<?xml version="1.0" encoding="UTF-8"?>
<!--generator='jetpack-15.9-beta'-->
<!--Jetpack_Sitemap_Buffer_News_XMLWriter-->
<?xml-stylesheet type="text/xsl" href="//aibr.jp/news-sitemap.xsl"?>
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:news="http://www.google.com/schemas/sitemap-news/0.9" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.sitemaps.org/schemas/sitemap/0.9 http://www.sitemaps.org/schemas/sitemap/0.9/sitemap.xsd">
 <url>
  <loc>https://aibr.jp/archives/698542</loc>
  <lastmod>2026-06-08T22:24:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次ツイスト分布とハドロン性CP変動の関係（Relating hadronic CP-violation to higher-twist distributions）</news:title>
   <news:publication_date>2026-06-08T22:24:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698540</loc>
  <lastmod>2026-06-08T22:24:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国語ピンイン支援IME — 入力していない文字を補完する手法 (Chinese Pinyin Aided IME, Input What You Have Not Keystroked Yet)</news:title>
   <news:publication_date>2026-06-08T22:24:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698538</loc>
  <lastmod>2026-06-08T22:24:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車車間通信における非協力的周波数資源割当のゲーム理論的解析（Learning to Entangle Radio Resources in Vehicular Communications: An Oblivious Game-Theoretic Perspective）</news:title>
   <news:publication_date>2026-06-08T22:24:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698536</loc>
  <lastmod>2026-06-08T22:22:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑ネットワークにおける知識合意と学習の役割（Knowledge Consensus in complex networks: the role of learning）</news:title>
   <news:publication_date>2026-06-08T22:22:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698534</loc>
  <lastmod>2026-06-08T22:22:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手作業特徴量と深層ニューラルネットワークによるOCT画像分類の比較（A Comparison of Handcrafted and Deep Neural Network Feature Extraction for Classifying Optical Coherence Tomography (OCT) Images）</news:title>
   <news:publication_date>2026-06-08T22:22:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698532</loc>
  <lastmod>2026-06-08T22:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数データ源を統合する拡張結合隠れマルコフモデルによる株価予測（Enhancing Stock Market Prediction with Extended Coupled Hidden Markov Model over Multi-Sourced Data）</news:title>
   <news:publication_date>2026-06-08T22:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698530</loc>
  <lastmod>2026-06-08T22:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度分類のための探索学習（Learning to Navigate for Fine-grained Classification）</news:title>
   <news:publication_date>2026-06-08T22:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698528</loc>
  <lastmod>2026-06-08T21:31:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い教師ありニューラル文書分類（Weakly-Supervised Neural Text Classification）</news:title>
   <news:publication_date>2026-06-08T21:31:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698526</loc>
  <lastmod>2026-06-08T21:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現論に基づく塑性流動の機械学習モデル（Machine learning models of plastic flow based on representation theory）</news:title>
   <news:publication_date>2026-06-08T21:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698524</loc>
  <lastmod>2026-06-08T21:30:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期動画の間を自然に埋める確率的手法（Stochastic Dynamics for Video Inﬁlling）</news:title>
   <news:publication_date>2026-06-08T21:30:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698522</loc>
  <lastmod>2026-06-08T21:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床試験における文脈バンディットによる意思決定支援（A Contextual-bandit-based Approach for Informed Decision-making in Clinical Trials）</news:title>
   <news:publication_date>2026-06-08T21:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698520</loc>
  <lastmod>2026-06-08T21:30:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集合住宅地下駐車場における小型自律走行車による監視システム（Car Monitoring System in Apartment Garages）</news:title>
   <news:publication_date>2026-06-08T21:30:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698518</loc>
  <lastmod>2026-06-08T21:29:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習を用いたネットワーク侵入検知の手法（Machine Learning Methods for Network Intrusion Detection）</news:title>
   <news:publication_date>2026-06-08T21:29:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698516</loc>
  <lastmod>2026-06-08T21:29:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語自己注意型翻訳モデルにおけるパラメータ共有手法（Parameter Sharing Methods for Multilingual Self-Attentional Translation Models）</news:title>
   <news:publication_date>2026-06-08T21:29:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698514</loc>
  <lastmod>2026-06-08T20:38:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短尺動画における大規模行動認識（ACTIVITY RECOGNITION ON A LARGE SCALE IN SHORT VIDEOS - MOMENTS IN TIME DATASET）</news:title>
   <news:publication_date>2026-06-08T20:38:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698512</loc>
  <lastmod>2026-06-08T20:38:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートシティ向け低コストIoTと機械学習による騒音分類（A Machine Learning Driven IoT Solution for Noise Classification in Smart Cities）</news:title>
   <news:publication_date>2026-06-08T20:38:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698510</loc>
  <lastmod>2026-06-08T20:37:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠ステージ分類：分散アプローチのスケーラビリティ評価（Sleep Stage Classification: Scalability Evaluations of Distributed Approaches）</news:title>
   <news:publication_date>2026-06-08T20:37:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698508</loc>
  <lastmod>2026-06-08T20:37:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VoxSegNet：ボクセルベースの3D部分分割を可能にする畳み込みネットワーク (VoxSegNet: Volumetric CNNs for Semantic Part Segmentation of 3D Shapes)</news:title>
   <news:publication_date>2026-06-08T20:37:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698506</loc>
  <lastmod>2026-06-08T20:36:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定義モデルによる答えの発見（Finding the Answers With Definition Models）</news:title>
   <news:publication_date>2026-06-08T20:36:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698504</loc>
  <lastmod>2026-06-08T20:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語情報抽出パイプラインによる調査報道支援（A Multilingual Information Extraction Pipeline for Investigative Journalism）</news:title>
   <news:publication_date>2026-06-08T20:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698502</loc>
  <lastmod>2026-06-08T20:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層線形モデルによる授業規模と学習成果の関係検証（Hierarchical Linear Modeling Approach to Measuring the Effects of Class Size and Other Classroom Characteristics on Student Learning in an Active-Learning Based Introductory Physics Course）</news:title>
   <news:publication_date>2026-06-08T20:36:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698500</loc>
  <lastmod>2026-06-08T19:45:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競走馬の虹彩と眼周囲を使った個体識別（Iris and Periocular Recognition in Arabian Race Horses Using Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-08T19:45:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698498</loc>
  <lastmod>2026-06-08T19:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュース翻訳タスクへのMicrosoftの提出（Microsoft’s Submission to the WMT2018 News Translation Task）</news:title>
   <news:publication_date>2026-06-08T19:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698496</loc>
  <lastmod>2026-06-08T19:44:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データドロップアウト：畳み込みニューラルネットワークの訓練データ最適化（Data Dropout: Optimizing Training Data for Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-08T19:44:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698494</loc>
  <lastmod>2026-06-08T19:44:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件カーネル平均埋め込みのハイパーパラメータ学習（Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds）</news:title>
   <news:publication_date>2026-06-08T19:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698492</loc>
  <lastmod>2026-06-08T19:44:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲートテレポーテーションに基づく普遍的盲目量子計算（Gate Teleportation-based Universal Blind Quantum Computation）</news:title>
   <news:publication_date>2026-06-08T19:44:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698490</loc>
  <lastmod>2026-06-08T19:44:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンデータを使った人間開発指数（HDI）の政策最適化モデル（Open Data Analytical Model for Human Development Index Optimization to Support Government Policy）</news:title>
   <news:publication_date>2026-06-08T19:44:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698488</loc>
  <lastmod>2026-06-08T19:43:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の半教師あり学習にGANを応用する（Semi-supervised Learning on Graphs with Generative Adversarial Nets）</news:title>
   <news:publication_date>2026-06-08T19:43:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698486</loc>
  <lastmod>2026-06-08T18:52:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>将来実験に向けたパートン分布の理論的展望 (Theoretical perspective for the future experiments on parton densities)</news:title>
   <news:publication_date>2026-06-08T18:52:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698484</loc>
  <lastmod>2026-06-08T18:52:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>友人を介した小さな漏洩がもたらすリスク（What’s a Little Leakage Between Friends?）</news:title>
   <news:publication_date>2026-06-08T18:52:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698482</loc>
  <lastmod>2026-06-08T18:52:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆流の注目機構と予測（Attentive Crowd Flow Machines）</news:title>
   <news:publication_date>2026-06-08T18:52:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698480</loc>
  <lastmod>2026-06-08T18:51:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測量間の動的構造を抽出するためのベクトル値再生核ヒルベルト空間における動的モード分解（Dynamic mode decomposition in vector-valued reproducing kernel Hilbert spaces for extracting dynamical structure among observables）</news:title>
   <news:publication_date>2026-06-08T18:51:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698478</loc>
  <lastmod>2026-06-08T18:51:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Extractive Adversarial Networksによる高再現率な説明手法（Extractive Adversarial Networks: High-Recall Explanations for Identifying Personal Attacks in Social Media Posts）</news:title>
   <news:publication_date>2026-06-08T18:51:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698476</loc>
  <lastmod>2026-06-08T18:51:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度・スパースニューラルネットワークの学習と学習可能な正則化（Learning Sparse Low-Precision Neural Networks With Learnable Regularization）</news:title>
   <news:publication_date>2026-06-08T18:51:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698474</loc>
  <lastmod>2026-06-08T18:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットの動作に“様式”を与えるコスト関数（Cost Functions for Robot Motion Style）</news:title>
   <news:publication_date>2026-06-08T18:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698472</loc>
  <lastmod>2026-06-08T17:59:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タグベース推薦システムをプロファイル注入攻撃から守る比較研究（Securing Tag-based recommender systems against profile injection attacks: A comparative study）</news:title>
   <news:publication_date>2026-06-08T17:59:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698470</loc>
  <lastmod>2026-06-08T17:58:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>配分問題における学習のための公正なアルゴリズム（Fair Algorithms for Learning in Allocation Problems）</news:title>
   <news:publication_date>2026-06-08T17:58:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698468</loc>
  <lastmod>2026-06-08T17:57:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Total Recall: 深層階層畳み込みネットワークによる交通標識認識（Total Recall: Understanding Traffic Signs using Deep Hierarchical Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-08T17:57:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698466</loc>
  <lastmod>2026-06-08T17:57:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語指示で操るスケッチ彩色システム（LUCSS: Language-based User-customized Colorization of Scene Sketches）</news:title>
   <news:publication_date>2026-06-08T17:57:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698464</loc>
  <lastmod>2026-06-08T17:57:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調フィルタリングのためのオートエンコーダ大規模学習への試み（Towards Large Scale Training Of Autoencoders For Collaborative Filtering）</news:title>
   <news:publication_date>2026-06-08T17:57:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698462</loc>
  <lastmod>2026-06-08T17:57:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的データに対する自己注意ネットワークと請求処理への応用（A Self-Attention Network for Hierarchical Data Structures with an Application to Claims Management）</news:title>
   <news:publication_date>2026-06-08T17:57:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698460</loc>
  <lastmod>2026-06-08T17:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ガウス型グラフモデルにおける一様推論（UNIFORM INFERENCE IN HIGH-DIMENSIONAL GAUSSIAN GRAPHICAL MODELS）</news:title>
   <news:publication_date>2026-06-08T17:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698458</loc>
  <lastmod>2026-06-08T17:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WFIRSTの弱い重力レンズ計測における光度法赤方偏移校正要件（PHOTOMETRIC REDSHIFT CALIBRATION REQUIREMENTS FOR WFIRST WEAK LENSING COSMOLOGY: PREDICTIONS FROM CANDELS）</news:title>
   <news:publication_date>2026-06-08T17:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698456</loc>
  <lastmod>2026-06-08T16:58:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル協調フィルタリング（Spectral Collaborative Filtering）</news:title>
   <news:publication_date>2026-06-08T16:58:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698454</loc>
  <lastmod>2026-06-08T16:57:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SDSS銀河のHIガスと質量-金属量関係（HI gas content of SDSS galaxies revealed by ALFALFA: implications for the mass-metallicity relation and the environmental dependence of HI in the local Universe）</news:title>
   <news:publication_date>2026-06-08T16:57:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698452</loc>
  <lastmod>2026-06-08T16:56:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能的サイドチャネルのデータ駆動デバッグ（Data-Driven Debugging for Functional Side Channels）</news:title>
   <news:publication_date>2026-06-08T16:56:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698450</loc>
  <lastmod>2026-06-08T16:56:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペルセウス銀河団コアの密度揺らぎはスロッシングかAGNか（What fraction of the density fluctuations in the Perseus cluster core is due to gas sloshing rather than AGN feedback?）</news:title>
   <news:publication_date>2026-06-08T16:56:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698448</loc>
  <lastmod>2026-06-08T16:55:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M31の北部円盤におけるChandraとHubbleの比較（COMPARING CHANDRA AND HUBBLE IN THE NORTHERN DISK OF M31）</news:title>
   <news:publication_date>2026-06-08T16:55:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698446</loc>
  <lastmod>2026-06-08T16:55:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で量子カオスの“見分け”をする（Machine learning, quantum chaos, and pseudorandom evolution）</news:title>
   <news:publication_date>2026-06-08T16:55:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698444</loc>
  <lastmod>2026-06-08T16:03:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガイド付き補助監督によるエンドツーエンド自動運転学習（Learning End-to-end Autonomous Driving using Guided Auxiliary Supervision）</news:title>
   <news:publication_date>2026-06-08T16:03:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698442</loc>
  <lastmod>2026-06-08T15:56:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネスト化したマルチインスタンス画像分類（Nested Multi-Instance Image Classification）</news:title>
   <news:publication_date>2026-06-08T15:56:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698440</loc>
  <lastmod>2026-06-08T15:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス中心注意ネットワークによる人と物の関係検出（iCAN: Instance-Centric Attention Network for Human-Object Interaction Detection）</news:title>
   <news:publication_date>2026-06-08T15:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698438</loc>
  <lastmod>2026-06-08T15:55:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学際的視点で「現実世界」を再定義する教育研究（Using disciplinary perspectives to refine conceptions of the &amp;quot;real world&amp;quot;）</news:title>
   <news:publication_date>2026-06-08T15:55:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698436</loc>
  <lastmod>2026-06-08T15:54:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非侵襲的な転倒検出へ向けた時空間畳み込みオートエンコーダの応用（DeepFall – Non-invasive Fall Detection with Deep Spatio-Temporal Convolutional Autoencoders）</news:title>
   <news:publication_date>2026-06-08T15:54:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698434</loc>
  <lastmod>2026-06-08T15:53:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的モーメンタム手法の統一的解析（A Unified Analysis of Stochastic Momentum Methods for Deep Learning）</news:title>
   <news:publication_date>2026-06-08T15:53:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698432</loc>
  <lastmod>2026-06-08T15:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類データセットの特徴付け — メタラーニングのためのメタフィーチャ研究（Characterizing classification datasets: a study of meta-features for meta-learning）</news:title>
   <news:publication_date>2026-06-08T15:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698430</loc>
  <lastmod>2026-06-08T15:01:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列脳機能接続を深層学習する（Deep Chronnectome Learning via Full Bidirectional LSTM Networks for MCI Diagnosis）</news:title>
   <news:publication_date>2026-06-08T15:01:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698428</loc>
  <lastmod>2026-06-08T15:00:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LUDBによる12誘導心電図（ECG）波形境界注釈データベースの価値（LUDB: a new open-access validation tool for electrocardiogram delineation algorithms）</news:title>
   <news:publication_date>2026-06-08T15:00:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698426</loc>
  <lastmod>2026-06-08T15:00:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>robot gym: クラウド上のシミュレーションで加速するロボット学習（robot gym: accelerated robot training through simulation in the cloud with ROS and Gazebo）</news:title>
   <news:publication_date>2026-06-08T15:00:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698424</loc>
  <lastmod>2026-06-08T15:00:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様な画像データに強いGAN：混合ガウス潜在分布による生成と無監督クラスタリング（Gaussian Mixture Generative Adversarial Networks for Diverse Datasets, and the Unsupervised Clustering of Images）</news:title>
   <news:publication_date>2026-06-08T15:00:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698422</loc>
  <lastmod>2026-06-08T15:00:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内部アンサンブル平均（Inner Ensemble Average: IEA）が畳み込みニューラルネットワークをどう変えるか（IEA: INNER ENSEMBLE AVERAGE WITHIN A CONVOLUTIONAL NEURAL NETWORK）</news:title>
   <news:publication_date>2026-06-08T15:00:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698420</loc>
  <lastmod>2026-06-08T14:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダルデータ融合ワークショップ報告（MMDF2018 Workshop Report）</news:title>
   <news:publication_date>2026-06-08T14:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698418</loc>
  <lastmod>2026-06-08T14:59:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>座標に依存しないスケーラブルな自然勾配の構築（A Coordinate-Free Construction of Scalable Natural Gradient）</news:title>
   <news:publication_date>2026-06-08T14:59:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698416</loc>
  <lastmod>2026-06-08T14:08:07Z</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におけるスキップグラム単語埋め込み（SKIP-GRAM WORD EMBEDDINGS IN HYPERBOLIC SPACE）</news:title>
   <news:publication_date>2026-06-08T14:08:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698414</loc>
  <lastmod>2026-06-08T13:59:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボリック知識をニューラルで一般化する方法（GENERALIZE SYMBOLIC KNOWLEDGE WITH NEURAL RULE ENGINE）</news:title>
   <news:publication_date>2026-06-08T13:59:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698412</loc>
  <lastmod>2026-06-08T13:59:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳の皮質下3D形状モデルの品質管理に対する深層学習の応用（Deep Learning for Quality Control of Subcortical Brain 3D Shape Models）</news:title>
   <news:publication_date>2026-06-08T13:59:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698410</loc>
  <lastmod>2026-06-08T13:58:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PPF-FoldNetによる回転不変な3D局所記述子の無監督学習（PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors）</news:title>
   <news:publication_date>2026-06-08T13:58:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698408</loc>
  <lastmod>2026-06-08T13:58:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitter上の虐待的言語検出の比較研究（Comparative Studies of Detecting Abusive Language on Twitter）</news:title>
   <news:publication_date>2026-06-08T13:58:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698406</loc>
  <lastmod>2026-06-08T13:57:27Z</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への不可視な摂動によるバックドア埋め込み（Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation）</news:title>
   <news:publication_date>2026-06-08T13:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698404</loc>
  <lastmod>2026-06-08T13:57:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>屋外画像におけるベイズ的欠陥検出の実務的意義（Bayesian Outdoor Defect Detection）</news:title>
   <news:publication_date>2026-06-08T13:57:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698402</loc>
  <lastmod>2026-06-08T13:06:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者適応を学ぶ：スピーカー適応のためのメタラーニング手法 (Learning to adapt: a meta-learning approach for speaker adaptation)</news:title>
   <news:publication_date>2026-06-08T13:06:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698400</loc>
  <lastmod>2026-06-08T13:05:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆の中で友人を見つける：マルチモーダルモバイルセンシングによる社会的相互作用の検出（Finding Dory in the Crowd: Detecting Social Interactions using Multi-Modal Mobile Sensing）</news:title>
   <news:publication_date>2026-06-08T13:05:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698398</loc>
  <lastmod>2026-06-08T13:05:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己対戦強化学習を四人制不完全情報ゲームに適用する意義（Application of Self-Play Reinforcement Learning to a Four-Player Game of Imperfect Information）</news:title>
   <news:publication_date>2026-06-08T13:05:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698396</loc>
