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   <news:title>信用できない環境でのプライベートなマルチパーティ機械学習（Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting）</news:title>
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   <news:title>脳に学ぶ注意の学習――ATTNetによる視覚注意の強化学習的モデル化（Learning to attend in a brain-inspired deep neural network）</news:title>
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   <news:title>曲率正則化によるロバスト性の向上（Robustness via curvature regularization, and vice versa）</news:title>
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    <news:language>ja</news:language>
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   <news:title>深層ニューラルネットワーク説明のための代表点選択（Representer Point Selection for Explaining Deep Neural Networks）</news:title>
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   <news:title>TorchProteinLibrary：高速で微分可能なタンパク質構造表現（TorchProteinLibrary: A computationally efﬁcient, differentiable representation of protein structure）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>教師なしで脳白質病変を自動検出する技術の本質（Unsupervised brain lesion segmentation from MRI using a convolutional autoencoder）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>深層特徴とスパース表現を組み合わせたCBIRの比較検討（Detailed Investigation of Deep Features with Sparse Representation and Dimensionality Reduction in CBIR: A Comparative Study）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>子宮頸部細胞画像のための新しいデータセットと核検出法の提案（A NEW CERVICAL CYTOLOGY DATASET FOR NUCLEUS DETECTION AND IMAGE CLASSIFICATION (CERVIX93)）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ASASSN-18btの系統解析：非縮退伴星の否定によるIa型超新星論の再整理（No Stripped Companion Material in the Nebular Spectrum of the “Two-Component” Type Ia Supernova ASASSN-18bt）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>意思決定カスケードにおける信念の役割（Beliefs in Decision-Making Cascades）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-09T04:04:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>太陽系に取り込まれた恒星間天体の識別法（Identifying Interstellar Objects Trapped in the Solar System through Their Orbital Parameters）</news:title>
   <news:publication_date>2026-07-09T04:04:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-09T03:12:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>FLaREONによる高速なLyα放射の予測（FLaREON: a fast computation of Lyα escape fractions and line profiles）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ギャップ内での惑星による分子線幅拡張の観測的指標（Observational Signatures of Planets in Protoplanetary Disks: Planet-Induced Line Broadening in Gaps）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709748</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Model-Based Reinforcement Learningを用いた敗血症治療（Model-Based Reinforcement Learning for Sepsis Treatment）</news:title>
   <news:publication_date>2026-07-09T03:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>分子における関係性を発見・統合するスペクトル・マルチグラフネットワーク（Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>長文翻訳に強い階層型ニューラルネットワークの提案（A Hierarchical Neural Network for Sequence-to-Sequences Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>学習理論における普遍的推定量の再検討（Note on universal algorithms for learning theory）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的イノベーションと創造的で持続可能な世界観の進化（Social Innovation and the Evolution of Creative, Sustainable Worldviews）</news:title>
   <news:publication_date>2026-07-09T03:11:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-09T02:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>未知のガウス過程事前分布を伴うメタベイズ最適化の後悔境界（Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>遺伝子発現データの二方向クラスタリングにおけるFCAとアソシエーションルールの活用（Biclustering Gene Expression Data Using FCA and Association Rules）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>カーネルに基づく生成ネットワークの学習（Kernel-Based Training of Generative Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709732</loc>
  <lastmod>2026-07-09T02:14:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Lipschitz正則化がGAN訓練に与える影響（How does Lipschitz Regularization Influence GAN Training?）</news:title>
   <news:publication_date>2026-07-09T02:14:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>超高次元コンピューティングのナノシステム（Hyperdimensional Computing Nanosystem）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-09T02:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VGGを用いた自動ぶどう樹フェノタイピングの適応的手法（An Adaptive Approach for Automated Grapevine Phenotyping using VGG-based Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-09T02:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-09T02:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成記憶のためのアトラクタダイナミクス学習（Learning Attractor Dynamics for Generative Memory）</news:title>
   <news:publication_date>2026-07-09T02:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-07-09T01:21:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダーで見つける慣性多様体の次元（Estimating of the inertial manifold dimension for a chaotic attractor of complex Ginzburg-Landau equation using a neural network）</news:title>
   <news:publication_date>2026-07-09T01:21:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709722</loc>
  <lastmod>2026-07-09T01:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核弾頭認証プロトコルにおけるプライバシーの定量化（Quantifying Privacy in Nuclear Warhead Authentication Protocols）</news:title>
   <news:publication_date>2026-07-09T01:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/709720</loc>
  <lastmod>2026-07-09T01:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元分類におけるℓ0ペナルティ付き経験的リスク最小化（High Dimensional Classification through ℓ0-Penalized Empirical Risk Minimization）</news:title>
   <news:publication_date>2026-07-09T01:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709718</loc>
  <lastmod>2026-07-09T01:20:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非ガウス分布データ解析の実務的手法（Selected Methods for non-Gaussian Data Analysis）</news:title>
   <news:publication_date>2026-07-09T01:20:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/709716</loc>
  <lastmod>2026-07-09T01:20:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海中ハイドロフォンの特性評価とKM3NeT実験の示唆（Hydrophone characterization for the KM3NeT experiment）</news:title>
   <news:publication_date>2026-07-09T01:20:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/709714</loc>
  <lastmod>2026-07-09T01:20:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>惑星探査ローバのグローバル経路計画に関する学習ベースの新手法（A Novel Learning-based Global Path Planning Algorithm for Planetary Rovers）</news:title>
   <news:publication_date>2026-07-09T01:20:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/709712</loc>
  <lastmod>2026-07-09T01:20:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜画像における視神経乳頭（Optic Disc）と中心窩（Fovea）の位置推定に関する関係ネットワークの応用（Relation Networks for Optic Disc and Fovea Localization in Retinal Images）</news:title>
   <news:publication_date>2026-07-09T01:20:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709710</loc>
  <lastmod>2026-07-09T00:28:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実データの特徴を合成空間へ写像する手法の実務的意義（Mapping Unlabeled Real Data for Label AUstERity）</news:title>
   <news:publication_date>2026-07-09T00:28:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709708</loc>
  <lastmod>2026-07-09T00:27:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差が特徴となる稲妻予測（The Error is the Feature: How to Forecast Lightning using a Model Prediction Error）</news:title>
   <news:publication_date>2026-07-09T00:27:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709706</loc>
  <lastmod>2026-07-09T00:27:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Privacy-preserving Stackingによる組織間糖尿病予測の秘匿化（Privacy-preserving Stacking with Application to Cross-organizational Diabetes Prediction）</news:title>
   <news:publication_date>2026-07-09T00:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709704</loc>
  <lastmod>2026-07-09T00:27:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列逐次モンテカルロによる非凸確率的最適化（Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization）</news:title>
   <news:publication_date>2026-07-09T00:27:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709702</loc>
  <lastmod>2026-07-09T00:26:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みにおけるフィルタサイズの重要性（On Filter Size in Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-07-09T00:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709700</loc>
  <lastmod>2026-07-09T00:26:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAV画像による欠陥検出とリージョンベースCNNの応用（Defect Detection from UAV Images based on Region-Based CNNs）</news:title>
   <news:publication_date>2026-07-09T00:26:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709698</loc>
  <lastmod>2026-07-09T00:26:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床概念埋め込みを用いた英国EHRにおける心不全予測の応用（Application of Clinical Concept Embeddings for Heart Failure Prediction in UK EHR data）</news:title>
   <news:publication_date>2026-07-09T00:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709696</loc>
  <lastmod>2026-07-08T23:35:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホップフィールド網を使った量子状態準備の地上状態設計（Designing ground states of Hopﬁeld networks for quantum state preparation）</news:title>
   <news:publication_date>2026-07-08T23:35:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709694</loc>
  <lastmod>2026-07-08T23:35:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経架構探索と量子化の共同探索（Joint Neural Architecture Search and Quantization）</news:title>
   <news:publication_date>2026-07-08T23:35:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709692</loc>
  <lastmod>2026-07-08T23:34:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低資源環境における医療分野のタスク指向対話の自然言語理解（Natural language understanding for task oriented dialog in the biomedical domain in a low resources context）</news:title>
   <news:publication_date>2026-07-08T23:34:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709690</loc>
  <lastmod>2026-07-08T23:34:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師あり学習による時系列一貫性の獲得（Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation）</news:title>
   <news:publication_date>2026-07-08T23:34:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709688</loc>
  <lastmod>2026-07-08T23:34:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語レベルの明示的相互作用によるテキスト分類（Explicit Interaction Model towards Text Classification）</news:title>
   <news:publication_date>2026-07-08T23:34:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709686</loc>
  <lastmod>2026-07-08T23:34:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの3D物体再構築に向けた多視点点群回帰（MVPNet: Multi-View Point Regression Networks for 3D Object Reconstruction from A Single Image）</news:title>
   <news:publication_date>2026-07-08T23:34:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709684</loc>
  <lastmod>2026-07-08T23:33:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習アルゴリズムの複数デフォルト学習（Learning Multiple Defaults for Machine Learning Algorithms）</news:title>
   <news:publication_date>2026-07-08T23:33:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709682</loc>
  <lastmod>2026-07-08T22:42:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散系におけるネットワーク制約付き需要応答価格設定のオンライン学習（Online Learning for Network Constrained Demand Response Pricing in Distribution Systems）</news:title>
   <news:publication_date>2026-07-08T22:42:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709680</loc>
  <lastmod>2026-07-08T22:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多チャネル遠隔音声認識における周波数変調特徴量の改善（Improved Frequency Modulation Features for Multichannel Distant Speech Recognition）</news:title>
   <news:publication_date>2026-07-08T22:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709678</loc>
  <lastmod>2026-07-08T22:41:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強力なベースラインの重要性（On the Importance of Strong Baselines in Bayesian Deep Learning）</news:title>
   <news:publication_date>2026-07-08T22:41:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709676</loc>
  <lastmod>2026-07-08T22:41:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>i.i.d. を仮定しない非線形回帰（Nonlinear Regression without i.i.d. Assumption）</news:title>
   <news:publication_date>2026-07-08T22:41:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709674</loc>
  <lastmod>2026-07-08T22:41:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群の回転不変特徴抽出手法（Pointwise Rotation-Invariant Network with Adaptive Sampling and 3D Spherical Voxel Convolution）</news:title>
   <news:publication_date>2026-07-08T22:41:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709672</loc>
  <lastmod>2026-07-08T22:41:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データに強い平均推定をほぼ線形時間で行う方法（High-Dimensional Robust Mean Estimation in Nearly-Linear Time）</news:title>
   <news:publication_date>2026-07-08T22:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709670</loc>
  <lastmod>2026-07-08T22:41:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外国語から発音を学ぶ音声合成ネットワーク（Learning pronunciation from a foreign language in speech synthesis networks）</news:title>
   <news:publication_date>2026-07-08T22:41:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709668</loc>
  <lastmod>2026-07-08T21:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公共データから作る保健脆弱性マップ（Construcción de un Mapa de Vulnerabilidad Sanitaria）</news:title>
   <news:publication_date>2026-07-08T21:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709666</loc>
  <lastmod>2026-07-08T21:49:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AdamとRMSPropの収束を保証する十分条件（A Sufficient Condition for Convergences of Adam and RMSProp）</news:title>
   <news:publication_date>2026-07-08T21:49:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709664</loc>
  <lastmod>2026-07-08T21:48:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>雑音に強い話者埋め込みを学習するマルチタスク敵対的ネットワーク（TRAINING MULTI-TASK ADVERSARIAL NETWORK FOR EXTRACTING NOISE-ROBUST SPEAKER EMBEDDING）</news:title>
   <news:publication_date>2026-07-08T21:48:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709662</loc>
  <lastmod>2026-07-08T21:48:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非i.i.d.サンプリングによる効率的学習と汎化の向上（A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better Generalization）</news:title>
   <news:publication_date>2026-07-08T21:48:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709660</loc>
  <lastmod>2026-07-08T21:48:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークによる無線多重経路フェージング・シナリオ識別（Deep Neural Network Aided Scenario Identification in Wireless Multi-path Fading Channels）</news:title>
   <news:publication_date>2026-07-08T21:48:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709658</loc>
  <lastmod>2026-07-08T21:47:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語を発見し、接地し、利用する学習（Learning to Discover, Ground and Use Words with Segmental Neural Language Models）</news:title>
   <news:publication_date>2026-07-08T21:47:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709656</loc>
