paths: Modeling Co-occurrences of Word Pairs and Dependency Paths for Recognizing Lexical Semantic Relations）</news:title>
   <news:publication_date>2026-06-11T20:23:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699621</loc>
  <lastmod>2026-06-11T20:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>裁判記録における文間関係の特定（Identifying Relationships Among Sentences in Court Case Transcripts using Discourse Relations）</news:title>
   <news:publication_date>2026-06-11T20:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699619</loc>
  <lastmod>2026-06-11T20:23:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルクラウドにおけるプライベート深層学習の性能改善（Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud）</news:title>
   <news:publication_date>2026-06-11T20:23:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699617</loc>
  <lastmod>2026-06-11T19:32:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>想像とヒューリスティックを結合して一般化可能な戦略を学ぶ（Combining imagination and heuristics to learn strategies that generalize）</news:title>
   <news:publication_date>2026-06-11T19:32:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699615</loc>
  <lastmod>2026-06-11T19:31:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見る・尋ねる・推測するを共同で学ぶ研究の本質（Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat）</news:title>
   <news:publication_date>2026-06-11T19:31:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699613</loc>
  <lastmod>2026-06-11T19:31:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タッチ操作で個人認証は可能か（Does Your Phone Know Your Touch?）</news:title>
   <news:publication_date>2026-06-11T19:31:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699611</loc>
  <lastmod>2026-06-11T19:30:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平な機械学習を道徳的に解釈する枠組み（A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity）</news:title>
   <news:publication_date>2026-06-11T19:30:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699609</loc>
  <lastmod>2026-06-11T19:30:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波MIMO-OFDMの動的サブアレイに対する機械学習ベースのハイブリッドプレコーディング（Machine Learning Based Hybrid Precoding for MmWave MIMO-OFDM with Dynamic Subarray）</news:title>
   <news:publication_date>2026-06-11T19:30:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699607</loc>
  <lastmod>2026-06-11T19:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心音の分節と分類におけるマルコフ・スイッチングモデルの応用（A Markov-Switching Model Approach to Heart Sound Segmentation and Classification）</news:title>
   <news:publication_date>2026-06-11T19:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699605</loc>
  <lastmod>2026-06-11T19:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPASS: 火星探査ローバー向け能動的科学探索システム（SPASS: Scientific Prominence Active Search System with Deep Image Captioning Network）</news:title>
   <news:publication_date>2026-06-11T19:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699603</loc>
  <lastmod>2026-06-11T18:38:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WUDSによる高赤方偏移銀河の近赤外サーベイが示す要点（The WIRCam Ultra Deep Survey (WUDS): survey overview and UV luminosity functions at z∼5–6）</news:title>
   <news:publication_date>2026-06-11T18:38:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699601</loc>
  <lastmod>2026-06-11T18:37:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的バイナリニューラルネットワークの実用性と経営判断への示唆（Probabilistic Binary Neural Networks）</news:title>
   <news:publication_date>2026-06-11T18:37:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699599</loc>
  <lastmod>2026-06-11T18:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Torchbearer：PyTorch向けモデルフィッティングライブラリの設計と実装（Torchbearer: A Model Fitting Library for PyTorch）</news:title>
   <news:publication_date>2026-06-11T18:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699597</loc>
  <lastmod>2026-06-11T18:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙に広がる拡散ラジオ源の深層学習による検出（Deep Learning Based Detection of Cosmological Diffuse Radio Sources）</news:title>
   <news:publication_date>2026-06-11T18:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699595</loc>
  <lastmod>2026-06-11T18:36:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化境界を機械学習で改善する：決定図と深層強化学習の出会い（Improving Optimization Bounds Using Machine Learning: Decision Diagrams Meet Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-11T18:36:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699593</loc>
  <lastmod>2026-06-11T18:36:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ズーム学習：サリエンシーに基づくサンプリング層（Learning to Zoom: a Saliency-Based Sampling Layer for Neural Networks）</news:title>
   <news:publication_date>2026-06-11T18:36:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699591</loc>
  <lastmod>2026-06-11T18:35:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>xSenseによる説明可能な単語意味表現の学習（xSense: Learning Sense-Separated Sparse Representations and Textual Definitions for Explainable Word Sense Networks）</news:title>
   <news:publication_date>2026-06-11T18:35:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699589</loc>
  <lastmod>2026-06-11T17:44:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ決定過程の到達確率検証におけるMCTS応用（Monte Carlo Tree Search for Verifying Reachability in Markov Decision Processes）</news:title>
   <news:publication_date>2026-06-11T17:44:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699587</loc>
  <lastmod>2026-06-11T17:44:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界カラー画像のノイズ除去に関する簡潔なレビュー（A Brief Review of Real-World Color Image Denoising）</news:title>
   <news:publication_date>2026-06-11T17:44:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699585</loc>
  <lastmod>2026-06-11T17:43:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>把持成功の予測と品質指標（Grasp success prediction with quality metrics）</news:title>
   <news:publication_date>2026-06-11T17:43:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699583</loc>
  <lastmod>2026-06-11T17:42:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み伝送によるプライバシー保護型深層学習（Privacy-Preserving Deep Learning via Weight Transmission）</news:title>
   <news:publication_date>2026-06-11T17:42:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699581</loc>
  <lastmod>2026-06-11T17:42:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的手法による深層畳み込みニューラルネットワークのトポロジ探索（Finding Better Topologies for Deep Convolutional Neural Networks by Evolution）</news:title>
   <news:publication_date>2026-06-11T17:42:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699579</loc>
  <lastmod>2026-06-11T17:42:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再生成による分類の原理と実践（Classification by Re-generation—Towards Classification Based on Variational Inference）</news:title>
   <news:publication_date>2026-06-11T17:42:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699577</loc>
  <lastmod>2026-06-11T17:42:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相を用いた動き表現による行動認識の再考（Using phase instead of optical flow for action recognition）</news:title>
   <news:publication_date>2026-06-11T17:42:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699575</loc>
  <lastmod>2026-06-11T16:50:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多文脈深層ネットワークによる前眼部OCTを用いた閉塞隅角緑内障スクリーニング（Multi-Context Deep Network for Angle-Closure Glaucoma Screening in Anterior Segment OCT）</news:title>
   <news:publication_date>2026-06-11T16:50:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699573</loc>
  <lastmod>2026-06-11T16:50:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光で駆動する軟らかいマイクロロボットの歩行学習（Gait learning for soft microrobots controlled by light fields）</news:title>
   <news:publication_date>2026-06-11T16:50:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699571</loc>
  <lastmod>2026-06-11T16:50:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトなセマンティック状態を用いた深層強化学習による自律走行の適応的行動生成 (Adaptive Behavior Generation for Autonomous Driving using Deep Reinforcement Learning with Compact Semantic States)</news:title>
   <news:publication_date>2026-06-11T16:50:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699569</loc>
  <lastmod>2026-06-11T16:49:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列知識グラフ補完の系列エンコーダ学習（Learning Sequence Encoders for Temporal Knowledge Graph Completion）</news:title>
   <news:publication_date>2026-06-11T16:49:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699567</loc>
  <lastmod>2026-06-11T16:49:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択バイアスを考慮したPositive-Unlabeled学習の拡張（Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled Data）</news:title>
   <news:publication_date>2026-06-11T16:49:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699565</loc>
  <lastmod>2026-06-11T16:49:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話文脈とドメイン知識を取り込む応答選択の改良（Improving Response Selection in Multi-turn Dialogue Systems by Incorporating Domain Knowledge）</news:title>
   <news:publication_date>2026-06-11T16:49:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699563</loc>
  <lastmod>2026-06-11T16:48:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語からの構造化クエリ生成を間接監督で学ぶ（Learning to Generate Structured Queries from Natural Language with Indirect Supervision）</news:title>
   <news:publication_date>2026-06-11T16:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699561</loc>
  <lastmod>2026-06-11T15:57:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインディスプレイ広告におけるインプレッション配分のマルチエージェント強化学習法（A Multi-Agent Reinforcement Learning Method for Impression Allocation in Online Display Advertising）</news:title>
   <news:publication_date>2026-06-11T15:57:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699559</loc>
  <lastmod>2026-06-11T15:49:48Z</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時代の物体検出研究の到達点（Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-11T15:49:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699557</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-11T15:49:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-11T14:45:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-11T14:44:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ベースラインを用いたモンテカルロ反事実後悔最小化における分散削減（Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games using Baselines）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>多語表現（MWE）識別の汎化力を高めたニューラル手法（Neural Multiword Expression Tagging with High Generalisation）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>距離保存型グラフ・ラプラシアンの次元削減とクラスター解析（Distance Preserving Model Order Reduction of Graph-Laplacians and Cluster Analysis）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-11T11:55:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-06-11T11:54:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>道路のひび割れとポットホール検出の自律手法（Crack-pot: Autonomous Road Crack and Pothole Detection）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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  <lastmod>2026-06-11T11:01:25Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弾力的需要を活用した需要予測の精度改善（Leveraging Elastic Demand for Forecasting）</news:title>
   <news:publication_date>2026-06-11T11:01:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699485</loc>
  <lastmod>2026-06-11T11:00:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検証を早くするための訓練法（TRAINING FOR FASTER ADVERSARIAL ROBUSTNESS VERIFICATION VIA INDUCING RELU STABILITY）</news:title>
   <news:publication_date>2026-06-11T11:00:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699483</loc>
  <lastmod>2026-06-11T11:00:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置情報を用いたミリ波ビーム訓練のオンライン学習（Online Learning for Position-Aided Millimeter Wave Beam Training）</news:title>
   <news:publication_date>2026-06-11T11:00:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699481</loc>
  <lastmod>2026-06-11T11:00:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習の誤差指標の体系化と実務的意義（Performance Metrics (Error Measures) in Machine Learning Regression, Forecasting and Prognostics: Properties and Typology）</news:title>
   <news:publication_date>2026-06-11T11:00:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699479</loc>
  <lastmod>2026-06-11T11:00:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話生成モデルは文の構成と談話構造を学べるか（Can Neural Generators for Dialogue Learn Sentence Planning and Discourse Structuring?）</news:title>
   <news:publication_date>2026-06-11T11:00:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699477</loc>
  <lastmod>2026-06-11T10:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔形状を考慮した顔画像の補完と編集（Geometry-Aware Face Completion and Editing）</news:title>
   <news:publication_date>2026-06-11T10:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699475</loc>
  <lastmod>2026-06-11T10:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像から透水性を読む：畳み込みニューラルネットワークによる高速予測（Seeing Permeability From Images: Fast Prediction with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-11T10:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699473</loc>
  <lastmod>2026-06-11T10:08:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LS-Netが切り拓く非線形最小二乗の学習的最適化（LS-Net: Learning to Solve Nonlinear Least Squares for Monocular Stereo）</news:title>
   <news:publication_date>2026-06-11T10:08:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699471</loc>
  <lastmod>2026-06-11T10:07:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Approximation Error in Non-negative Matrix Factorization（Variational Approximation Error in Non-negative Matrix Factorization）</news:title>
   <news:publication_date>2026-06-11T10:07:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699469</loc>
  <lastmod>2026-06-11T10:07:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セルラー環境下のUAV軌道設計に強化学習を使う意義（Reinforcement Learning for Decentralized Trajectory Design in Cellular UAV Networks with Sense-and-Send Protocol）</news:title>
   <news:publication_date>2026-06-11T10:07:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699467</loc>