  <lastmod>2026-06-08T13:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Baidu Apolloの車両縦方向自動キャリブレーション（Baidu Apollo Auto-Calibration System - An Industry-Level Data-Driven and Learning based Vehicle Longitude Dynamic Calibrating Algorithm）</news:title>
   <news:publication_date>2026-06-08T13:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698394</loc>
  <lastmod>2026-06-08T13:04:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少量データで実用音声を作る半教師ありTacotron訓練（SEMI‑SUPERVISED TRAINING FOR IMPROVING DATA EFFICIENCY IN END–TO–END SPEECH SYNTHESIS）</news:title>
   <news:publication_date>2026-06-08T13:04:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698392</loc>
  <lastmod>2026-06-08T13:03:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepCESTによる3Tデータからの9.4T CESTコントラスト予測（DeepCEST: 9.4 T Chemical Exchange Saturation Transfer MRI contrast predicted from 3T data - a proof of concept study）</news:title>
   <news:publication_date>2026-06-08T13:03:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698390</loc>
  <lastmod>2026-06-08T13:03:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VirtualIdentityによるプライバシー保護されたユーザープロファイリング（VirtualIdentity: Privacy-Preserving User Profiling）</news:title>
   <news:publication_date>2026-06-08T13:03:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698388</loc>
  <lastmod>2026-06-08T12:12:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルテンプレート学習によるテキスト生成の再構成（Learning Neural Templates for Text Generation）</news:title>
   <news:publication_date>2026-06-08T12:12:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698386</loc>
  <lastmod>2026-06-08T12:12:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ADMMベースの差分プライバシー分散学習（DP-ADMM: ADMM-based Distributed Learning with Differential Privacy）</news:title>
   <news:publication_date>2026-06-08T12:12:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698384</loc>
  <lastmod>2026-06-08T12:11:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全情報ゲームにおける学習と探索の統合（ExIt-OOS: Towards Learning from Planning in Imperfect Information Games）</news:title>
   <news:publication_date>2026-06-08T12:11:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698382</loc>
  <lastmod>2026-06-08T12:11:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国語談話分割における二言語談話共通性の活用（Chinese Discourse Segmentation Using Bilingual Discourse Commonality）</news:title>
   <news:publication_date>2026-06-08T12:11:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698380</loc>
  <lastmod>2026-06-08T12:10:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深宇宙向けコンテンツ転送のためのDCSMプロトコル（DCSM Protocol for Content Transfer in Deep Space Network）</news:title>
   <news:publication_date>2026-06-08T12:10:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698378</loc>
  <lastmod>2026-06-08T12:10:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNN-PSによる非凸面の法線推定の新機軸（CNN-PS: CNN-based Photometric Stereo for General Non-Convex Surfaces）</news:title>
   <news:publication_date>2026-06-08T12:10:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698376</loc>
  <lastmod>2026-06-08T12:10:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似性の識別学習と群等変表現（Discriminative Learning of Similarity and Group Equivariant Representations）</news:title>
   <news:publication_date>2026-06-08T12:10:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698374</loc>
  <lastmod>2026-06-08T11:18:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子光学ニューラルネットワーク（Quantum Optical Neural Networks）</news:title>
   <news:publication_date>2026-06-08T11:18:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698372</loc>
  <lastmod>2026-06-08T11:10:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効果的な深層埋め込みによるゼロショット学習の実践（Towards Effective Deep Embedding for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-06-08T11:10:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698370</loc>
  <lastmod>2026-06-08T11:09:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラショナルニューラルネットワークによるグラフ畳み込みのジャンプ不連続近似（Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator）</news:title>
   <news:publication_date>2026-06-08T11:09:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698368</loc>
  <lastmod>2026-06-08T11:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練例のスペクトル事前変調が位相抽出ニューラルネットワーク(PhENN)の空間分解能を高める（Spectral pre-modulation of training examples enhances the spatial resolution of the Phase Extraction Neural Network (PhENN))</news:title>
   <news:publication_date>2026-06-08T11:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698366</loc>
  <lastmod>2026-06-08T11:08:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシーで変える分布変化検出（Differentially Private Change-Point Detection）</news:title>
   <news:publication_date>2026-06-08T11:08:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698364</loc>
  <lastmod>2026-06-08T11:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力波でガンマ線バーストを事前予測する可能性（Forecasting Gamma-Ray Bursts using Gravitational Waves）</news:title>
   <news:publication_date>2026-06-08T11:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698362</loc>
  <lastmod>2026-06-08T11:07:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペトリネットと流れるものの機械（Petri Nets and Machines of Things That Flow）</news:title>
   <news:publication_date>2026-06-08T11:07:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698360</loc>
  <lastmod>2026-06-08T10:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェンダー中立な単語埋め込みの学習（Learning Gender-Neutral Word Embeddings）</news:title>
   <news:publication_date>2026-06-08T10:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698358</loc>
  <lastmod>2026-06-08T10:15:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交通監視映像による適応的異常検知（AAD: Adaptive Anomaly Detection through traffic surveillance videos）</news:title>
   <news:publication_date>2026-06-08T10:15:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698356</loc>
  <lastmod>2026-06-08T10:15:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>戦場のIoTに心理を持ち込む──動的心理ゲーム理論によるIoBT防御（Dynamic Psychological Game Theory for Secure Internet of Battlefield Things (IoBT) Systems）</news:title>
   <news:publication_date>2026-06-08T10:15:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698354</loc>
  <lastmod>2026-06-08T10:15:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字単位変換における非単調ハード注意の導出（Hard Non-Monotonic Attention for Character-Level Transduction）</news:title>
   <news:publication_date>2026-06-08T10:15:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698352</loc>
  <lastmod>2026-06-08T10:14:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非拘束環境での虹彩認証における前処理が深層表現に与える影響（The Impact of Preprocessing on Deep Representations for Iris Recognition on Unconstrained Environments）</news:title>
   <news:publication_date>2026-06-08T10:14:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698350</loc>
  <lastmod>2026-06-08T10:14:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>展開型ISTAの線形収束理論と実用的重み・閾値（Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds）</news:title>
   <news:publication_date>2026-06-08T10:14:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698348</loc>
  <lastmod>2026-06-08T10:13:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Drosophilaにおける転写後制御を物理に基づくガウス過程で記述する手法（PHYSICALLY-INSPIRED GAUSSIAN PROCESS MODELS FOR POST-TRANSCRIPTIONAL REGULATION IN DROSOPHILA）</news:title>
   <news:publication_date>2026-06-08T10:13:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698346</loc>
  <lastmod>2026-06-08T09:22:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無制約学習が暗黙に優先する公平性基準（The implicit fairness criterion of unconstrained learning）</news:title>
   <news:publication_date>2026-06-08T09:22:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698344</loc>
  <lastmod>2026-06-08T09:22:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機会的アクティブラーニングの方策学習（Learning a Policy for Opportunistic Active Learning）</news:title>
   <news:publication_date>2026-06-08T09:22:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698342</loc>
  <lastmod>2026-06-08T09:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な直感的物理モデル（Interpretable Intuitive Physics Model）</news:title>
   <news:publication_date>2026-06-08T09:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698340</loc>
  <lastmod>2026-06-08T09:20:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一光子とカイラルフォノンのもたらす新しい量子相関（Entanglement of single-photons and chiral phonons in atomically thin WSe2）</news:title>
   <news:publication_date>2026-06-08T09:20:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698338</loc>
  <lastmod>2026-06-08T09:20:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カルダヤ三次元多様体上の直線束コホモロジーの公式化 (Formulae for Line Bundle Cohomology on Calabi–Yau Threefolds)</news:title>
   <news:publication_date>2026-06-08T09:20:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698336</loc>
  <lastmod>2026-06-08T09:20:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移の銀河合体で星形成率増加や金属希釈は見られない（THE MOSDEF SURVEY: NO SIGNIFICANT ENHANCEMENT IN STAR FORMATION OR DEFICIT IN METALLICITY IN MERGING GALAXY PAIRS AT 1.5 ≲z ≲3.51）</news:title>
   <news:publication_date>2026-06-08T09:20:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698334</loc>
  <lastmod>2026-06-08T09:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル言語モデルによる文法誘導の再現研究（Grammar Induction with Neural Language Models: An Unusual Replication）</news:title>
   <news:publication_date>2026-06-08T09:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698332</loc>
  <lastmod>2026-06-08T08:28:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポートフォリオ管理における敵対的深層強化学習（Adversarial Deep Reinforcement Learning in Portfolio Management）</news:title>
   <news:publication_date>2026-06-08T08:28:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698330</loc>
  <lastmod>2026-06-08T08:28:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問応答のためのニューラル合成的記号意味論（Neural Compositional Denotational Semantics for Question Answering）</news:title>
   <news:publication_date>2026-06-08T08:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698328</loc>
  <lastmod>2026-06-08T08:27:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字単位ニューラル機械翻訳の再検討 — 容量と圧縮を巡る検討 (Revisiting Character-Based Neural Machine Translation with Capacity and Compression)</news:title>
   <news:publication_date>2026-06-08T08:27:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698326</loc>
  <lastmod>2026-06-08T08:27:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Certified Mapper：Mapper解析の正当性を確かめる反復的検定手法（CERTIFIED MAPPER: REPEATED TESTING FOR ACYCLICITY AND OBSTRUCTIONS TO THE NERVE LEMMA）</news:title>
   <news:publication_date>2026-06-08T08:27:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698324</loc>
  <lastmod>2026-06-08T08:26:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書横断で推論する質問応答とグラフ畳み込みネットワーク（Question Answering by Reasoning Across Documents with Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-06-08T08:26:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698322</loc>
  <lastmod>2026-06-08T08:26:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多被験者fMRIデータからの群代表機能ネットワーク推定（Group-Representative Functional Network Estimation from Multi-Subject fMRI Data via MRF-based Image Segmentation）</news:title>
   <news:publication_date>2026-06-08T08:26:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698320</loc>
  <lastmod>2026-06-08T08:26:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を用いたニューラルテキスト分割（Attention-based Neural Text Segmentation）</news:title>
   <news:publication_date>2026-06-08T08:26:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698318</loc>
  <lastmod>2026-06-08T07:35:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tabu DropoutによるDropoutの多様化と正則化効果（DROPOUT WITH TABU STRATEGY FOR REGULARIZING DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-08T07:35:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698316</loc>
  <lastmod>2026-06-08T07:35:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声だけで映画を探すインターフェースから得た初期知見（Early Lessons from a Voice-Only Interface for Finding Movies）</news:title>
   <news:publication_date>2026-06-08T07:35:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698314</loc>
  <lastmod>2026-06-08T07:34:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極値理論によるオープンセット分類（Extreme Value Theory for Open Set Classification – GPD and GEV Classifiers）</news:title>
   <news:publication_date>2026-06-08T07:34:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698312</loc>
  <lastmod>2026-06-08T07:34:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レビュー有用性予測におけるEmbedding-Gated CNNの実践的意義（Review Helpfulness Prediction with Embedding-Gated CNN）</news:title>
   <news:publication_date>2026-06-08T07:34:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698310</loc>
  <lastmod>2026-06-08T07:34:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クオークニウム生成における二重パートン散乱の理論解析（Theoretical analysis of double parton scatterings in quarkonium production in proton-proton collisions at the LHC）</news:title>
   <news:publication_date>2026-06-08T07:34:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698308</loc>
  <lastmod>2026-06-08T07:33:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>規制と違法適応のはざまで（Enforcing Regulation under Illicit Adaptation）</news:title>
   <news:publication_date>2026-06-08T07:33:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698306</loc>
  <lastmod>2026-06-08T07:33:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トップダウン注意型再帰VLAD符号化による動画行動認識（Top-down Attention Recurrent VLAD Encoding for Action Recognition in Videos）</news:title>
   <news:publication_date>2026-06-08T07:33:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698304</loc>
  <lastmod>2026-06-08T06:42:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称KLダイバージェンスに基づく多項分布テキスト分類のセントロイド推定（Centroid estimation based on symmetric KL divergence for Multinomial text classification problem）</news:title>
   <news:publication_date>2026-06-08T06:42:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698302</loc>
  <lastmod>2026-06-08T06:42:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的時間伸縮距離の半計量化（Semi-Metrification of the Dynamic Time Warping Distance）</news:title>
   <news:publication_date>2026-06-08T06:42:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698300</loc>
  <lastmod>2026-06-08T06:42:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クォークニアを用いたグルーオンTMDの探索 (Probing the gluon TMDs with quarkonia)</news:title>
   <news:publication_date>2026-06-08T06:42:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698298</loc>
  <lastmod>2026-06-08T06:41:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非構造化ニュースから概念ツリーを作る手法（Analyze Unstructured Data Patterns for Conceptual Representation）</news:title>
   <news:publication_date>2026-06-08T06:41:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698296</loc>
  <lastmod>2026-06-08T06:41:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デバイス配慮型ニューラルアーキテクチャ探索のパレート最適化（SEARCHING TOWARD PARETO-OPTIMAL DEVICE-AWARE NEURAL ARCHITECTURES）</news:title>
   <news:publication_date>2026-06-08T06:41:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698294</loc>
  <lastmod>2026-06-08T06:40:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>岩石ファシーズ分類に物理を取り入れた特徴量拡張の応用（Application of Machine Learning in Rock Facies Classification with Physics-Motivated Feature Augmentation）</news:title>
   <news:publication_date>2026-06-08T06:40:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698292</loc>
  <lastmod>2026-06-08T06:40:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマホのタイピングで感情を読む時代が来るか（dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction）</news:title>
   <news:publication_date>2026-06-08T06:40:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698290</loc>
  <lastmod>2026-06-08T05:49:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人撮影写真列からの飲食場所認識（MACNet: Multi-scale Atrous Convolution Networks for Food Places Classification in Egocentric Photo-streams）</news:title>
   <news:publication_date>2026-06-08T05:49:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698288</loc>
  <lastmod>2026-06-08T05:49:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関時系列予測における深層ニューラルネットワークの要点（Correlated Time Series Forecasting using Deep Neural Networks: A Summary of Results）</news:title>
   <news:publication_date>2026-06-08T05:49:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698286</loc>
  <lastmod>2026-06-08T05:49:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態抽象化による近似的探索の理論と実務的示唆（Approximate Exploration through State Abstraction）</news:title>
   <news:publication_date>2026-06-08T05:49:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698284</loc>
  <lastmod>2026-06-08T05:48:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソル整列に基づくドメイン適応とその応用（Tensor Alignment Based Domain Adaptation for Hyperspectral Image Classification）</news:title>
   <news:publication_date>2026-06-08T05:48:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698282</loc>
  <lastmod>2026-06-08T05:48:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジでのラベルなし学習によるトラフィック制御（Label-less Learning for Traffic Control in an Edge Network）</news:title>
   <news:publication_date>2026-06-08T05:48:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698280</loc>
  <lastmod>2026-06-08T05:48:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習済みモデルの全体説明のための規則導出（Rule induction for global explanation of trained models）</news:title>
   <news:publication_date>2026-06-08T05:48:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698278</loc>
  <lastmod>2026-06-08T05:48:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理における深層学習の要点と実務的示唆（Notes on Deep Learning for NLP）</news:title>
   <news:publication_date>2026-06-08T05:48:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698276</loc>
  <lastmod>2026-06-08T04:57:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別最適化された問題作成への道（Bringing personalized learning into computer-aided question generation）</news:title>
   <news:publication_date>2026-06-08T04:57:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698274</loc>
  <lastmod>2026-06-08T04:57:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメイン協調学習による高分解能画像分類の改良（Cross-Domain Collaborative Learning via Cluster Canonical Correlation Analysis and Random Walker for Hyperspectral Image Classification）</news:title>
   <news:publication_date>2026-06-08T04:57:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698272</loc>
  <lastmod>2026-06-08T04:57:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の遠隔監督を組み合わせる低資源言語の品詞タグ付け（Distant Supervision from Disparate Sources for Low-Resource Part-of-Speech Tagging）</news:title>
   <news:publication_date>2026-06-08T04:57:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698270</loc>
  <lastmod>2026-06-08T04:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>英語学習者向け個別化自動問題生成の効果と要点（Development and Evaluation of a Personalized Computer-aided Question Generation for English Learners to Improve Proficiency and Correct Mistakes）</news:title>
   <news:publication_date>2026-06-08T04:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698268</loc>
  <lastmod>2026-06-08T04:56:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GWAPによる潜在因子の可視化と説明（Understanding Latent Factors Using a GWAP）</news:title>
   <news:publication_date>2026-06-08T04:56:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698266</loc>
  <lastmod>2026-06-08T04:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>演奏拡張技法の認識が切り開く次の段階（Extended playing techniques: The next milestone in musical instrument recognition）</news:title>
   <news:publication_date>2026-06-08T04:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698264</loc>
  <lastmod>2026-06-08T04:55:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カタリナ観測から更新された4680個のAlgol型食変光連星カタログ（An Updated Catalog of 4680 Northern Eclipsing Binaries with Algol-Type Light Curve Morphology in the Catalina Sky Surveys）</news:title>
   <news:publication_date>2026-06-08T04:55:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698262</loc>
  <lastmod>2026-06-08T04:04:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極端にデータが少ない分類のための深層敵対的データ拡張（DADA: Deep Adversarial Data Augmentation for Extremely Low Data Regime Classification）</news:title>
   <news:publication_date>2026-06-08T04:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698260</loc>
  <lastmod>2026-06-08T04:04:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線のインペインティングと生成モデルの適用（Chest X-ray Inpainting with Deep Generative Models）</news:title>
   <news:publication_date>2026-06-08T04:04:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698258</loc>
  <lastmod>2026-06-08T04:04:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味タグ付けから学べること（What can we learn from Semantic Tagging?）</news:title>
   <news:publication_date>2026-06-08T04:04:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698256</loc>
  <lastmod>2026-06-08T04:03:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QuasarNET：人間並みのスペクトル分類と赤方偏移推定（QuasarNET: Human-level spectral classification and redshifting with Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-08T04:03:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698254</loc>
  <lastmod>2026-06-08T04:03:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNを用いた肺がん患者の画像ベース生存予測（Image-Based Survival Prediction for Lung Cancer Patients Using CNNs）</news:title>
   <news:publication_date>2026-06-08T04:03:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698252</loc>
  <lastmod>2026-06-08T04:03:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接ブースティング：非微分損失を最小化する弱学習器の集約（Proximal boosting: aggregating weak learners to minimize non-differentiable losses）</news:title>
   <news:publication_date>2026-06-08T04:03:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698250</loc>
  <lastmod>2026-06-08T04:03:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Scalingアルゴリズムと応用の最近の進展（Recent progress on scaling algorithms and applications）</news:title>
   <news:publication_date>2026-06-08T04:03:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698248</loc>
  <lastmod>2026-06-08T03:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈の輸送で表現を作る――Context Mover’s Distance とバリセントル（Context Mover’s Distance &amp;amp; Barycenters）</news:title>
   <news:publication_date>2026-06-08T03:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698246</loc>
  <lastmod>2026-06-08T03:11:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子選択暗号文攻撃とLearning with Errorsの脆弱性（On Quantum Chosen-Ciphertext Attacks and Learning with Errors）</news:title>