  <lastmod>2026-07-08T21:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>財務記録と自己注意型循環ニューラルネットワークによる糖尿病進展予測（Predicting Diabetes Disease Evolution Using Financial Records and Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-08T21:47:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709654</loc>
  <lastmod>2026-07-08T20:56:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イールドカーブの特徴抽出に機械学習を使う（MACHINE LEARNING FOR YIELD CURVE FEATURE EXTRACTION: APPLICATION TO ILLIQUID CORPORATE BONDS）</news:title>
   <news:publication_date>2026-07-08T20:56:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709652</loc>
  <lastmod>2026-07-08T20:46:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの構造的プルーニングと予算意識正則化（Structured Pruning of Neural Networks with Budget-Aware Regularization）</news:title>
   <news:publication_date>2026-07-08T20:46:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709650</loc>
  <lastmod>2026-07-08T20:45:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共鳴電荷交換衝突における量子力学的ポテンシャルと非活性電子の影響 (Quantum Mechanical Potentials and Inactive Electron Effects in Resonant Charge Exchange Collisions)</news:title>
   <news:publication_date>2026-07-08T20:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709648</loc>
  <lastmod>2026-07-08T20:45:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多数は力になる：敵対的学習で強化するアンサンブルの有効性（STRENGTH IN NUMBERS: TRADING-OFF ROBUSTNESS AND COMPUTATION VIA ADVERSARIALLY-TRAINED ENSEMBLES）</news:title>
   <news:publication_date>2026-07-08T20:45:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709646</loc>
  <lastmod>2026-07-08T20:45:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生存解析における特徴選択とDeep Learningの改善（Feature Selection for Survival Analysis with Competing Risks using Deep Learning）</news:title>
   <news:publication_date>2026-07-08T20:45:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709644</loc>
  <lastmod>2026-07-08T20:44:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメトリックノイズ注入によるDNNの頑健化（Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack）</news:title>
   <news:publication_date>2026-07-08T20:44:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709642</loc>
  <lastmod>2026-07-08T20:44:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MR-GANによる生成モデルの幾何学的正則化（MR-GAN: Manifold Regularized Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-08T20:44:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709640</loc>
  <lastmod>2026-07-08T19:53:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一望遠鏡で揃えた超新星サーベイの意義（The Foundation Supernova Survey: Measuring Cosmological Parameters with Supernovae from a Single Telescope）</news:title>
   <news:publication_date>2026-07-08T19:53:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709638</loc>
  <lastmod>2026-07-08T19:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>傾斜Ni(111)表面上の六方窒化ホウ素単層成長の系統的研究（Boron nitride monolayer growth on vicinal Ni(111) surfaces systematically studied with a curved crystal）</news:title>
   <news:publication_date>2026-07-08T19:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709636</loc>
  <lastmod>2026-07-08T19:53:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M31の元素組成に関する知見（Elemental Abundances in M31: Alpha and Iron Element Abundances from Low-Resolution Resolved Stellar Spectroscopy in the Stellar Halo）</news:title>
   <news:publication_date>2026-07-08T19:53:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709634</loc>
  <lastmod>2026-07-08T19:52:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zastavnyi演算子と正定値放射関数の意義（Zastavnyi Operators and Positive Definite Radial Functions）</news:title>
   <news:publication_date>2026-07-08T19:52:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709632</loc>
  <lastmod>2026-07-08T19:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境での部分勾配の符号化計算（DISTRIBUTED GRADIENT DESCENT WITH CODED PARTIAL GRADIENT COMPUTATIONS）</news:title>
   <news:publication_date>2026-07-08T19:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709630</loc>
  <lastmod>2026-07-08T19:51:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次力定数抽出のためのhiphiveパッケージ (The hiphive package for the extraction of high-order force constants by machine learning)</news:title>
   <news:publication_date>2026-07-08T19:51:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709628</loc>
  <lastmod>2026-07-08T19:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元量子エンコーディングと光子減算を用いた符号化手法（High-dimensional quantum encoding via photon-subtracted squeezed states）</news:title>
   <news:publication_date>2026-07-08T19:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709626</loc>
  <lastmod>2026-07-08T19:00:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Legendre級数畳み込みによるオプション価格付けとヘッジ（Hedging and Pricing European-type, Early-Exercise and Discrete Barrier Options using an Algorithm for the Convolution of Legendre Series）</news:title>
   <news:publication_date>2026-07-08T19:00:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709624</loc>
  <lastmod>2026-07-08T19:00:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TimbreTron：CQT＋CycleGAN＋WaveNetによる音色転送パイプライン（TIMBRETRON: A WAVENET(CYCLEGAN(CQT(AUDIO))) PIPELINE FOR MUSICAL TIMBRE TRANSFER）</news:title>
   <news:publication_date>2026-07-08T19:00:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709622</loc>
  <lastmod>2026-07-08T18:59:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GuacaMolによる新しい分子設計の評価フレームワーク（GuacaMol: Benchmarking Models for De Novo Molecular Design）</news:title>
   <news:publication_date>2026-07-08T18:59:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709620</loc>
  <lastmod>2026-07-08T18:58:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FAIM：3次元医用画像レジストレーションの高速・折り畳み抑制手法（FAIM – A ConvNet Method for Unsupervised 3D Medical Image Registration）</news:title>
   <news:publication_date>2026-07-08T18:58:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709618</loc>
  <lastmod>2026-07-08T18:58:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不安全なシステムの監督と動的安全エンベロープ（Oversight of Unsafe Systems via Dynamic Safety Envelopes）</news:title>
   <news:publication_date>2026-07-08T18:58:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709616</loc>
  <lastmod>2026-07-08T18:58:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語義誘導の自動化モデルが変える意味の捉え方（AutoSense Model for Word Sense Induction）</news:title>
   <news:publication_date>2026-07-08T18:58:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709614</loc>
  <lastmod>2026-07-08T18:57:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低メモリで高解像度映像を学習する時系列GANの手法 (Train Sparsely, Generate Densely: Memory-efficient Unsupervised Training of High-resolution Temporal GAN)</news:title>
   <news:publication_date>2026-07-08T18:57:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709612</loc>
  <lastmod>2026-07-08T18:06:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学校のバリュー・アッド指標で生徒背景を調整すべきか（Should we adjust for pupil background in school value-added models?）</news:title>
   <news:publication_date>2026-07-08T18:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709610</loc>
  <lastmod>2026-07-08T18:06:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガンマ線パルサー：ab-initio運動論的シミュレーションから何を学んだか（Gamma-ray pulsars: What have we learned from ab-initio kinetic simulations?）</news:title>
   <news:publication_date>2026-07-08T18:06:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709608</loc>
  <lastmod>2026-07-08T18:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三次元クロマチン構造とその時間的挙動の推定 (Inference of the three-dimensional chromatin structure and its temporal behavior)</news:title>
   <news:publication_date>2026-07-08T18:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709606</loc>
  <lastmod>2026-07-08T18:05:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的アンサンブル選択とデータ前処理による多クラス不均衡学習の実証的分析（On dynamic ensemble selection and data preprocessing for multi-class imbalance learning）</news:title>
   <news:publication_date>2026-07-08T18:05:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709604</loc>
  <lastmod>2026-07-08T18:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮動画の画質を向上させる多帧注視ネットワーク（MGANet: A Robust Model for Quality Enhancement of Compressed Video）</news:title>
   <news:publication_date>2026-07-08T18:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709602</loc>
  <lastmod>2026-07-08T18:04:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己進度型敵対的訓練によるマルチモーダル少数ショット学習（Self Paced Adversarial Training for Multimodal Few-shot Learning）</news:title>
   <news:publication_date>2026-07-08T18:04:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709600</loc>
  <lastmod>2026-07-08T18:04:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トレーニングデータ無しで学ぶ方法 — 銀河応用のベイズ的アプローチ (Learning in the Absence of Training Data – a Galactic Application)</news:title>
   <news:publication_date>2026-07-08T18:04:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709598</loc>
  <lastmod>2026-07-08T17:12:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理によるセルビア語の比喩（直喩）コーパス構築（Creating a contemporary corpus of similes in Serbian by using natural language processing）</news:title>
   <news:publication_date>2026-07-08T17:12:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709596</loc>
  <lastmod>2026-07-08T17:12:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブスレッショルドスイングの改訂理論限界（Revised Theoretical Limit of Subthreshold Swing in Field-Effect Transistors）</news:title>
   <news:publication_date>2026-07-08T17:12:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709594</loc>
  <lastmod>2026-07-08T17:11:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再電離シミュレーションのパワースペクトルを高速予測する機械学習の実用性（Evaluating machine learning techniques for predicting power spectra from reionization simulations）</news:title>
   <news:publication_date>2026-07-08T17:11:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709592</loc>
  <lastmod>2026-07-08T17:11:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑材料のBRDF推定とネスト学習（BRDF Estimation of Complex Materials with Nested Learning）</news:title>
   <news:publication_date>2026-07-08T17:11:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709590</loc>
  <lastmod>2026-07-08T17:11:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>座位における褥瘡予防のためのリアルタイム個別化モデリング（Personalized modeling for real-time pressure ulcer prevention in sitting posture）</news:title>
   <news:publication_date>2026-07-08T17:11:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709588</loc>
  <lastmod>2026-07-08T17:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で長時間の分子光動力学が可能に（Machine learning enables long time scale molecular photodynamics）</news:title>
   <news:publication_date>2026-07-08T17:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709586</loc>
  <lastmod>2026-07-08T17:09:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドライバー行動認識のための多入力インターウーブンCNN（Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets with Multi-stream Inputs）</news:title>
   <news:publication_date>2026-07-08T17:09:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709584</loc>
  <lastmod>2026-07-08T16:18:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ELMの条件数最適化：マルチタスクビートル触角群最適化法（Conditioning Optimization of Extreme Learning Machine by Multitask Beetle Antennae Swarm Algorithm）</news:title>
   <news:publication_date>2026-07-08T16:18:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709582</loc>
  <lastmod>2026-07-08T16:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己対戦で学ぶ目標埋め込みと階層型強化学習（Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-08T16:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709580</loc>
  <lastmod>2026-07-08T16:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Multi-Task GANで臨床画像の不均衡を扱う（Multi-Task Generative Adversarial Network for Handling Imbalanced Clinical Data）</news:title>
   <news:publication_date>2026-07-08T16:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709578</loc>
  <lastmod>2026-07-08T16:17:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DCE-MRIでの腫瘍追跡を自動化するCNN種点生成と制約付き体積増殖（Response monitoring of breast cancer on DCE-MRI using convolutional neural network-generated seed points and constrained volume growing）</news:title>
   <news:publication_date>2026-07-08T16:17:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709576</loc>
  <lastmod>2026-07-08T16:17:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム射影によるニューラルネットワークの表現力強化と高速学習（Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections）</news:title>
   <news:publication_date>2026-07-08T16:17:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709574</loc>
  <lastmod>2026-07-08T16:17:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PSICA：カテゴリカル処置に対する確率的サブグループ同定（PSICA: decision trees for probabilistic subgroup identification with categorical treatments）</news:title>
   <news:publication_date>2026-07-08T16:17:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709572</loc>
  <lastmod>2026-07-08T16:17:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集団動物移動活動のオンライン認識（Online Collective Animal Movement Activity Recognition）</news:title>
   <news:publication_date>2026-07-08T16:17:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709570</loc>
  <lastmod>2026-07-08T15:25:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-08T15:25:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709568</loc>
  <lastmod>2026-07-08T15:25:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-08T15:25:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709566</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-08T15:24:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709564</loc>
  <lastmod>2026-07-08T15:24:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間的確率制約を持つバンディット問題 (Bandits with Temporal Stochastic Constraints)</news:title>
   <news:publication_date>2026-07-08T15:24:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709562</loc>
  <lastmod>2026-07-08T15:24:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-08T15:24:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709560</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-08T15:23:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709558</loc>
  <lastmod>2026-07-08T15:23:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-08T15:23:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709556</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚的距離に基づくタスク汎用的な敵対的攻撃（Task-generalizable Adversarial Attack based on Perceptual Metric）</news:title>
   <news:publication_date>2026-07-08T14:32:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709554</loc>
  <lastmod>2026-07-08T14:32:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイト単位の多言語音声認識と合成が切り拓く実務応用（BYTES ARE ALL YOU NEED: END-TO-END MULTILINGUAL SPEECH RECOGNITION AND SYNTHESIS WITH BYTES）</news:title>
   <news:publication_date>2026-07-08T14:32:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709552</loc>