  <lastmod>2026-06-11T10:06:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セル・オートマトンを畳み込みニューラルネットワークとして表現する（Cellular automata as convolutional neural networks）</news:title>
   <news:publication_date>2026-06-11T10:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699465</loc>
  <lastmod>2026-06-11T10:06:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠隔医療向け自動斜視検出（Automated Strabismus Detection for Telemedicine Applications）</news:title>
   <news:publication_date>2026-06-11T10:06:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699463</loc>
  <lastmod>2026-06-11T09:14:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮想から現実へ──確率的相互状況認識と予測（Generic Probabilistic Interactive Situation Recognition and Prediction: From Virtual to Real）</news:title>
   <news:publication_date>2026-06-11T09:14:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699461</loc>
  <lastmod>2026-06-11T09:14:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的逆強化学習による相互運転行動の確率的予測 (Probabilistic Prediction of Interactive Driving Behavior via Hierarchical Inverse Reinforcement Learning)</news:title>
   <news:publication_date>2026-06-11T09:14:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699459</loc>
  <lastmod>2026-06-11T09:14:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプル効率と報酬バイアスを同時に解決する方法（Discriminator-Actor-Critic）</news:title>
   <news:publication_date>2026-06-11T09:14:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699457</loc>
  <lastmod>2026-06-11T09:12:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問応答データセットを推論データに変換する手法（Transforming Question Answering Datasets Into Natural Language Inference Datasets）</news:title>
   <news:publication_date>2026-06-11T09:12:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699455</loc>
  <lastmod>2026-06-11T09:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルツハイマー病の二値分類におけるsMRIと深層学習（Binary Classification of Alzheimer’s Disease using sMRI Imaging modality and Deep Learning）</news:title>
   <news:publication_date>2026-06-11T09:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699453</loc>
  <lastmod>2026-06-11T09:12:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ効率の高いブラックボックス攻撃：入力フリーの視点（Towards Query Efficient Black-box Attacks: An Input-free Perspective）</news:title>
   <news:publication_date>2026-06-11T09:12:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699451</loc>
  <lastmod>2026-06-11T09:12:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>食品画像の状態識別を小データで可能にした転移学習の実践（Fine-Tuning VGG Neural Network For Fine-grained State Recognition of Food Images）</news:title>
   <news:publication_date>2026-06-11T09:12:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699449</loc>
  <lastmod>2026-06-11T08:20:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震位相の結びつけを深層学習で行うPhaseLink（PhaseLink: A Deep Learning Approach to Seismic Phase Association）</news:title>
   <news:publication_date>2026-06-11T08:20:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699447</loc>
  <lastmod>2026-06-11T08:19:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コスト感度を取り入れた能動学習による頭部CT出血検出（Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection）</news:title>
   <news:publication_date>2026-06-11T08:19:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699445</loc>
  <lastmod>2026-06-11T08:19:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム偽装顔認識のための教師あり学習手法（A Supervised Learning Methodology for Real-Time Disguised Face Recognition in the Wild）</news:title>
   <news:publication_date>2026-06-11T08:19:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699443</loc>
  <lastmod>2026-06-11T08:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トラッケルト協調による教師なし人物再識別（Unsupervised Person Re-identification by Deep Learning Tracklet Association）</news:title>
   <news:publication_date>2026-06-11T08:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699441</loc>
  <lastmod>2026-06-11T08:18:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>攻撃が“転移”する理由 ― 侵入と毒殺攻撃の伝播性の解明（Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks）</news:title>
   <news:publication_date>2026-06-11T08:18:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699439</loc>
  <lastmod>2026-06-11T08:18:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的逐次学習者の機械教授（Machine Teaching of Active Sequential Learners）</news:title>
   <news:publication_date>2026-06-11T08:18:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699437</loc>
  <lastmod>2026-06-11T08:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン適応法、普遍性と加速（Online Adaptive Methods, Universality and Acceleration）</news:title>
   <news:publication_date>2026-06-11T08:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699435</loc>
  <lastmod>2026-06-11T07:26:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的に相互作用するElastic Netによる最も情報量の多い特徴抽出（Identifying The Most Informative Features Using A Structurally Interacting Elastic Net）</news:title>
   <news:publication_date>2026-06-11T07:26:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699433</loc>
  <lastmod>2026-06-11T07:26:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PMUデータを用いたリアルタイム過渡安定性評価へのEOS-ELMとBinary Jaya特徴選択の適用（Application of EOS-ELM with Binary Jaya-Based Feature Selection to Real-Time Transient Stability Assessment Using PMU Data）</news:title>
   <news:publication_date>2026-06-11T07:26:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699431</loc>
  <lastmod>2026-06-11T07:25:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ELMと改良アントマイナーによる過渡安定性評価のルール抽出（Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment）</news:title>
   <news:publication_date>2026-06-11T07:25:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699429</loc>
  <lastmod>2026-06-11T07:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路品質情報を組み込む動的経路計画（iDriveSense: Dynamic Route Planning Involving Roads Quality Information）</news:title>
   <news:publication_date>2026-06-11T07:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699427</loc>
  <lastmod>2026-06-11T07:24:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍法で解釈するニューラルネットワーク（Interpreting Neural Networks With Nearest Neighbors）</news:title>
   <news:publication_date>2026-06-11T07:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699425</loc>
  <lastmod>2026-06-11T07:24:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計測率可変型ニューラルネットワークによる空間マルチプレクサ（Rate-Adaptive Neural Networks for Spatial Multiplexers）</news:title>
   <news:publication_date>2026-06-11T07:24:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699423</loc>
  <lastmod>2026-06-11T07:23:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インターネット動画から学ぶスポーツ用カメラ選択（Learning Sports Camera Selection from Internet Videos）</news:title>
   <news:publication_date>2026-06-11T07:23:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699421</loc>
  <lastmod>2026-06-11T06:32:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチGPU環境におけるモデル並列化による効率的かつ頑健なDNN訓練（Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform）</news:title>
   <news:publication_date>2026-06-11T06:32:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699419</loc>
  <lastmod>2026-06-11T06:32:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タイプIIケフェイドにおける多様な力学現象（Diversity of dynamical phenomena in type II Cepheids of the OGLE collection）</news:title>
   <news:publication_date>2026-06-11T06:32:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699417</loc>
  <lastmod>2026-06-11T06:31:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル誘導制約論理プログラミングによるプログラム合成（Neural Guided Constraint Logic Programming for Program Synthesis）</news:title>
   <news:publication_date>2026-06-11T06:31:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699415</loc>
  <lastmod>2026-06-11T06:31:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインニュースにおける利用者反応のマルチラベル分類（Multi-label Classification of User Reactions in Online News）</news:title>
   <news:publication_date>2026-06-11T06:31:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699413</loc>
  <lastmod>2026-06-11T06:31:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリック変分推論とグラフ畳み込みによるガウス過程（Non-Parametric Variational Inference with Graph Convolutional Networks for Gaussian Processes）</news:title>
   <news:publication_date>2026-06-11T06:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699411</loc>
  <lastmod>2026-06-11T06:31:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュース記事から都市間の意味的関連性を抽出する方法（Extracting and Analyzing Semantic Relatedness between Cities Using News Articles）</news:title>
   <news:publication_date>2026-06-11T06:31:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699409</loc>
  <lastmod>2026-06-11T06:31:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Context-Free Transductions with Neural Stacks（Context-Free Transductions with Neural Stacks）</news:title>
   <news:publication_date>2026-06-11T06:31:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699407</loc>
  <lastmod>2026-06-11T05:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビルクホフダイヤモンドの二重役割（The Birkhoff Diamond as Double Agent）</news:title>
   <news:publication_date>2026-06-11T05:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699405</loc>
  <lastmod>2026-06-11T05:39:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像に映る煙を深層顕著性で検出する（Video Smoke Detection Based on Deep Saliency Network）</news:title>
   <news:publication_date>2026-06-11T05:39:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699403</loc>
  <lastmod>2026-06-11T05:39:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル再利用による概念ドリフトの扱い（Handling Concept Drift via Model Reuse）</news:title>
   <news:publication_date>2026-06-11T05:39:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699401</loc>
  <lastmod>2026-06-11T05:38:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界指標を用いた注目型意味役割付与（Attentive Semantic Role Labeling with Boundary Indicator）</news:title>
   <news:publication_date>2026-06-11T05:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699399</loc>
  <lastmod>2026-06-11T05:38:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト理解のための明示的文脈セマンティクス（Explicit Contextual Semantics for Text Comprehension）</news:title>
   <news:publication_date>2026-06-11T05:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699397</loc>
  <lastmod>2026-06-11T05:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAVによる地形モニタリング向け情報指向経路計画フレームワーク（An informative path planning framework for UAV-based terrain monitoring）</news:title>
   <news:publication_date>2026-06-11T05:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699395</loc>
  <lastmod>2026-06-11T05:37:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク埋め込みに対する高速勾配攻撃（Fast Gradient Attack on Network Embedding）</news:title>
   <news:publication_date>2026-06-11T05:37:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699393</loc>
  <lastmod>2026-06-11T04:46:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造を保つ変換による多様で転送可能な敵対的例の生成（Structure-Preserving Transformation: Generating Diverse and Transferable Adversarial Examples）</news:title>
   <news:publication_date>2026-06-11T04:46:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699391</loc>
  <lastmod>2026-06-11T04:46:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像鑑識のための敵対的学習とAtrous畳み込みを用いた深度マッチング（Adversarial Learning for Image Forensics Deep Matching with Atrous Convolution）</news:title>
   <news:publication_date>2026-06-11T04:46:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699389</loc>
  <lastmod>2026-06-11T04:45:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンスベースの深層転移学習（Instance-based Deep Transfer Learning）</news:title>
   <news:publication_date>2026-06-11T04:45:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699387</loc>
  <lastmod>2026-06-11T04:44:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマン・イン・ザ・ループにおける“弱い制御”の提案（“Weak” Control for Human-in-the-loop Systems）</news:title>
   <news:publication_date>2026-06-11T04:44:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699385</loc>
  <lastmod>2026-06-11T04:44:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アキレス腱断裂のリハビリ予後を同時に補完と予測する確率的手法（Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation）</news:title>
   <news:publication_date>2026-06-11T04:44:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699383</loc>
  <lastmod>2026-06-11T04:44:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像で説明できる単語表現の探求（Exploration on Grounded Word Embedding: Matching Words and Images with Image-Enhanced Skip-Gram Model）</news:title>
   <news:publication_date>2026-06-11T04:44:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699381</loc>
  <lastmod>2026-06-11T04:43:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合統計推定法による相互情報量推定と情報流の解析（Hybrid Statistical Estimation of Mutual Information and its Application to Information Flow）</news:title>
   <news:publication_date>2026-06-11T04:43:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699379</loc>
  <lastmod>2026-06-11T03:52:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超高輝度超新星 SN 2015bn のX線非検出が示す「失われたエネルギー」問題（Where is the engine hiding its missing energy?）</news:title>
   <news:publication_date>2026-06-11T03:52:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699377</loc>
  <lastmod>2026-06-11T03:52:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響反響を取り除き音声認証を強化する二重ラベル深層LSTM（Dual-label Deep LSTM Dereverberation for Speaker Verification）</news:title>
   <news:publication_date>2026-06-11T03:52:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699375</loc>
  <lastmod>2026-06-11T03:51:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>千日間のSN 2015bnが示すマグネター駆動の兆候（One thousand days of SN 2015bn: HST imaging shows a light curve flattening consistent with magnetar predictions）</news:title>
   <news:publication_date>2026-06-11T03:51:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699373</loc>