   <news:publication_date>2026-06-08T03:11:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698244</loc>
  <lastmod>2026-06-08T03:10:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>APRILによる対話的要約学習の実務的意義（APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-08T03:10:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698242</loc>
  <lastmod>2026-06-08T03:10:07Z</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ICA: 非凸最適化の大域動態を拡散過程で理解する（Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes）</news:title>
   <news:publication_date>2026-06-08T03:10:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698240</loc>
  <lastmod>2026-06-08T03:09:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像付きコミュニティQ&amp;amp;AのためのVQA応用手法（Adapting Visual Question Answering Models for Enhancing Multimodal Community Q&amp;amp;A Platforms）</news:title>
   <news:publication_date>2026-06-08T03:09:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698238</loc>
  <lastmod>2026-06-08T03:09:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン主成分推定に対する拡散近似と全体収束の考察（Diffusion Approximations for Online Principal Component Estimation and Global Convergence）</news:title>
   <news:publication_date>2026-06-08T03:09:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698236</loc>
  <lastmod>2026-06-08T03:09:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wavelet によるエッジ強調が CNN の性能を変える（Wavelet based edge feature enhancement for convolutional neural networks）</news:title>
   <news:publication_date>2026-06-08T03:09:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698234</loc>
  <lastmod>2026-06-08T02:18:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交渉対話における戦略と生成の切り離し（Decoupling Strategy and Generation in Negotiation Dialogues）</news:title>
   <news:publication_date>2026-06-08T02:18:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698232</loc>
  <lastmod>2026-06-08T02:17:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメイン特徴に基づく音声変換（Voice Conversion Based on Cross-Domain Features Using Variational Auto Encoders）</news:title>
   <news:publication_date>2026-06-08T02:17:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698230</loc>
  <lastmod>2026-06-08T02:17:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再生攻撃（リプレイ）に対する多目的学習による音声なりすまし検出（Replay spoofing detection system for automatic speaker verification using multi-task learning of noise classes）</news:title>
   <news:publication_date>2026-06-08T02:17:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698228</loc>
  <lastmod>2026-06-08T02:17:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度単語照合による語義対応を取り入れたネットワーク埋め込み（Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment）</news:title>
   <news:publication_date>2026-06-08T02:17:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698226</loc>
  <lastmod>2026-06-08T02:16:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震の震源をネットワークで特定する深層学習手法（Locating earthquakes with a network of seismic stations via a deep learning method）</news:title>
   <news:publication_date>2026-06-08T02:16:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698224</loc>
  <lastmod>2026-06-08T02:16:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経路上の弾性帯：DTWの下限を下げる新しい枠組みと手法（Elastic bands across the path: A new framework and method to lower bound DTW）</news:title>
   <news:publication_date>2026-06-08T02:16:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698222</loc>
  <lastmod>2026-06-08T02:16:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド量子コンピュータによる非線形回帰（Nonlinear regression based on a hybrid quantum computer）</news:title>
   <news:publication_date>2026-06-08T02:16:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698220</loc>
  <lastmod>2026-06-08T01:25:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的スパース部分空間クラスタリングと遅延アソシエーション（Probabilistic Sparse Subspace Clustering Using Delayed Association）</news:title>
   <news:publication_date>2026-06-08T01:25:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698218</loc>
  <lastmod>2026-06-08T01:25:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>風力発電アレイ配置が大規模ファームの出力に与える影響（Effect of layout on asymptotic boundary layer regime in deep wind farms）</news:title>
   <news:publication_date>2026-06-08T01:25:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698216</loc>
  <lastmod>2026-06-08T01:24:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身体表現から感情を認識する自動化の挑戦（ARBEE: Towards Automated Recognition of Bodily Expression of Emotion In the Wild）</news:title>
   <news:publication_date>2026-06-08T01:24:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698214</loc>
  <lastmod>2026-06-08T01:23:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野良画像から学ぶ非線形3Dモーファブルモデル（On Learning 3D Face Morphable Model from In-the-wild Images）</news:title>
   <news:publication_date>2026-06-08T01:23:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698212</loc>
  <lastmod>2026-06-08T01:23:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字レベルのニューラルネットワークが言語ルールを発見するか（Explaining Character-Aware Neural Networks for Word-Level Prediction: Do They Discover Linguistic Rules?）</news:title>
   <news:publication_date>2026-06-08T01:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698210</loc>
  <lastmod>2026-06-08T01:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エゴセントリック映像における時間的注目度適応（Temporal Saliency Adaptation in Egocentric Videos）</news:title>
   <news:publication_date>2026-06-08T01:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698208</loc>
  <lastmod>2026-06-08T01:23:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少データ環境での意味役割付与を強化する半教師あり学習（Towards Semi-Supervised Learning for Deep Semantic Role Labeling）</news:title>
   <news:publication_date>2026-06-08T01:23:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698206</loc>
  <lastmod>2026-06-08T00:31:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層軌跡LSTMの発想と実務的意味（Layer Trajectory LSTM）</news:title>
   <news:publication_date>2026-06-08T00:31:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698204</loc>
  <lastmod>2026-06-08T00:23:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層化量子化表現によるスクリプト生成（Hierarchical Quantized Representations for Script Generation）</news:title>
   <news:publication_date>2026-06-08T00:23:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698202</loc>
  <lastmod>2026-06-08T00:23:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LiDARだけで動く車両の動態を理解する深層CNN（Deep Lidar CNN to Understand the Dynamics of Moving Vehicles）</news:title>
   <news:publication_date>2026-06-08T00:23:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698200</loc>
  <lastmod>2026-06-08T00:22:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リプシッツ正則化による深層ニューラルネットワークの汎化と攻撃耐性（Lipschitz Regularized Deep Neural Networks Generalize and Are Adversarially Robust）</news:title>
   <news:publication_date>2026-06-08T00:22:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698198</loc>
  <lastmod>2026-06-08T00:22:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未観測交絡を想定した条件付き平均処置効果の上界と下界（Bounds on the conditional and average treatment effect with unobserved confounding factors）</news:title>
   <news:publication_date>2026-06-08T00:22:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698196</loc>
  <lastmod>2026-06-08T00:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタックド・オートエンコーダによるT2Dゲノムデータのエピスタシス抽出（Extracting Epistatic Interactions in Type 2 Diabetes Genome-Wide Data Using Stacked Autoencoder）</news:title>
   <news:publication_date>2026-06-08T00:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698194</loc>
  <lastmod>2026-06-08T00:22:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話で解く自然言語規則の解釈（Interpretation of Natural Language Rules in Conversational Machine Reading）</news:title>
   <news:publication_date>2026-06-08T00:22:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698192</loc>
  <lastmod>2026-06-07T23:30:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復最適化での適応的プライバシー配分（Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget）</news:title>
   <news:publication_date>2026-06-07T23:30:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698190</loc>
  <lastmod>2026-06-07T23:30:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形態素・音韻サブワード表現による単語埋め込みの新言語適応（Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations）</news:title>
   <news:publication_date>2026-06-07T23:30:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698188</loc>
  <lastmod>2026-06-07T23:30:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InfoInternetによる教育アクセスの拡張（InfoInternet for Education in the Global South）</news:title>
   <news:publication_date>2026-06-07T23:30:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698186</loc>
  <lastmod>2026-06-07T23:29:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Krasulina推定量の収束速度（Convergence Rate of Krasulina Estimator）</news:title>
   <news:publication_date>2026-06-07T23:29:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698184</loc>
  <lastmod>2026-06-07T23:29:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文を分割して書き換える学習（Learning To Split and Rephrase From Wikipedia Edit History）</news:title>
   <news:publication_date>2026-06-07T23:29:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698182</loc>
  <lastmod>2026-06-07T23:29:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要語に注目して情報を引く新方式（Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question Answering）</news:title>
   <news:publication_date>2026-06-07T23:29:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698180</loc>
  <lastmod>2026-06-07T23:29:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話型エージェントの計画学習を堅牢にする方法（Discriminative Deep Dyna-Q: Robust Planning for Dialogue Policy Learning）</news:title>
   <news:publication_date>2026-06-07T23:29:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698178</loc>
  <lastmod>2026-06-07T22:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衝突する銀河団Abell 2034の新知見（New insights on the dissociative merging galaxy cluster Abell 2034）</news:title>
   <news:publication_date>2026-06-07T22:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698176</loc>
  <lastmod>2026-06-07T22:37:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常雑音下の音声雑音除去におけるモンテカルロドロップアウトの活用（Using Monte Carlo dropout for non-stationary noise reduction from speech）</news:title>
   <news:publication_date>2026-06-07T22:37:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698174</loc>
  <lastmod>2026-06-07T22:37:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WikiAtomicEdits：編集履歴から学ぶ言語と談話のコーパス（WikiAtomicEdits: A Multilingual Corpus of Wikipedia Edits for Modeling Language and Discourse）</news:title>
   <news:publication_date>2026-06-07T22:37:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698172</loc>
  <lastmod>2026-06-07T22:36:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Taste Groupを用いた協調フィルタリング（Using Taste Groups for Collaborative Filtering）</news:title>
   <news:publication_date>2026-06-07T22:36:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698170</loc>
  <lastmod>2026-06-07T22:36:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストのプライバシーを守るニューラル表現（Privacy-preserving Neural Representations of Text）</news:title>
   <news:publication_date>2026-06-07T22:36:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698168</loc>
  <lastmod>2026-06-07T22:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習システムの差分ファジング検査（DLFuzz: Differential Fuzzing Testing of Deep Learning Systems）</news:title>
   <news:publication_date>2026-06-07T22:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698166</loc>
  <lastmod>2026-06-07T22:35:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号付きラプラシアンを用いた識別表現学習（Learning Discriminative Representation with Signed Laplacian Restricted Boltzmann Machine）</news:title>
   <news:publication_date>2026-06-07T22:35:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698164</loc>
  <lastmod>2026-06-07T21:44:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単層ニューラルネットワークの平均場解析と中心極限定理（Mean Field Analysis of Neural Networks: A Central Limit Theorem）</news:title>
   <news:publication_date>2026-06-07T21:44:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698162</loc>
  <lastmod>2026-06-07T21:43:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列分解は共起行列の有効表現である（Matrix Factorization Equals Efficient Co-occurrence Representation）</news:title>
   <news:publication_date>2026-06-07T21:43:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698160</loc>
  <lastmod>2026-06-07T21:43:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の根拠から機械の注意を導く方法（Deriving Machine Attention from Human Rationales）</news:title>
   <news:publication_date>2026-06-07T21:43:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698158</loc>
  <lastmod>2026-06-07T21:42:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D認識を取り込んだシーン編集（3D-Aware Scene Manipulation via Inverse Graphics）</news:title>
   <news:publication_date>2026-06-07T21:42:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698156</loc>
  <lastmod>2026-06-07T21:42:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rational Recurrences（Rational Recurrences）</news:title>
   <news:publication_date>2026-06-07T21:42:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698154</loc>
  <lastmod>2026-06-07T21:42:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用遷移型DAGパーサによるUniversal Dependencies解析（Universal Dependency Parsing with a General Transition-Based DAG Parser）</news:title>
   <news:publication_date>2026-06-07T21:42:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698152</loc>
  <lastmod>2026-06-07T21:41:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン適応における特徴の同時最適化（Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation）</news:title>
   <news:publication_date>2026-06-07T21:41:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698150</loc>
  <lastmod>2026-06-07T20:49:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二言語辞書の自動構築を確率モデルで解く（A Discriminative Latent-Variable Model for Bilingual Lexicon Induction）</news:title>
   <news:publication_date>2026-06-07T20:49:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698148</loc>
  <lastmod>2026-06-07T20:49:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載CANデータの形状を利用した侵入検知（Exploiting the Shape of CAN Data for In-Vehicle Intrusion Detection）</news:title>
   <news:publication_date>2026-06-07T20:49:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698146</loc>
  <lastmod>2026-06-07T20:49:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル推論における知識ギャップを埋める手法（Bridging Knowledge Gaps in Neural Entailment via Symbolic Models）</news:title>
   <news:publication_date>2026-06-07T20:49:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698144</loc>
  <lastmod>2026-06-07T20:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重いbクォークを含む t¯t b¯b 生成のNLOマッチング（NLO matching for t¯tb¯b production with massive b quarks）</news:title>
   <news:publication_date>2026-06-07T20:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698142</loc>
  <lastmod>2026-06-07T20:48:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路網の位相抽出に向けた反復型深層学習（Iterative Deep Learning for Road Topology Extraction）</news:title>
   <news:publication_date>2026-06-07T20:48:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698140</loc>
  <lastmod>2026-06-07T20:48:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己認識システムとオーガニックコンピューティングの比較（Comparison of Self-Aware and Organic Computing Systems）</news:title>
   <news:publication_date>2026-06-07T20:48:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698138</loc>
  <lastmod>2026-06-07T20:47:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最先端のPOWHEGジェネレータによるトップ質量測定（State of the art POWHEG generators for top mass measurements at the LHC）</news:title>
   <news:publication_date>2026-06-07T20:47:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698136</loc>
  <lastmod>2026-06-07T19:56:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン選択による感情分類の移転最適化（Distance Based Source Domain Selection for Sentiment Classification）</news:title>
   <news:publication_date>2026-06-07T19:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698134</loc>
  <lastmod>2026-06-07T19:56:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子内点法が開く線形計画法・半正定値計画法の新展開（A Quantum Interior Point Method for LPs and SDPs）</news:title>
   <news:publication_date>2026-06-07T19:56:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698132</loc>
  <lastmod>2026-06-07T19:56:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スーパーハイウェイで解くデータ希薄性（Superhighway: Bypass Data Sparsity in Cross-Domain CF）</news:title>
   <news:publication_date>2026-06-07T19:56:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698130</loc>
  <lastmod>2026-06-07T19:55:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層状トリカルコゲナイドにおける圧力誘起Mott金属–絶縁体転移（Mott metal-insulator transitions in pressurized layered trichalcogenides）</news:title>
   <news:publication_date>2026-06-07T19:55:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698128</loc>
  <lastmod>2026-06-07T19:55:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られた光子コピーから量子ビット状態を学習で復元する（Reconstruction of a Photonic Qubit State with Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-07T19:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698126</loc>
  <lastmod>2026-06-07T19:55:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮想化ネットワークサービスの開発機能導入（Introducing Development Features for Virtualized Network Services）</news:title>
   <news:publication_date>2026-06-07T19:55:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698124</loc>
  <lastmod>2026-06-07T19:54:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語義曖昧性解消のための知識駆動型教師あり学習フレームワーク（KDSL: a Knowledge-Driven Supervised Learning Framework for Word Sense Disambiguation）</news:title>
   <news:publication_date>2026-06-07T19:54:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698122</loc>
  <lastmod>2026-06-07T19:02:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形分類器と最小二乗誤差、外れ値の扱い（Linear classifier, least-squares cost function, and outliers）</news:title>
   <news:publication_date>2026-06-07T19:02:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698120</loc>
  <lastmod>2026-06-07T19:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D手の姿勢と形状のエンドツーエンド推定（DeepHPS: End-to-end Estimation of 3D Hand Pose and Shape by Learning from Synthetic Depth）</news:title>
   <news:publication_date>2026-06-07T19:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698118</loc>
  <lastmod>2026-06-07T19:01:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像を起点に音楽を薦める表現学習（Representation Learning for Image-based Music Recommendation）</news:title>
   <news:publication_date>2026-06-07T19:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698116</loc>
  <lastmod>2026-06-07T19:01:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散乱媒質における超音波変調光トモグラフィー：光学診断窓における持続的スペクトルホールバーンに基づくフラックスフィルタリング (Ultrasound modulated optical tomography in scattering media: flux filtering based on persistent spectral hole burning in the optical diagnosis window)</news:title>
   <news:publication_date>2026-06-07T19:01:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698114</loc>
  <lastmod>2026-06-07T19:01:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>W+W−生成過程の高精度予測とマッチング技術（W +W −production at NNLO+PS）</news:title>
   <news:publication_date>2026-06-07T19:01:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698112</loc>
  <lastmod>2026-06-07T19:01:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所性誘導学習による歩行者属性認識（Localization Guided Learning for Pedestrian Attribute Recognition）</news:title>
   <news:publication_date>2026-06-07T19:01:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698110</loc>
  <lastmod>2026-06-07T18:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Policy Guided Monte Carlo（Policy Guided Monte Carlo: Reinforcement Learning Markov Chain Dynamics）</news:title>
   <news:publication_date>2026-06-07T18:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698108</loc>
  <lastmod>2026-06-07T18:09:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発話の乱れを自動検出する自己相関ニューラルネットワーク（Disfluency Detection using Auto-Correlational Neural Networks）</news:title>
   <news:publication_date>2026-06-07T18:09:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698106</loc>
  <lastmod>2026-06-07T18:07:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMを使ったノイジーチャネルによる発話の脱流暢検出（Disfluency Detection using a Noisy Channel Model and a Deep Neural Language Model）</news:title>
   <news:publication_date>2026-06-07T18:07:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698104</loc>
  <lastmod>2026-06-07T18:07:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カプセルネットにおける認知的一貫性ルーティング（Cognitive Consistency Routing Algorithm of Capsule-network）</news:title>
   <news:publication_date>2026-06-07T18:07:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698102</loc>
  <lastmod>2026-06-07T18:07:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>損失関数、公理、そして査読（Loss Functions, Axioms, and Peer Review）</news:title>
   <news:publication_date>2026-06-07T18:07:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698100</loc>
  <lastmod>2026-06-07T18:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>比較ネットワーク埋め込み可視化のためのEmbeddingVis（EmbeddingVis: A Visual Analytics Approach to Comparative Network Embedding Inspection）</news:title>
   <news:publication_date>2026-06-07T18:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698098</loc>
  <lastmod>2026-06-07T18:06:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手作り特徴量は死んでいない：深層モデルにおける再評価（Evaluating the Utility of Hand-crafted Features in Sequence Labelling）</news:title>
   <news:publication_date>2026-06-07T18:06:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698096</loc>
  <lastmod>2026-06-07T17:15:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混成次元における超低温Yb–7Li混合系の実験的実現（Experimental realization of ultracold Yb-7Li mixtures in mixed dimensions）</news:title>
   <news:publication_date>2026-06-07T17:15:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698094</loc>
  <lastmod>2026-06-07T17:15:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト表現の敵対的分解（Adversarial Decomposition of Text Representation）</news:title>
   <news:publication_date>2026-06-07T17:15:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698092</loc>