  <lastmod>2026-07-08T14:32:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造生成とディテール強調による顔の高解像化と復元（Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement）</news:title>
   <news:publication_date>2026-07-08T14:32:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709550</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースなショートカットトポロジーがもたらす表現力の飛躍（On a Sparse Shortcut Topology of Artificial Neural Networks）</news:title>
   <news:publication_date>2026-07-08T14:30:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709548</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-08T14:30:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709546</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-08T14:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709544</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフポリシー方策勾配定理とエンファティック重み付け（An Off-policy Policy Gradient Theorem Using Emphatic Weightings）</news:title>
   <news:publication_date>2026-07-08T14:30:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709542</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-08T13:38:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/709540</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HyperAdam：タスク適応型学習可能Adam（HyperAdam: A Learnable Task-Adaptive Adam for Network Training）</news:title>
   <news:publication_date>2026-07-08T13:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709538</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一次元系におけるソリトンとBCS–BECクロスオーバー（Solitons in One Dimensional Systems at BCS-BEC Crossover）</news:title>
   <news:publication_date>2026-07-08T13:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709536</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グレイボックス・ファジングを効率化するプログラム挙動のモデリング（Improving Grey-Box Fuzzing by Modeling Program Behavior）</news:title>
   <news:publication_date>2026-07-08T13:37:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709534</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-08T13:36:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709532</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポラリティ損失によるゼロショット物体検出の改良（Polarity Loss for Zero-shot Object Detection）</news:title>
   <news:publication_date>2026-07-08T13:36:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709530</loc>
  <lastmod>2026-07-08T13:36:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ連鎖に基づくブロック座標降下法（Markov Chain Block Coordinate Descent）</news:title>
   <news:publication_date>2026-07-08T13:36:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709527</loc>
  <lastmod>2026-07-08T12:44:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布の重なりを作ることで定義できる差異指標 ― Spread Divergence（Spread Divergence）</news:title>
   <news:publication_date>2026-07-08T12:44:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709525</loc>
  <lastmod>2026-07-08T12:44:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低解像度顔認識の挑戦と解決（Low-Resolution Face Recognition）</news:title>
   <news:publication_date>2026-07-08T12:44:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709523</loc>
  <lastmod>2026-07-08T12:44:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-08T12:44:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709521</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線における肺炎検出の自動化（Pneumonia Detection in Chest Radiographs）</news:title>
   <news:publication_date>2026-07-08T12:43:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709519</loc>
  <lastmod>2026-07-08T12:43:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在交絡因子モデルにおける個別処置効果推定の敵対学習（Estimation of Individual Treatment Effect in Latent Confounder Models via Adversarial Learning）</news:title>
   <news:publication_date>2026-07-08T12:43:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709517</loc>
  <lastmod>2026-07-08T12:43:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力と電磁気の幾何学的統一（Geometrical Unification of Gravitation and Electromagnetism）</news:title>
   <news:publication_date>2026-07-08T12:43:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709515</loc>
  <lastmod>2026-07-08T12:42:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク・モーション計画と強化学習を統合したロバスト意思決定（Integrating Task-Motion Planning with Reinforcement Learning for Robust Decision Making in Mobile Robots）</news:title>
   <news:publication_date>2026-07-08T12:42:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709513</loc>
  <lastmod>2026-07-08T11:51:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己敵対学習によるベイズサンプリング（Self-Adversarially Learned Bayesian Sampling）</news:title>
   <news:publication_date>2026-07-08T11:51:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709511</loc>
  <lastmod>2026-07-08T11:51:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的でロバストなフィルタ生成のための教師なし学習フレームワーク（Generating adaptive and robust filter sets using an unsupervised learning framework）</news:title>
   <news:publication_date>2026-07-08T11:51:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709509</loc>
  <lastmod>2026-07-08T11:51:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Learningと密度汎関数理論の融合（Deep Learning and Density Functional Theory）</news:title>
   <news:publication_date>2026-07-08T11:51:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709507</loc>
  <lastmod>2026-07-08T11:50:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語に基づく動画の時間局所化のための活動概念抽出（MAC: Mining Activity Concepts for Language-based Temporal Localization）</news:title>
   <news:publication_date>2026-07-08T11:50:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709505</loc>
  <lastmod>2026-07-08T11:50:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>開かれたドメイン動画におけるマルチビュー相関からの学習（LEARNING FROM MULTIVIEW CORRELATIONS IN OPEN-DOMAIN VIDEOS）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709503</loc>
  <lastmod>2026-07-08T11:50:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力定数が変わる世界の力学（Gravitational Potential and Nonrelativistic Lagrangian in Modified Gravity with Varying G）</news:title>
   <news:publication_date>2026-07-08T11:50:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709501</loc>
  <lastmod>2026-07-08T11:49:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図信号分類のためのロバストな能動学習（Robust Active Learning for Electrocardiographic Signal Classification）</news:title>
   <news:publication_date>2026-07-08T11:49:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-07-08T10:59:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックホール内部とモジュラー包含（Comments on black hole interiors and modular inclusions）</news:title>
   <news:publication_date>2026-07-08T10:58:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709495</loc>
  <lastmod>2026-07-08T10:58:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過剰パラメータ化したDeep ReLUネットワークをSGDが最適化する（Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks）</news:title>
   <news:publication_date>2026-07-08T10:58:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709493</loc>
  <lastmod>2026-07-08T10:57:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理的外挿を可能にするガウス過程の一般化（Physical extrapolation of quantum observables by generalization with Gaussian Processes）</news:title>
   <news:publication_date>2026-07-08T10:57:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709491</loc>
  <lastmod>2026-07-08T10:57:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェア意識混合精度自動量子化（Hardware-Aware Automated Quantization with Mixed Precision）</news:title>
   <news:publication_date>2026-07-08T10:57:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709489</loc>
  <lastmod>2026-07-08T10:57:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な非近視的アクティブサーチ（Efficient Nonmyopic Active Search）</news:title>
   <news:publication_date>2026-07-08T10:57:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709487</loc>
  <lastmod>2026-07-08T10:57:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン逆強化学習の非線形系への拡張（Online inverse reinforcement learning for nonlinear systems）</news:title>
   <news:publication_date>2026-07-08T10:57:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709485</loc>
  <lastmod>2026-07-08T10:05:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOOCフォーラムにおけるリソース言及抽出（Resource Mention Extraction for MOOC Discussion Forums）</news:title>
   <news:publication_date>2026-07-08T10:05:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709483</loc>
  <lastmod>2026-07-08T10:05:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可視化可能なシーングラフ生成モデルが変える視覚理解（An Interpretable Model for Scene Graph Generation）</news:title>
   <news:publication_date>2026-07-08T10:05:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709481</loc>
  <lastmod>2026-07-08T10:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習を取り入れた自己学習による胸部X線肺結節セグメンテーション（Integrating Reinforcement Learning to Self Training for Pulmonary Nodule Segmentation in Chest X-rays）</news:title>
   <news:publication_date>2026-07-08T10:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709479</loc>
  <lastmod>2026-07-08T10:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な階層分類を用いる音の手動アノテーション支援（Facilitating the Manual Annotation of Sounds When Using Large Taxonomies）</news:title>
   <news:publication_date>2026-07-08T10:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709477</loc>
  <lastmod>2026-07-08T10:04:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標を早期に視覚に組み込むロボット視覚（EARLY FUSION for Goal Directed Robotic Vision）</news:title>
   <news:publication_date>2026-07-08T10:04:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709475</loc>
  <lastmod>2026-07-08T10:03:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速化MRIのための大規模データセットとベンチマーク（fastMRI: An Open Dataset and Benchmarks for Accelerated MRI）</news:title>
   <news:publication_date>2026-07-08T10:03:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709473</loc>
  <lastmod>2026-07-08T10:03:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチメソッドで画像品質評価を高める発想（Boosting in Image Quality Assessment）</news:title>
   <news:publication_date>2026-07-08T10:03:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709471</loc>
  <lastmod>2026-07-08T09:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴空間における運動学習：局所一貫性を持つ変形畳み込みネットワークによる微細動作検出（Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection）</news:title>
   <news:publication_date>2026-07-08T09:12:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709469</loc>
  <lastmod>2026-07-08T09:11:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低資源言語間の単語トランスダクション機構（NMT word transduction mechanisms for LRL）</news:title>
   <news:publication_date>2026-07-08T09:11:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709467</loc>
  <lastmod>2026-07-08T09:10:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データ分類のための敵対的再重み付け（Adversarial Classifier for Imbalanced Problems）</news:title>
   <news:publication_date>2026-07-08T09:10:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709465</loc>
  <lastmod>2026-07-08T09:10:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マージナル加重最尤法による効率的学習（Marginal Weighted Maximum Log-likelihood for Efficient Learning of Perturb-and-Map models）</news:title>
   <news:publication_date>2026-07-08T09:10:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709463</loc>
  <lastmod>2026-07-08T09:10:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>尤度非計算型推論の逐次ニューラル手法（Sequential Neural Methods for Likelihood-free Inference）</news:title>
   <news:publication_date>2026-07-08T09:10:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709461</loc>
  <lastmod>2026-07-08T09:10:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層グラフに対する半教師あり分類のGCN拡張（MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-07-08T09:10:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709459</loc>
  <lastmod>2026-07-08T09:09:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関と因果を見分ける：ゲノムワイド関連解析からの示唆（Distinguishing correlation from causation using genome-wide association studies）</news:title>
   <news:publication_date>2026-07-08T09:09:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709457</loc>
  <lastmod>2026-07-08T08:18:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン生成アルゴリズムのインライン検知（Inline Detection of Domain Generation Algorithms with Context-Sensitive Word Embeddings）</news:title>
   <news:publication_date>2026-07-08T08:18:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709455</loc>
  <lastmod>2026-07-08T08:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復的グローバル探索とカオス理論に基づくPSO特徴選択の改良（Improving PSO Global Method for Feature Selection According to Iterations Global Search and Chaotic Theory）</news:title>
   <news:publication_date>2026-07-08T08:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709453</loc>
  <lastmod>2026-07-08T08:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造ベースのネットワークによる薬物検証（Structure-Based Networks for Drug Validation）</news:title>
   <news:publication_date>2026-07-08T08:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709451</loc>
  <lastmod>2026-07-08T08:16:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー保護された協調予測とランダムフォレスト（Privacy-Preserving Collaborative Prediction using Random Forests）</news:title>
   <news:publication_date>2026-07-08T08:16:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709449</loc>
  <lastmod>2026-07-08T08:16:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動塩層分割：深層学習アプローチ（Automatic salt deposits segmentation: A deep learning approach）</news:title>
   <news:publication_date>2026-07-08T08:16:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709447</loc>
  <lastmod>2026-07-08T08:16:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代理モデル支援パラレルテンパリングによるベイズニューラル学習（Surrogate-assisted parallel tempering for Bayesian neural learning）</news:title>
   <news:publication_date>2026-07-08T08:16:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709445</loc>
  <lastmod>2026-07-08T08:16:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態空間に基づく疎な動的ネットワーク再構築（A state-space approach to sparse dynamic network reconstruction）</news:title>
   <news:publication_date>2026-07-08T08:16:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709443</loc>
  <lastmod>2026-07-08T07:24:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボリュームCT画像からの気道抽出のグラフ洗練法（Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks）</news:title>
   <news:publication_date>2026-07-08T07:24:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709441</loc>
  <lastmod>2026-07-08T07:23:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ誘導グラフィカルラッソによる分子パスウェイ間相互作用の発見（Group induced graphical lasso allows for discovery of molecular pathways-pathways interactions）</news:title>
   <news:publication_date>2026-07-08T07:23:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709439</loc>
  <lastmod>2026-07-08T07:22:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子強化学習の進展（Advances in Quantum Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-08T07:22:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709437</loc>