  <lastmod>2026-06-11T03:50:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子ハイパーグラフ文法による分子最適化（Molecular Hypergraph Grammar with Its Application to Molecular Optimization）</news:title>
   <news:publication_date>2026-06-11T03:50:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699371</loc>
  <lastmod>2026-06-11T03:50:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネステッド・ダイコトミーの較正が大規模多クラスで果たす役割（On the Calibration of Nested Dichotomies for Large Multiclass Tasks）</news:title>
   <news:publication_date>2026-06-11T03:50:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699369</loc>
  <lastmod>2026-06-11T03:50:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの実世界点群生成（RealPoint3D: Point Cloud Generation from a Single Image with Complex Background）</news:title>
   <news:publication_date>2026-06-11T03:50:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699367</loc>
  <lastmod>2026-06-11T03:49:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RF駆動アンビエントバックキャッターの動的スペクトラム利用とオンライン強化学習（Optimal and Low-Complexity Dynamic Spectrum Access for RF-Powered Ambient Backscatter System with Online Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-11T03:49:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699365</loc>
  <lastmod>2026-06-11T02:58:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入れ子二分法アンサンブルの複数部分集合評価（Ensembles of Nested Dichotomies with Multiple Subset Evaluation）</news:title>
   <news:publication_date>2026-06-11T02:58:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699363</loc>
  <lastmod>2026-06-11T02:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習型画像圧縮における自己回帰と階層的事前分布の併用による飛躍的改善（Joint Autoregressive and Hierarchical Priors for Learned Image Compression）</news:title>
   <news:publication_date>2026-06-11T02:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699361</loc>
  <lastmod>2026-06-11T02:57:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可逆（Invertible）なデコーダを利用した教師なし文表現学習（Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning）</news:title>
   <news:publication_date>2026-06-11T02:57:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699359</loc>
  <lastmod>2026-06-11T02:57:03Z</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電子密度とエネルギーの高速予測（Deep Neural Network Computes Electron Densities and Energies of a Large Set of Organic Molecules Faster than Density Functional Theory）</news:title>
   <news:publication_date>2026-06-11T02:57:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699357</loc>
  <lastmod>2026-06-11T02:56:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習でNP完全問題を解く：決定版TSPのためのグラフニューラルネットワーク (Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP)</news:title>
   <news:publication_date>2026-06-11T02:56:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699355</loc>
  <lastmod>2026-06-11T02:56:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境での差分プライバシー付き置換なし確率的勾配降下法（Decentralized Differentially Private Without-Replacement Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-06-11T02:56:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699353</loc>
  <lastmod>2026-06-11T02:55:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Coupled IGMM-GANsによる深層多峰性異常検知（Coupled IGMM-GANs for deep multimodal anomaly detection in human mobility data）</news:title>
   <news:publication_date>2026-06-11T02:55:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699351</loc>
  <lastmod>2026-06-11T02:05:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DensSiamが変えたトラッキングの常識 — 密結合と自己注意で精度と速度を両立する （DensSiam: End-to-End Densely-Siamese Network with Self-Attention Model for Object Tracking）</news:title>
   <news:publication_date>2026-06-11T02:05:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699349</loc>
  <lastmod>2026-06-11T02:04:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模行動集合グラフ上のバンディット（BLAG: Bandit on Large Action Set Graph）</news:title>
   <news:publication_date>2026-06-11T02:04:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699347</loc>
  <lastmod>2026-06-11T02:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークにおける辺特徴の活用（Exploiting Edge Features in Graph Neural Networks）</news:title>
   <news:publication_date>2026-06-11T02:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699345</loc>
  <lastmod>2026-06-11T02:03:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的に発火するアームを伴う組合せ多腕バンディットに対するThompson Samplingの解析（Thompson Sampling for Combinatorial Multi-armed Bandit with Probabilistically Triggered Arms）</news:title>
   <news:publication_date>2026-06-11T02:03:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699343</loc>
  <lastmod>2026-06-11T02:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移住をサブモジュラー最適化として扱う（Migration as Submodular Optimization）</news:title>
   <news:publication_date>2026-06-11T02:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699341</loc>
  <lastmod>2026-06-11T02:03:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム学習者成績予測とドメイン適応（GritNet 2: Real-Time Student Performance Prediction with Domain Adaptation）</news:title>
   <news:publication_date>2026-06-11T02:03:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699339</loc>
  <lastmod>2026-06-11T02:02:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック一貫性を訓練目標に組み込む手法（Coherence-Aware Neural Topic Modeling）</news:title>
   <news:publication_date>2026-06-11T02:02:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699337</loc>
  <lastmod>2026-06-11T01:11:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ類似度評価を変える手法：Return Probabilityに基づくGraph Kernel（RetGK: Graph Kernels based on Return Probabilities of Random Walks）</news:title>
   <news:publication_date>2026-06-11T01:11:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699335</loc>
  <lastmod>2026-06-11T01:11:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的グラフ埋め込みでネットワークの時間変化をつかむ（dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning）</news:title>
   <news:publication_date>2026-06-11T01:11:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699333</loc>
  <lastmod>2026-06-11T01:11:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知資源の動的モデルが示すテスト中のパフォーマンス変化（Model of Cognitive Dynamics Predicts Performance on Standardized Tests）</news:title>
   <news:publication_date>2026-06-11T01:11:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699331</loc>
  <lastmod>2026-06-11T01:10:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし文章圧縮：ノイズ除去オートエンコーダによるアプローチ (Unsupervised Sentence Compression using Denoising Auto-Encoders)</news:title>
   <news:publication_date>2026-06-11T01:10:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699329</loc>
  <lastmod>2026-06-11T01:10:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照画像による検証を伴う分類（Are You Sure You Want To Do That? Classification with Verification）</news:title>
   <news:publication_date>2026-06-11T01:10:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699327</loc>
  <lastmod>2026-06-11T01:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習可能なデータベース向け自然言語インタフェース（A Transfer-Learnable Natural Language Interface for Databases）</news:title>
   <news:publication_date>2026-06-11T01:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699325</loc>
  <lastmod>2026-06-11T01:09:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様な質問のニューラル生成（Neural Generation of Diverse Questions using Answer Focus, Contextual and Linguistic Features）</news:title>
   <news:publication_date>2026-06-11T01:09:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699323</loc>
  <lastmod>2026-06-11T00:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Unityを用いた汎用的知能エージェントプラットフォーム（Unity: A General Platform for Intelligent Agents）</news:title>
   <news:publication_date>2026-06-11T00:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699321</loc>
  <lastmod>2026-06-11T00:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的に妥当なグラフの制約付き生成を実現する正則化VAE（Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders）</news:title>
   <news:publication_date>2026-06-11T00:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699319</loc>
  <lastmod>2026-06-11T00:18:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同次線形偏微分方程式のための量子アルゴリズム（Quantum algorithm for non-homogeneous linear partial differential equations）</news:title>
   <news:publication_date>2026-06-11T00:18:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699317</loc>
  <lastmod>2026-06-11T00:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データに対する変分オーバーサンプリング（VOS: a Method for Variational Oversampling of Imbalanced Data）</news:title>
   <news:publication_date>2026-06-11T00:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699315</loc>
  <lastmod>2026-06-11T00:17:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SECS: 環境に応じたクラススキューで効率化する深層ストリーム処理（SECS: Efficient Deep Stream Processing via Class Skew Dichotomy）</news:title>
   <news:publication_date>2026-06-11T00:17:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699313</loc>
  <lastmod>2026-06-11T00:17:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練セット中心点の原理的構成と確率的サンプリングによる最近傍分類精度の向上 (Improving the accuracy of nearest-neighbor classification using principled construction and stochastic sampling of training-set centroids)</news:title>
   <news:publication_date>2026-06-11T00:17:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699311</loc>
  <lastmod>2026-06-11T00:16:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間ボトルネックによる畳み込み高速化（Accelerating Deep Neural Networks with Spatial Bottleneck Modules）</news:title>
   <news:publication_date>2026-06-11T00:16:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699309</loc>
  <lastmod>2026-06-10T23:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表意文字のサブワードモデル（LOGOGRAPHIC SUBWORD MODEL FOR NEURAL MACHINE TRANSLATION）</news:title>
   <news:publication_date>2026-06-10T23:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699307</loc>
  <lastmod>2026-06-10T23:25:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>方策の不変量学習による汎化（Learning Invariances for Policy Generalization）</news:title>
   <news:publication_date>2026-06-10T23:25:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699305</loc>
  <lastmod>2026-06-10T23:24:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HyperGCN：ハイパーグラフ上でのGCN学習手法（HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs）</news:title>
   <news:publication_date>2026-06-10T23:24:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699303</loc>
  <lastmod>2026-06-10T23:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>360度映像のための自己教師あり空間音声生成（Self-Supervised Generation of Spatial Audio for 360◦Video）</news:title>
   <news:publication_date>2026-06-10T23:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699301</loc>
  <lastmod>2026-06-10T23:24:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SENetと半教師あり学習のアンサンブルによる皮膚病変分類（Skin lesion classification with ensemble of squeeze-and-excitation networks and semi-supervised learning）</news:title>
   <news:publication_date>2026-06-10T23:24:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699299</loc>
  <lastmod>2026-06-10T23:23:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NV中心を用いたnano-NMRと深層学習による雑音克服（NV center based nano-NMR enhanced by deep learning）</news:title>
   <news:publication_date>2026-06-10T23:23:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699297</loc>
  <lastmod>2026-06-10T23:23:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D形状分類器の深掘り（A Deeper Look at 3D Shape Classifiers）</news:title>
   <news:publication_date>2026-06-10T23:23:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699295</loc>
  <lastmod>2026-06-10T22:32:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層仮説検定による異種ネットワーク母集団の比較（Multi-level hypothesis testing for populations of heterogeneous networks）</news:title>
   <news:publication_date>2026-06-10T22:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699293</loc>
  <lastmod>2026-06-10T22:24:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トーリック多様体上の射影束コホモロジーを機械学習で解析する（Machine Learning Line Bundle Cohomologies of Hypersurfaces in Toric Varieties）</news:title>
   <news:publication_date>2026-06-10T22:24:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699291</loc>
  <lastmod>2026-06-10T22:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列平均化の誤差を再考する（Revisiting Inaccuracies of Time Series Averaging under Dynamic Time Warping）</news:title>
   <news:publication_date>2026-06-10T22:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699289</loc>
  <lastmod>2026-06-10T22:24:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の概念知識を模倣する疎（スパース）マルチモーダル埋め込み（Using sparse semantic embeddings learned from multimodal text and image data to model human conceptual knowledge）</news:title>
   <news:publication_date>2026-06-10T22:24:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699287</loc>
  <lastmod>2026-06-10T22:23:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推薦システムにおける行動条件付き系列モデリング（Action-conditional Sequence Modeling for Recommendation）</news:title>
   <news:publication_date>2026-06-10T22:23:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699285</loc>
  <lastmod>2026-06-10T22:23:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果的公平性モデルによるバイアスデータの学習（Fairness through Causal Awareness: Learning Causal Latent-Variable Models for Biased Data）</news:title>
   <news:publication_date>2026-06-10T22:23:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699283</loc>
  <lastmod>2026-06-10T22:22:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MixUpの外部マニフェールド局所線形正則化としての解釈 (MixUp as Locally Linear Out-Of-Manifold Regularization)</news:title>
   <news:publication_date>2026-06-10T22:22:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699281</loc>
  <lastmod>2026-06-10T21:31:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースカーネルPCAによる外れ値検知（Sparse Kernel PCA for Outlier Detection）</news:title>