  <lastmod>2026-06-07T17:15:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散電力網の運用リスク評価のための敵対的特徴学習（Adversarial Feature Learning of Online Monitoring Data for Operational Risk Assessment in Distribution Networks）</news:title>
   <news:publication_date>2026-06-07T17:15:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698090</loc>
  <lastmod>2026-06-07T17:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理シナリオ間で知識を移す――ニューラルネットによる転移の実証 (Migrating Knowledge between Physical Scenarios based on Artificial Neural Networks)</news:title>
   <news:publication_date>2026-06-07T17:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698088</loc>
  <lastmod>2026-06-07T17:14:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要度重み付けと変分推論（Importance Weighting and Variational Inference）</news:title>
   <news:publication_date>2026-06-07T17:14:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698086</loc>
  <lastmod>2026-06-07T17:14:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一例学習による知識グラフの関係推定（One-Shot Relational Learning for Knowledge Graphs）</news:title>
   <news:publication_date>2026-06-07T17:14:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698084</loc>
  <lastmod>2026-06-07T17:13:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文献参照解析を「選ぶ」時代へ（ParsRec: Meta-Learning Recommendations for Bibliographic Reference Parsing）</news:title>
   <news:publication_date>2026-06-07T17:13:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698082</loc>
  <lastmod>2026-06-07T16:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピラミッド型再帰ユニットによる言語モデリング（Pyramidal Recurrent Unit for Language Modeling）</news:title>
   <news:publication_date>2026-06-07T16:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698080</loc>
  <lastmod>2026-06-07T16:22:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>帯域効率を考慮したリアルタイム歩行者検出手法（REAL-TIME PEDESTRIAN DETECTION APPROACH WITH AN EFFICIENT DATA COMMUNICATION BANDWIDTH STRATEGY）</news:title>
   <news:publication_date>2026-06-07T16:22:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698078</loc>
  <lastmod>2026-06-07T16:21:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NGC-3175銀河群における微小衛星銀河の調査（Faint Satellite Population of the NGC-3175 Group - a Local Group Analogue）</news:title>
   <news:publication_date>2026-06-07T16:21:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698076</loc>
  <lastmod>2026-06-07T16:20:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既知の言語知識を新言語に生かす手法 ― Python知識の移転支援（It’s Like Python But: Towards Supporting Transfer of Programming Language Knowledge）</news:title>
   <news:publication_date>2026-06-07T16:20:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698074</loc>
  <lastmod>2026-06-07T16:20:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空画像における微細特徴の分類データセットと課題（Classification Of Fine-Grained Features In Aerial Images）</news:title>
   <news:publication_date>2026-06-07T16:20:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698072</loc>
  <lastmod>2026-06-07T16:20:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル変分モデルによる自然言語生成（Natural Language Generation with Neural Variational Models）</news:title>
   <news:publication_date>2026-06-07T16:20:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698070</loc>
  <lastmod>2026-06-07T16:19:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学入試と採用の「下流効果」を考える（Downstream Effects of Affirmative Action）</news:title>
   <news:publication_date>2026-06-07T16:19:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698068</loc>
  <lastmod>2026-06-07T15:28:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習に対するデータポイズニング攻撃の構造と示唆（Data Poisoning Attacks against Online Learning）</news:title>
   <news:publication_date>2026-06-07T15:28:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698066</loc>
  <lastmod>2026-06-07T15:28:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層オートエンコーダを用いた新物理探索（Searching for New Physics with Deep Autoencoders）</news:title>
   <news:publication_date>2026-06-07T15:28:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698064</loc>
  <lastmod>2026-06-07T15:28:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ型属性を用いた開放集合の漢字認識（Open Set Chinese Character Recognition using Multi-typed Attributes）</news:title>
   <news:publication_date>2026-06-07T15:28:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698062</loc>
  <lastmod>2026-06-07T15:27:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QCD or What?——ジェット解析における教師なし異常検知の実践（QCD or What?）</news:title>
   <news:publication_date>2026-06-07T15:27:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698060</loc>
  <lastmod>2026-06-07T15:27:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力波ベンチマークにおける共鳴二重ヒッグス生成のコリダースタディ（Resonant Di-Higgs Production at Gravitational Wave Benchmarks: A Collider Study using Machine Learning）</news:title>
   <news:publication_date>2026-06-07T15:27:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698058</loc>
  <lastmod>2026-06-07T15:27:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>V-matrix法の限界（A Limitation of V-Matrix based Methods）</news:title>
   <news:publication_date>2026-06-07T15:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698056</loc>
  <lastmod>2026-06-07T15:27:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NeuralCubesによる可視化向け深層表現（NeuralCubes: Deep Representations for Visual Data Exploration）</news:title>
   <news:publication_date>2026-06-07T15:27:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698054</loc>
  <lastmod>2026-06-07T14:36:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非教師あり多言語単語埋め込み（Unsupervised Multilingual Word Embeddings）</news:title>
   <news:publication_date>2026-06-07T14:36:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698052</loc>
  <lastmod>2026-06-07T14:27:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈化単語埋め込みの解剖（Dissecting Contextual Word Embeddings: Architecture and Representation）</news:title>
   <news:publication_date>2026-06-07T14:27:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698050</loc>
  <lastmod>2026-06-07T14:26:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>励起固有状態のエンタングルメントエントロピーにおけるボリューム則と量子臨界性（Volume Law and Quantum Criticality in the Entanglement Entropy of Excited Eigenstates of the Quantum Ising Model）</news:title>
   <news:publication_date>2026-06-07T14:26:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698048</loc>
  <lastmod>2026-06-07T14:26:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コミュニティ別ニュース興味の予測モデル（Models for Predicting Community-Specific Interest in News Articles）</news:title>
   <news:publication_date>2026-06-07T14:26:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698046</loc>
  <lastmod>2026-06-07T14:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期運用可能な自律水上艇（An Autonomous Surface Vehicle for Long Term Operations）</news:title>
   <news:publication_date>2026-06-07T14:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698044</loc>
  <lastmod>2026-06-07T14:25:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像からの意味抽出を強化する統計的意味モデル（Improving Information Extraction from Images with Learned Semantic Models）</news:title>
   <news:publication_date>2026-06-07T14:25:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698042</loc>
  <lastmod>2026-06-07T14:25:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者モニター由来PTTのノコギリ状アーティファクト（Unexpected sawtooth artifact in beat-to-beat pulse transit time measured from patient monitor data）</news:title>
   <news:publication_date>2026-06-07T14:25:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698040</loc>
  <lastmod>2026-06-07T13:34:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張（dilated）畳み込みの“滑らか化”による密な予測改善（Smoothed Dilated Convolutions for Improved Dense Prediction）</news:title>
   <news:publication_date>2026-06-07T13:34:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698038</loc>
  <lastmod>2026-06-07T13:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>片持ち構造における応力場予測を高速化するCNNアプローチ（STRESS FIELD PREDICTION IN CANTILEVERED STRUCTURES USING CONVOLUTIONAL NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-07T13:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698036</loc>
  <lastmod>2026-06-07T13:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分析記事からの感情態度の抽出（Extracting Sentiment Attitudes from Analytical Texts）</news:title>
   <news:publication_date>2026-06-07T13:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698034</loc>
  <lastmod>2026-06-07T13:32:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助的なキューモードを用いた量子線形回帰の実現（Realizing quantum linear regression with auxiliary qumodes）</news:title>
   <news:publication_date>2026-06-07T13:32:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698032</loc>
  <lastmod>2026-06-07T13:32:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Conditional Residual U-netによるマンモグラム腫瘤セグメンテーションの改善（Improved Breast Mass Segmentation in Mammograms with Conditional Residual U-net）</news:title>
   <news:publication_date>2026-06-07T13:32:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698030</loc>
  <lastmod>2026-06-07T13:32:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期駆動量子系の強化学習制御 — フロquet（Floquet）制御で倒立状態を自律準備する方法（Reinforcement learning for autonomous preparation of Floquet-engineered states: Inverting the quantum Kapitza oscillator）</news:title>
   <news:publication_date>2026-06-07T13:32:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698028</loc>
  <lastmod>2026-06-07T13:32:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味解析におけるゼロショット転移学習（Zero-shot Transfer Learning for Semantic Parsing）</news:title>
   <news:publication_date>2026-06-07T13:32:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698026</loc>
  <lastmod>2026-06-07T12:40:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深部組織で高精度に生体指標を測る光ファイバーセンサー（High fidelity fibre-based physiological sensing deep in tissue）</news:title>
   <news:publication_date>2026-06-07T12:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698024</loc>
  <lastmod>2026-06-07T12:40:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽の子午面循環を21年分の観測でたどる（Solar meridional circulation from twenty-one years of SOHO/MDI and SDO/HMI observations）</news:title>
   <news:publication_date>2026-06-07T12:40:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698022</loc>
  <lastmod>2026-06-07T12:40:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>気候データの次元削減に向けた畳み込みオートエンコーダの利用（Dimensionality-Reduction of Climate Data Using Deep Autoencoders）</news:title>
   <news:publication_date>2026-06-07T12:40:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698020</loc>
  <lastmod>2026-06-07T12:39:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル機械翻訳における強化学習の研究（A Study of Reinforcement Learning for Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-07T12:39:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698018</loc>
  <lastmod>2026-06-07T12:39:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ぼろぼろの顔画像から情報を取り戻す条件付きGANの試み（Facial Information Recovery from Heavily Damaged Images using Generative Adversarial Network - PART 1）</news:title>
   <news:publication_date>2026-06-07T12:39:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698016</loc>
  <lastmod>2026-06-07T12:38:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期確率的勾配降下法の高速化（Accelerating Asynchronous Stochastic Gradient Descent for Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-07T12:38:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698014</loc>
  <lastmod>2026-06-07T12:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BézierGANによる滑らかな曲線自動生成（BézierGAN: Automatic Generation of Smooth Curves from Interpretable Low-Dimensional Parameters）</news:title>
   <news:publication_date>2026-06-07T12:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698012</loc>
  <lastmod>2026-06-07T11:47:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像・動画に対する標的型非線形敵対的摂動（Targeted Nonlinear Adversarial Perturbations in Images and Videos）</news:title>
   <news:publication_date>2026-06-07T11:47:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698010</loc>
  <lastmod>2026-06-07T11:47:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意見要約の弱教師あり統合――アスペクト抽出と感情予測の同時利用（Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised）</news:title>
   <news:publication_date>2026-06-07T11:47:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698008</loc>
  <lastmod>2026-06-07T11:46:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数事業者による周波数共有の最適化（Multi-Operator Spectrum Sharing using Matching Game in Small Cells Network）</news:title>
   <news:publication_date>2026-06-07T11:46:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698006</loc>
  <lastmod>2026-06-07T11:45:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問類似性ランキングの強力なベースライン（A strong baseline for question relevancy ranking）</news:title>
   <news:publication_date>2026-06-07T11:45:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698004</loc>
  <lastmod>2026-06-07T11:45:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差をつける時系列表現の学び方 ― 微分可能な近似ホワイトニングで学ぶスローフィーチャー（Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening）</news:title>
   <news:publication_date>2026-06-07T11:45:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698002</loc>
  <lastmod>2026-06-07T11:45:07Z</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MDNetによる高速視覚トラッキング（Real-Time MDNet）</news:title>
   <news:publication_date>2026-06-07T11:45:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/698000</loc>
  <lastmod>2026-06-07T11:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点情報から動画・3Dボリュームを分割する反復的マルチパストラッキング（Iterative multi-path tracking for video and volume segmentation with sparse point supervision）</news:title>
   <news:publication_date>2026-06-07T11:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697998</loc>
  <lastmod>2026-06-07T10:53:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常マルコフ連鎖の指数不等式の拡張（Exponential inequalities for nonstationary Markov Chains）</news:title>
   <news:publication_date>2026-06-07T10:53:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697996</loc>
  <lastmod>2026-06-07T10:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔スプーフィング検出のための識別表現の組合せ（Discriminative Representation Combinations for Accurate Face Spoofing Detection）</news:title>
   <news:publication_date>2026-06-07T10:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697994</loc>
  <lastmod>2026-06-07T10:52:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均と分位数回帰を同時に学習する深層モデルが描く時空間予測の全体像（Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problems）</news:title>
   <news:publication_date>2026-06-07T10:52:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697992</loc>
  <lastmod>2026-06-07T10:52:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPULTRAによる低線量CT再構成の革新（SPULTRA: Low-Dose CT Image Reconstruction with Joint Statistical and Learned Image Models）</news:title>
   <news:publication_date>2026-06-07T10:52:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697990</loc>
  <lastmod>2026-06-07T10:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク適応再構成による逆問題の最適化（Task Adapted Reconstruction for Inverse Problems）</news:title>
   <news:publication_date>2026-06-07T10:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697988</loc>
  <lastmod>2026-06-07T10:52:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像から深度と自己運動を教師なしで推定するUnDEMoN（A Deeper Insight into the UnDEMoN: Unsupervised Deep Network for Depth and Ego-Motion Estimation）</news:title>
   <news:publication_date>2026-06-07T10:52:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697986</loc>
  <lastmod>2026-06-07T10:51:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発話レベルの意味依存を学習する自己符号化器マッチング（An Auto-Encoder Matching Model for Learning Utterance-Level Semantic Dependency in Dialogue Generation）</news:title>
   <news:publication_date>2026-06-07T10:51:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697984</loc>
  <lastmod>2026-06-07T10:00:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベント駆動型M2Mトラフィック予測のための有向情報学習フレームワーク（A Directed Information Learning Framework for Event-Driven M2M Traffic Prediction）</news:title>
   <news:publication_date>2026-06-07T10:00:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697982</loc>
  <lastmod>2026-06-07T10:00:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープニューラルネットワークのスパース化とその組込み応用（Sparsity in Deep Neural Networks - An Empirical Investigation with TensorQuant）</news:title>
   <news:publication_date>2026-06-07T10:00:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697980</loc>
  <lastmod>2026-06-07T09:59:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習済み言語モデルによる感情予測の転移学習（Amobee at IEST 2018: Transfer Learning from Language Models）</news:title>
   <news:publication_date>2026-06-07T09:59:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697978</loc>
  <lastmod>2026-06-07T09:59:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在距離空間で学ぶ多言語単語埋め込み（Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach）</news:title>
   <news:publication_date>2026-06-07T09:59:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697976</loc>
  <lastmod>2026-06-07T09:59:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>両言語の語彙埋め込みを中間で融合する方法（Improving Cross-Lingual Word Embeddings by Meeting in the Middle）</news:title>
   <news:publication_date>2026-06-07T09:59:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697974</loc>
  <lastmod>2026-06-07T09:58:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療検査データに対するDBNの適応構造学習と知識抽出（Adaptive Structural Learning of Deep Belief Network for Medical Examination Data and Its Knowledge Extraction by using C4.5）</news:title>
   <news:publication_date>2026-06-07T09:58:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697972</loc>
  <lastmod>2026-06-07T09:58:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模画像位置特定のための確率的引寄せ・反発埋め込み（Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization）</news:title>
   <news:publication_date>2026-06-07T09:58:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697970</loc>
  <lastmod>2026-06-07T09:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽観的方策反復法の収束性（ON THE CONVERGENCE OF OPTIMISTIC POLICY ITERATION FOR STOCHASTIC SHORTEST PATH PROBLEM）</news:title>
   <news:publication_date>2026-06-07T09:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697968</loc>
  <lastmod>2026-06-07T09:06:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全辞書学習の識別可能性の解明（Identifiability of Complete Dictionary Learning）</news:title>
   <news:publication_date>2026-06-07T09:06:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697966</loc>
  <lastmod>2026-06-07T09:06:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチストリーム時間畳み込みネットワークによる行動コンテキスト認識（Learning behavioral context recognition with multi-stream temporal convolutional networks）</news:title>
   <news:publication_date>2026-06-07T09:06:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697964</loc>
  <lastmod>2026-06-07T09:06:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル付きポジティブと未ラベルデータから学ぶ：選択時ランダム仮定（Learning from Positive and Unlabeled Data under the Selected At Random Assumption）</news:title>
   <news:publication_date>2026-06-07T09:06:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697962</loc>
  <lastmod>2026-06-07T09:05:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然風景の何が記憶に残るのか（What Makes Natural Scene Memorable?）</news:title>
   <news:publication_date>2026-06-07T09:05:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697960</loc>
  <lastmod>2026-06-07T09:05:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復改良エンコーダによる文埋め込みと自然言語推論（Sentence Embeddings in NLI with Iterative Refinement Encoders）</news:title>
   <news:publication_date>2026-06-07T09:05:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697958</loc>
  <lastmod>2026-06-07T09:05:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間と深層ニューラルネットワークにおける汎化（Generalisation in humans and deep neural networks）</news:title>
   <news:publication_date>2026-06-07T09:05:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697956</loc>
  <lastmod>2026-06-07T08:14:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続対称性を要さないLieb–Schultz–Mattis型定理の拡張（Lieb-Schultz-Mattis type theorems for quantum spin chains without continuous symmetry）</news:title>
   <news:publication_date>2026-06-07T08:14:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697954</loc>
  <lastmod>2026-06-07T08:13:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可積分二次元ソリトンの普遍的なホーキング蒸発（Universal quantum Hawking evaporation of integrable two-dimensional solitons）</news:title>
   <news:publication_date>2026-06-07T08:13:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697952</loc>
  <lastmod>2026-06-07T08:13:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速道路の流れを最適化する多エージェント強化学習（MARL-FWC: OPTIMAL COORDINATION OF FREEWAY TRAFFIC CONTROL MEASURES）</news:title>
   <news:publication_date>2026-06-07T08:13:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697950</loc>
  <lastmod>2026-06-07T08:12:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイドアクティベーションによる高効率・高精度な単一画像超解像（Wide Activation for Efficient and Accurate Image Super-Resolution）</news:title>
   <news:publication_date>2026-06-07T08:12:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697948</loc>
  <lastmod>2026-06-07T08:12:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Skip-Thoughtを用いた敵対的学習による文章生成（Generating Text through Adversarial Training using Skip-Thought Vectors）</news:title>
   <news:publication_date>2026-06-07T08:12:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697946</loc>
  <lastmod>2026-06-07T08:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>累積排出量制約下の二酸化炭素削減の経済学（Economics of carbon-dioxide abatement under an exogenous constraint on cumulative emissions）</news:title>
   <news:publication_date>2026-06-07T08:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697944</loc>
  <lastmod>2026-06-07T08:11:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰系列モデルにおける事前定義スパース性（Predefined Sparseness in Recurrent Sequence Models）</news:title>
   <news:publication_date>2026-06-07T08:11:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697942</loc>
  <lastmod>2026-06-07T07:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一混合画像からのステレオ推定（Stereo Computation for a Single Mixture Image）</news:title>
   <news:publication_date>2026-06-07T07:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697940</loc>