  <lastmod>2026-07-08T07:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字レベルCNNによる悪意あるWebリクエスト検知（Malicious Web Request Detection Using Character-level CNN）</news:title>
   <news:publication_date>2026-07-08T07:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709435</loc>
  <lastmod>2026-07-08T07:22:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声認識における四元数ニューラルネットワーク（Speech Recognition with Quaternion Neural Networks）</news:title>
   <news:publication_date>2026-07-08T07:22:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709433</loc>
  <lastmod>2026-07-08T07:22:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何相位顕微鏡による定量位相イメージング（GEOMETRIC-PHASE MICROSCOPY FOR QUANTITATIVE PHASE IMAGING）</news:title>
   <news:publication_date>2026-07-08T07:22:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709431</loc>
  <lastmod>2026-07-08T07:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PersEmoN：外見的パーソナリティと感情を同時解析する深層ネットワーク（PersEmoN: A Deep Network for Joint Analysis of Apparent Personality, Emotion and Their Relationship）</news:title>
   <news:publication_date>2026-07-08T07:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709429</loc>
  <lastmod>2026-07-08T06:30:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補償付き統合勾配によるEEG分類の信頼できる解釈（Compensated Integrated Gradients to Reliably Interpret EEG Classification）</news:title>
   <news:publication_date>2026-07-08T06:30:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709427</loc>
  <lastmod>2026-07-08T06:29:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像の雨粒除去を木構造で達成する（A Deep Tree-Structured Fusion Model for Single Image Deraining）</news:title>
   <news:publication_date>2026-07-08T06:29:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709425</loc>
  <lastmod>2026-07-08T06:29:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>第一原理に基づく水の熱力学――液体と氷の安定性を機械学習で定量化する（Ab initio thermodynamics of liquid and solid water）</news:title>
   <news:publication_date>2026-07-08T06:29:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/709423</loc>
  <lastmod>2026-07-08T06:28:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重障害ポテンシャルを伴う腫瘍成長モデルの最適性条件（Optimality conditions for an extended tumor growth model with double obstacle potential via deep quench approach）</news:title>
   <news:publication_date>2026-07-08T06:28:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709421</loc>
  <lastmod>2026-07-08T06:28:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク深層形態素解析器（Multi Task Deep Morphological Analyzer: Context Aware Neural Joint Morphological Tagging and Lemma Prediction）</news:title>
   <news:publication_date>2026-07-08T06:28:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709419</loc>
  <lastmod>2026-07-08T06:28:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化ネットワークを備えたニューラルネットワーク（Neural Networks with Activation Networks）</news:title>
   <news:publication_date>2026-07-08T06:28:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709417</loc>
  <lastmod>2026-07-08T06:27:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>角度ベースの距離学習で3D形状検索を改善する手法（Angular Triplet-Center Loss for Multi-view 3D Shape Retrieval）</news:title>
   <news:publication_date>2026-07-08T06:27:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709415</loc>
  <lastmod>2026-07-08T05:36:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医用画像とレポートの教師なしマルチモーダル表現学習 (Unsupervised Multimodal Representation Learning across Medical Images and Reports)</news:title>
   <news:publication_date>2026-07-08T05:36:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709413</loc>
  <lastmod>2026-07-08T05:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト検出と認識を統合する新しい枠組み（A Novel Integrated Framework for Learning both Text Detection and Recognition）</news:title>
   <news:publication_date>2026-07-08T05:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709411</loc>
  <lastmod>2026-07-08T05:35:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理を取り込んだ深層生成モデルによるマイクロ構造合成（Physics-aware Deep Generative Models for Creating Synthetic Microstructures）</news:title>
   <news:publication_date>2026-07-08T05:35:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709409</loc>
  <lastmod>2026-07-08T05:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による高精度ポリマーのクラウドポイント逆設計（Machine learning enables polymer cloud-point engineering via inverse design）</news:title>
   <news:publication_date>2026-07-08T05:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709407</loc>
  <lastmod>2026-07-08T05:35:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Joint Mapping and Calibration via Differentiable Sensor Fusion（Joint Mapping and Calibration via Differentiable Sensor Fusion）</news:title>
   <news:publication_date>2026-07-08T05:35:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709405</loc>
  <lastmod>2026-07-08T05:35:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>場面文字検出の文脈強化手法がもたらす実務的インパクト（Scene Text Detection with Supervised Pyramid Context Network）</news:title>
   <news:publication_date>2026-07-08T05:35:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709403</loc>
  <lastmod>2026-07-08T05:35:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間帯フィルターを用いたz∼5の微光クエーサー発見（Discovery of Faint Quasars at z ∼5 with a Medium-band-based Approach）</news:title>
   <news:publication_date>2026-07-08T05:35:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709401</loc>
  <lastmod>2026-07-08T04:44:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルから誰でも試着可能にする技術（M2E-Try On Net: Fashion from Model to Everyone）</news:title>
   <news:publication_date>2026-07-08T04:44:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709399</loc>
  <lastmod>2026-07-08T04:43:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈化された非ローカルニューラルネットワークによる系列学習の革新（Contextualized Non-local Neural Networks for Sequence Learning）</news:title>
   <news:publication_date>2026-07-08T04:43:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709397</loc>
  <lastmod>2026-07-08T04:43:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FFTによる勾配スパース化で分散学習を効率化する手法（FFT-based Gradient Sparsification for the Distributed Training of Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-08T04:43:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709395</loc>
  <lastmod>2026-07-08T04:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graph-Adaptive PruningによるCNN推論高速化（Graph-Adaptive Pruning for Efficient Inference of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-08T04:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709393</loc>
  <lastmod>2026-07-08T04:43:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市部走行における多目的深層強化学習（Urban Driving with Multi-Objective Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-08T04:43:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709391</loc>
  <lastmod>2026-07-08T04:42:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的特徴整合による非教師ありドメイン適応（Progressive Feature Alignment for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-07-08T04:42:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709389</loc>
  <lastmod>2026-07-08T04:42:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話し言葉と3D顔表情から抑うつ症状の重症度を測る（Measuring Depression Symptom Severity from Spoken Language and 3D Facial Expressions）</news:title>
   <news:publication_date>2026-07-08T04:42:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709387</loc>
  <lastmod>2026-07-08T03:51:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンセット認識の最近の進展（Recent Advances in Open Set Recognition: A Survey）</news:title>
   <news:publication_date>2026-07-08T03:51:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709385</loc>
  <lastmod>2026-07-08T03:51:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人口属性を考慮した階層ベイズ型ドメイン適応（Population-aware Hierarchical Bayesian Domain Adaptation）</news:title>
   <news:publication_date>2026-07-08T03:51:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709383</loc>
  <lastmod>2026-07-08T03:50:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運動学習は「動かずに」起きるか：受動的訓練での手位置推定の再考（Motor Learning Without Moving: Hand Localization after Passive Training）</news:title>
   <news:publication_date>2026-07-08T03:50:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709381</loc>
  <lastmod>2026-07-08T03:50:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非教師単一画像の雨除去を自己監督制約で解く（Unsupervised Single Image Deraining with Self-supervised Constraints）</news:title>
   <news:publication_date>2026-07-08T03:50:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709379</loc>
  <lastmod>2026-07-08T03:50:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物再識別のための深層特徴の適応的再ランキング（Adaptive Re-ranking of Deep Features for Person Re-identification）</news:title>
   <news:publication_date>2026-07-08T03:50:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709377</loc>
  <lastmod>2026-07-08T03:49:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測下における高水準戦略選択（High-Level Strategy Selection under Partial Observability in StarCraft: Brood War）</news:title>
   <news:publication_date>2026-07-08T03:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709375</loc>
  <lastmod>2026-07-08T03:49:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Softmax出力は敵対的例の強度評価を誤らせる（How the Softmax Output is Misleading for Evaluating the Strength of Adversarial Examples）</news:title>
   <news:publication_date>2026-07-08T03:49:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709373</loc>
  <lastmod>2026-07-08T02:58:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>翻訳の「抜け」を減らす学習法（Neural Machine Translation with Adequacy-Oriented Learning）</news:title>
   <news:publication_date>2026-07-08T02:58:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709371</loc>
  <lastmod>2026-07-08T02:58:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットで高速に予測する電子衝突イオン化質量分析（Rapid Prediction of Electron-Ionization Mass Spectrometry using Neural Networks）</news:title>
   <news:publication_date>2026-07-08T02:58:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709369</loc>
  <lastmod>2026-07-08T02:58:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース強化学習が示すサンプル効率の飛躍（Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches）</news:title>
   <news:publication_date>2026-07-08T02:58:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709367</loc>
  <lastmod>2026-07-08T02:57:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>食道組織のがん・前がん病変検出に対する注意機構型深層ニューラルネットワーク（Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides）</news:title>
   <news:publication_date>2026-07-08T02:57:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709365</loc>
  <lastmod>2026-07-08T02:56:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗所での視覚を改善する再帰型畳み込みニューラルネットワーク（Seeing in the dark with recurrent convolutional neural networks）</news:title>
   <news:publication_date>2026-07-08T02:56:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709363</loc>
  <lastmod>2026-07-08T02:56:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水中でのCNNベース密な3Dシーン再構築（CNN based dense underwater 3D scene reconstruction by transfer learning using bubble database）</news:title>
   <news:publication_date>2026-07-08T02:56:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709361</loc>
  <lastmod>2026-07-08T02:56:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層音声強調のための微分可能な整合性制約（Differentiable Consistency Constraints for Improved Deep Speech Enhancement）</news:title>
   <news:publication_date>2026-07-08T02:56:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709359</loc>
  <lastmod>2026-07-08T02:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小規模X線回折データの高速で解釈可能な分類（Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks）</news:title>
   <news:publication_date>2026-07-08T02:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709357</loc>
  <lastmod>2026-07-08T01:55:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多視点データの結合的関連と分類解析（Joint association and classification analysis of multi-view data）</news:title>
   <news:publication_date>2026-07-08T01:55:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709355</loc>
  <lastmod>2026-07-08T01:55:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バランスの取れたデータセットでは不十分（Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations）</news:title>
   <news:publication_date>2026-07-08T01:55:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709353</loc>
  <lastmod>2026-07-08T01:54:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライマル・デュアルQ学習フレームワークによるLQR設計（Primal-Dual Q-Learning Framework for LQR Design）</news:title>
   <news:publication_date>2026-07-08T01:54:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709351</loc>
  <lastmod>2026-07-08T01:54:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定的な相手の影響を利用する学習（Stable Opponent Shaping in Differentiable Games）</news:title>
   <news:publication_date>2026-07-08T01:54:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709349</loc>
  <lastmod>2026-07-08T01:53:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MimicGANによる盲点補正と敵対的防御の実務的意義（MimicGAN: Corruption-Mimicking for Blind Image Recovery &amp;amp; Adversarial Defense）</news:title>
   <news:publication_date>2026-07-08T01:53:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709347</loc>
  <lastmod>2026-07-08T01:53:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イタリア上院における政治的DNAの学習（Learning Political DNA in the Italian Senate）</news:title>
   <news:publication_date>2026-07-08T01:53:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709338</loc>
  <lastmod>2026-07-08T01:02:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動フローワークフレームによる機械学習を用いた材料探索（MACHINE LEARNING, PHASE STABILITY, AND DISORDER WITH THE AUTOMATIC FLOW FRAMEWORK FOR MATERIALS DISCOVERY）</news:title>
   <news:publication_date>2026-07-08T01:02:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709336</loc>
  <lastmod>2026-07-08T01:01:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間層に着目した敵対的攻撃の転移性向上（Intermediate Level Adversarial Attack for Enhanced Transferability）</news:title>
   <news:publication_date>2026-07-08T01:01:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709334</loc>
  <lastmod>2026-07-08T01:01:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>色の恒常性を学習するCNNと角度損失（Artificial Color Constancy via GoogLeNet with Angular Loss Function）</news:title>
   <news:publication_date>2026-07-08T01:01:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709332</loc>
  <lastmod>2026-07-08T01:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ波長観測を用いた電波トランジェント分類（Multiwavelength Classification of Radio Transients）</news:title>
   <news:publication_date>2026-07-08T01:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709330</loc>