   <news:publication_date>2026-06-10T21:31:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699279</loc>
  <lastmod>2026-06-10T21:30:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FI-GRL: 投影コスト保存による高速帰納的グラフ表現学習（FI-GRL: Fast Inductive Graph Representation Learning via Projection-Cost Preservation）</news:title>
   <news:publication_date>2026-06-10T21:30:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699277</loc>
  <lastmod>2026-06-10T21:30:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様体として読む都市データの解像度（Manifold Cities: Social variables of urban areas in the UK）</news:title>
   <news:publication_date>2026-06-10T21:30:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699275</loc>
  <lastmod>2026-06-10T21:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StackNetによる継続学習の設計（StackNet: Stacking feature maps for Continual learning）</news:title>
   <news:publication_date>2026-06-10T21:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699273</loc>
  <lastmod>2026-06-10T21:30:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BiasedWalkによるグラフ表現学習の新展開（BiasedWalk: Biased Sampling for Representation Learning on Graphs）</news:title>
   <news:publication_date>2026-06-10T21:30:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699271</loc>
  <lastmod>2026-06-10T21:29:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタモルフィック関係に基づく敵対的攻撃と微分可能ニューラルコンピュータ（Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer）</news:title>
   <news:publication_date>2026-06-10T21:29:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699269</loc>
  <lastmod>2026-06-10T21:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークによるテキスト分類とオープンドメイン質問応答への応用（Convolutional Neural Network: Text Classification Model for Open Domain Question Answering System）</news:title>
   <news:publication_date>2026-06-10T21:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699267</loc>
  <lastmod>2026-06-10T20:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳活動と一致する深層ビデオ表現の最適化 (Optimizing deep video representation to match brain activity)</news:title>
   <news:publication_date>2026-06-10T20:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699265</loc>
  <lastmod>2026-06-10T20:38:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号付きソーシャルネットワークにおけるノード分類と拡散界面法（Node Classification for Signed Social Networks Using Diffuse Interface Methods）</news:title>
   <news:publication_date>2026-06-10T20:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699263</loc>
  <lastmod>2026-06-10T20:37:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果推論の入門—データサイエンスにおける因果の道筋（A Primer on Causality in Data Science）</news:title>
   <news:publication_date>2026-06-10T20:37:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699261</loc>
  <lastmod>2026-06-10T20:37:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別時系列予測に挑むDeep Recurrent Survival Analysis（Deep Recurrent Survival Analysis）</news:title>
   <news:publication_date>2026-06-10T20:37:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699259</loc>
  <lastmod>2026-06-10T20:36:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的な敵対的入力の検出と人間可解釈な防御（Detecting Potential Local Adversarial Examples for Human-Interpretable Defense）</news:title>
   <news:publication_date>2026-06-10T20:36:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699257</loc>
  <lastmod>2026-06-10T20:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチネットワークトポロジーの深層特徴学習（Deep Feature Learning of Multi-Network Topology for Node Classification）</news:title>
   <news:publication_date>2026-06-10T20:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699255</loc>
  <lastmod>2026-06-10T20:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回答分離によるニューラル質問生成の改善（Improving Neural Question Generation using Answer Separation）</news:title>
   <news:publication_date>2026-06-10T20:36:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699253</loc>
  <lastmod>2026-06-10T19:45:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点を切り替えて学ぶ直観的物理予測（Neural Allocentric Intuitive Physics Prediction from Real Videos）</news:title>
   <news:publication_date>2026-06-10T19:45:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699251</loc>
  <lastmod>2026-06-10T19:44:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練されたフィードバックネットワークにおける大域的安定性の幾何学的解析（A geometrical analysis of global stability in trained feedback networks）</news:title>
   <news:publication_date>2026-06-10T19:44:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699249</loc>
  <lastmod>2026-06-10T19:44:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過去報酬統計を活用したオンポリシー学習の改善（Improving On-policy Learning with Statistical Reward Accumulation）</news:title>
   <news:publication_date>2026-06-10T19:44:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699247</loc>
  <lastmod>2026-06-10T19:43:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続稼働タスク向けにシミュレーション期間を可変化したモンテカルロ木探索（Monte Carlo Tree Search with Scalable Simulation Periods for Continuously Running Tasks）</news:title>
   <news:publication_date>2026-06-10T19:43:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699245</loc>
  <lastmod>2026-06-10T19:43:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列変量の歪んだ混合ビリニア因子解析（Mixtures of Skewed Matrix Variate Bilinear Factor Analyzers）</news:title>
   <news:publication_date>2026-06-10T19:43:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699243</loc>
  <lastmod>2026-06-10T19:42:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群ベースの分離表現学習と新規コンテンツへの一般化（Group-based Learning of Disentangled Representations with Generalizability for Novel Contents）</news:title>
   <news:publication_date>2026-06-10T19:42:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699241</loc>
  <lastmod>2026-06-10T19:42:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>On2Vecによるオントロジー充填の新展開（On2Vec: Embedding-based Relation Prediction for Ontology Population）</news:title>
   <news:publication_date>2026-06-10T19:42:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699239</loc>
  <lastmod>2026-06-10T18:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WCE画像における胃潰瘍検出のための無限カリキュラム学習（Infinite Curriculum Learning for Efficiently Detecting Gastric Ulcers in WCE Images）</news:title>
   <news:publication_date>2026-06-10T18:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699237</loc>
  <lastmod>2026-06-10T18:51:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AIがブラック・ショールズ方程式数値解法の次元の呪いを克服する証明（A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations）</news:title>
   <news:publication_date>2026-06-10T18:51:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699235</loc>
  <lastmod>2026-06-10T18:51:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタパス埋め込みによる知識グラフの特徴学習（Feature Learning for Meta-Paths in Knowledge Graphs）</news:title>
   <news:publication_date>2026-06-10T18:51:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699233</loc>
  <lastmod>2026-06-10T18:50:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論に基づく能動学習で効率的に画像検索を改善する（Information-Theoretic Active Learning for Content-Based Image Retrieval）</news:title>
   <news:publication_date>2026-06-10T18:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699231</loc>
  <lastmod>2026-06-10T18:50:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形最適化向けの高速アンダーソン・チェビシェフ加速（A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization）</news:title>
   <news:publication_date>2026-06-10T18:50:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699229</loc>
  <lastmod>2026-06-10T18:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチターゲット予測の統一的視点（Multi-target prediction: A unifying view on problems and methods）</news:title>
   <news:publication_date>2026-06-10T18:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699227</loc>
  <lastmod>2026-06-10T18:49:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNと手作り特徴の融合で肺結節の悪性度を予測する手法（Predicting Lung Nodule Malignancies by Combining Deep Convolutional Neural Network and Handcrafted Features）</news:title>
   <news:publication_date>2026-06-10T18:49:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699225</loc>
  <lastmod>2026-06-10T17:58:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模閉ループ産業プロセスの分散動的モデリングとモニタリング（Distributed dynamic modeling and monitoring for large-scale industrial processes under closed-loop control）</news:title>
   <news:publication_date>2026-06-10T17:58:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699223</loc>
  <lastmod>2026-06-10T17:57:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速グリーディ法による辞書選択と一般化スパース制約（Fast greedy algorithms for dictionary selection with generalized sparsity constraints）</news:title>
   <news:publication_date>2026-06-10T17:57:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699221</loc>
  <lastmod>2026-06-10T17:57:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>掘進機の運転データから地質を予測する手法の実用性（Geology prediction based on operation data of TBM: comparison between deep neural network and statistical learning methods）</news:title>
   <news:publication_date>2026-06-10T17:57:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699219</loc>
  <lastmod>2026-06-10T17:56:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均分散最適化のためのブロック座標上昇アルゴリズム（A Block Coordinate Ascent Algorithm for Mean-Variance Optimization）</news:title>
   <news:publication_date>2026-06-10T17:56:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699217</loc>
  <lastmod>2026-06-10T17:56:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語ニューラル言語モデルによる教師なしクロスリンガル単語埋め込み（Unsupervised Cross-lingual Word Embedding by Multilingual Neural Language Models）</news:title>
   <news:publication_date>2026-06-10T17:56:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699215</loc>
  <lastmod>2026-06-10T17:56:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間でのランク最小化によるテンソルリング補完（Tensor Ring Decomposition with Rank Minimization on Latent Space）</news:title>
   <news:publication_date>2026-06-10T17:56:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699213</loc>
  <lastmod>2026-06-10T17:55:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロン統合層による漸進的冗長性削減（Neurons Merging Layer: Towards Progressive Redundancy Reduction for Deep Supervised Hashing）</news:title>
   <news:publication_date>2026-06-10T17:55:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699211</loc>
  <lastmod>2026-06-10T17:04:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係的プログラム合成（Relational Program Synthesis）</news:title>
   <news:publication_date>2026-06-10T17:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699209</loc>
  <lastmod>2026-06-10T17:04:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的クラスタリングの近似アルゴリズム（Approximation algorithms for stochastic clustering）</news:title>
   <news:publication_date>2026-06-10T17:04:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699207</loc>
  <lastmod>2026-06-10T17:03:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト付き有向ネットワークの埋め込み学習（Learning Embeddings of Directed Networks with Text-Associated Nodes—with Application in Software Package Dependency Networks）</news:title>
   <news:publication_date>2026-06-10T17:03:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699205</loc>
  <lastmod>2026-06-10T17:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BubGANによる気泡流画像合成（BubGAN: Bubble Generative Adversarial Networks for Synthesizing Realistic Bubbly Flow Images）</news:title>
   <news:publication_date>2026-06-10T17:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699203</loc>
  <lastmod>2026-06-10T17:02:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジスティック回帰で背景ノードを除外するネットワークのコミュニティ検出（Logistic Regression Augmented Community Detection for Network Data）</news:title>
   <news:publication_date>2026-06-10T17:02:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699201</loc>
  <lastmod>2026-06-10T17:02:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動優性多発性嚢胞腎のCT画像から腎臓総量を算出する多目的3D畳み込みニューラルネットワーク（Computation of Total Kidney Volume from CT images in Autosomal Dominant Polycystic Kidney Disease using Multi-Task 3D Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-10T17:02:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699199</loc>
  <lastmod>2026-06-10T17:02:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ意味を考慮した表現学習が変えるバイオ医療知識発見（edge2vec: Representation learning using edge semantics for biomedical knowledge discovery）</news:title>
   <news:publication_date>2026-06-10T17:02:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699197</loc>
  <lastmod>2026-06-10T16:10:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチソースからのドメイン適応を重み付き専門家で行う考え方（Multi-Source Domain Adaptation with Mixture of Experts）</news:title>
   <news:publication_date>2026-06-10T16:10:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699195</loc>
  <lastmod>2026-06-10T16:10:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超小型矮小銀河候補の本質（On the Nature of Ultra-faint Dwarf Galaxy Candidates. III. Horologium I, Pictor I, Grus I, and Phoenix II）</news:title>
   <news:publication_date>2026-06-10T16:10:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699193</loc>
  <lastmod>2026-06-10T16:09:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォーラム間で学ぶ重複質問検出の実用性（Adversarial Domain Adaptation for Duplicate Question Detection）</news:title>
   <news:publication_date>2026-06-10T16:09:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699191</loc>
  <lastmod>2026-06-10T16:08:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共有入力を持つ合成関数に対する量子アルゴリズムと近似多項式（Quantum algorithms and approximating polynomials for composed functions with shared inputs）</news:title>
   <news:publication_date>2026-06-10T16:08:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699189</loc>
  <lastmod>2026-06-10T16:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイクル一貫性を用いた音声強調（Cycle-Consistent Speech Enhancement）</news:title>
   <news:publication_date>2026-06-10T16:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699187</loc>