  <lastmod>2026-06-07T07:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマノイドロボットの自己ノイズに強い音声認識（Augmenting Bottleneck Features of Deep Neural Network Employing Motor State for Speech Recognition at Humanoid Robots）</news:title>
   <news:publication_date>2026-06-07T07:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697938</loc>
  <lastmod>2026-06-07T07:19:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層監督による深度マップ超解像を新規視点合成として考える（Deeply Supervised Depth Map Super-Resolution as Novel View Synthesis）</news:title>
   <news:publication_date>2026-06-07T07:19:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697936</loc>
  <lastmod>2026-06-07T07:19:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙の感情分類にELMoとBiLSTMを用いる手法（Implicit Emotion Classification With Deep Contextualized Word Representations）</news:title>
   <news:publication_date>2026-06-07T07:19:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697934</loc>
  <lastmod>2026-06-07T07:19:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差拡張畳み込みによる中国語臨床固有表現抽出の高速・高精度化（Fast and Accurate Recognition of Chinese Clinical Named Entities with Residual Dilated Convolutions）</news:title>
   <news:publication_date>2026-06-07T07:19:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697932</loc>
  <lastmod>2026-06-07T07:19:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>干渉がある実験におけるグローバル処置効果推定のための回帰調整（Regression adjustments for estimating the global treatment effect in experiments with interference）</news:title>
   <news:publication_date>2026-06-07T07:19:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697930</loc>
  <lastmod>2026-06-07T07:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートナーサリーにおけるFaster R-CNNとSSDの適用検討（Exploring the Applications of Faster R-CNN and Single-Shot Multi-box Detection in a Smart Nursery Domain）</news:title>
   <news:publication_date>2026-06-07T07:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697928</loc>
  <lastmod>2026-06-07T06:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速超解像3D SARイメージング（Fast Super-resolution 3D SAR Imaging Using an Unfolded Deep Network）</news:title>
   <news:publication_date>2026-06-07T06:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697926</loc>
  <lastmod>2026-06-07T06:27:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>戦略的操作の不平等効果（The Disparate Effects of Strategic Manipulation）</news:title>
   <news:publication_date>2026-06-07T06:27:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697924</loc>
  <lastmod>2026-06-07T06:26:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twin-GAN による未対応ドメイン間画像翻訳（Twin-GAN – Unpaired Cross-Domain Image Translation with Weight-Sharing GANs）</news:title>
   <news:publication_date>2026-06-07T06:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697922</loc>
  <lastmod>2026-06-07T06:26:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反応拡散系におけるモーメント閉鎖の学習（Learning Moment Closure in Reaction-Diffusion Systems with Spatial Dynamic Boltzmann Distributions）</news:title>
   <news:publication_date>2026-06-07T06:26:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697920</loc>
  <lastmod>2026-06-07T06:26:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層ネットワーク埋め込みとブーステッド低ランク行列近似（Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation）</news:title>
   <news:publication_date>2026-06-07T06:26:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697918</loc>
  <lastmod>2026-06-07T06:26:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>渦励起振動の深層学習（Deep Learning of Vortex Induced Vibrations）</news:title>
   <news:publication_date>2026-06-07T06:26:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697916</loc>
  <lastmod>2026-06-07T06:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関関係を使った外れ値検出法の実務的解説（Detecting Outliers in Data with Correlated Measures）</news:title>
   <news:publication_date>2026-06-07T06:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697914</loc>
  <lastmod>2026-06-07T05:35:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測データに潜む差別的増幅を検出するためのα‑ハイブリッド世界観とα‑Disparity検定（α‑Hybrid Worldviews and the α‑Disparity Test）</news:title>
   <news:publication_date>2026-06-07T05:35:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697912</loc>
  <lastmod>2026-06-07T05:35:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Learningの計算的側面がもたらす実務的インパクト（Deep Learning: Computational Aspects）</news:title>
   <news:publication_date>2026-06-07T05:35:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697910</loc>
  <lastmod>2026-06-07T05:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>鳥類のGPS軌跡から性別を予測するアンサンブル学習（Ensemble Learning Applied to Classify GPS Trajectories of Birds into Male or Female）</news:title>
   <news:publication_date>2026-06-07T05:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697908</loc>
  <lastmod>2026-06-07T05:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像の霧除去における一般的規則性の利用（Single Image Dehazing Based on Generic Regularity）</news:title>
   <news:publication_date>2026-06-07T05:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697906</loc>
  <lastmod>2026-06-07T05:34:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>吸収性媒質に埋め込まれた球状粒子の散乱と消光（Scattering and extinction by spherical particles immersed in an absorbing host medium）</news:title>
   <news:publication_date>2026-06-07T05:34:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697904</loc>
  <lastmod>2026-06-07T05:34:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理ベースレンダリングで改善する内在画像分解（CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering）</news:title>
   <news:publication_date>2026-06-07T05:34:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697902</loc>
  <lastmod>2026-06-07T05:33:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>論理知識を組み込むための敵対的正則化によるNLIモデル強化（Adversarially Regularising Neural NLI Models to Integrate Logical Background Knowledge）</news:title>
   <news:publication_date>2026-06-07T05:33:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697900</loc>
  <lastmod>2026-06-07T04:42:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低サンプリング水使用分解のための形状特徴に基づくベイズ判別スパースコーディング（Water Disaggregation via Shape Features based Bayesian Discriminative Sparse Coding）</news:title>
   <news:publication_date>2026-06-07T04:42:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697898</loc>
  <lastmod>2026-06-07T04:42:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形状補正型マルチタスク深層学習による心臓3D二心室自動セグメンテーション (Automatic 3D bi-ventricular segmentation of cardiac images by a shape-refined multi-task deep learning approach)</news:title>
   <news:publication_date>2026-06-07T04:42:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697896</loc>
  <lastmod>2026-06-07T04:42:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タイトルガイド付き符号化によるキーフレーズ生成（Title-Guided Encoding for Keyphrase Generation）</news:title>
   <news:publication_date>2026-06-07T04:42:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697894</loc>
  <lastmod>2026-06-07T04:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空撮画像における車両検出と識別を結ぶCNNの実践（Convolutional Neural Networks for Aerial Vehicle Detection and Recognition）</news:title>
   <news:publication_date>2026-06-07T04:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697892</loc>
  <lastmod>2026-06-07T04:41:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習された深層ASR性能予測モデルの表現解析（Analyzing Learned Representations of a Deep ASR Performance Prediction Model）</news:title>
   <news:publication_date>2026-06-07T04:41:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697890</loc>
  <lastmod>2026-06-07T04:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>失業給付の二項分析（A Dichotomous Analysis of Unemployment Benefits）</news:title>
   <news:publication_date>2026-06-07T04:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697888</loc>
  <lastmod>2026-06-07T04:40:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック単位に基づく拡張畳み込みによるマルチラベル文章分類（Semantic-Unit-Based Dilated Convolution for Multi-Label Text Classification）</news:title>
   <news:publication_date>2026-06-07T04:40:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697886</loc>
  <lastmod>2026-06-07T03:49:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>突発的投票におけるSNS利用者の投票意向の即時推定（Nowcasting the Stance of Social Media Users in a Sudden Vote: The Case of the Greek Referendum）</news:title>
   <news:publication_date>2026-06-07T03:49:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697884</loc>
  <lastmod>2026-06-07T03:49:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトラルプルーニングによるニューラルネット圧縮（Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error）</news:title>
   <news:publication_date>2026-06-07T03:49:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697882</loc>
  <lastmod>2026-06-07T03:48:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像における雨筋除去の新展開（Rain Streak Removal for Single Image via Kernel Guided CNN）</news:title>
   <news:publication_date>2026-06-07T03:48:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697880</loc>
  <lastmod>2026-06-07T03:47:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星モザイク画像の分散処理によるオブジェクト抽出フレームワーク（A MapReduce based Big-data Framework for Object Extraction from Mosaic Satellite Images）</news:title>
   <news:publication_date>2026-06-07T03:47:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697878</loc>
  <lastmod>2026-06-07T03:47:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常データストリームに対応する深層進化型ファジィニューラルネットワーク（An Incremental Construction of Deep Neuro Fuzzy System for Continual Learning of Non-Stationary Data Streams）</news:title>
   <news:publication_date>2026-06-07T03:47:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697876</loc>
  <lastmod>2026-06-07T03:47:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報流通と偏向の臨界点：確認バイアスが生むネットワーク分極（When facts fail: Bias, polarisation and truth in social networks）</news:title>
   <news:publication_date>2026-06-07T03:47:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697874</loc>
  <lastmod>2026-06-07T03:47:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepTrackerによるCNN学習過程の可視化（DeepTracker: Visualizing the Training Process of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-07T03:47:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697872</loc>
  <lastmod>2026-06-07T02:54:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な単一画像超解像のための学習済みグループ畳み込みの強化（Efficient Single Image Super Resolution using Enhanced Learned Group Convolutions）</news:title>
   <news:publication_date>2026-06-07T02:54:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697870</loc>
  <lastmod>2026-06-07T02:54:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mallowsランキングモデルの最尤推定と再生性（Mallows Ranking Models: Maximum Likelihood Estimate and Regeneration）</news:title>
   <news:publication_date>2026-06-07T02:54:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697868</loc>
  <lastmod>2026-06-07T02:53:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークにおけるコミュニティ検出の理論的進展（A Survey on Theoretical Advances of Community Detection in Networks）</news:title>
   <news:publication_date>2026-06-07T02:53:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697866</loc>
  <lastmod>2026-06-07T02:53:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈に応じてパラメータを生成する多言語機械翻訳（Contextual Parameter Generation for Universal Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-07T02:53:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697864</loc>
  <lastmod>2026-06-07T02:52:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DreamNLP: 臨床報告からのメタデータ抽出を効率化するデータストリーミング手法（DreamNLP: Novel NLP System for Clinical Report Metadata Extraction using Count Sketch Data Streaming Algorithm: Preliminary Results）</news:title>
   <news:publication_date>2026-06-07T02:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697862</loc>
  <lastmod>2026-06-07T02:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Probabilistic Logicによる間接教師あり学習の統一枠組み（Deep Probabilistic Logic: A Unifying Framework for Indirect Supervision）</news:title>
   <news:publication_date>2026-06-07T02:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697860</loc>
  <lastmod>2026-06-07T02:52:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>壁乱流の普遍的分数モデル（A Universal Fractional Model of Wall-Turbulence）</news:title>
   <news:publication_date>2026-06-07T02:52:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697858</loc>
  <lastmod>2026-06-07T02:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交差点における異常軌跡検出の実務的インパクト（Road User Abnormal Trajectory Detection using a Deep Autoencoder）</news:title>
   <news:publication_date>2026-06-07T02:00:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697856</loc>
  <lastmod>2026-06-07T02:00:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚病変の深層学習アンサンブルによる分析と分類（Deep-Learning Ensembles for Skin-Lesion Segmentation, Analysis, Classification: RECOD Titans at ISIC Challenge 2018）</news:title>
   <news:publication_date>2026-06-07T02:00:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697854</loc>
  <lastmod>2026-06-07T02:00:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の枠を越える発想：GANによるImage Outpaintingの実践（Painting Outside the Box: Image Outpainting with GANs）</news:title>
   <news:publication_date>2026-06-07T02:00:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697852</loc>
  <lastmod>2026-06-07T02:00:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MSCEによる超解像の精度向上と現場導入の勘所（MSCE: An edge preserving robust loss function for improving super-resolution algorithms）</news:title>
   <news:publication_date>2026-06-07T02:00:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697850</loc>
  <lastmod>2026-06-07T01:59:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間中心の屋内シーン合成：確率文法による3D/2Dデータ生成（Human-centric Indoor Scene Synthesis Using Stochastic Grammar）</news:title>
   <news:publication_date>2026-06-07T01:59:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697848</loc>
  <lastmod>2026-06-07T01:59:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディア利用者の表現を用いた皮肉検出（Representing Social Media Users for Sarcasm Detection）</news:title>
   <news:publication_date>2026-06-07T01:59:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697846</loc>
  <lastmod>2026-06-07T01:59:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列依存グループ観測からのネットワーク推定 (Network Inference from Temporal-Dependent Grouped Observations)</news:title>
   <news:publication_date>2026-06-07T01:59:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697844</loc>
  <lastmod>2026-06-07T01:08:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二段階スケールを用いた分布的最近傍法による最適非パラメトリック推論（Optimal Nonparametric Inference with Two-Scale Distributional Nearest Neighbors）</news:title>
   <news:publication_date>2026-06-07T01:08:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697842</loc>
  <lastmod>2026-06-07T01:08:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル数学環境の現状と展望（Mobile Mathematical Environments: current state and development prospects）</news:title>
   <news:publication_date>2026-06-07T01:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697840</loc>
  <lastmod>2026-06-07T01:08:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>戦略的分類の社会的コスト（The Social Cost of Strategic Classification）</news:title>
   <news:publication_date>2026-06-07T01:08:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697838</loc>
  <lastmod>2026-06-07T01:07:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NNLO PDFsがLHC解析にもたらした変化（NNLO PDFs for the LHC）</news:title>
   <news:publication_date>2026-06-07T01:07:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697836</loc>
  <lastmod>2026-06-07T01:07:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>本の装丁デザインをCNNはどう学ぶか（How do Convolutional Neural Networks Learn Design?）</news:title>
   <news:publication_date>2026-06-07T01:07:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697834</loc>
  <lastmod>2026-06-07T01:07:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情を深層学習で再現する試み（Deep Emotion: A Computational Model of Emotion Using Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-07T01:07:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697832</loc>
  <lastmod>2026-06-07T00:16:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>火星視覚ナビゲーションの新しい深層ニューラルネットアーキテクチャ（A Novel Deep Neural Network Architecture for Mars Visual Navigation）</news:title>
   <news:publication_date>2026-06-07T00:16:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697830</loc>
  <lastmod>2026-06-07T00:16:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>監視学習を用いた原始星（プロトスター）分類（Protostellar classification using supervised machine learning algorithms）</news:title>
   <news:publication_date>2026-06-07T00:16:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697828</loc>
  <lastmod>2026-06-07T00:15:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NavigationNetに見る屋内自律移動の現実解（NavigationNet: A Large-scale Interactive Indoor Navigation Dataset）</news:title>
   <news:publication_date>2026-06-07T00:15:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697826</loc>
  <lastmod>2026-06-07T00:14:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データベース非依存のワークロード管理（Database-Agnostic Workload Management）</news:title>
   <news:publication_date>2026-06-07T00:14:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697824</loc>
  <lastmod>2026-06-07T00:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称・反対称関係のデータ駆動学習による知識ベース補完（Data-dependent Learning of Symmetric/Antisymmetric Relations for Knowledge Base Completion）</news:title>
   <news:publication_date>2026-06-07T00:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697822</loc>
  <lastmod>2026-06-07T00:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>And-Orグラフ表現によるニューラルタスクプランニング (Neural Task Planning with And-Or Graph Representations)</news:title>
   <news:publication_date>2026-06-07T00:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697820</loc>
  <lastmod>2026-06-07T00:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データに対するパラメータ別共クラスタリング（Parameter-Wise Co-Clustering for High-Dimensional Data）</news:title>
   <news:publication_date>2026-06-07T00:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697818</loc>
  <lastmod>2026-06-06T23:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>砂嵐（ダストストーム）が太陽光発電に与える影響と深層学習による予測（Forecasting solar radiation during dust storms using deep learning）</news:title>
   <news:publication_date>2026-06-06T23:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697816</loc>
  <lastmod>2026-06-06T23:21:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PLDAの多目的最適化学習が話者識別を進化させる（MULTI-OBJECTIVE OPTIMIZATION TRAINING OF PLDA FOR SPEAKER VERIFICATION）</news:title>
   <news:publication_date>2026-06-06T23:21:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697814</loc>
  <lastmod>2026-06-06T23:20:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン逆学習で深層分類器のバイアスを低減する手法（Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINERνA experiment）</news:title>
   <news:publication_date>2026-06-06T23:20:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697812</loc>
  <lastmod>2026-06-06T23:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的エンティティ関連性ランキングの三位一体ニューラルモデル（A Trio Neural Model for Dynamic Entity Relatedness Ranking）</news:title>
   <news:publication_date>2026-06-06T23:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697810</loc>
  <lastmod>2026-06-06T23:20:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタリングすべきか否かの判断指標（To Cluster, or Not to Cluster: An Analysis of Clusterability Methods）</news:title>
   <news:publication_date>2026-06-06T23:20:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697808</loc>
  <lastmod>2026-06-06T23:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>6D物体姿勢推定のベンチマーク（BOP: Benchmark for 6D Object Pose Estimation）</news:title>
   <news:publication_date>2026-06-06T23:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697806</loc>
  <lastmod>2026-06-06T23:19:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定論的自己組織化マップと衛星データを用いた雲分類の応用（A Deterministic Self-Organizing Map Approach and its Application on Satellite Data based Cloud Type Classification）</news:title>
   <news:publication_date>2026-06-06T23:19:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697804</loc>
  <lastmod>2026-06-06T22:28:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学校年齢の児童における自閉症スペクトラム障害の洞察を深める複合心拍変動バイオマーカーの可能性（Can a composite heart rate variability biomarker shed new insights about autism spectrum disorder in school-aged children?）</news:title>
   <news:publication_date>2026-06-06T22:28:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697802</loc>
  <lastmod>2026-06-06T22:27:51Z</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SampleRNNによる音声変換（Voice Conversion with Conditional SampleRNN）</news:title>
   <news:publication_date>2026-06-06T22:27:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697800</loc>
  <lastmod>2026-06-06T22:27:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新生児の泣き声で見抜く低コスト診断（Infant Cry Classification for Perinatal Asphyxia）</news:title>
   <news:publication_date>2026-06-06T22:27:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697798</loc>
  <lastmod>2026-06-06T22:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察から学ぶロボット学習の定義（Defining the problem of Observation Learning）</news:title>
   <news:publication_date>2026-06-06T22:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697796</loc>
  <lastmod>2026-06-06T22:27:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増強分解アルゴリズムの収束性（Convergence of the Augmented Decomposition Algorithm）</news:title>
   <news:publication_date>2026-06-06T22:27:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697794</loc>
  <lastmod>2026-06-06T22:26:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の例を学習することでのMLモデルの一般化 (Learning Unknown Examples For ML Model)</news:title>
   <news:publication_date>2026-06-06T22:26:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697792</loc>
  <lastmod>2026-06-06T22:26:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的グラフィカルモデルによる動的PETの直接パラメトリック再構成（Probabilistic Graphical Modeling approach to dynamic PET direct parametric map estimation and image reconstruction）</news:title>
   <news:publication_date>2026-06-06T22:26:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697790</loc>
  <lastmod>2026-06-06T21:35:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Thompson Samplingによる適応型グレイボックスファズテスト（Adaptive Grey-Box Fuzz-Testing with Thompson Sampling）</news:title>
   <news:publication_date>2026-06-06T21:35:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697788</loc>