  <lastmod>2026-07-08T01:00:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチラベル画像分類における強力なベースライン（A BASELINE FOR MULTI-LABEL IMAGE CLASSIFICATION USING AN ENSEMBLE OF DEEP CONVOLUTIONAL NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-07-08T01:00:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709328</loc>
  <lastmod>2026-07-08T01:00:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプリングは最適化よりも速いことがある（Sampling Can Be Faster Than Optimization）</news:title>
   <news:publication_date>2026-07-08T01:00:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709326</loc>
  <lastmod>2026-07-08T01:00:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込みと出力層の圧縮を実現するWEST（Word Encoded Sequence Transducers）</news:title>
   <news:publication_date>2026-07-08T01:00:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709324</loc>
  <lastmod>2026-07-08T00:08:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gen-Oja：ストリーミングCCAの二段階技法（Gen-Oja: A Two-time-scale approach for Streaming CCA）</news:title>
   <news:publication_date>2026-07-08T00:08:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709322</loc>
  <lastmod>2026-07-08T00:08:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>植物苗の画像を深層学習で識別する意義（Deep Convolutional Neural Network for Plant Seedlings Classification）</news:title>
   <news:publication_date>2026-07-08T00:08:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709320</loc>
  <lastmod>2026-07-08T00:08:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一ラベル多クラス画像分類における深層ロジスティック回帰（Single-Label Multi-Class Image Classification by Deep Logistic Regression）</news:title>
   <news:publication_date>2026-07-08T00:08:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709318</loc>
  <lastmod>2026-07-08T00:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>刺激アーティファクトを拡張的に取り除く拡散幾何学アプローチ（Diffusion geometry approach to efficiently remove electrical stimulation artifacts in intracranial electroencephalography）</news:title>
   <news:publication_date>2026-07-08T00:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709316</loc>
  <lastmod>2026-07-08T00:07:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカル差分プライバシー下でのガウス分布平均推定（Locally Private Gaussian Estimation）</news:title>
   <news:publication_date>2026-07-08T00:07:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709314</loc>
  <lastmod>2026-07-08T00:06:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造的プルーニングによる効率的なConvNet（Structured Pruning for Efficient ConvNets via Incremental Regularization）</news:title>
   <news:publication_date>2026-07-08T00:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709312</loc>
  <lastmod>2026-07-08T00:06:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボリック音楽生成における深層ニューラルネットワークの明示的構造符号化の効果 (The Effect of Explicit Structure Encoding of Deep Neural Networks for Symbolic Music Generation)</news:title>
   <news:publication_date>2026-07-08T00:06:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709310</loc>
  <lastmod>2026-07-07T23:15:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列グラフのオフセット再構成による時間的に頑健な表現学習（Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation Learning）</news:title>
   <news:publication_date>2026-07-07T23:15:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709308</loc>
  <lastmod>2026-07-07T23:14:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオ行動認識における汎化可能な表現のマルチタスク学習（MULTI-TASK LEARNING OF GENERALIZABLE REPRESENTATIONS FOR VIDEO ACTION RECOGNITION）</news:title>
   <news:publication_date>2026-07-07T23:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709306</loc>
  <lastmod>2026-07-07T23:14:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層系列学習モデルのグレイボックス可視化とデバッグ手法（A Gray Box Interpretable Visual Debugging Approach for Deep Sequence Learning Model）</news:title>
   <news:publication_date>2026-07-07T23:14:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709304</loc>
  <lastmod>2026-07-07T23:14:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層カーネルによる指数族密度の学習（Learning Deep Kernels for Exponential Family Densities）</news:title>
   <news:publication_date>2026-07-07T23:14:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709302</loc>
  <lastmod>2026-07-07T23:13:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pepperのための近リアルタイム物体認識（Near Real-Time Object Recognition for Pepper based on Deep Neural Networks Running on a Backpack）</news:title>
   <news:publication_date>2026-07-07T23:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709300</loc>
  <lastmod>2026-07-07T23:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練済みニューラルネットワークのための強い混合整数計画法の定式化（Strong mixed-integer programming formulations for trained neural networks）</news:title>
   <news:publication_date>2026-07-07T23:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709298</loc>
  <lastmod>2026-07-07T23:13:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様化したマイクロドップラーで学ぶDNN転移学習（DNN Transfer Learning from Diversified Micro-Doppler for Motion Classification）</news:title>
   <news:publication_date>2026-07-07T23:13:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709296</loc>
  <lastmod>2026-07-07T22:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テクスチャに基づく顔認識の新しい一手法：LGLG-WPCA（LGLG-WPCA: An Effective Texture-based Method for Face Recognition）</news:title>
   <news:publication_date>2026-07-07T22:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709294</loc>
  <lastmod>2026-07-07T22:22:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字図式による因果推論の図式手術（Causal Inference by String Diagram Surgery）</news:title>
   <news:publication_date>2026-07-07T22:22:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709292</loc>
  <lastmod>2026-07-07T22:22:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックス自己回帰密度推定による状態空間モデルの近似ベイズ推定（Black-Box Autoregressive Density Estimation for State-Space Models）</news:title>
   <news:publication_date>2026-07-07T22:22:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709290</loc>
  <lastmod>2026-07-07T22:21:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定性に基づくフィルタ剪定による深層CNN高速化（Stability Based Filter Pruning for Accelerating Deep CNNs）</news:title>
   <news:publication_date>2026-07-07T22:21:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709288</loc>
  <lastmod>2026-07-07T22:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存テストを自動で“強化”する技術の実務的意義（Automatic Test Improvement with DSpot）</news:title>
   <news:publication_date>2026-07-07T22:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709286</loc>
  <lastmod>2026-07-07T22:20:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒト-物体相互作用検出のための転移可能な相互作用性知識（Transferable Interactiveness Knowledge for Human-Object Interaction Detection）</news:title>
   <news:publication_date>2026-07-07T22:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709284</loc>
  <lastmod>2026-07-07T22:20:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不規則サンプリング時系列のデータ拡張手法 T-CGAN（T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling）</news:title>
   <news:publication_date>2026-07-07T22:20:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709282</loc>
  <lastmod>2026-07-07T21:29:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FALCON: 高速かつプライバシー保護されたCNN推論の実装（FALCON: A Fourier Transform Based Approach for Fast and Secure Convolutional Neural Network Predictions）</news:title>
   <news:publication_date>2026-07-07T21:29:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709280</loc>
  <lastmod>2026-07-07T21:29:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fristonの能動推論の幾何学（Geometry of Friston’s active inference）</news:title>
   <news:publication_date>2026-07-07T21:29:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709278</loc>
  <lastmod>2026-07-07T21:29:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Unfolded Robust PCAによる超音波クラッタ除去の実務的意義（Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound）</news:title>
   <news:publication_date>2026-07-07T21:29:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709276</loc>
  <lastmod>2026-07-07T21:28:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化分類器の第一歩（Self Organizing Classifiers: First Steps in Structured Evolutionary Machine Learning）</news:title>
   <news:publication_date>2026-07-07T21:28:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709274</loc>
  <lastmod>2026-07-07T21:28:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化分類器とニッチ化された適応（Self Organizing Classifiers and Niched Fitness）</news:title>
   <news:publication_date>2026-07-07T21:28:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709272</loc>
  <lastmod>2026-07-07T21:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり空間・スペクトル正則化マニフォールド局所スケーリングカットによるハイパースペクトル画像の次元削減（A Semi-supervised Spatial Spectral Regularized Manifold Local Scaling Cut With HGF for Dimensionality Reduction of Hyperspectral Images）</news:title>
   <news:publication_date>2026-07-07T21:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709270</loc>
  <lastmod>2026-07-07T21:27:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分析的ネットワーク学習（Analytic Network Learning）</news:title>
   <news:publication_date>2026-07-07T21:27:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709268</loc>
  <lastmod>2026-07-07T20:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正射影特徴変換による単眼3D物体検出（Orthographic Feature Transform for Monocular 3D Object Detection）</news:title>
   <news:publication_date>2026-07-07T20:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709266</loc>
  <lastmod>2026-07-07T20:28:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Contingency Training：不要変数に強い学習を作る訓練法（Contingency Training）</news:title>
   <news:publication_date>2026-07-07T20:28:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709264</loc>
  <lastmod>2026-07-07T20:27:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳に学ぶスティグメルギー学習（Brain-Inspired Stigmergy Learning）</news:title>
   <news:publication_date>2026-07-07T20:27:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709262</loc>
  <lastmod>2026-07-07T20:27:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相情報のマルチスケール集約によるCNNベースDOA推定の計算コスト削減（MULTI-SCALE AGGREGATION OF PHASE INFORMATION FOR REDUCING COMPUTATIONAL COST OF CNN BASED DOA ESTIMATION）</news:title>
   <news:publication_date>2026-07-07T20:27:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709260</loc>
  <lastmod>2026-07-07T20:26:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>曲特徴を取り込む注意機構付きニューラル構造による音楽レコメンド（Attentive Neural Architecture Incorporating Song Features For Music Recommendation）</news:title>
   <news:publication_date>2026-07-07T20:26:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709258</loc>
  <lastmod>2026-07-07T20:26:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平な機械学習の最前線（State of the Art in Fair Machine Learning）</news:title>
   <news:publication_date>2026-07-07T20:26:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709256</loc>
  <lastmod>2026-07-07T20:25:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CGNet: 軽量コンテキストガイドネットワークによるセマンティックセグメンテーション（CGNet: A Light-weight Context Guided Network for Semantic Segmentation）</news:title>
   <news:publication_date>2026-07-07T20:25:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709254</loc>
  <lastmod>2026-07-07T19:34:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN生成画像の起源特定とフィンガープリント解析（Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints）</news:title>
   <news:publication_date>2026-07-07T19:34:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709252</loc>
  <lastmod>2026-07-07T19:34:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古い文献が示す洞察と現代物理学の接点（Coffee stains, cell receptors, and time crystals: Lessons from the old literature）</news:title>
   <news:publication_date>2026-07-07T19:34:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709250</loc>
  <lastmod>2026-07-07T19:34:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換入力とロバストなテンソル分解に基づく畳み込みニューラルネットワーク（Convolutional Neural Networks with Transformed Input based on Robust Tensor Network Decomposition）</news:title>
   <news:publication_date>2026-07-07T19:34:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709248</loc>
  <lastmod>2026-07-07T19:33:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胎児超音波画像における影領域信頼度マップの弱教師あり推定（Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging）</news:title>
   <news:publication_date>2026-07-07T19:33:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709246</loc>
  <lastmod>2026-07-07T19:33:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクタースケッチ認識のための注意型ネットワーク（Sketch-R2CNN: An Attentive Network for Vector Sketch Recognition）</news:title>
   <news:publication_date>2026-07-07T19:33:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709244</loc>
  <lastmod>2026-07-07T19:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形の概念を機械が自ら学ぶ方法（Unsupervised Learning of Shape Concepts – From Real-World Objects to Mental Simulation）</news:title>
   <news:publication_date>2026-07-07T19:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709242</loc>
  <lastmod>2026-07-07T19:33:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hedge手法を巡る攻防：適応的意思決定と最悪ケースの解析（Playing with and against Hedge）</news:title>
   <news:publication_date>2026-07-07T19:33:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709240</loc>
  <lastmod>2026-07-07T18:41:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>De Sitterの地平線とホログラフィック流体（De Sitter Horizons &amp;amp; Holographic Liquids）</news:title>
   <news:publication_date>2026-07-07T18:41:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709238</loc>
  <lastmod>2026-07-07T18:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNを用いた可逆データ圧縮（DeepZip: Lossless Data Compression using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-07T18:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709236</loc>
  <lastmod>2026-07-07T18:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による脳外科スキル判定（Machine Learning Distinguishes Neurosurgical Skill Levels in a Virtual Reality Tumor Resection Task）</news:title>
   <news:publication_date>2026-07-07T18:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709234</loc>
  <lastmod>2026-07-07T18:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的学習による点群整合（Adversarial point set registration）</news:title>
   <news:publication_date>2026-07-07T18:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709232</loc>
  <lastmod>2026-07-07T18:40:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深さと幅が局所最小値に与える影響（Effect of Depth and Width on Local Minima in Deep Learning）</news:title>
   <news:publication_date>2026-07-07T18:40:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709230</loc>
  <lastmod>2026-07-07T18:40:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNが画像をどう見るか（How you see me）</news:title>
   <news:publication_date>2026-07-07T18:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709228</loc>