  <lastmod>2026-06-10T16:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的特徴変換による音声強調（Adversarial Feature-Mapping for Speech Enhancement）</news:title>
   <news:publication_date>2026-06-10T16:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699185</loc>
  <lastmod>2026-06-10T16:08:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な公平政策の学習（Learning Optimal Fair Policies）</news:title>
   <news:publication_date>2026-06-10T16:08:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699183</loc>
  <lastmod>2026-06-10T15:16:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要インフラに対する適応型戦略的サイバー防御（Adaptive Strategic Cyber Defense for Advanced Persistent Threats in Critical Infrastructure Networks）</news:title>
   <news:publication_date>2026-06-10T15:16:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699181</loc>
  <lastmod>2026-06-10T15:09:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多腕バンディット的アプローチによる多重検定と偽発見率制御（A Bandit Approach to Multiple Testing with False Discovery Control）</news:title>
   <news:publication_date>2026-06-10T15:09:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699179</loc>
  <lastmod>2026-06-10T15:09:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2段階フィルタ剪定によるCNN圧縮（Two-Phase Filter Pruning Based on Conditional Entropy）</news:title>
   <news:publication_date>2026-06-10T15:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699177</loc>
  <lastmod>2026-06-10T15:08:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プレイヤー経験をゲーム映像から抽出する方法（Player Experience Extraction from Gameplay Video）</news:title>
   <news:publication_date>2026-06-10T15:08:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699175</loc>
  <lastmod>2026-06-10T15:08:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングによるデリバティブ評価の革新（Deeply Learning Derivatives）</news:title>
   <news:publication_date>2026-06-10T15:08:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699173</loc>
  <lastmod>2026-06-10T15:07:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチチャネル・マルチタッチ帰属に対する注意機構付き深層ニューラルネット（Deep Neural Net with Attention for Multi-channel Multi-touch Attribution）</news:title>
   <news:publication_date>2026-06-10T15:07:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699171</loc>
  <lastmod>2026-06-10T15:06:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パターン化画像におけるユーザーマーキングの内容に基づく伝播（Content-based Propagation of User Markings for Interactive Segmentation of Patterned Images）</news:title>
   <news:publication_date>2026-06-10T15:06:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699169</loc>
  <lastmod>2026-06-10T14:15:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈と時間の課題に挑む強化学習ベンチマーク：Space Fortressの導入（Challenges of Context and Time in Reinforcement Learning: Introducing Space Fortress as a Benchmark）</news:title>
   <news:publication_date>2026-06-10T14:15:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699167</loc>
  <lastmod>2026-06-10T14:14:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dynamic Hierarchical Empirical Bayes を用いたオンライン広告予測の実務的意義（Dynamic Hierarchical Empirical Bayes: A Predictive Model Applied to Online Advertising）</news:title>
   <news:publication_date>2026-06-10T14:14:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699165</loc>
  <lastmod>2026-06-10T14:14:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ProdSumNetによるパラメータ削減の実務的示唆（ProdSumNet: reducing model parameters in deep neural networks via product-of-sums matrix decompositions）</news:title>
   <news:publication_date>2026-06-10T14:14:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699163</loc>
  <lastmod>2026-06-10T14:14:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>論理ルール誘導と理論学習をニューラル定理証明で実現する手法（Logical Rule Induction and Theory Learning Using Neural Theorem Proving）</news:title>
   <news:publication_date>2026-06-10T14:14:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699161</loc>
  <lastmod>2026-06-10T14:13:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ的非パラメトリックスペクトル推定（Bayesian Nonparametric Spectral Estimation）</news:title>
   <news:publication_date>2026-06-10T14:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699159</loc>
  <lastmod>2026-06-10T14:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイアスとスプリアス変動を明示的に除去する方法（Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings）</news:title>
   <news:publication_date>2026-06-10T14:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699157</loc>
  <lastmod>2026-06-10T14:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指数族モデルに対する差分プライバシー下のベイズ推論（Differentially Private Bayesian Inference for Exponential Families）</news:title>
   <news:publication_date>2026-06-10T14:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699155</loc>
  <lastmod>2026-06-10T13:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付き最適化におけるサドルポイント回避の方法（Escaping Saddle Points in Constrained Optimization）</news:title>
   <news:publication_date>2026-06-10T13:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699153</loc>
  <lastmod>2026-06-10T13:21:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般物体検出における深層学習の総覧（Deep Learning for Generic Object Detection: A Survey）</news:title>
   <news:publication_date>2026-06-10T13:21:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699151</loc>
  <lastmod>2026-06-10T13:21:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基地局のオン／オフ制御を深層強化学習で最適化する手法（DRAG: Deep Reinforcement Learning Based Base Station Activation in Heterogeneous Networks）</news:title>
   <news:publication_date>2026-06-10T13:21:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699149</loc>
  <lastmod>2026-06-10T13:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像キャプションにおける物体誤認（Object Hallucination in Image Captioning）</news:title>
   <news:publication_date>2026-06-10T13:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699147</loc>
  <lastmod>2026-06-10T13:20:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頑健なストリーミングテンソル分解と補完の変分ベイズ推論（Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion）</news:title>
   <news:publication_date>2026-06-10T13:20:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699145</loc>
  <lastmod>2026-06-10T13:20:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FATSからfeetsへ：天文時系列特徴抽出ツール改良の要点（From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning）</news:title>
   <news:publication_date>2026-06-10T13:20:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699143</loc>
  <lastmod>2026-06-10T13:19:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再現核クレイン空間におけるスケーラブル学習（Scalable Learning in Reproducing Kernel Krein Spaces）</news:title>
   <news:publication_date>2026-06-10T13:19:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699133</loc>
  <lastmod>2026-06-10T12:28:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似度ベースのスペクトル解析による地理的表現の強化（Deriving Enhanced Geographical Representations via Similarity-based Spectral Analysis: Predicting Colorectal Cancer Survival Curves in Iowa）</news:title>
   <news:publication_date>2026-06-10T12:28:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699131</loc>
  <lastmod>2026-06-10T12:28:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローマ字化サンスクリットのOCR再利用によるポストOCR誤り訂正（Upcycle Your OCR: Reusing OCRs for Post-OCR Text Correction in Romanised Sanskrit）</news:title>
   <news:publication_date>2026-06-10T12:28:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699129</loc>
  <lastmod>2026-06-10T12:28:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発散最小化を超えるGAN（GANs beyond divergence minimization）</news:title>
   <news:publication_date>2026-06-10T12:28:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699127</loc>
  <lastmod>2026-06-10T12:27:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANによる有効場理論モデル生成（GANs for generating EFT models）</news:title>
   <news:publication_date>2026-06-10T12:27:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699125</loc>
  <lastmod>2026-06-10T12:27:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的一貫性と制御性を両立する多様な彩色（Structural Consistency and Controllability for Diverse Colorization）</news:title>
   <news:publication_date>2026-06-10T12:27:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699123</loc>
  <lastmod>2026-06-10T12:27:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河中心マグネターの電波パルス形状解析（Pulse Morphology of the Galactic Center Magnetar PSR J1745–2900）</news:title>
   <news:publication_date>2026-06-10T12:27:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699121</loc>
  <lastmod>2026-06-10T12:26:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙シミュレーションで学ぶ遠方銀河合体の自動分類（Automated Distant Galaxy Merger Classifications from Space Telescope Images using the Illustris Simulation）</news:title>
   <news:publication_date>2026-06-10T12:26:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699119</loc>
  <lastmod>2026-06-10T11:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学ぶべきでない行動の見切り術（Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-10T11:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699117</loc>
  <lastmod>2026-06-10T11:35:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬スケーリングと適応ネットワークスケーリング（Adaptive Network Scaling for Deep Rectifier Reinforcement Learning Models）</news:title>
   <news:publication_date>2026-06-10T11:35:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699115</loc>
  <lastmod>2026-06-10T11:35:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚と音声で読む話し言葉の大規模自動認識（Deep Audio-Visual Speech Recognition）</news:title>
   <news:publication_date>2026-06-10T11:35:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699113</loc>
  <lastmod>2026-06-10T11:34:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリーネットワークによる多変量時系列予測の解法（A Memory-Network Based Solution for Multivariate Time-Series Forecasting）</news:title>
   <news:publication_date>2026-06-10T11:34:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699111</loc>
  <lastmod>2026-06-10T11:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込みにおける発散する言語情報の発見（Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluation）</news:title>
   <news:publication_date>2026-06-10T11:34:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699109</loc>
  <lastmod>2026-06-10T11:33:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IDSGANによる侵入検知回避攻撃の生成（IDSGAN: Generative Adversarial Networks for Attack Generation against Intrusion Detection）</news:title>
   <news:publication_date>2026-06-10T11:33:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699107</loc>
  <lastmod>2026-06-10T11:33:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的例は不可避か？（Are Adversarial Examples Inevitable?）</news:title>
   <news:publication_date>2026-06-10T11:33:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699105</loc>
  <lastmod>2026-06-10T10:41:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市交通シーンにおけるマルチクラス物体検出器を用いた複数物体追跡（Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detector）</news:title>
   <news:publication_date>2026-06-10T10:41:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699103</loc>
  <lastmod>2026-06-10T10:31:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>in vitro用製剤予測のためのディープラーニング（Deep learning for in vitro prediction of pharmaceutical formulations）</news:title>
   <news:publication_date>2026-06-10T10:31:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699101</loc>
  <lastmod>2026-06-10T10:31:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ARCHERによるHERのバイアス是正（ARCHER: Aggressive Rewards to Counter bias in Hindsight Experience Replay）</news:title>
   <news:publication_date>2026-06-10T10:31:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699099</loc>
  <lastmod>2026-06-10T10:30:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次元確率的構成ネットワークを画像解析に活かす（Two Dimensional Stochastic Configuration Networks for Image Data Analytics）</news:title>
   <news:publication_date>2026-06-10T10:30:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699097</loc>
  <lastmod>2026-06-10T10:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新しいカテゴリを忘れずに生成する仕組み（Memory Replay GANs: learning to generate images from new categories without forgetting）</news:title>
   <news:publication_date>2026-06-10T10:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699095</loc>
  <lastmod>2026-06-10T10:30:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>（121514）1999 UJ7：原始的で遅い回転を示す火星トロヤ群小惑星（(121514) 1999 UJ7: A primitive, slow-rotating Martian Trojan）</news:title>
   <news:publication_date>2026-06-10T10:30:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699093</loc>
  <lastmod>2026-06-10T10:30:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプル効率の高い模倣学習（Sample-Efficient Imitation Learning via Generative Adversarial Nets）</news:title>
   <news:publication_date>2026-06-10T10:30:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699091</loc>
  <lastmod>2026-06-10T09:38:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seq2seq出力の統語的性質評価と広範囲HPSGの活用（Evaluating Syntactic Properties of Seq2seq Output with a Broad Coverage HPSG: A Case Study on Machine Translation）</news:title>
   <news:publication_date>2026-06-10T09:38:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699089</loc>
  <lastmod>2026-06-10T09:38:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビン化データに対するガウス過程回帰（Gaussian Process Regression for Binned Data）</news:title>
   <news:publication_date>2026-06-10T09:38:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699087</loc>
  <lastmod>2026-06-10T09:38:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽フレア由来ニュートリノとメガトン検出器が変える宇宙飛行の安全性（Solar neutrino flare, megaton neutrino detectors and human space journey）</news:title>
   <news:publication_date>2026-06-10T09:38:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699085</loc>
  <lastmod>2026-06-10T09:37:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密なポーズ転送（Dense Pose Transfer）</news:title>