  <lastmod>2026-06-06T21:26:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数回答を許容する目的指向対話の学習（Learning End-to-End Goal-Oriented Dialog with Multiple Answers）</news:title>
   <news:publication_date>2026-06-06T21:26:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697786</loc>
  <lastmod>2026-06-06T21:26:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高品質な顔面表面とテクスチャの合成（High Quality Facial Surface and Texture Synthesis via Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-06T21:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697784</loc>
  <lastmod>2026-06-06T21:26:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テスト時予算下での頑健なテキスト分類器（Robust Text Classifier on Test-Time Budgets）</news:title>
   <news:publication_date>2026-06-06T21:26:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697782</loc>
  <lastmod>2026-06-06T21:25:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知ダイナミクス下における人間機械共有制御の学習モデル（Learning Models for Shared Control of Human-Machine Systems with Unknown Dynamics）</news:title>
   <news:publication_date>2026-06-06T21:25:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697780</loc>
  <lastmod>2026-06-06T21:25:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚注意に基づくマルチモーダル翻訳モデル（A Visual Attention Grounding Neural Model for Multimodal Machine Translation）</news:title>
   <news:publication_date>2026-06-06T21:25:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697778</loc>
  <lastmod>2026-06-06T21:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ur-Alternativesに基づく自然の統一的記述（Die einheitliche Beschreibung der fundamentalen Objekte und Wechselwirkungen der Natur in der Quantentheorie der Ur-Alternativen）</news:title>
   <news:publication_date>2026-06-06T21:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697776</loc>
  <lastmod>2026-06-06T20:34:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DUNEによる次世代の太陽ニュートリノ観測（DUNE as the Next-Generation Solar Neutrino Experiment）</news:title>
   <news:publication_date>2026-06-06T20:34:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697774</loc>
  <lastmod>2026-06-06T20:34:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>製品の複雑性とデータ正規化の効果（Complexity of products: the effect of data regularisation）</news:title>
   <news:publication_date>2026-06-06T20:34:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697772</loc>
  <lastmod>2026-06-06T20:33:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Chebyshevテンソルによる動的初期証拠金の高速計算（Dynamic Initial Margin via Chebyshev Tensors）</news:title>
   <news:publication_date>2026-06-06T20:33:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697770</loc>
  <lastmod>2026-06-06T20:33:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素平面上のd個のマーキング点の配置空間の幾何的不変量（GEOMETRIC INVARIANTS OF THE CONFIGURATION SPACE OF d MARKED POINTS ON THE COMPLEX PLANE）</news:title>
   <news:publication_date>2026-06-06T20:33:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697768</loc>
  <lastmod>2026-06-06T20:32:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ乱れが生む見かけのせん断バンド（Effect of edge disturbance on shear banding in polymeric solutions）</news:title>
   <news:publication_date>2026-06-06T20:32:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697766</loc>
  <lastmod>2026-06-06T20:32:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未来の自動化工学を支える構造的グラフ畳み込みニューラルネットワーク（Future Automation Engineering using Structural Graph Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-06T20:32:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697764</loc>
  <lastmod>2026-06-06T20:32:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電力系における機械学習の脆弱性：データ操作で精度が崩れる仕組み（Is Machine Learning in Power Systems Vulnerable?）</news:title>
   <news:publication_date>2026-06-06T20:32:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697762</loc>
  <lastmod>2026-06-06T19:41:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アカウントの不審なログイン通知と利用者対応の国際比較（“Should I Worry?” A Cross-Cultural Examination of Account Security Incident Response）</news:title>
   <news:publication_date>2026-06-06T19:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697760</loc>
  <lastmod>2026-06-06T19:41:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コミュニティ形成をネットワークで読む（Studying community development: a network analytical approach）</news:title>
   <news:publication_date>2026-06-06T19:41:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697758</loc>
  <lastmod>2026-06-06T19:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列ネットワーク整列におけるGoT-WAVEの提案（GoT-WAVE: Temporal network alignment using graphlet-orbit transitions）</news:title>
   <news:publication_date>2026-06-06T19:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697756</loc>
  <lastmod>2026-06-06T19:40:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みスパイキングニューラルネットワークによるSTDP学習（STDP Learning of Image Patches with Convolutional Spiking Neural Networks）</news:title>
   <news:publication_date>2026-06-06T19:40:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697754</loc>
  <lastmod>2026-06-06T19:39:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続時間ガウス過程動的モデルによる遺伝子制御ネットワーク推論（CONTINUOUS TIME GAUSSIAN PROCESS DYNAMICAL MODELS IN GENE REGULATORY NETWORK INFERENCE）</news:title>
   <news:publication_date>2026-06-06T19:39:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697752</loc>
  <lastmod>2026-06-06T19:39:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバル情報を用いた新しいドロップアウト（From Random to Supervised: A Novel Dropout Mechanism Integrated with Global Information）</news:title>
   <news:publication_date>2026-06-06T19:39:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697750</loc>
  <lastmod>2026-06-06T19:39:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>豊富なサブグループ公平性の実証的研究（An Empirical Study of Rich Subgroup Fairness for Machine Learning）</news:title>
   <news:publication_date>2026-06-06T19:39:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697748</loc>
  <lastmod>2026-06-06T18:47:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Erlangで実装する連合学習の実践（Functional Federated Learning in Erlang）</news:title>
   <news:publication_date>2026-06-06T18:47:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697746</loc>
  <lastmod>2026-06-06T18:47:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Apple Create MLを用いた非小細胞肺癌の検出とサブクラス分類（Using Apple Machine Learning Algorithms to Detect and Subclassify Non-Small Cell Lung Cancer）</news:title>
   <news:publication_date>2026-06-06T18:47:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697744</loc>
  <lastmod>2026-06-06T18:46:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMの記憶時間と多人数音声分離（Memory Time Span in LSTMs for Multi-Speaker Source Separation）</news:title>
   <news:publication_date>2026-06-06T18:46:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697742</loc>
  <lastmod>2026-06-06T18:46:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチシナリオ深層学習による多人数音声分離の示す実務的意義（MULTI-SCENARIO DEEP LEARNING FOR MULTI-SPEAKER SOURCE SEPARATION）</news:title>
   <news:publication_date>2026-06-06T18:46:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697740</loc>
  <lastmod>2026-06-06T18:46:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己段階型マルチタスククラスタリングの提案（Self-Paced Multi-Task Clustering）</news:title>
   <news:publication_date>2026-06-06T18:46:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697738</loc>
  <lastmod>2026-06-06T18:46:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パノラマX線画像からの頸動脈プラーク自動検出（Atherosclerotic carotid plaques on panoramic imaging: an automatic detection using deep learning with small dataset）</news:title>
   <news:publication_date>2026-06-06T18:46:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697736</loc>
  <lastmod>2026-06-06T18:46:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習に基づく最適HASの設計（Towards Machine Learning-Based Optimal HAS）</news:title>
   <news:publication_date>2026-06-06T18:46:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697734</loc>
  <lastmod>2026-06-06T17:55:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mollweideの公式を教える意義（Mollweide’s formula in teaching trigonometry）</news:title>
   <news:publication_date>2026-06-06T17:55:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697732</loc>
  <lastmod>2026-06-06T17:54:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスペクトルフィルタアレイ向け深層デモザイキングの実装と意義（Deep demosaicking for multispectral filter arrays）</news:title>
   <news:publication_date>2026-06-06T17:54:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697730</loc>
  <lastmod>2026-06-06T17:54:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテキスト対応POI埋め込みによる旅行推薦（A Jointly Learned Context-Aware Place of Interest Embedding for Trip Recommendations）</news:title>
   <news:publication_date>2026-06-06T17:54:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697728</loc>
  <lastmod>2026-06-06T17:54:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同一独立確率変数のパーセンタイルに関する非漸近的境界（Non-asymptotic bounds for percentiles of independent non-identical random variables）</news:title>
   <news:publication_date>2026-06-06T17:54:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697726</loc>
  <lastmod>2026-06-06T17:53:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似分布マッチングによる系列変換の改善（Approximate Distribution Matching for Sequence-to-Sequence Learning）</news:title>
   <news:publication_date>2026-06-06T17:53:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697724</loc>
  <lastmod>2026-06-06T17:53:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Feature Pyramid Reconﬁguration for Object Detection（Deep Feature Pyramid Reconfiguration for Object Detection）</news:title>
   <news:publication_date>2026-06-06T17:53:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697722</loc>
  <lastmod>2026-06-06T17:53:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズデータからの文レベル関係分類の強化学習（Reinforcement Learning for Relation Classification from Noisy Data）</news:title>
   <news:publication_date>2026-06-06T17:53:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697720</loc>
  <lastmod>2026-06-06T17:02:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極めて早産の新生児における抜管準備の予測に対するアンダーサンプリングとバッグド決定木の応用（Undersampling and Bagging of Decision Trees in the Analysis of Cardiorespiratory Behavior for the Prediction of Extubation Readiness in Extremely Preterm Infants）</news:title>
   <news:publication_date>2026-06-06T17:02:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697718</loc>
  <lastmod>2026-06-06T17:02:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極低出生体重児の抜管準備予測：呼吸パターン解析による可視化と予測（Predicting Extubation Readiness in Extreme Preterm Infants based on Patterns of Breathing）</news:title>
   <news:publication_date>2026-06-06T17:02:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697716</loc>
  <lastmod>2026-06-06T17:01:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳児の呼吸パターンをモデリングする半マルコフ連鎖アプローチ（A Semi-Markov Chain Approach to Modeling Respiratory Patterns Prior to Extubation in Preterm Infants）</news:title>
   <news:publication_date>2026-06-06T17:01:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697714</loc>
  <lastmod>2026-06-06T17:01:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接方策最適化とその動的版（Proximal Policy Optimization and its Dynamic Version for Sequence Generation）</news:title>
   <news:publication_date>2026-06-06T17:01:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697712</loc>
  <lastmod>2026-06-06T17:01:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープニューラルネットワークによるオントロジー推論（Ontology Reasoning with Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-06T17:01:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697710</loc>
  <lastmod>2026-06-06T17:01:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層拡散ネットワークの推定（Inferring Multiplex Diffusion Network via Multivariate Marked Hawkes Process）</news:title>
   <news:publication_date>2026-06-06T17:01:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697708</loc>
  <lastmod>2026-06-06T17:00:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ対照推定の漸近分散解析（Analysis of Noise Contrastive Estimation from the Perspective of Asymptotic Variance）</news:title>
   <news:publication_date>2026-06-06T17:00:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697706</loc>
  <lastmod>2026-06-06T16:09:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>左心室計測における時空間CNNの応用（Left ventricle quantification through spatio-temporal CNNs）</news:title>
   <news:publication_date>2026-06-06T16:09:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697704</loc>
  <lastmod>2026-06-06T16:09:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中性子星の半径と潮汐ポーラリザビリティに及ぼす核対称性エネルギーの影響（Delineating Effects of Nuclear Symmetry Energy on the Radii and Tidal Polarizabilities of Neutron Stars）</news:title>
   <news:publication_date>2026-06-06T16:09:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697702</loc>
  <lastmod>2026-06-06T16:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と物の相互作用を学ぶグラフ解析ニューラルネットワーク（Learning Human-Object Interactions by Graph Parsing Neural Networks）</news:title>
   <news:publication_date>2026-06-06T16:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697700</loc>
  <lastmod>2026-06-06T16:08:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群データに対するデコンボリューションネットワークを用いた車両検出と追跡（Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios）</news:title>
   <news:publication_date>2026-06-06T16:08:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697698</loc>
  <lastmod>2026-06-06T16:08:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヤコビ行列に基づく最大サリエンシー攻撃の発展（Maximal Jacobian-based Saliency Map Attack）</news:title>
   <news:publication_date>2026-06-06T16:08:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697696</loc>
  <lastmod>2026-06-06T16:07:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手作業特徴量から深層学習へ移行するがんラジオミクスの挑戦と展望（From Hand‑Crafted to Deep Learning‑based Cancer Radiomics: Challenges and Opportunities）</news:title>
   <news:publication_date>2026-06-06T16:07:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697694</loc>
  <lastmod>2026-06-06T16:07:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>金融分野のアスペクト別感情分析と深層表現の活用（Financial Aspect-Based Sentiment Analysis using Deep Representations）</news:title>
   <news:publication_date>2026-06-06T16:07:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697692</loc>
  <lastmod>2026-06-06T15:16:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル数学学習環境の構成要素設計（METHODOLOGY OF SEPARATE COMPONENTS FORMATION OF MOBILE MATHEMATICAL ENVIRONMENT &amp;quot;HIGHER MATHEMATICS&amp;quot;）</news:title>
   <news:publication_date>2026-06-06T15:16:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697690</loc>
  <lastmod>2026-06-06T15:08:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PhaseMACによる低消費電力・小面積のMAC回路（PhaseMAC: A 14 TOPS/W 8bit GRO based Phase Domain MAC Circuit for In-Sensor-Computed Deep Learning Accelerators）</news:title>
   <news:publication_date>2026-06-06T15:08:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697688</loc>
  <lastmod>2026-06-06T15:08:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SOTERによるロボット安全の実行時保証フレームワーク（SOTER: A Runtime Assurance Framework for Programming Safe Robotics Systems）</news:title>
   <news:publication_date>2026-06-06T15:08:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697686</loc>
  <lastmod>2026-06-06T15:08:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MH-IIIの状態方程式――タイタンと超タイタンにおける深部メタン貯留庫の可能性 (The Equation of State of MH-III: A Possible Deep CH4 Reservoir in Titan, Super-Titan Exoplanets and Moons)</news:title>
   <news:publication_date>2026-06-06T15:08:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697684</loc>
  <lastmod>2026-06-06T15:06:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>要約生成における抽象化の向上（Improving Abstraction in Text Summarization）</news:title>
   <news:publication_date>2026-06-06T15:06:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697682</loc>
  <lastmod>2026-06-06T15:06:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2次元深水における孤立波の不存在（NO SOLITARY WAVES IN 2-D GRAVITY AND CAPILLARY WAVES IN DEEP WATER）</news:title>
   <news:publication_date>2026-06-06T15:06:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697680</loc>
  <lastmod>2026-06-06T15:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>加速器用真空ウィンドウの製造技術と教訓（OVERVIEW OF FABRICATION TECHNIQUES AND LESSONS LEARNED WITH ACCELERATOR VACUUM WINDOWS）</news:title>
   <news:publication_date>2026-06-06T15:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697678</loc>
  <lastmod>2026-06-06T14:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LIFT: データ処理システムにおけるデモから学ぶ強化学習（LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations）</news:title>
   <news:publication_date>2026-06-06T14:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697676</loc>
  <lastmod>2026-06-06T14:14:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成順序が言語モデルを変える――二段階生成の示した洞察（The Importance of Generation Order in Language Modeling）</news:title>
   <news:publication_date>2026-06-06T14:14:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697674</loc>
  <lastmod>2026-06-06T14:12:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列ベースのR´enyi α次エントロピーの多変量拡張（Multivariate Extension of Matrix-based R´enyi’s α-order Entropy Functional）</news:title>
   <news:publication_date>2026-06-06T14:12:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697672</loc>
  <lastmod>2026-06-06T14:12:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高フレームレート心臓超音波画像における深層学習による補正（High frame-rate cardiac ultrasound imaging with deep learning）</news:title>
   <news:publication_date>2026-06-06T14:12:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697670</loc>
  <lastmod>2026-06-06T14:12:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライマリサンプル空間における重要度サンプリングの学習（Learning to Importance Sample in Primary Sample Space）</news:title>
   <news:publication_date>2026-06-06T14:12:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697668</loc>
  <lastmod>2026-06-06T14:12:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ATLASのトップ粒子とWボソンの識別性能（Performance of top-quark and W-boson tagging with ATLAS in Run 2 of the LHC）</news:title>
   <news:publication_date>2026-06-06T14:12:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697666</loc>
  <lastmod>2026-06-06T14:11:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタイル転移を無教師で行う手法（Style Transfer as Unsupervised Machine Translation）</news:title>
   <news:publication_date>2026-06-06T14:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697664</loc>
  <lastmod>2026-06-06T13:20:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果効果推定のための転移学習（Transfer Learning for Estimating Causal Effects using Neural Networks）</news:title>
   <news:publication_date>2026-06-06T13:20:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697662</loc>
  <lastmod>2026-06-06T13:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高品質な超音波マルチライン送信を深層学習で改善する（High quality ultrasonic multi-line transmission through deep learning）</news:title>
   <news:publication_date>2026-06-06T13:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697660</loc>
  <lastmod>2026-06-06T13:19:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトルグラフクラスタリングにおける「Two Truths」現象（On a &amp;#039;Two Truths&amp;#039; Phenomenon in Spectral Graph Clustering）</news:title>
   <news:publication_date>2026-06-06T13:19:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697658</loc>
  <lastmod>2026-06-06T13:19:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電波画像における一過性・変動源の検出手法（Identifying transient and variable sources in radio images）</news:title>
   <news:publication_date>2026-06-06T13:19:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697656</loc>
  <lastmod>2026-06-06T13:19:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Webly Supervised Joint Embeddingによる画像–テキスト検索のスケール拡張（Webly Supervised Joint Embedding for Cross-Modal Image-Text Retrieval）</news:title>
   <news:publication_date>2026-06-06T13:19:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697654</loc>
  <lastmod>2026-06-06T13:18:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車種識別の深層学習パイプラインがもたらす実務的変化（Deep Learning Based Vehicle Make-Model Classification）</news:title>
   <news:publication_date>2026-06-06T13:18:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697652</loc>
  <lastmod>2026-06-06T13:18:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間無関係予測（Time-Agnostic Prediction: Predicting Predictable Video Frames）</news:title>
   <news:publication_date>2026-06-06T13:18:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697650</loc>
  <lastmod>2026-06-06T12:27:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みニューラルネットワークの拓く地平（Topology and Prediction Focused Research on Graph Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-06T12:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697648</loc>
  <lastmod>2026-06-06T12:27:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポートレート画像の補完と外挿（Deep Portrait Image Completion and Extrapolation）</news:title>
   <news:publication_date>2026-06-06T12:27:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697646</loc>
  <lastmod>2026-06-06T12:27:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間およびチャネルのSqueeze &amp;amp; ExcitationでF-CNNを再較正する手法（Recalibrating Fully Convolutional Networks with Spatial and Channel &amp;#039;Squeeze &amp;amp; Excitation&amp;#039; Blocks）</news:title>
   <news:publication_date>2026-06-06T12:27:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697644</loc>
  <lastmod>2026-06-06T12:26:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>論理ルールを再考する：感情分類におけるエンコーディングの重要性（Revisiting the Importance of Encoding Logic Rules in Sentiment Classification）</news:title>
   <news:publication_date>2026-06-06T12:26:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697642</loc>
  <lastmod>2026-06-06T12:26:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝的プログラミングによるタイムドオートマトン学習（Learning Timed Automata via Genetic Programming）</news:title>
   <news:publication_date>2026-06-06T12:26:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697640</loc>
  <lastmod>2026-06-06T12:26:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索戦略の多様性を報酬に変える手法（Diversity-Driven Selection of Exploration Strategies in Multi-Armed Bandits）</news:title>
   <news:publication_date>2026-06-06T12:26:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697638</loc>
  <lastmod>2026-06-06T12:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストを知識グラフの実体へ写像する手法（Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs）</news:title>