  <lastmod>2026-07-07T18:40:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>即時変化検出の学習：遡及畳み込みと静的サンプル合成 (Learning to Detect Instantaneous Changes with Retrospective Convolution and Static Sample Synthesis)</news:title>
   <news:publication_date>2026-07-07T18:40:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709226</loc>
  <lastmod>2026-07-07T17:48:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的フィードバックループによる生成画像の品質改善（Adversarial Feedback Loop）</news:title>
   <news:publication_date>2026-07-07T17:48:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709224</loc>
  <lastmod>2026-07-07T17:48:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DarwinML: グラフベースの進化的AutoML（DarwinML: A Graph-based Evolutionary Algorithm for Automated Machine Learning）</news:title>
   <news:publication_date>2026-07-07T17:48:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709222</loc>
  <lastmod>2026-07-07T17:48:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Auto-Set: ウェアラブルを用いた活動認識のための深層オートエンコーダセット（Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables）</news:title>
   <news:publication_date>2026-07-07T17:48:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709220</loc>
  <lastmod>2026-07-07T17:47:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルノイズ下で主要パターンを最大限学習する方法（Limited Gradient Descent: Learning With Noisy Labels）</news:title>
   <news:publication_date>2026-07-07T17:47:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709218</loc>
  <lastmod>2026-07-07T17:47:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーケンス基盤の人物属性認識とJoint CTC-Attentionモデル（Sequence-based Person Attribute Recognition with Joint CTC-Attention Model）</news:title>
   <news:publication_date>2026-07-07T17:47:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709216</loc>
  <lastmod>2026-07-07T17:47:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トラフィックを考慮したNFVスケーリングの閾値調整（Traffic-aware Threshold Adjustment for NFV Scaling using DRL）</news:title>
   <news:publication_date>2026-07-07T17:47:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709214</loc>
  <lastmod>2026-07-07T17:47:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在因子モデルの説明可能化と影響関数（Explaining Latent Factor Models for Recommendation with Influence Functions）</news:title>
   <news:publication_date>2026-07-07T17:47:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709212</loc>
  <lastmod>2026-07-07T16:55:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動フォント生成におけるマルチスケール埋め込みと生成的敵対学習の意義（Pyramid Embedded Generative Adversarial Network for Automated Font Generation）</news:title>
   <news:publication_date>2026-07-07T16:55:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709210</loc>
  <lastmod>2026-07-07T16:55:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト監督を付与したSeq2Seq音声変換の改善（IMPROVING SEQUENCE-TO-SEQUENCE VOICE CONVERSION BY ADDING TEXT-SUPERVISION）</news:title>
   <news:publication_date>2026-07-07T16:55:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709208</loc>
  <lastmod>2026-07-07T16:54:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔検出のための特徴融合とセグメンテーション監督による学習（Learning Better Features for Face Detection with Feature Fusion and Segmentation Supervision）</news:title>
   <news:publication_date>2026-07-07T16:54:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709206</loc>
  <lastmod>2026-07-07T16:54:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話生成の多様性を高める新しい目的関数（Another Diversity-Promoting Objective Function for Neural Dialogue Generation）</news:title>
   <news:publication_date>2026-07-07T16:54:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709204</loc>
  <lastmod>2026-07-07T16:54:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>先読み探索による連続制御の学習革新（Model Learning for Look-ahead Exploration in Continuous Control）</news:title>
   <news:publication_date>2026-07-07T16:54:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709202</loc>
  <lastmod>2026-07-07T16:54:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能なマルチプル・カーネル学習による統合的がんサブタイプの発見（An interpretable multiple kernel learning approach for the discovery of integrative cancer subtypes）</news:title>
   <news:publication_date>2026-07-07T16:54:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709200</loc>
  <lastmod>2026-07-07T16:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向敵対的オートエンコーダによるゼロショット学習（Bi-Adversarial Auto-Encoder for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-07-07T16:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709198</loc>
  <lastmod>2026-07-07T16:02:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Multiple-Instance Learning を無限のシェイプレットで拡張する手法（Multiple-Instance Learning by Boosting Infinitely Many Shapelet-based Classifiers）</news:title>
   <news:publication_date>2026-07-07T16:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709196</loc>
  <lastmod>2026-07-07T16:02:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ChainGAN: 逐次的編集で生成を安定化させるアプローチ（CHAINGAN: A SEQUENTIAL APPROACH TO GANS）</news:title>
   <news:publication_date>2026-07-07T16:02:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709194</loc>
  <lastmod>2026-07-07T16:01:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量リプシッツ・マージン学習による証明済み防御の実装可能性（Lightweight Lipschitz Margin Training for Certified Defense against Adversarial Examples）</news:title>
   <news:publication_date>2026-07-07T16:01:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709192</loc>
  <lastmod>2026-07-07T16:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歩行者軌跡の表現学習――Actor–Critic Sequence-to-Sequence Autoencoderによる新展開（Representation Learning of Pedestrian Trajectories Using Actor-Critic Sequence-to-Sequence Autoencoder）</news:title>
   <news:publication_date>2026-07-07T16:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709190</loc>
  <lastmod>2026-07-07T16:01:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列ニューラルネットワークから学ぶ異種音声特徴の頑健学習（Learning Robust Heterogeneous Signal Features from Parallel Neural Network for Audio Sentiment Analysis）</news:title>
   <news:publication_date>2026-07-07T16:01:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709188</loc>
  <lastmod>2026-07-07T16:01:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遮蔽下で手と目を協調させる強化学習（Reinforcement Learning of Active Vision for Manipulating Objects under Occlusions）</news:title>
   <news:publication_date>2026-07-07T16:01:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709186</loc>
  <lastmod>2026-07-07T16:00:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Factorized DistillationによるHolistic Person Re-identificationの効率化（Factorized Distillation: Training Holistic Person Re-identiﬁcation Model by Distilling an Ensemble of Partial ReID Models）</news:title>
   <news:publication_date>2026-07-07T16:00:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709184</loc>
  <lastmod>2026-07-07T15:09:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外観変化下の視覚的自己位置推定：フィルタリング手法の可能性（Visual Localization Under Appearance Change: Filtering Approaches）</news:title>
   <news:publication_date>2026-07-07T15:09:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709182</loc>
  <lastmod>2026-07-07T15:09:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配整合型強正則化による深層学習の安定化（Gradient-Coherent Strong Regularization for Deep Neural Networks with Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-07-07T15:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709180</loc>
  <lastmod>2026-07-07T15:09:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模行列の対数行列式を並列で速く計算する方法（Parallel Matrix Condensation for Calculating Log-Determinant of Large Matrix）</news:title>
   <news:publication_date>2026-07-07T15:09:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709178</loc>
  <lastmod>2026-07-07T15:08:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量時系列データにおける教師なし異常検知と診断の深層ニューラルネットワーク（A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data）</news:title>
   <news:publication_date>2026-07-07T15:08:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709176</loc>
  <lastmod>2026-07-07T15:08:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多声音楽作曲のための結合リカレントモデル (Coupled Recurrent Models for Polyphonic Music Composition)</news:title>
   <news:publication_date>2026-07-07T15:08:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709174</loc>
  <lastmod>2026-07-07T15:08:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率粒子最適化サンプリングにおける分散削減（Variance Reduced Stochastic Particle-Optimization Sampling）</news:title>
   <news:publication_date>2026-07-07T15:08:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709172</loc>
  <lastmod>2026-07-07T15:07:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶を保存せずに継続学習する手法の要点解説（Learning without Memorizing）</news:title>
   <news:publication_date>2026-07-07T15:07:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709170</loc>
  <lastmod>2026-07-07T14:16:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテ上の抽出型要約のための無監督擬似ラベリング（Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records）</news:title>
   <news:publication_date>2026-07-07T14:16:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709168</loc>
  <lastmod>2026-07-07T14:16:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fenchel Lifted Networksによるニューラルネットワーク学習のラグランジュ緩和（Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training）</news:title>
   <news:publication_date>2026-07-07T14:16:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709166</loc>
  <lastmod>2026-07-07T14:15:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>携帯型単一導聯心電図からの同時12誘導心電図合成（Simultaneous 12-Lead Electrocardiogram Synthesis using a Single-Lead ECG Signal: Application to Handheld ECG Devices）</news:title>
   <news:publication_date>2026-07-07T14:15:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709164</loc>
  <lastmod>2026-07-07T14:15:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サロゲート機械学習モデルによる低スケーリングNEB計算法（Low-Scaling Algorithm for Nudged Elastic Band Calculations Using a Surrogate Machine Learning Model）</news:title>
   <news:publication_date>2026-07-07T14:15:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709162</loc>
  <lastmod>2026-07-07T14:14:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手のジェスチャーで舌を操るリアルタイム調音音声合成（SOUND-STREAM II: TOWARDS REAL-TIME GESTURE-CONTROLLED ARTICULATORY SOUND SYNTHESIS）</news:title>
   <news:publication_date>2026-07-07T14:14:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709160</loc>
  <lastmod>2026-07-07T14:14:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Role Action Embeddings: ネットワーク上の位置を捉える新しい表現（Role Action Embeddings: scalable representation of network positions）</news:title>
   <news:publication_date>2026-07-07T14:14:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709158</loc>
  <lastmod>2026-07-07T14:14:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Landerによる安定なドローン着陸制御（Neural Lander: Stable Drone Landing Control Using Learned Dynamics）</news:title>
   <news:publication_date>2026-07-07T14:14:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709156</loc>
  <lastmod>2026-07-07T13:23:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォントの組み合わせを学習する（Learning to Pair Fonts）</news:title>
   <news:publication_date>2026-07-07T13:23:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709154</loc>
  <lastmod>2026-07-07T13:22:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stackelberg GANによるGAN訓練の安定化（Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures）</news:title>
   <news:publication_date>2026-07-07T13:22:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709152</loc>
  <lastmod>2026-07-07T13:22:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Explain to Fix: DNN物体検出器の誤りを解釈して修正する枠組み（Explain to Fix: A Framework to Interpret and Correct DNN Object Detector Predictions）</news:title>
   <news:publication_date>2026-07-07T13:22:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709150</loc>
  <lastmod>2026-07-07T13:21:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続空間でのエンドツーエンド検索（End-to-End Retrieval in Continuous Space）</news:title>
   <news:publication_date>2026-07-07T13:21:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709148</loc>
  <lastmod>2026-07-07T13:21:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成3D肺結節画像生成とオートエンコーダ（Synthetic Lung Nodule 3D Image Generation Using Autoencoders）</news:title>
   <news:publication_date>2026-07-07T13:21:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709146</loc>
  <lastmod>2026-07-07T13:21:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルなロゴ認識とプロキシ学習（Scalable Logo Recognition using Proxies）</news:title>
   <news:publication_date>2026-07-07T13:21:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709144</loc>
  <lastmod>2026-07-07T13:20:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質の折りたたみと機械学習の基礎（Protein Folding and Machine Learning: Fundamentals）</news:title>
   <news:publication_date>2026-07-07T13:20:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709142</loc>
  <lastmod>2026-07-07T12:29:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的意味埋め込みに基づく汎化ゼロショット認識（Generalized Zero-Shot Recognition based on Visually Semantic Embedding）</news:title>
   <news:publication_date>2026-07-07T12:29:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709140</loc>
  <lastmod>2026-07-07T12:29:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検出器アレイを用いた自由空間光通信（Free-Space Optical Communications with Detector Arrays）</news:title>
   <news:publication_date>2026-07-07T12:29:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709138</loc>
  <lastmod>2026-07-07T12:29:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成顔はデータセットの偏りを解消するか（Can Synthetic Faces Undo the Damage of Dataset Bias To Face Recognition and Facial Landmark Detection?）</news:title>
   <news:publication_date>2026-07-07T12:29:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709136</loc>
  <lastmod>2026-07-07T12:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称結合とヘッブ則で学ぶ深層学習（Deep learning with asymmetric connections and Hebbian updates）</news:title>
   <news:publication_date>2026-07-07T12:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709134</loc>
  <lastmod>2026-07-07T12:28:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識の地図化が変える学術理解と応用（A Map of Knowledge）</news:title>
   <news:publication_date>2026-07-07T12:28:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709132</loc>
  <lastmod>2026-07-07T12:27:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライベート候補からの選択問題（Private Selection from Private Candidates）</news:title>
   <news:publication_date>2026-07-07T12:27:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709130</loc>
  <lastmod>2026-07-07T12:27:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Informed MCMCとベイズニューラルネットワークによる顔画像解析の実用化（Informed MCMC with Bayesian Neural Networks for Facial Image Analysis）</news:title>