   <news:publication_date>2026-06-10T09:37:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699083</loc>
  <lastmod>2026-06-10T09:37:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業用センサデータの超解像知覚（Super Resolution Perception of Industrial Sensor Data）</news:title>
   <news:publication_date>2026-06-10T09:37:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699081</loc>
  <lastmod>2026-06-10T09:36:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二方向問答ネットワークによる機械読解（Dual Ask-Answer Network for Machine Reading Comprehension）</news:title>
   <news:publication_date>2026-06-10T09:36:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699079</loc>
  <lastmod>2026-06-10T09:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点描法に学ぶ単一画像からの3D復元（3D Surface Reconstruction by Pointillism）</news:title>
   <news:publication_date>2026-06-10T09:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699077</loc>
  <lastmod>2026-06-10T08:45:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様性とスパース性：インデックス・トラッキングの新視点（DIVERSITY AND SPARSITY: A NEW PERSPECTIVE ON INDEX TRACKING）</news:title>
   <news:publication_date>2026-06-10T08:45:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699075</loc>
  <lastmod>2026-06-10T08:45:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量的推定の評価指標の検討（Evaluation Measures for Quantification）</news:title>
   <news:publication_date>2026-06-10T08:45:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699073</loc>
  <lastmod>2026-06-10T08:45:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>年齢層を考慮したマルチエキスパートによる性別分類（Multi-Expert Gender Classification on Age Group by Integrating Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-10T08:45:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699071</loc>
  <lastmod>2026-06-10T08:43:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バランス化されたマルチショットEPIを用いた高速Cartesian MRF（Balanced multi-shot EPI for accelerated Cartesian MRF: An alternative to spiral MRF）</news:title>
   <news:publication_date>2026-06-10T08:43:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699069</loc>
  <lastmod>2026-06-10T08:43:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コードスイッチ言語モデルの改良（Code-switched Language Models Using Dual RNNs and Same-Source Pretraining）</news:title>
   <news:publication_date>2026-06-10T08:43:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699067</loc>
  <lastmod>2026-06-10T08:43:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度指紋画像における孔（ポア）検出とDeepResPore（Pore detection in high-resolution fingerprint images using Deep Residual Network）</news:title>
   <news:publication_date>2026-06-10T08:43:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699065</loc>
  <lastmod>2026-06-10T08:43:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Particle Swarm Optimizationクラスタリング入門（A tutorial on Particle Swarm Optimization Clustering）</news:title>
   <news:publication_date>2026-06-10T08:43:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699063</loc>
  <lastmod>2026-06-10T07:51:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的制御を用いた合成最適化の新手法（Stochastically Controlled Stochastic Gradient for the Convex and Non-convex Composition problem）</news:title>
   <news:publication_date>2026-06-10T07:51:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699061</loc>
  <lastmod>2026-06-10T07:51:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線で捉える空気シャワーのリアルタイム検出（Towards online triggering for the radio detection of air showers using deep neural networks）</news:title>
   <news:publication_date>2026-06-10T07:51:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699059</loc>
  <lastmod>2026-06-10T07:49:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズA最適設計とグループラッソーの意外な接点（An unexpected connection between Bayes A-optimal designs and the Group Lasso）</news:title>
   <news:publication_date>2026-06-10T07:49:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699057</loc>
  <lastmod>2026-06-10T07:49:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固定集合探索（Fixed Set Search）を巡る考察（Fixed set search applied to the traveling salesman problem）</news:title>
   <news:publication_date>2026-06-10T07:49:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699055</loc>
  <lastmod>2026-06-10T07:49:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gaussian Processesをゼロから実装する実践ハンドブック（Hands-on Experience with Gaussian Processes (GPs): Implementing GPs in Python - I）</news:title>
   <news:publication_date>2026-06-10T07:49:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699053</loc>
  <lastmod>2026-06-10T07:48:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一撃学習でのiEEG発作検出—二値化処理と高次元コンピューティングの融合（One-shot Learning for iEEG Seizure Detection Using End-to-end Binary Operations）</news:title>
   <news:publication_date>2026-06-10T07:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699051</loc>
  <lastmod>2026-06-10T07:48:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リッチデータが貧弱データを助ける模倣学習（RDPD: Rich Data Helps Poor Data via Imitation）</news:title>
   <news:publication_date>2026-06-10T07:48:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699049</loc>
  <lastmod>2026-06-10T06:56:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全身高解像度アニメ生成のための段階的構造条件付GAN（Full-body High-resolution Anime Generation with Progressive Structure-conditional Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-10T06:56:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699047</loc>
  <lastmod>2026-06-10T06:56:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒエラルキー化CNNとLSTMによる走行速度予測（Travel Speed Prediction with a Hierarchical Convolutional Neural Network and Long Short-Term Memory Model Framework）</news:title>
   <news:publication_date>2026-06-10T06:56:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699045</loc>
  <lastmod>2026-06-10T06:56:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース正則化を使った深層強化学習（Model-Based Regularization for Deep Reinforcement Learning with Transcoder Networks）</news:title>
   <news:publication_date>2026-06-10T06:56:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699043</loc>
  <lastmod>2026-06-10T06:55:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マーケットプレイス向け深層ニューラルレコメンダーの5つの教訓（Five lessons from building a deep neural network recommender for marketplaces）</news:title>
   <news:publication_date>2026-06-10T06:55:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699041</loc>
  <lastmod>2026-06-10T06:55:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的文脈の重要性とシーン理解におけるデータ拡張の役割（On the Importance of Visual Context for Data Augmentation in Scene Understanding）</news:title>
   <news:publication_date>2026-06-10T06:55:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699039</loc>
  <lastmod>2026-06-10T06:55:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CoverBLIP：スケーラブル反復マッチドフィルタリングによるMR Fingerprint回復（CoverBLIP: scalable iterative matched filtering for MR Fingerprint recovery）</news:title>
   <news:publication_date>2026-06-10T06:55:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699037</loc>
  <lastmod>2026-06-10T06:54:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定で解釈可能な予測とKnockoffs推論（IPAD: Stable Interpretable Forecasting with Knockoffs Inference）</news:title>
   <news:publication_date>2026-06-10T06:54:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699035</loc>
  <lastmod>2026-06-10T06:03:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約列符号の深層学習による復号化（Deep Learning-Based Decoding for Constrained Sequence Codes）</news:title>
   <news:publication_date>2026-06-10T06:03:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699033</loc>
  <lastmod>2026-06-10T06:02:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マーケットプレイスにおける深層ニューラルネットワーク推薦器のオンライン実験（Deep neural network marketplace recommenders in online experiments）</news:title>
   <news:publication_date>2026-06-10T06:02:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699031</loc>
  <lastmod>2026-06-10T06:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAMENet：薬物併用の安全性を考慮したメモリ拡張グラフネットワーク（GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination）</news:title>
   <news:publication_date>2026-06-10T06:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699029</loc>
  <lastmod>2026-06-10T06:01:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木探索を組み合わせる強化学習の実践的示唆（How to Combine Tree-Search Methods in Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-10T06:01:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699027</loc>
  <lastmod>2026-06-10T06:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点不変な動作表現の教師なし学習（Unsupervised Learning of View-invariant Action Representations）</news:title>
   <news:publication_date>2026-06-10T06:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699025</loc>
  <lastmod>2026-06-10T06:01:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoU損失は部分加法性である（Yes, IoU loss is submodular – as a function of the mispredictions）</news:title>
   <news:publication_date>2026-06-10T06:01:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699023</loc>
  <lastmod>2026-06-10T06:00:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習ベースの物体検出器作成支援（Guiding the Creation of Deep Learning-based Object Detectors）</news:title>
   <news:publication_date>2026-06-10T06:00:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699021</loc>
  <lastmod>2026-06-10T05:09:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフ上のWassersteinソフトラベル伝播（Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds）</news:title>
   <news:publication_date>2026-06-10T05:09:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699019</loc>
  <lastmod>2026-06-10T05:08:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類ニューラルネットワークの敵対的再プログラミング（Adversarial Reprogramming of Text Classification Neural Networks）</news:title>
   <news:publication_date>2026-06-10T05:08:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699017</loc>
  <lastmod>2026-06-10T05:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固有分解を不要にしたグラフ信号のサンプリング選択（Eigendecomposition-Free Sampling Set Selection for Graph Signals）</news:title>
   <news:publication_date>2026-06-10T05:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699015</loc>
  <lastmod>2026-06-10T05:07:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アニーリング変分目的による変分推論の探索性向上（Improving Explorability in Variational Inference with Annealed Variational Objectives）</news:title>
   <news:publication_date>2026-06-10T05:07:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699013</loc>
  <lastmod>2026-06-10T05:07:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転経験の転移によるエンドツーエンド自動運転制御（Driving Experience Transfer Method for End-to-End Control of Self-Driving Cars）</news:title>
   <news:publication_date>2026-06-10T05:07:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699011</loc>
  <lastmod>2026-06-10T05:07:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズの多い時系列データにおけるモチーフ認識と状態割当（MASA: Motif-Aware State Assignment in Noisy Time Series Data）</news:title>
   <news:publication_date>2026-06-10T05:07:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699009</loc>
  <lastmod>2026-06-10T05:06:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像のノイズ除去と高次視覚タスクの連携（Connecting Image Denoising and High-Level Vision Tasks via Deep Learning）</news:title>
   <news:publication_date>2026-06-10T05:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699007</loc>
  <lastmod>2026-06-10T04:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン適応型画像再構成（Online Adaptive Image Reconstruction (OnAIR) Using Dictionary Models）</news:title>
   <news:publication_date>2026-06-10T04:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699005</loc>
  <lastmod>2026-06-10T04:14:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模動画オブジェクトセグメンテーションデータセットの構築が変えたこと（YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark）</news:title>
   <news:publication_date>2026-06-10T04:14:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699003</loc>
  <lastmod>2026-06-10T04:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大型二十面体ウイルスが足場タンパク質を必要とする理由（Why large icosahedral viruses need scaffolding proteins: The interplay of Gaussian curvature and disclination interactions）</news:title>
   <news:publication_date>2026-06-10T04:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699001</loc>
  <lastmod>2026-06-10T04:13:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化知識ベースの自然言語生成（Describing a Knowledge Base）</news:title>
   <news:publication_date>2026-06-10T04:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698999</loc>
  <lastmod>2026-06-10T04:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きモデルにおけるNoise Contrastive EstimationとNegative Samplingの整合性と効率（Noise Contrastive Estimation and Negative Sampling for Conditional Models: Consistency and Statistical Efficiency）</news:title>
   <news:publication_date>2026-06-10T04:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698997</loc>
  <lastmod>2026-06-10T04:13:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元高階データの最適スパース特異値分解（Optimal Sparse Singular Value Decomposition for High-dimensional High-order Data）</news:title>
   <news:publication_date>2026-06-10T04:13:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698995</loc>
  <lastmod>2026-06-10T04:12:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変数自己符号化器における影響因子の発見（Discovering Influential Factors in Variational Autoencoder）</news:title>
   <news:publication_date>2026-06-10T04:12:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698993</loc>
  <lastmod>2026-06-10T03:22:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MDCNによる物体検出の効率化（Multi-Scale, Deep Inception Convolutional Neural Networks for Efficient Object Detection）</news:title>
   <news:publication_date>2026-06-10T03:22:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698991</loc>