   <news:publication_date>2026-06-06T12:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697636</loc>
  <lastmod>2026-06-06T11:34:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線信号分類に対する敵対的攻撃の実装と意味（Adversarial Attacks on Deep-Learning Based Radio Signal Classification）</news:title>
   <news:publication_date>2026-06-06T11:34:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697634</loc>
  <lastmod>2026-06-06T11:34:45Z</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ニューラルエンティティリンク（End-to-End Neural Entity Linking）</news:title>
   <news:publication_date>2026-06-06T11:34:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697632</loc>
  <lastmod>2026-06-06T11:34:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数NLPタスクの共有構造と階層の探索（Exploring Shared Structures and Hierarchies for Multiple NLP Tasks）</news:title>
   <news:publication_date>2026-06-06T11:34:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697630</loc>
  <lastmod>2026-06-06T11:34:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イントネーションが英語スピーキング評価で果たす役割（Role of Intonation in Scoring Spoken English）</news:title>
   <news:publication_date>2026-06-06T11:34:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697628</loc>
  <lastmod>2026-06-06T11:34:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習で学んだニューラルネットが能動流れ制御の戦略を発見（ARTIFICIAL NEURAL NETWORKS TRAINED THROUGH DEEP REINFORCEMENT LEARNING DISCOVER CONTROL STRATEGIES FOR ACTIVE FLOW CONTROL）</news:title>
   <news:publication_date>2026-06-06T11:34:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697626</loc>
  <lastmod>2026-06-06T11:33:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PVNetによる点群と多視点の統合3D形状認識（PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape Recognition）</news:title>
   <news:publication_date>2026-06-06T11:33:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697624</loc>
  <lastmod>2026-06-06T11:33:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地理的整合性を組み込んだ空中画像の深層マルチタスク学習（Deep multi-task learning for a geographically-regularized semantic segmentation of aerial images）</news:title>
   <news:publication_date>2026-06-06T11:33:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697622</loc>
  <lastmod>2026-06-06T10:43:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジで学習する機械学習アーキテクチャと5G適用（Machine Learning at the Edge: A Data-Driven Architecture with Applications to 5G Cellular Networks）</news:title>
   <news:publication_date>2026-06-06T10:43:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697620</loc>
  <lastmod>2026-06-06T10:42:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過去へ向けた局所実在論の検証（Testing Local Realism into the Past without Detection and Locality Loopholes）</news:title>
   <news:publication_date>2026-06-06T10:42:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697618</loc>
  <lastmod>2026-06-06T10:42:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス・ユニバーサムSVM（Multiclass Universum SVM）</news:title>
   <news:publication_date>2026-06-06T10:42:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697616</loc>
  <lastmod>2026-06-06T10:42:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自閉スペクトラム症における脳バイオマーカー解釈と深層学習（Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI）</news:title>
   <news:publication_date>2026-06-06T10:42:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697614</loc>
  <lastmod>2026-06-06T10:42:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>20 Questionsを政策ベース強化学習で解く（Playing 20 Question Game with Policy-Based Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-06T10:42:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697612</loc>
  <lastmod>2026-06-06T10:41:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己学習で泳ぐ微小スイマーの設計（Self-learning how to swim at low Reynolds number）</news:title>
   <news:publication_date>2026-06-06T10:41:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697610</loc>
  <lastmod>2026-06-06T10:41:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>昆虫サイボーグ：少量データで機械学習を改善する生体模倣特徴生成器 (Insect cyborgs: Bio-mimetic feature generators improve machine learning accuracy on limited data)</news:title>
   <news:publication_date>2026-06-06T10:41:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697608</loc>
  <lastmod>2026-06-06T09:50:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インターネット価格競争に対する潜在ディリクレ配分法（Latent Dirichlet Allocation for Internet Price War）</news:title>
   <news:publication_date>2026-06-06T09:50:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697606</loc>
  <lastmod>2026-06-06T09:50:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レビュー駆動型マルチラベル音楽スタイル分類（Review-Driven Multi-Label Music Style Classification）</news:title>
   <news:publication_date>2026-06-06T09:50:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697604</loc>
  <lastmod>2026-06-06T09:50:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常検知に効く生成的データ増強 DOPING（DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN）</news:title>
   <news:publication_date>2026-06-06T09:50:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697602</loc>
  <lastmod>2026-06-06T09:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳腫瘍の磁気共鳴スペクトロスコピー信号を生成する手法（Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models）</news:title>
   <news:publication_date>2026-06-06T09:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697600</loc>
  <lastmod>2026-06-06T09:49:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定論的状況における情報ボトルネックの注意点（Caveats for Information Bottleneck in Deterministic Scenarios）</news:title>
   <news:publication_date>2026-06-06T09:49:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697598</loc>
  <lastmod>2026-06-06T09:49:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムマルチモデル深層学習による分類改善（An Improvement of Data Classification Using Random Multimodel Deep Learning (RMDL))</news:title>
   <news:publication_date>2026-06-06T09:49:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697596</loc>
  <lastmod>2026-06-06T09:49:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RF駆動のコグニティブ無線に強化学習を応用する意義（Reinforcement Learning Approach for RF-Powered Cognitive Radio Network with Ambient Backscatter）</news:title>
   <news:publication_date>2026-06-06T09:49:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697594</loc>
  <lastmod>2026-06-06T08:58:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Anytime Learningが切り開く有機的コンピューティングの次段階（Anytime Learning - The next Step in Organic Computing?）</news:title>
   <news:publication_date>2026-06-06T08:58:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697592</loc>
  <lastmod>2026-06-06T08:57:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通信効率化された確率的勾配降下法の統一フレームワーク（Cooperative SGD: A Unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms）</news:title>
   <news:publication_date>2026-06-06T08:57:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697590</loc>
  <lastmod>2026-06-06T08:57:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Approximation Treesによるモデル蒸留の統計的安定性（Approximation Trees: Statistical Stability in Model Distillation）</news:title>
   <news:publication_date>2026-06-06T08:57:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697588</loc>
  <lastmod>2026-06-06T08:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴学習を用いた頑健な反事実推論（ROBUST COUNTERFACTUAL INFERENCES USING FEATURE LEARNING AND THEIR APPLICATIONS）</news:title>
   <news:publication_date>2026-06-06T08:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697586</loc>
  <lastmod>2026-06-06T08:56:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>透明な注意機構で深い翻訳モデルを学習する（Training Deeper Neural Machine Translation Models with Transparent Attention）</news:title>
   <news:publication_date>2026-06-06T08:56:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697584</loc>
  <lastmod>2026-06-06T08:56:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的セマンティック画像操作の学習（Learning Hierarchical Semantic Image Manipulation through Structured Representations）</news:title>
   <news:publication_date>2026-06-06T08:56:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697582</loc>
  <lastmod>2026-06-06T08:56:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランドマークベースの視覚的場所認識への深い洞察（Towards A Deep Insight into Landmark-based Visual Place Recognition: Methodology and Practice）</news:title>
   <news:publication_date>2026-06-06T08:56:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697580</loc>
  <lastmod>2026-06-06T08:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的学習による単眼深度推定の再考（Rethinking Monocular Depth Estimation with Adversarial Training）</news:title>
   <news:publication_date>2026-06-06T08:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697578</loc>
  <lastmod>2026-06-06T08:04:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワーク構造と変分不等式の接点（Deep Neural Network Structures Solving Variational Inequalities）</news:title>
   <news:publication_date>2026-06-06T08:04:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697576</loc>
  <lastmod>2026-06-06T08:04:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像で注目領域を自動活用するAttention Gate（Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images）</news:title>
   <news:publication_date>2026-06-06T08:04:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697574</loc>
  <lastmod>2026-06-06T08:03:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオ・ジグソー：映像の時空間文脈を利用した自己教師あり学習（Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition）</news:title>
   <news:publication_date>2026-06-06T08:03:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697572</loc>
  <lastmod>2026-06-06T08:03:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合型データに対応する拡張PCA：XPCA（XPCA: Extending PCA for a Combination of Discrete and Continuous Variables）</news:title>
   <news:publication_date>2026-06-06T08:03:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697570</loc>
  <lastmod>2026-06-06T08:02:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次特徴の民主的集約（Second-order Democratic Aggregation）</news:title>
   <news:publication_date>2026-06-06T08:02:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697568</loc>
  <lastmod>2026-06-06T08:02:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実務向けに再設計されたキャリブレーション用スコアリング（Calibration Scoring Rules for Practical Prediction Training）</news:title>
   <news:publication_date>2026-06-06T08:02:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697566</loc>
  <lastmod>2026-06-06T07:11:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深掘り：STUDIESが明かす微弱サブミリ波銀河の構造（SCUBA-2 ULTRA DEEP IMAGING EAO SURVEY (STUDIES) II: STRUCTURAL PROPERTIES AND NEAR-INFRARED MORPHOLOGIES OF FAINT SUBMILLIMETER GALAXIES）</news:title>
   <news:publication_date>2026-06-06T07:11:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697564</loc>
  <lastmod>2026-06-06T07:11:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深宇宙分布から宇宙論を推定するベイズ的フォワードモデリング（Cosmological inference from Bayesian forward modelling of deep galaxy redshift surveys）</news:title>
   <news:publication_date>2026-06-06T07:11:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697562</loc>
  <lastmod>2026-06-06T07:10:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形状ノイズ限界を超える弱レンズせん断推定（Weak lensing shear estimation beyond the shape-noise limit: a machine learning approach）</news:title>
   <news:publication_date>2026-06-06T07:10:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697560</loc>
  <lastmod>2026-06-06T07:09:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dトポロジー最適化を加速する畳み込みニューラルネットワーク（3D Topology Optimization Using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-06T07:09:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697558</loc>
  <lastmod>2026-06-06T07:09:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化された直交分解によるテンソル解析の拡張（GENERALIZED CANONICAL POLYADIC TENSOR DECOMPOSITION）</news:title>
   <news:publication_date>2026-06-06T07:09:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697556</loc>
  <lastmod>2026-06-06T07:09:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRからCTを合成するDeep Boosted Regression（Deep Boosted Regression for MR to CT Synthesis）</news:title>
   <news:publication_date>2026-06-06T07:09:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697554</loc>
  <lastmod>2026-06-06T07:09:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粗視化と微修正を同時に学ぶ光学フロー推定（JOINT COARSE-AND-FINE REASONING FOR DEEP OPTICAL FLOW）</news:title>
   <news:publication_date>2026-06-06T07:09:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697552</loc>
  <lastmod>2026-06-06T06:17:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然景観の属性操作を幻視で行う手法（Manipulating Attributes of Natural Scenes via Hallucination）</news:title>
   <news:publication_date>2026-06-06T06:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697550</loc>
  <lastmod>2026-06-06T06:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的ニューラルネットワーク構成による分割定数近似（AN EXPLICIT NEURAL NETWORK CONSTRUCTION FOR PIECEWISE CONSTANT FUNCTION APPROXIMATION）</news:title>
   <news:publication_date>2026-06-06T06:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697548</loc>
  <lastmod>2026-06-06T06:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全条件下のキュービック正則化ニュートン法の実用化（A Note on Inexact Condition for Cubic Regularized Newton’s Method）</news:title>
   <news:publication_date>2026-06-06T06:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697546</loc>
  <lastmod>2026-06-06T06:16:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的自己注意による文埋め込みの改良（Dynamic Self-Attention: Computing Attention over Words Dynamically）</news:title>
   <news:publication_date>2026-06-06T06:16:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697544</loc>
  <lastmod>2026-06-06T06:15:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意の「柔らかさ」を学習する—自己適応的注意温度（Self-Adaptive Attention Temperature）</news:title>
   <news:publication_date>2026-06-06T06:15:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697542</loc>
  <lastmod>2026-06-06T06:15:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KŁ性質下における三次正則化法の収束解析（Convergence of Cubic Regularization for Nonconvex Optimization under KŁ Property）</news:title>
   <news:publication_date>2026-06-06T06:15:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697540</loc>
  <lastmod>2026-06-06T06:15:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダンス動作のモーション転送技術（Everybody Dance Now）</news:title>
   <news:publication_date>2026-06-06T06:15:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697538</loc>
  <lastmod>2026-06-06T05:23:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブワード単位からのニューラル固有表現認識（Neural Named Entity Recognition from Subword Units）</news:title>
   <news:publication_date>2026-06-06T05:23:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697536</loc>
  <lastmod>2026-06-06T05:23:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数枝シアムネットワークとオンライン選択による物体追跡（Multi-Branch Siamese Networks with Online Selection for Object Tracking）</news:title>
   <news:publication_date>2026-06-06T05:23:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697534</loc>
  <lastmod>2026-06-06T05:23:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質構造分類と予測のためのカプセルネットワーク（Capsule Networks for Protein Structure Classification and Prediction）</news:title>
   <news:publication_date>2026-06-06T05:23:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697532</loc>
  <lastmod>2026-06-06T05:22:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>4つのコズミックシア調査を統一解析する手法が示した本質（A Unified Analysis of Four Cosmic Shear Surveys）</news:title>
   <news:publication_date>2026-06-06T05:22:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697530</loc>
  <lastmod>2026-06-06T05:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙ベクトルの拡張的レトロフィッティング（Expansional Retrofitting for Word Vector Enrichment）</news:title>
   <news:publication_date>2026-06-06T05:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697527</loc>
  <lastmod>2026-06-06T05:22:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少量データで複数領域を横断する文書レイアウト理解（Multidomain Document Layout Understanding using Few Shot Object Detection）</news:title>
   <news:publication_date>2026-06-06T05:22:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697525</loc>
  <lastmod>2026-06-06T05:21:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セミトレインドメムリスタクロスバーとオンデバイス学習加速器（Semi-Trained Memristive Crossbar Computing Engine with In-Situ Learning Accelerator）</news:title>
   <news:publication_date>2026-06-06T05:21:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697523</loc>
  <lastmod>2026-06-06T04:30:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダルデータにおける隠れ成分の回復（RECOVERING HIDDEN COMPONENTS IN MULTIMODAL DATA WITH COMPOSITE DIFFUSION OPERATORS）</news:title>
   <news:publication_date>2026-06-06T04:30:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697521</loc>
  <lastmod>2026-06-06T04:20:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構付き畳み込みニューラルネットワークによる文分類（An attention-gated convolutional neural network for sentence classification）</news:title>
   <news:publication_date>2026-06-06T04:20:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697519</loc>
  <lastmod>2026-06-06T04:20:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽的洗練度の推定（Predicting Musical Sophistication from Music Listening Behaviors）</news:title>
   <news:publication_date>2026-06-06T04:20:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697517</loc>
  <lastmod>2026-06-06T04:19:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルなしで学ぶ動画人物再識別の新枠組み（Deep Association Learning for Unsupervised Video Person Re-identification）</news:title>
   <news:publication_date>2026-06-06T04:19:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697515</loc>
  <lastmod>2026-06-06T04:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情メモリによる非並列データでの感情変換（Learning Sentiment Memories for Sentiment Modification without Parallel Data）</news:title>
   <news:publication_date>2026-06-06T04:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697513</loc>
  <lastmod>2026-06-06T04:18:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepCorrによるTorの流量相関攻撃（DeepCorr: Strong Flow Correlation Attacks on Tor Using Deep Learning）</news:title>
   <news:publication_date>2026-06-06T04:18:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697511</loc>
  <lastmod>2026-06-06T04:18:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オークション詐欺データのクラスタリングとラベリング（Clustering and Labelling Auction Fraud Data）</news:title>
   <news:publication_date>2026-06-06T04:18:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697509</loc>
  <lastmod>2026-06-06T03:26:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サポート集合の構造情報を活かす一撃学習（Learning to Support: Exploiting Structure Information in Support Sets for One-Shot Learning）</news:title>
   <news:publication_date>2026-06-06T03:26:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697507</loc>
  <lastmod>2026-06-06T03:18:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ネットワーク生成画像の識別における色成分の差異（Identification of Deep Network Generated Images Using Disparities in Color Components）</news:title>
   <news:publication_date>2026-06-06T03:18:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697505</loc>
  <lastmod>2026-06-06T03:17:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CentralNet: マルチモーダル融合を階層的に実現する手法（CentralNet: a Multilayer Approach for Multimodal Fusion）</news:title>
   <news:publication_date>2026-06-06T03:17:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697503</loc>
  <lastmod>2026-06-06T03:17:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列に適応する深層プーリングによる行動認識（Deep Adaptive Temporal Pooling for Activity Recognition）</news:title>
   <news:publication_date>2026-06-06T03:17:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697501</loc>
  <lastmod>2026-06-06T03:16:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LASSOのスケーリングによる改善（On an improvement of LASSO by scaling）</news:title>
   <news:publication_date>2026-06-06T03:16:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697499</loc>
  <lastmod>2026-06-06T03:16:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MicroBooNEの画素レベル電磁粒子同定を可能にした深層ニューラルネットワーク（A Deep Neural Network for Pixel-Level Electromagnetic Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber）</news:title>
   <news:publication_date>2026-06-06T03:16:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697497</loc>
  <lastmod>2026-06-06T03:16:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約空間におけるモード崩壊からの脱出（Escaping from Collapsing Modes in a Constrained Space）</news:title>
   <news:publication_date>2026-06-06T03:16:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697495</loc>
  <lastmod>2026-06-06T02:24:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた現代の物体検出サーベイ（A Survey of Modern Object Detection Literature using Deep Learning）</news:title>
   <news:publication_date>2026-06-06T02:24:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697493</loc>
  <lastmod>2026-06-06T02:24:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スポンサードサーチの反実仮想ポリシー推定器Genie（Genie: An Open Box Counterfactual Policy Estimator for Optimizing Sponsored Search Marketplace）</news:title>
   <news:publication_date>2026-06-06T02:24:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697491</loc>
  <lastmod>2026-06-06T02:24:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークラッソによる半教師付き回帰の解析（Analysis of Network Lasso for Semi-Supervised Regression）</news:title>
   <news:publication_date>2026-06-06T02:24:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697489</loc>
  <lastmod>2026-06-06T02:23:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像における弱教師あり局所化のための深層マルチスケール特徴学習（Deep multiscale convolutional feature learning for weakly supervised localization of chest pathologies in X-ray images）</news:title>
   <news:publication_date>2026-06-06T02:23:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697487</loc>
  <lastmod>2026-06-06T02:23:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト感情表現の最適化（Finding Good Representations of Emotions for Text Classification）</news:title>
   <news:publication_date>2026-06-06T02:23:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697485</loc>
  <lastmod>2026-06-06T02:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的文脈化表現によるマルチターン応答選択の改善（Improving Matching Models with Hierarchical Contextualized Representations for Multi-turn Response Selection）</news:title>
   <news:publication_date>2026-06-06T02:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697483</loc>