   <news:publication_date>2026-07-07T12:27:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709128</loc>
  <lastmod>2026-07-07T11:35:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的合成における構造不整合の緩和（Mitigating Architectural Mismatch During the Evolutionary Synthesis of Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-07T11:35:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709126</loc>
  <lastmod>2026-07-07T11:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル変化検出と機械学習への応用（MODEL CHANGE DETECTION WITH APPLICATION TO MACHINE LEARNING）</news:title>
   <news:publication_date>2026-07-07T11:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709124</loc>
  <lastmod>2026-07-07T11:35:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Optimal Transport Classifierによる敵対的攻撃への防御（Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding）</news:title>
   <news:publication_date>2026-07-07T11:35:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709122</loc>
  <lastmod>2026-07-07T11:34:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LoTSS/HETDEXによる光学選択クエasarの低周波電波特性（LoTSS/HETDEX: Low-frequency radio properties of optically selected quasars）</news:title>
   <news:publication_date>2026-07-07T11:34:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709120</loc>
  <lastmod>2026-07-07T11:34:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絶縁相に残る整列した位相振動の理論（Theory of coherent phase modes in insulating Josephson junction chains）</news:title>
   <news:publication_date>2026-07-07T11:34:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709118</loc>
  <lastmod>2026-07-07T11:33:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定性を統合するアンサンブル特徴選択（Ensemble Feature Selection Integrating Stability）</news:title>
   <news:publication_date>2026-07-07T11:33:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709116</loc>
  <lastmod>2026-07-07T11:33:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による合成：低・高空間周波数の分離と再結合による画像回復（Learning to synthesize: splitting and recombining low and high spatial frequencies for image recovery）</news:title>
   <news:publication_date>2026-07-07T11:33:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709114</loc>
  <lastmod>2026-07-07T10:42:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DUNEのMeVニュートリノ観測可能性の開拓（Developing the MeV potential of DUNE: Detailed considerations of muon-induced spallation and other backgrounds）</news:title>
   <news:publication_date>2026-07-07T10:42:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709112</loc>
  <lastmod>2026-07-07T10:41:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語による指示で学ぶ方策（Guiding Policies with Language via Meta-Learning）</news:title>
   <news:publication_date>2026-07-07T10:41:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709110</loc>
  <lastmod>2026-07-07T10:41:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明と予測が人間の判断に与える影響（On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection）</news:title>
   <news:publication_date>2026-07-07T10:41:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709108</loc>
  <lastmod>2026-07-07T10:40:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬モデリングによるスケーラブルなエージェント整合性（Scalable agent alignment via reward modeling: a research direction）</news:title>
   <news:publication_date>2026-07-07T10:40:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709106</loc>
  <lastmod>2026-07-07T10:40:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>日周縁（ペニュンブラル）マイクロジェットの観測に基づくモデル（OBSERVATIONALLY BASED MODELS OF PENUMBRAL MICROJETS）</news:title>
   <news:publication_date>2026-07-07T10:40:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709104</loc>
  <lastmod>2026-07-07T10:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現実的走行環境における深層強化学習と決定性有限状態機械による自動運転シミュレーション（Simulated Autonomous Driving in a Realistic Driving Environment using Deep Reinforcement Learning and a Deterministic Finite State Machine）</news:title>
   <news:publication_date>2026-07-07T10:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709102</loc>
  <lastmod>2026-07-07T10:40:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測に基づく意思決定と公正性のカタログ（Prediction-Based Decisions and Fairness: A Catalogue of Choices, Assumptions, and Definitions）</news:title>
   <news:publication_date>2026-07-07T10:40:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709100</loc>
  <lastmod>2026-07-07T09:48:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非部分加法性（Non-submodular）関数の最大化とマトロイド制約への拡張（Non-submodular Function Maximization subject to a Matroid Constraint, with Applications）</news:title>
   <news:publication_date>2026-07-07T09:48:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709098</loc>
  <lastmod>2026-07-07T09:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Prefetchファイルを使った振る舞い型マルウェア分類（Behavioral Malware Classification using Convolutional Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-07T09:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709096</loc>
  <lastmod>2026-07-07T09:47:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OrthoSeg：多モーダル正射画像のセマンティックセグメンテーション用深層畳み込みニューラルネットワーク（ORTHOSEG: A DEEP MULTIMODAL CONVOLUTIONAL NEURAL NETWORK ARCHITECTURE FOR SEMANTIC SEGMENTATION OF ORTHOIMAGERY）</news:title>
   <news:publication_date>2026-07-07T09:47:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709094</loc>
  <lastmod>2026-07-07T09:47:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>H35 HV-CMOS 単一化ピクセルセンサーの特性評価（Characterisation of AMS H35 HV-CMOS monolithic active pixel sensor prototypes for HEP applications）</news:title>
   <news:publication_date>2026-07-07T09:47:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709092</loc>
  <lastmod>2026-07-07T09:47:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標条件付き方策で学ぶ操作可能表現（Learning Actionable Representations with Goal-Conditioned Policies）</news:title>
   <news:publication_date>2026-07-07T09:47:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709090</loc>
  <lastmod>2026-07-07T09:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル信念伝搬デコーダによる量子誤り訂正（Neural Belief-Propagation Decoders for Quantum Error-Correcting Codes）</news:title>
   <news:publication_date>2026-07-07T09:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709088</loc>
  <lastmod>2026-07-07T09:46:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なランダムグラフの対応付け手法（Efficient random graph matching via degree profiles）</news:title>
   <news:publication_date>2026-07-07T09:46:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709086</loc>
  <lastmod>2026-07-07T08:55:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載CANのトークン化と翻訳（ACTT: Automotive CAN Tokenization and Translation）</news:title>
   <news:publication_date>2026-07-07T08:55:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709084</loc>
  <lastmod>2026-07-07T08:54:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波であぶり出すジェットの偏波――3C 84核領域の線偏波の空間分解（Spatially resolved origin of mm-wave linear polarization in the nuclear region of 3C 84）</news:title>
   <news:publication_date>2026-07-07T08:54:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709082</loc>
  <lastmod>2026-07-07T08:54:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次観測に基づくネットワーク平均信念の分散学習（Distributed Learning of Average Belief Over Networks Using Sequential Observations）</news:title>
   <news:publication_date>2026-07-07T08:54:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709080</loc>
  <lastmod>2026-07-07T08:54:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの高速・高密度変形再構成を実現するDeep SfT（Deep Shape-from-Template: Wide-Baseline, Dense and Fast Registration and Deformable Reconstruction from a Single Image）</news:title>
   <news:publication_date>2026-07-07T08:54:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709078</loc>
  <lastmod>2026-07-07T08:54:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Visual Question Answeringに学ぶ「データバイアスの可視化」と経営応用（Explicit Bias Discovery in Visual Question Answering Models）</news:title>
   <news:publication_date>2026-07-07T08:54:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709076</loc>
  <lastmod>2026-07-07T08:53:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepIRによる画像リターゲティング（DeepIR: A Deep Semantics Driven Framework for Image Retargeting）</news:title>
   <news:publication_date>2026-07-07T08:53:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709074</loc>
  <lastmod>2026-07-07T08:53:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ETSチャレンジ：金融時系列シミュレーションのリアリズム評価手法（The ETS challenges: a machine learning approach to the evaluation of simulated financial time series for improving generation processes）</news:title>
   <news:publication_date>2026-07-07T08:53:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709072</loc>
  <lastmod>2026-07-07T08:02:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散探索によるベストアーム同定の進化（Decentralized Exploration in Multi-Armed Bandits - Extended version）</news:title>
   <news:publication_date>2026-07-07T08:02:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709070</loc>
  <lastmod>2026-07-07T08:01:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群の局所幾何構造をモデル化するGeo-CNN（Modeling Local Geometric Structure of 3D Point Clouds using Geo-CNN）</news:title>
   <news:publication_date>2026-07-07T08:01:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709068</loc>
  <lastmod>2026-07-07T08:01:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューリスティックを使った差分プライバシーの実装指針（How to Use Heuristics for Differential Privacy）</news:title>
   <news:publication_date>2026-07-07T08:01:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709066</loc>
  <lastmod>2026-07-07T08:00:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SEIGANによる合成的画像生成（SEIGAN: Towards Compositional Image Generation by Simultaneously Learning to Segment, Enhance, and Inpaint）</news:title>
   <news:publication_date>2026-07-07T08:00:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709064</loc>
  <lastmod>2026-07-07T08:00:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広視野地上観測における系外惑星トランジット検出と候補検証の機械学習手法（Machine-learning Approaches to Exoplanet Transit Detection and Candidate Validation in Wide-field Ground-based Surveys）</news:title>
   <news:publication_date>2026-07-07T08:00:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709062</loc>
  <lastmod>2026-07-07T08:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユニタリ群畳み込みによる効率的な深層ニューラルネットワークの構築（Building Efficient Deep Neural Networks with Unitary Group Convolutions）</news:title>
   <news:publication_date>2026-07-07T08:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709060</loc>
  <lastmod>2026-07-07T08:00:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スラムの個別検出と変化検知を実現する深層学習手法（Slum Segmentation and Change Detection : A Deep Learning Approach）</news:title>
   <news:publication_date>2026-07-07T08:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709058</loc>
  <lastmod>2026-07-07T07:08:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正確な追跡を追求するATOM（Accurate Tracking by Overlap Maximization）</news:title>
   <news:publication_date>2026-07-07T07:08:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709056</loc>
  <lastmod>2026-07-07T07:07:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性を超えて：ゼロショット学習のための敵対的消去埋め込みネットワーク（Beyond Attributes: Adversarial Erasing Embedding Network for Zero-shot Learning）</news:title>
   <news:publication_date>2026-07-07T07:07:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709054</loc>
  <lastmod>2026-07-07T07:06:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数のハウスホルダー反射子で近似固有値分解を実現する方法（Approximate Eigenvalue Decompositions of Linear Transformations with a Few Householder Reflectors）</news:title>
   <news:publication_date>2026-07-07T07:06:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709052</loc>
  <lastmod>2026-07-07T07:06:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外れ値に配慮した属性付きネットワーク埋め込み（Outlier Aware Network Embedding for Attributed Networks）</news:title>
   <news:publication_date>2026-07-07T07:06:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709050</loc>
  <lastmod>2026-07-07T07:06:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群のコンパクト表現を作る敵対的オートエンコーダ（Adversarial Autoencoders for Compact Representations of 3D Point Clouds）</news:title>
   <news:publication_date>2026-07-07T07:06:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709048</loc>
  <lastmod>2026-07-07T07:06:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆最近傍を用いた高効率な密度ベースクラスタリング（An efficient density-based clustering algorithm using reverse nearest neighbour）</news:title>
   <news:publication_date>2026-07-07T07:06:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709046</loc>
  <lastmod>2026-07-07T06:15:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己参照型深層学習（Self-Referenced Deep Learning）</news:title>
   <news:publication_date>2026-07-07T06:15:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709044</loc>
  <lastmod>2026-07-07T06:14:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話ボットにおけるチットチャット処理の信頼性・責任性・解釈可能性（A Trustworthy, Responsible and Interpretable System to Handle Chit Chat in Conversational Bots）</news:title>
   <news:publication_date>2026-07-07T06:14:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709042</loc>
  <lastmod>2026-07-07T06:14:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>測定に基づく適応プロトコルと量子強化学習（Measurement-Based Adaptation Protocol with Quantum Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-07T06:14:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709040</loc>
  <lastmod>2026-07-07T06:13:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルアーキテクチャ探索を組み込んだ深層能動学習（Deep Active Learning with a Neural Architecture Search）</news:title>
   <news:publication_date>2026-07-07T06:13:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709038</loc>
  <lastmod>2026-07-07T06:13:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一度見ただけで場所を想像して自己位置を推定する技術（Localisation via Deep Imagination: learn the features not the map）</news:title>
   <news:publication_date>2026-07-07T06:13:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709036</loc>
  <lastmod>2026-07-07T06:13:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習を用いた無線センサーネットワークの省エネ（Energy Efficiency in Reinforcement Learning for Wireless Sensor Networks）</news:title>
   <news:publication_date>2026-07-07T06:13:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709034</loc>
  <lastmod>2026-07-07T06:13:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の最適化をシンプルにする新手法（Deep Frank-Wolfe for Neural Network Optimization）</news:title>
   <news:publication_date>2026-07-07T06:13:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709032</loc>
  <lastmod>2026-07-07T05:21:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CA3Netによる歩行者再識別の文脈注意ネットワーク（CA3Net: Contextual-Attentional Attribute-Appearance Network for Person Re-Identification）</news:title>