  <lastmod>2026-06-10T03:21:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AMIネットワークにおける深層再帰型不正電力検知（Deep Recurrent Electricity Theft Detection in AMI Networks with Random Tuning of Hyper-parameters）</news:title>
   <news:publication_date>2026-06-10T03:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698989</loc>
  <lastmod>2026-06-10T03:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー因子化オートエンコーダとネットワーク制約によるマルチオミク統合解析（Multi-view Factorization AutoEncoder with Network Constraints for Multi-omic Integrative Analysis）</news:title>
   <news:publication_date>2026-06-10T03:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698987</loc>
  <lastmod>2026-06-10T03:20:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>収束基準と機械学習によるMonkhorst-Pack k点および平面波カットオフ予測（Convergence and machine learning predictions of Monkhorst-Pack k-points and plane-wave cut-off in high-throughput DFT calculations）</news:title>
   <news:publication_date>2026-06-10T03:20:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698985</loc>
  <lastmod>2026-06-10T03:20:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層化テキスト分類と単語埋め込みの実践的解析（An Analysis of Hierarchical Text Classification Using Word Embeddings）</news:title>
   <news:publication_date>2026-06-10T03:20:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698983</loc>
  <lastmod>2026-06-10T03:20:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測下での効率的な確率的スパース回帰手法（Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation）</news:title>
   <news:publication_date>2026-06-10T03:20:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698981</loc>
  <lastmod>2026-06-10T03:19:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチフィンガー二分探索木の概説（Multi-finger binary search trees）</news:title>
   <news:publication_date>2026-06-10T03:19:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698979</loc>
  <lastmod>2026-06-10T02:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カルネギー・シカゴ・ハッブル・プログラム V：赤色巨星分岐点によるNGC 1448とNGC 1316の距離測定 (THE CARNEGIE-CHICAGO HUBBLE PROGRAM. V. THE DISTANCES TO NGC 1448 AND NGC 1316 VIA THE TIP OF THE RED GIANT BRANCH)</news:title>
   <news:publication_date>2026-06-10T02:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698977</loc>
  <lastmod>2026-06-10T02:28:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>喫煙イベント予測のための時変半パラメトリックホーキス過程（Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model）</news:title>
   <news:publication_date>2026-06-10T02:28:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698975</loc>
  <lastmod>2026-06-10T02:27:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習でMRFの辞書負荷を60倍削減する方法（GEOMETRY OF DEEP LEARNING FOR MAGNETIC RESONANCE FINGERPRINTING）</news:title>
   <news:publication_date>2026-06-10T02:27:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698973</loc>
  <lastmod>2026-06-10T02:27:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習と暗号理論を結ぶ敵対的攻撃防御の考え方（Bridging machine learning and cryptography in defence against adversarial attacks）</news:title>
   <news:publication_date>2026-06-10T02:27:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698971</loc>
  <lastmod>2026-06-10T02:26:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声と映像を揃えて雑音に強くする方法（Attention-based Audio-Visual Fusion for Robust Automatic Speech Recognition）</news:title>
   <news:publication_date>2026-06-10T02:26:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698969</loc>
  <lastmod>2026-06-10T02:26:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイド情報による単一コミュニティ復元の情報理論的限界（Recovering a Single Community with Side Information）</news:title>
   <news:publication_date>2026-06-10T02:26:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698967</loc>
  <lastmod>2026-06-10T02:26:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線画像と3D畳み込みを融合した頸部リンパ節転移予測（Combining Many-objective Radiomics and 3-dimensional Convolutional Neural Network through Evidential Reasoning to Predict Lymph Node Metastasis in Head and Neck Cancer）</news:title>
   <news:publication_date>2026-06-10T02:26:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698965</loc>
  <lastmod>2026-06-10T01:34:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カバレッジベースのサンプル設計によるハイパーパラメータ最適化の改善（Improving Hyper-Parameter Optimization Using Coverage-Based Sample Designs）</news:title>
   <news:publication_date>2026-06-10T01:34:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698963</loc>
  <lastmod>2026-06-10T01:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幹細胞の時空間動態を数理で解く（Statistical and mathematical modeling of spatiotemporal dynamics of stem cells）</news:title>
   <news:publication_date>2026-06-10T01:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698961</loc>
  <lastmod>2026-06-10T01:33:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーボリック空間でのメトリック学習によるレコメンダー性能向上（HyperML: A Boosting Metric Learning Approach in Hyperbolic Space for Recommender Systems）</news:title>
   <news:publication_date>2026-06-10T01:33:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698959</loc>
  <lastmod>2026-06-10T01:32:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙予測による文生成の強化学習高速化（Accelerated Reinforcement Learning for Sentence Generation by Vocabulary Prediction）</news:title>
   <news:publication_date>2026-06-10T01:32:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698957</loc>
  <lastmod>2026-06-10T01:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マンモグラムにおける乳腺腫瘍のセグメンテーションと形状分類（Breast Tumor Segmentation and Shape Classification in Mammograms using Generative Adversarial and Convolutional Neural Network）</news:title>
   <news:publication_date>2026-06-10T01:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698955</loc>
  <lastmod>2026-06-10T01:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における高速物体検出のための領域パッキング（Pack and Detect: Fast Object Detection in Videos Using Region-of-Interest Packing）</news:title>
   <news:publication_date>2026-06-10T01:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698953</loc>
  <lastmod>2026-06-10T01:31:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河検出と識別における深層学習とデータ拡張の実用化（Galaxy detection and identification using deep learning and data augmentation）</news:title>
   <news:publication_date>2026-06-10T01:31:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698951</loc>
  <lastmod>2026-06-10T00:40:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単視点深度とオプティカルフローの教師なし共同学習（DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency）</news:title>
   <news:publication_date>2026-06-10T00:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698949</loc>
  <lastmod>2026-06-10T00:39:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元共通トレンド交絡を扱う効率的Difference-in-Differences推定（Efficient Difference-in-Differences Estimation with High-Dimensional Common Trend Confounding）</news:title>
   <news:publication_date>2026-06-10T00:39:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698947</loc>
  <lastmod>2026-06-10T00:39:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書関連度ランキングの深層的改良（Deep Relevance Ranking Using Enhanced Document-Query Interactions）</news:title>
   <news:publication_date>2026-06-10T00:39:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698945</loc>
  <lastmod>2026-06-10T00:38:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子力学の理解を深める（Making Better Sense of Quantum Mechanics）</news:title>
   <news:publication_date>2026-06-10T00:38:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698943</loc>
  <lastmod>2026-06-10T00:38:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシー化されたWilcoxon符号付き順位検定の実装と意義（A Differentially Private Wilcoxon Signed-Rank Test）</news:title>
   <news:publication_date>2026-06-10T00:38:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698941</loc>
  <lastmod>2026-06-10T00:38:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>標的指向性を持つ分子設計の潜在空間最適化（Latent Molecular Optimization for Targeted Therapeutic Design）</news:title>
   <news:publication_date>2026-06-10T00:38:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698939</loc>
  <lastmod>2026-06-10T00:37:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な自分視点の視覚認識（Efficient Egocentric Visual Perception）</news:title>
   <news:publication_date>2026-06-10T00:37:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698937</loc>
  <lastmod>2026-06-09T23:46:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的分類器選択のためのオンライン局所プール生成（Online local pool generation for dynamic classifier selection: an extended version）</news:title>
   <news:publication_date>2026-06-09T23:46:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698935</loc>
  <lastmod>2026-06-09T23:45:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字・単語埋め込みを用いたテキスト正規化（Utilizing Character and Word Embeddings for Text Normalization with Sequence-to-Sequence Models）</news:title>
   <news:publication_date>2026-06-09T23:45:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698933</loc>
  <lastmod>2026-06-09T23:45:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル法に基づく遺伝子シェービング（Gene Shaving using influence function of a kernel method）</news:title>
   <news:publication_date>2026-06-09T23:45:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698931</loc>
  <lastmod>2026-06-09T23:45:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストからの画像注釈自動生成のための2モーダルネットワークアーキテクチャ（Bimodal network architectures for automatic generation of image annotation from text）</news:title>
   <news:publication_date>2026-06-09T23:45:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698929</loc>
  <lastmod>2026-06-09T23:44:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセット結合の深層学習による手法（Merging Datasets Through Deep learning）</news:title>
   <news:publication_date>2026-06-09T23:44:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698927</loc>
  <lastmod>2026-06-09T23:44:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損値がある場合の異常検知の扱い（Anomaly Detection in the Presence of Missing Values）</news:title>
   <news:publication_date>2026-06-09T23:44:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698925</loc>
  <lastmod>2026-06-09T22:53:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN Labによる生成モデル学習の可視化と教育効果（GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation）</news:title>
   <news:publication_date>2026-06-09T22:53:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698923</loc>
  <lastmod>2026-06-09T22:52:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳児との多者間マルチモーダル対話管理（Multimodal Dialogue Management for Multiparty Interaction with Infants）</news:title>
   <news:publication_date>2026-06-09T22:52:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698921</loc>
  <lastmod>2026-06-09T22:52:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>被写界深度ブラーを活用した深層深度推定（Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?）</news:title>
   <news:publication_date>2026-06-09T22:52:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698919</loc>
  <lastmod>2026-06-09T22:51:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脅威下の強化学習：Threatened Markov Decision Processes（Reinforcement Learning under Threats）</news:title>
   <news:publication_date>2026-06-09T22:51:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698917</loc>
  <lastmod>2026-06-09T22:51:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交通密度推定にCNNを用いる方法（Traffic Density Estimation using a Convolutional Neural Network）</news:title>
   <news:publication_date>2026-06-09T22:51:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698915</loc>
  <lastmod>2026-06-09T22:00:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学生の物理自己効力感の低下を社会的ネットワークの視点から読み解く（Beyond performance metrics: Examining a decrease in students’ physics self-efficacy through a social networks lens）</news:title>
   <news:publication_date>2026-06-09T22:00:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698913</loc>
  <lastmod>2026-06-09T21:49:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスペクトログラム融合による音響シーン分類の向上（Multi-Spectrogram Fusion for Acoustic Scene Classification）</news:title>
   <news:publication_date>2026-06-09T21:49:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698911</loc>
  <lastmod>2026-06-09T21:49:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的文脈感応型時間減衰アテンションによる対話モデルの改善（Dynamically Context-Sensitive Time-Decay Attention for Dialogue Modeling）</news:title>
   <news:publication_date>2026-06-09T21:49:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698909</loc>
  <lastmod>2026-06-09T21:49:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈付き多言語語形変化推定の実装と成果（Multilingual Inflection in Context with Explicit Morphosyntactic Decoding）</news:title>
   <news:publication_date>2026-06-09T21:49:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698907</loc>
  <lastmod>2026-06-09T21:48:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VLSTM：超長時系列を扱うLSTMの拡張（VLSTM: VERY LONG SHORT-TERM MEMORY NETWORKS FOR HIGH-FREQUENCY TRADING）</news:title>
   <news:publication_date>2026-06-09T21:48:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698905</loc>
  <lastmod>2026-06-09T21:48:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>液体の流れに関する人間の直感のモデル化（Modeling human intuitions about liquid flow with particle-based simulation）</news:title>
   <news:publication_date>2026-06-09T21:48:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698903</loc>
  <lastmod>2026-06-09T21:48:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ信号からコミュニティを「盲検出」する手法（Blind Community Detection from Low-rank Excitations of a Graph）</news:title>
   <news:publication_date>2026-06-09T21:48:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698901</loc>
  <lastmod>2026-06-09T20:57:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層バイレベル学習（Deep Bilevel Learning）</news:title>
   <news:publication_date>2026-06-09T20:57:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698899</loc>