  <lastmod>2026-06-06T02:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類器間の「議論が起きる領域」を見つける手法（Controversy Rules — Discovering Regions Where Classifiers (Dis-)Agree Exceptionally）</news:title>
   <news:publication_date>2026-06-06T02:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697481</loc>
  <lastmod>2026-06-06T01:31:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続最適化によるニューラルアーキテクチャ探索（Neural Architecture Optimization）</news:title>
   <news:publication_date>2026-06-06T01:31:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697479</loc>
  <lastmod>2026-06-06T01:27:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリック回帰と教師あり機械学習のための統一導関数ベースのモデル解釈（Model Interpretation: A Unified Derivative-based Framework for Nonparametric Regression and Supervised Machine Learning）</news:title>
   <news:publication_date>2026-06-06T01:27:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697477</loc>
  <lastmod>2026-06-06T01:21:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合密度ネットワークによる核検出（Nuclei Detection Using Mixture Density Networks）</news:title>
   <news:publication_date>2026-06-06T01:21:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697475</loc>
  <lastmod>2026-06-06T01:21:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>授業前動画への応答収集システム（Response Collector: A Video Learning System for Flipped Classrooms）</news:title>
   <news:publication_date>2026-06-06T01:21:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697473</loc>
  <lastmod>2026-06-06T01:20:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きなミニバッチを使うな、ローカルSGDを使え（DON&amp;#039;T USE LARGE MINI-BATCHES, USE LOCAL SGD）</news:title>
   <news:publication_date>2026-06-06T01:20:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697471</loc>
  <lastmod>2026-06-06T01:20:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポーカー確率を深層学習で近似する（Approximating Poker Probabilities with Deep Learning）</news:title>
   <news:publication_date>2026-06-06T01:20:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697469</loc>
  <lastmod>2026-06-06T01:19:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均場近似、凸ヒエラルキー、および相関ラウンディングの最適性（Mean-field approximation, convex hierarchies, and the optimality of correlation rounding）</news:title>
   <news:publication_date>2026-06-06T01:19:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697467</loc>
  <lastmod>2026-06-06T00:28:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム深層ネットワークのフィッシャー情報量と自然勾配学習（Fisher Information and Natural Gradient Learning of Random Deep Networks）</news:title>
   <news:publication_date>2026-06-06T00:28:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697465</loc>
  <lastmod>2026-06-06T00:20:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粗い注釈から高精度セマンティックセグメンテーションへ（Coarse-to-Fine Annotation Enrichment for Semantic Segmentation Learning）</news:title>
   <news:publication_date>2026-06-06T00:20:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697463</loc>
  <lastmod>2026-06-06T00:20:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在変数を用いた抽出型文書要約（Neural Latent Extractive Document Summarization）</news:title>
   <news:publication_date>2026-06-06T00:20:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697461</loc>
  <lastmod>2026-06-06T00:20:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2次元投影のみで3D姿勢は学習できるか（Can 3D Pose be Learned from 2D Projections Alone?）</news:title>
   <news:publication_date>2026-06-06T00:20:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697459</loc>
  <lastmod>2026-06-06T00:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタードラッソの効率的解法（Efficient sparse semismooth Newton methods for the clustered lasso problem）</news:title>
   <news:publication_date>2026-06-06T00:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697457</loc>
  <lastmod>2026-06-06T00:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ネットワークの信号空間の統計力学的幾何学（Statistical Neurodynamics of Deep Networks: Geometry of Signal Spaces）</news:title>
   <news:publication_date>2026-06-06T00:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697455</loc>
  <lastmod>2026-06-06T00:18:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HEARO-5に基づく心疾患検出のDNN最適化（On Deep Neural Networks for Detecting Heart Disease）</news:title>
   <news:publication_date>2026-06-06T00:18:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697453</loc>
  <lastmod>2026-06-05T23:26:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>漸近的ソフトフィルタープルーニング（Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-05T23:26:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697451</loc>
  <lastmod>2026-06-05T23:25:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分残差学習による超解像の改善（IMPROVING SUPER RESOLUTION METHODS VIA INCREMENTAL RESIDUAL LEARNING）</news:title>
   <news:publication_date>2026-06-05T23:25:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697449</loc>
  <lastmod>2026-06-05T23:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化と前処理による高速PET再構成（Faster PET Reconstruction with Randomization and Preconditioning）</news:title>
   <news:publication_date>2026-06-05T23:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697447</loc>
  <lastmod>2026-06-05T23:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対数凹性がない場合のサンプリングアルゴリズムの非漸近境界（Non-asymptotic bounds for sampling algorithms without log-concavity）</news:title>
   <news:publication_date>2026-06-05T23:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697445</loc>
  <lastmod>2026-06-05T23:24:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼度に基づくレコメンダー（CoBaR: Confidence-Based Recommender）</news:title>
   <news:publication_date>2026-06-05T23:24:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697443</loc>
  <lastmod>2026-06-05T23:24:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話相手を知ろうとすることで会話が魅力的になる（Aiming to Know You Better Perhaps Makes Me a More Engaging Dialogue Partner）</news:title>
   <news:publication_date>2026-06-05T23:24:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697441</loc>
  <lastmod>2026-06-05T23:23:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波システムの位置推定（Position Locationing for Millimeter Wave Systems）</news:title>
   <news:publication_date>2026-06-05T23:23:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697439</loc>
  <lastmod>2026-06-05T22:32:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動意思決定における人工的説明（Artificial Explanations in Automated Decision-Making）</news:title>
   <news:publication_date>2026-06-05T22:32:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697437</loc>
  <lastmod>2026-06-05T22:32:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調学習環境における学生成果（Student Outcomes Across Collaborative-Learning Environments）</news:title>
   <news:publication_date>2026-06-05T22:32:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697435</loc>
  <lastmod>2026-06-05T22:31:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による非局所相関の検出と定量化（Machine learning non-local correlations）</news:title>
   <news:publication_date>2026-06-05T22:31:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697433</loc>
  <lastmod>2026-06-05T22:31:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話型質問応答の挑戦（CoQA: A Conversational Question Answering Challenge）</news:title>
   <news:publication_date>2026-06-05T22:31:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697431</loc>
  <lastmod>2026-06-05T22:30:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異質性の呪い――スパース混合モデルと位相回復における計算的障壁（Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval）</news:title>
   <news:publication_date>2026-06-05T22:30:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697429</loc>
  <lastmod>2026-06-05T22:30:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話文脈における質問応答のデータセットが切り拓く地平（QuAC: Question Answering in Context）</news:title>
   <news:publication_date>2026-06-05T22:30:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697427</loc>
  <lastmod>2026-06-05T22:30:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーネットワークによる知識グラフ埋め込み（Hypernetwork Knowledge Graph Embeddings）</news:title>
   <news:publication_date>2026-06-05T22:30:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697425</loc>
  <lastmod>2026-06-05T21:39:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PDFマルウェア検出におけるMLPベース手法の実務的示唆（MLPdf: An Effective Machine Learning Based Approach for PDF Malware Detection）</news:title>
   <news:publication_date>2026-06-05T21:39:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697423</loc>
  <lastmod>2026-06-05T21:38:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Union of Intersectionsを用いた大規模統計推定の最適化（Optimizing the Union of Intersections LASSO (UoILASSO) and Vector Autoregressive (UoIVAR) Algorithms for Improved Statistical Estimation at Scale）</news:title>
   <news:publication_date>2026-06-05T21:38:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697421</loc>
  <lastmod>2026-06-05T21:38:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ESO 428-G014の深部Chandra観測：イオン化コーンと電波ジェット領域の高解像度分光イメージング（Deep Chandra Observations of ESO 428-G014: III. High Resolution Spectral Imaging of the Ionization Cone and Radio Jet Region）</news:title>
   <news:publication_date>2026-06-05T21:38:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697419</loc>
  <lastmod>2026-06-05T21:37:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>4DCTからの肺換気画像生成を深層CNNで直接推定する手法（Deriving ventilation imaging from 4DCT by deep convolutional neural network）</news:title>
   <news:publication_date>2026-06-05T21:37:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697417</loc>
  <lastmod>2026-06-05T21:37:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PSR J2055+2539の二本の尾の解析（The two tails of PSR J2055+2539 as seen by Chandra: Analysis of the nebular morphology and pulsar proper motion）</news:title>
   <news:publication_date>2026-06-05T21:37:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697415</loc>
  <lastmod>2026-06-05T21:37:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイドフィールド星のトレイル画像と深層学習による亜秒天文変動探索（Searching for Sub-Second Stellar Variability with Wide-Field Star Trails and Deep Learning）</news:title>
   <news:publication_date>2026-06-05T21:37:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697413</loc>
  <lastmod>2026-06-05T21:36:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変数選択のためのアンサンブル学習法（An ensemble learning method for variable selection: application to high-dimensional data and missing values）</news:title>
   <news:publication_date>2026-06-05T21:36:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697409</loc>
  <lastmod>2026-06-05T19:53:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文章の一貫性を高める骨格ベース生成（A Skeleton-Based Model for Promoting Coherence Among Sentences in Narrative Story Generation）</news:title>
   <news:publication_date>2026-06-05T19:53:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697407</loc>
  <lastmod>2026-06-05T19:52:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DFT駆動の多忠実度アプローチによる原子スケールエネルギーモデル（Smart energy models for atomistic simulations using a DFT-driven multifidelity approach）</news:title>
   <news:publication_date>2026-06-05T19:52:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697405</loc>
  <lastmod>2026-06-05T19:52:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バックプロパゲーションの生物学的妥当性を問い直す（Backpropagation and Biological Plausibility）</news:title>
   <news:publication_date>2026-06-05T19:52:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697403</loc>
  <lastmod>2026-06-05T19:51:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等長変換に不変なグラフベース深層ニューラルネットワーク（Isometric Transformation Invariant Graph-based Deep Neural Network）</news:title>
   <news:publication_date>2026-06-05T19:51:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697401</loc>
  <lastmod>2026-06-05T19:51:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>改善に基づく新しい獲得関数によるベイズ最適化の改良（On a New Improvement-Based Acquisition Function for Bayesian Optimization）</news:title>
   <news:publication_date>2026-06-05T19:51:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697399</loc>
  <lastmod>2026-06-05T19:51:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DevOpsにおけるパフォーマンス対応の実践調査（How is Performance Addressed in DevOps? A Survey on Industrial Practices）</news:title>
   <news:publication_date>2026-06-05T19:51:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697397</loc>
  <lastmod>2026-06-05T19:50:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルによる拡張可能な母集団合成（Scalable Population Synthesis with Deep Generative Modeling）</news:title>
   <news:publication_date>2026-06-05T19:50:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697395</loc>
  <lastmod>2026-06-05T18:59:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間系列予測の機械学習総説（Machine Learning for Spatiotemporal Sequence Forecasting: A Survey）</news:title>
   <news:publication_date>2026-06-05T18:59:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697393</loc>
  <lastmod>2026-06-05T18:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次元双磁気励起子の準安定束縛状態（Metastable Bound States of the Two-Dimensional Bi-magnetoexcitons in the Lowest Landau Levels Approximation）</news:title>
   <news:publication_date>2026-06-05T18:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697391</loc>
  <lastmod>2026-06-05T18:57:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模点群を効率的に処理するハイブリッド3D畳み込み（Fully-Convolutional Point Networks for Large-Scale Point Clouds）</news:title>
   <news:publication_date>2026-06-05T18:57:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697389</loc>
  <lastmod>2026-06-05T18:57:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練データへの改ざんが引き起こす深刻なリスク（Are You Tampering With My Data?）</news:title>
   <news:publication_date>2026-06-05T18:57:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697387</loc>
  <lastmod>2026-06-05T18:57:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語ニューラル機械翻訳が学ぶ意味抽象の測定（Measuring Semantic Abstraction of Multilingual NMT with Paraphrase Recognition and Generation Tasks）</news:title>
   <news:publication_date>2026-06-05T18:57:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697385</loc>
  <lastmod>2026-06-05T18:57:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストから画像を作る新しい道具：対称蒸留ネットワーク（Text-to-image Synthesis via Symmetrical Distillation Networks）</news:title>
   <news:publication_date>2026-06-05T18:57:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697383</loc>
  <lastmod>2026-06-05T18:56:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フレア核におけるベクトル磁場の測定（Measurement of Vector Magnetic Field in a Flare kernel with a Spectropolarimetric Observation in He I 10830 Å）</news:title>
   <news:publication_date>2026-06-05T18:56:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697381</loc>
  <lastmod>2026-06-05T18:05:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>zoNNscan: 境界エントロピーによる入力周辺検査インデックス（zoNNscan: a boundary-entropy index for zone inspection of neural models）</news:title>
   <news:publication_date>2026-06-05T18:05:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697379</loc>
  <lastmod>2026-06-05T18:05:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損モダリティに強い推薦学習（LRMM: Learning to Recommend with Missing Modalities）</news:title>
   <news:publication_date>2026-06-05T18:05:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697377</loc>
  <lastmod>2026-06-05T18:04:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセンター冷却の消費電力最適化のための強化学習テストベッド（Reinforcement Learning Testbed for Power-Consumption Optimization）</news:title>
   <news:publication_date>2026-06-05T18:04:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697375</loc>
  <lastmod>2026-06-05T18:03:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ithemalによる基本ブロック・スループット推定の実用化（Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-05T18:03:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697373</loc>
  <lastmod>2026-06-05T18:03:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床領域における自然言語推論からの教訓（Lessons from Natural Language Inference in the Clinical Domain）</news:title>
   <news:publication_date>2026-06-05T18:03:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697371</loc>
  <lastmod>2026-06-05T18:03:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり学習によるニューラルキーフレーズ生成（Semi-Supervised Learning for Neural Keyphrase Generation）</news:title>
   <news:publication_date>2026-06-05T18:03:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697369</loc>
  <lastmod>2026-06-05T18:02:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化された痛み認識のための多タスク多重カーネル機（Multi-task multiple kernel machines for personalized pain recognition from fNIRS）</news:title>
   <news:publication_date>2026-06-05T18:02:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697367</loc>
  <lastmod>2026-06-05T17:11:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的セマンティックパーシングによるIf-Thenレシピ合成（Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-05T17:11:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697365</loc>
  <lastmod>2026-06-05T17:10:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文内ノイズ低減と転移学習によるニューラル関係抽出（Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning）</news:title>
   <news:publication_date>2026-06-05T17:10:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697363</loc>
  <lastmod>2026-06-05T17:10:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非整合残差分布を正則化するWrapped Loss Function（Wrapped Loss Function for Regularizing Nonconforming Residual Distributions）</news:title>
   <news:publication_date>2026-06-05T17:10:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697361</loc>
  <lastmod>2026-06-05T17:09:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>損失データ分析（Loss Data Analytics）</news:title>
   <news:publication_date>2026-06-05T17:09:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697359</loc>
  <lastmod>2026-06-05T17:09:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>壊滅的忘却の重要性（Catastrophic Importance of Catastrophic Forgetting）</news:title>
   <news:publication_date>2026-06-05T17:09:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697357</loc>
  <lastmod>2026-06-05T17:09:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床時系列データにおける不変性を学習する手法（Sequence Transformer Networks）</news:title>
   <news:publication_date>2026-06-05T17:09:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697355</loc>
  <lastmod>2026-06-05T17:08:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速スペクトログラム反転とMCNNの実務的意義（Fast Spectrogram Inversion using Multi-head Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-05T17:08:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697353</loc>
  <lastmod>2026-06-05T16:17:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VIEW-ENHANCED RECURRENT ATTENTIONによる3D形状分類の能動的視点選択（VERAM: View-Enhanced Recurrent Attention Model for 3D Shape Classification）</news:title>
   <news:publication_date>2026-06-05T16:17:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697351</loc>
  <lastmod>2026-06-05T16:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像のメタデータ改竄検出の多モーダル手法（Deep Multimodal Image-Repurposing Detection）</news:title>
   <news:publication_date>2026-06-05T16:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697349</loc>
  <lastmod>2026-06-05T16:16:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Vapnik-Chervonenkis次元を用いたモデル選択（Use Of Vapnik-Chervonenkis Dimension in Model Selection）</news:title>
   <news:publication_date>2026-06-05T16:16:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697347</loc>
  <lastmod>2026-06-05T16:15:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Class2Strによる潜在階層学習（Class2Str: End to End Latent Hierarchy Learning）</news:title>
   <news:publication_date>2026-06-05T16:15:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697345</loc>
  <lastmod>2026-06-05T16:15:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep InfoMaxによる表現学習の再定義（LEARNING DEEP REPRESENTATIONS BY MUTUAL INFORMATION ESTIMATION AND MAXIMIZATION）</news:title>
   <news:publication_date>2026-06-05T16:15:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697343</loc>
  <lastmod>2026-06-05T16:15:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的対抗サンプリングによる能動学習の実用的意義（Adversarial Sampling for Active Learning）</news:title>
   <news:publication_date>2026-06-05T16:15:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697341</loc>
  <lastmod>2026-06-05T16:14:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の意味的ラベル表現を用いた外部分布検出（Out-of-Distribution Detection using Multiple Semantic Label Representations）</news:title>
   <news:publication_date>2026-06-05T16:14:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697339</loc>
  <lastmod>2026-06-05T15:23:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星の内部を</news:title>
   <news:publication_date>2026-06-05T15:23:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697337</loc>
  <lastmod>2026-06-05T15:23:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復によるプライバシー増幅（Privacy Amplification by Iteration）</news:title>
   <news:publication_date>2026-06-05T15:23:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697335</loc>
  <lastmod>2026-06-05T15:21:43Z</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設計のためのハイブリッド差分進化法 (A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image Classification)</news:title>
   <news:publication_date>2026-06-05T15:21:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697333</loc>
  <lastmod>2026-06-05T15:21:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト表現からの人口統計属性の逆例的除去（Adversarial Removal of Demographic Attributes from Text Data）</news:title>
   <news:publication_date>2026-06-05T15:21:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697331</loc>
  <lastmod>2026-06-05T15:21:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的組合せアンサンブルによる敵対的摂動への防御（Stochastic Combinatorial Ensembles for Defending Against Adversarial Examples）</news:title>
   <news:publication_date>2026-06-05T15:21:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697329</loc>
  <lastmod>2026-06-05T15:20:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>縦断データに対する監視付きカーネルPCAの提案（Supervised Kernel PCA For Longitudinal Data）</news:title>
   <news:publication_date>2026-06-05T15:20:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/697327</loc>
  <lastmod>2026-06-05T15:20:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽子スピンパズルの解明に向けて（Towards solving the proton spin puzzle）</news:title>
   <news:publication_date>2026-06-05T15:20:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
</urlset>