  <lastmod>2026-06-09T20:56:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポートフォリオの分散投資とモデル不確実性（Portfolio diversification and model uncertainty: a robust dynamic mean-variance approach）</news:title>
   <news:publication_date>2026-06-09T20:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698897</loc>
  <lastmod>2026-06-09T20:56:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈から感情を推定するモデル（Sentylic at IEST 2018: Gated Recurrent Neural Network and Capsule Network Based Approach for Implicit Emotion Detection）</news:title>
   <news:publication_date>2026-06-09T20:56:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698895</loc>
  <lastmod>2026-06-09T20:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepVAEとGMMによる星団検出（Stellar Cluster Detection using GMM with Deep Variational Autoencoder）</news:title>
   <news:publication_date>2026-06-09T20:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698893</loc>
  <lastmod>2026-06-09T20:55:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コントラストが深層ニューラルネットワークにどう符号化されているか（How is Contrast Encoded in Deep Neural Networks?）</news:title>
   <news:publication_date>2026-06-09T20:55:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698891</loc>
  <lastmod>2026-06-09T20:55:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変解析のためのデータ拡張（Data Augmentation for Skin Lesion Analysis）</news:title>
   <news:publication_date>2026-06-09T20:55:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698889</loc>
  <lastmod>2026-06-09T20:55:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>修正されたクラス確率多様性に基づく共学習によるハイパースペクトル画像分類（Modified Diversity of Class Probability Estimation Co-training for Hyperspectral Image Classification）</news:title>
   <news:publication_date>2026-06-09T20:55:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698887</loc>
  <lastmod>2026-06-09T20:03:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間におけるスパイク層誤差再割り当て（SLAYER: Spike Layer Error Reassignment in Time）</news:title>
   <news:publication_date>2026-06-09T20:03:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698885</loc>
  <lastmod>2026-06-09T20:02:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変性と反変性の再考（Covariance and Contravariance: A Fresh Look at an Old Issue）</news:title>
   <news:publication_date>2026-06-09T20:02:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698883</loc>
  <lastmod>2026-06-09T20:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変画像を高解像度で合成する手法（Generating Highly Realistic Images of Skin Lesions with GANs）</news:title>
   <news:publication_date>2026-06-09T20:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698881</loc>
  <lastmod>2026-06-09T20:01:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ほぼ等差数列として近づく素数の構造（Almost arithmetic progressions in the primes and other large sets）</news:title>
   <news:publication_date>2026-06-09T20:01:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698879</loc>
  <lastmod>2026-06-09T20:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚的識別器を用いた画像操作（Image Manipulation with Perceptual Discriminators）</news:title>
   <news:publication_date>2026-06-09T20:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698877</loc>
  <lastmod>2026-06-09T20:01:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大量のラベルなし顔データから識別力を引き出す合意駆動伝播（Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition）</news:title>
   <news:publication_date>2026-06-09T20:01:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698875</loc>
  <lastmod>2026-06-09T20:00:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意時点Hedgeアルゴリズムの確率的最適性（On the optimality of the Hedge algorithm in the stochastic regime）</news:title>
   <news:publication_date>2026-06-09T20:00:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698873</loc>
  <lastmod>2026-06-09T19:09:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク生成モデルの定量評価手法（Towards quantitative methods to assess network generative models）</news:title>
   <news:publication_date>2026-06-09T19:09:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698871</loc>
  <lastmod>2026-06-09T19:09:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SN 2013gyの初期光度曲線と前駆天体制約（The first 48: Discovery and progenitor constraints on the Type Ia supernova 2013gy）</news:title>
   <news:publication_date>2026-06-09T19:09:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698869</loc>
  <lastmod>2026-06-09T19:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチドメイン画像翻訳のための統一的特徴分離器（A Unified Feature Disentangler for Multi-Domain Image Translation and Manipulation）</news:title>
   <news:publication_date>2026-06-09T19:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698867</loc>
  <lastmod>2026-06-09T19:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロショット学習によるプログラミング教育の自動フィードバック（Zero Shot Learning for Code Education）</news:title>
   <news:publication_date>2026-06-09T19:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698865</loc>
  <lastmod>2026-06-09T19:08:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極端に少ない注釈で網膜血管を分割する手法（Retinal Vessel Segmentation under Extreme Low Annotation: A Generative Adversarial Network Approach）</news:title>
   <news:publication_date>2026-06-09T19:08:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698863</loc>
  <lastmod>2026-06-09T19:07:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック・ヒューマンマッティング（Semantic Human Matting）</news:title>
   <news:publication_date>2026-06-09T19:07:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698861</loc>
  <lastmod>2026-06-09T19:07:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>独立カーネル近似法（Independent Kernel Approximator）</news:title>
   <news:publication_date>2026-06-09T19:07:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698859</loc>
  <lastmod>2026-06-09T18:15:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル知識ベース埋め込みによるKB補完（Embedding Multimodal Relational Data for Knowledge Base Completion）</news:title>
   <news:publication_date>2026-06-09T18:15:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698857</loc>
  <lastmod>2026-06-09T18:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話における新しい“声”を作るニューラルモデル（Neural MultiVoice Models for Expressing Novel Personalities in Dialog）</news:title>
   <news:publication_date>2026-06-09T18:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698855</loc>
  <lastmod>2026-06-09T18:15:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ChannelNetsによる軽量化の設計思想（ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions）</news:title>
   <news:publication_date>2026-06-09T18:15:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698853</loc>
  <lastmod>2026-06-09T18:14:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザ好みの学習とカレンダー文脈の理解によるイベントスケジューリング（Learning User Preferences and Understanding Calendar Contexts for Event Scheduling）</news:title>
   <news:publication_date>2026-06-09T18:14:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698851</loc>
  <lastmod>2026-06-09T18:14:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>優先的サンプリングによる存在/不在データと存在のみデータの融合（Preferential sampling for presence/absence data and for fusion of presence/absence data with presence-only data）</news:title>
   <news:publication_date>2026-06-09T18:14:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698849</loc>
  <lastmod>2026-06-09T18:14:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化最小二乗法におけるクロスバリデーション残差とCookの距離の関係（Cross validation residuals for generalised least squares and other correlated data models）</news:title>
   <news:publication_date>2026-06-09T18:14:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698847</loc>
  <lastmod>2026-06-09T18:14:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNを心理言語学的被験者として扱う研究（RNNs as psycholinguistic subjects: Syntactic state and grammatical dependency）</news:title>
   <news:publication_date>2026-06-09T18:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698845</loc>
  <lastmod>2026-06-09T17:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的粒子最適化サンプリングと非漸近収束理論（Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory）</news:title>
   <news:publication_date>2026-06-09T17:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698843</loc>
  <lastmod>2026-06-09T17:21:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習に基づくロボット用オートフォーカス（A Robotic Auto-Focus System based on Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-09T17:21:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698841</loc>
  <lastmod>2026-06-09T17:21:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現（デノテーション）からのセマンティックパーシングにおける方策整形と一般化更新式（Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations）</news:title>
   <news:publication_date>2026-06-09T17:21:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698839</loc>
  <lastmod>2026-06-09T17:21:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模画像を用いた人間fMRIデータセットの公開（BOLD5000: A public fMRI dataset of 5000 images）</news:title>
   <news:publication_date>2026-06-09T17:21:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698837</loc>
  <lastmod>2026-06-09T17:21:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>鳥瞰視点による純粋視覚ベースの障害物検知（Developing a Purely Visual Based Obstacle Detection using Inverse Perspective Mapping）</news:title>
   <news:publication_date>2026-06-09T17:21:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698835</loc>
  <lastmod>2026-06-09T17:21:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>概念の抽象度を弱教師ありで推定する方法（Learning Concept Abstractness Using Weak Supervision）</news:title>
   <news:publication_date>2026-06-09T17:21:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698833</loc>
  <lastmod>2026-06-09T17:20:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モノリンガルだけで翻訳モデルを作る挑戦——Unsupervised Statistical Machine Translation（Unsupervised Statistical Machine Translation）</news:title>
   <news:publication_date>2026-06-09T17:20:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698831</loc>
  <lastmod>2026-06-09T16:29:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepHunterによるDNN欠陥検出の実務的意義（DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing）</news:title>
   <news:publication_date>2026-06-09T16:29:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698829</loc>
  <lastmod>2026-06-09T16:28:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的世界モデルが方策進化を促進する（Recurrent World Models Facilitate Policy Evolution）</news:title>
   <news:publication_date>2026-06-09T16:28:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698827</loc>
  <lastmod>2026-06-09T16:28:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内視鏡映像におけるポリープ検出の効率的手法（An Efficient Approach for Polyps Detection in Endoscopic Videos Based on Faster R-CNN）</news:title>
   <news:publication_date>2026-06-09T16:28:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698825</loc>
  <lastmod>2026-06-09T16:28:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>β-Ga2O3におけるドナーと深いアクセプターの実態（Donors and Deep Acceptors in β-Ga2O3）</news:title>
   <news:publication_date>2026-06-09T16:28:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/698823</loc>
  <lastmod>2026-06-09T16:27:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチアドバーサリアル領域適応（Multi-Adversarial Domain Adaptation）</news:title>
   <news:publication_date>2026-06-09T16:27:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698821</loc>
  <lastmod>2026-06-09T16:27:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>t-指数メモリネットワークによる質問応答機（t-Exponential Memory Networks for Question-Answering Machines）</news:title>
   <news:publication_date>2026-06-09T16:27:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698819</loc>
  <lastmod>2026-06-09T16:27:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>優先度付き深層ハッシングの実務的示唆（Deep Priority Hashing）</news:title>
   <news:publication_date>2026-06-09T16:27:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698817</loc>
  <lastmod>2026-06-09T15:36:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフから深い木へ変換する再帰型ニューラルネットワーク（GRAPH-BASED DEEP-TREE RECURSIVE NEURAL NETWORK (DTRNN) FOR TEXT CLASSIFICATION）</news:title>
   <news:publication_date>2026-06-09T15:36:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698815</loc>
  <lastmod>2026-06-09T15:36:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成確率平均勾配法（Compositional Stochastic Average Gradient for Machine Learning and Related Applications）</news:title>
   <news:publication_date>2026-06-09T15:36:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698813</loc>
  <lastmod>2026-06-09T15:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム言語モデルによる言語の構造生成の臨界現象（Random Language Model）</news:title>
   <news:publication_date>2026-06-09T15:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698811</loc>
  <lastmod>2026-06-09T15:35:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動きの顕著性に導かれる教師なし映像物体分割（Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation）</news:title>
   <news:publication_date>2026-06-09T15:35:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698809</loc>
  <lastmod>2026-06-09T15:35:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepPINKによるDNNの再現性ある特徴選択（DeepPINK: reproducible feature selection in deep neural networks）</news:title>
   <news:publication_date>2026-06-09T15:35:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698807</loc>
  <lastmod>2026-06-09T15:35:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SN 2012auにおけるパルサー風天体の証拠（Evidence for a pulsar wind nebula in the Type Ib-peculiar supernova SN 2012au）</news:title>
   <news:publication_date>2026-06-09T15:35:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698805</loc>
  <lastmod>2026-06-09T15:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MUSEによる超微光放射線銀河の分光同定（MUSE Spectroscopic Identiﬁcations of Ultra-Faint Emission Line Galaxies with MUV ∼-15）</news:title>
   <news:publication_date>2026-06-09T15:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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