   <news:publication_date>2026-07-07T05:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709030</loc>
  <lastmod>2026-07-07T05:13:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェブデータと補助カテゴリを組み合わせた細分類の学習（Fine-grained Classification using Heterogeneous Web Data and Auxiliary Categories）</news:title>
   <news:publication_date>2026-07-07T05:13:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709028</loc>
  <lastmod>2026-07-07T05:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル結合ソース・チャネル符号化（Neural Joint Source-Channel Coding）</news:title>
   <news:publication_date>2026-07-07T05:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709026</loc>
  <lastmod>2026-07-07T05:12:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三次元畳み込みニューラルネットワークの正則化ベース剪定（THREE-DIMENSIONAL CONVOLUTIONAL NEURAL NETWORK PRUNING WITH REGULARIZATION-BASED METHOD）</news:title>
   <news:publication_date>2026-07-07T05:12:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709024</loc>
  <lastmod>2026-07-07T05:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク完了型対話ポリシー学習の効率化—Switch‑DDQの提案（Switch-based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning）</news:title>
   <news:publication_date>2026-07-07T05:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709022</loc>
  <lastmod>2026-07-07T05:11:28Z</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DenseNetエンコーダを用いた脳腫瘍セグメンテーション（A Pretrained DenseNet Encoder for Brain Tumor Segmentation）</news:title>
   <news:publication_date>2026-07-07T05:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709020</loc>
  <lastmod>2026-07-07T05:10:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現と注意を強化したメタ学習（Representation based and Attention augmented Meta learning）</news:title>
   <news:publication_date>2026-07-07T05:10:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709018</loc>
  <lastmod>2026-07-07T04:20:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MIMOチャネル情報のフィードバックに深層リカレントネットワークを用いる（MIMO Channel Information Feedback Using Deep Recurrent Network）</news:title>
   <news:publication_date>2026-07-07T04:20:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709016</loc>
  <lastmod>2026-07-07T04:20:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層事前分布を用いた変分ベイズ的ドロップアウト（Variational Bayesian Dropout with a Hierarchical Prior）</news:title>
   <news:publication_date>2026-07-07T04:20:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709014</loc>
  <lastmod>2026-07-07T04:19:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴選択をSR-DAGで解く：最良葉識別によるモンテカルロ探索の応用 (Feature selection as Monte-Carlo Search in Growing Single Rooted Directed Acyclic Graph by Best Leaf Identification)</news:title>
   <news:publication_date>2026-07-07T04:19:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709012</loc>
  <lastmod>2026-07-07T04:19:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習可能な高次表現による行動認識（Learnable Higher-order Representation for Action Recognition）</news:title>
   <news:publication_date>2026-07-07T04:19:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709010</loc>
  <lastmod>2026-07-07T04:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGデータに対するリザバー型ニューラルネットの教師なし学習による感情認識（Unsupervised Learning in Reservoir Computing for EEG-based Emotion Recognition）</news:title>
   <news:publication_date>2026-07-07T04:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709008</loc>
  <lastmod>2026-07-07T04:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実用的な深層強化学習による株式トレーディング手法の検討（Practical Deep Reinforcement Learning Approach for Stock Trading）</news:title>
   <news:publication_date>2026-07-07T04:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709006</loc>
  <lastmod>2026-07-07T04:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多分野にまたがる学習内容を用いた電磁気学教育の実践（Teaching electromagnetism through demonstration of a practical application involving learning content from multiple disciplines）</news:title>
   <news:publication_date>2026-07-07T04:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709004</loc>
  <lastmod>2026-07-07T03:27:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NSEENによるエンティティ正規化の革新（NSEEN: Neural Semantic Embedding for Entity Normalization）</news:title>
   <news:publication_date>2026-07-07T03:27:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709002</loc>
  <lastmod>2026-07-07T03:27:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dセファロメトリ自動注釈と3D畳み込みニューラルネットワーク（Automatic Three-Dimensional Cephalometric Annotation System Using Three-Dimensional Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-07T03:27:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709000</loc>
  <lastmod>2026-07-07T03:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルリングでRNNを圧縮し行動認識へ応用（Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition）</news:title>
   <news:publication_date>2026-07-07T03:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708998</loc>
  <lastmod>2026-07-07T03:26:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数フレーム・複数特徴の統合によるロバスト視覚追跡（Robust Visual Tracking using Multi-Frame Multi-Feature Joint Modeling）</news:title>
   <news:publication_date>2026-07-07T03:26:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708996</loc>
  <lastmod>2026-07-07T03:26:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者単位での加齢黄斑変性重症度自動判定を実現したDeepSeeNet（DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs）</news:title>
   <news:publication_date>2026-07-07T03:26:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708994</loc>
  <lastmod>2026-07-07T03:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多プロトコルに対応する自己適応型ネットワークによる多発性硬化症病変セグメンテーション（A SELF-ADAPTIVE NETWORK FOR MULTIPLE SCLEROSIS LESION SEGMENTATION FROM MULTI-CONTRAST MRI WITH VARIOUS IMAGING PROTOCOLS）</news:title>
   <news:publication_date>2026-07-07T03:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708992</loc>
  <lastmod>2026-07-07T03:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FotonNetによる3D深度と2D分類の統合的物体検出（FotonNet: A HW-Efﬁcient Object Detection System Using 3D-Depth Segmentation and 2D-DNN Classifier）</news:title>
   <news:publication_date>2026-07-07T03:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708990</loc>
  <lastmod>2026-07-07T02:34:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Memory In Memory：時空間ダイナミクスから高次非定常性を学習する予測ニューラルネットワーク（Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics）</news:title>
   <news:publication_date>2026-07-07T02:34:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708988</loc>
  <lastmod>2026-07-07T02:34:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>操作スキルを新環境に拡張する方法（Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models）</news:title>
   <news:publication_date>2026-07-07T02:34:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708986</loc>
  <lastmod>2026-07-07T02:33:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一貫した注意機構を持つSiameseネットワークによる人物再識別（Re-Identification with Consistent Attentive Siamese Networks）</news:title>
   <news:publication_date>2026-07-07T02:33:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708984</loc>
  <lastmod>2026-07-07T02:32:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における鍵となる注目領域の再強調（Global and Local Sensitivity Guided Key Salient Object Re-augmentation for Video Saliency Detection）</news:title>
   <news:publication_date>2026-07-07T02:32:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708982</loc>
  <lastmod>2026-07-07T02:32:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像と弾幕による感情解析の統合モデル（Visual-Textual Emotion Analysis with Deep Coupled Video and Danmu Neural Networks）</news:title>
   <news:publication_date>2026-07-07T02:32:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708980</loc>
  <lastmod>2026-07-07T02:32:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意の分離と一貫性による学習の鋭敏化（Sharpen Focus: Learning with Attention Separability and Consistency）</news:title>
   <news:publication_date>2026-07-07T02:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708978</loc>
  <lastmod>2026-07-07T02:32:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連結バンディットにおける最良腕同定（Best Arm Identification in Linked Bandits）</news:title>
   <news:publication_date>2026-07-07T02:32:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708976</loc>
  <lastmod>2026-07-07T01:40:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療教育におけるハプティクスの可能性（Haptics for Medical Training）</news:title>
   <news:publication_date>2026-07-07T01:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708974</loc>
  <lastmod>2026-07-07T01:40:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における人物再識別のためのマルチスケール3D畳み込みネットワーク（Multi-scale 3D Convolution Network for Video Based Person Re-Identification）</news:title>
   <news:publication_date>2026-07-07T01:40:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708972</loc>
  <lastmod>2026-07-07T01:40:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子特性予測における不確実性定量化とベイズニューラルネットワークの実用性（Uncertainty quantification of molecular property prediction using Bayesian neural network models）</news:title>
   <news:publication_date>2026-07-07T01:40:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708970</loc>
  <lastmod>2026-07-07T01:39:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VIEW—エンジニアリングのための仮想インタラクティブなウェブ学習環境（VIEW – A Virtual Interactive Web-based Learning Environment for Engineering）</news:title>
   <news:publication_date>2026-07-07T01:39:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708968</loc>
  <lastmod>2026-07-07T01:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Indoor GeoNetによる屋内深度・カメラ姿勢推定の弱教師ありハイブリッド学習（Indoor GeoNet: Weakly Supervised Hybrid Learning for Depth and Pose Estimation）</news:title>
   <news:publication_date>2026-07-07T01:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708966</loc>
  <lastmod>2026-07-07T01:39:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイジアン・サイクルGANによる安定化と多様化（Bayesian Cycle-Consistent Generative Adversarial Networks via Marginalizing Latent Sampling）</news:title>
   <news:publication_date>2026-07-07T01:39:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708964</loc>
  <lastmod>2026-07-07T01:38:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師付きで複数行動を検出するSTARネットワーク（Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection）</news:title>
   <news:publication_date>2026-07-07T01:38:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708961</loc>
  <lastmod>2026-07-07T00:47:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類層の特徴を用いた転移学習（TRANSFER LEARNING USING CLASSIFICATION LAYER FEATURES OF CNN）</news:title>
   <news:publication_date>2026-07-07T00:47:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708959</loc>
  <lastmod>2026-07-07T00:47:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル正規化による汎化可能な敵対的訓練（Generalizable Adversarial Training via Spectral Normalization）</news:title>
   <news:publication_date>2026-07-07T00:47:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708957</loc>
  <lastmod>2026-07-07T00:47:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きなノルムはより転移しやすい：Adaptive Feature Normによるドメイン適応の簡潔解説（Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-07-07T00:47:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708955</loc>
  <lastmod>2026-07-07T00:46:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書き筆跡検証のハイブリッド特徴学習（Hybrid Feature Learning for Handwriting Verification）</news:title>
   <news:publication_date>2026-07-07T00:46:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708953</loc>
  <lastmod>2026-07-07T00:46:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PyTorch-Kaldiによる音声認識の実用化基盤（THE PYTORCH-KALDI SPEECH RECOGNITION TOOLKIT）</news:title>
   <news:publication_date>2026-07-07T00:46:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708951</loc>
  <lastmod>2026-07-07T00:46:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーツ合成で「見えない形」を生み出すCompoNet（CompoNet: Learning to Generate the Unseen by Part Synthesis and Composition）</news:title>
   <news:publication_date>2026-07-07T00:46:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708949</loc>
  <lastmod>2026-07-07T00:46:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ダブリング次元における幾何学的アライメント（On Geometric Alignment in Low Doubling Dimension）</news:title>
   <news:publication_date>2026-07-07T00:46:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708947</loc>
  <lastmod>2026-07-06T23:55:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pixel-Anchor：画素ベースとアンカーベースを融合した単発テキスト検出器（Pixel-Anchor: A Single-Shot Oriented Scene Text Detector）</news:title>
   <news:publication_date>2026-07-06T23:55:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708945</loc>
  <lastmod>2026-07-06T23:54:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的深層ネットワークが切り拓く「分布を扱う」AIの新地平（Stochastic Deep Networks）</news:title>
   <news:publication_date>2026-07-06T23:54:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708943</loc>
  <lastmod>2026-07-06T23:53:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUに組み込まれたディープラーニングアクセラレータのモデリング（Modeling Deep Learning Accelerator Enabled GPUs）</news:title>
   <news:publication_date>2026-07-06T23:53:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708941</loc>
  <lastmod>2026-07-06T23:53:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイムスケジューリングと電力配分を実現する深層学習の実装（Realtime Scheduling and Power Allocation Using Deep Neural Networks）</news:title>
   <news:publication_date>2026-07-06T23:53:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708939</loc>
  <lastmod>2026-07-06T23:53:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮テンソルのコア整合性が意味するもの（THE CORE CONSISTENCY OF A COMPRESSED TENSOR）</news:title>
   <news:publication_date>2026-07-06T23:53:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708937</loc>
  <lastmod>2026-07-06T23:53:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MALTS: 学習によるストレッチで改良するマッチング手法（MALTS: Matching After Learning to Stretch）</news:title>
   <news:publication_date>2026-07-06T23:53:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708935</loc>
  <lastmod>2026-07-06T23:52:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハーモニック・リコンポジションの条件付き自己回帰モデリング（Harmonic Recomposition using Conditional Autoregressive Modeling）</news:title>
   <news:publication_date>2026-07-06T23:52:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708933</loc>
  <lastmod>2026-07-06T23:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Taboo Trapによる敵対的サンプル検出の実装と意義（THE TABOO TRAP: BEHAVIOURAL DETECTION OF ADVERSARIAL SAMPLES）</news:title>
   <news:publication_date>2026-07-06T23:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708931</loc>
  <lastmod>2026-07-06T22:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル情報を深く結びつける設計の提案（Multimodal Densenet）</news:title>
   <news:publication_date>2026-07-06T22:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708929</loc>
  <lastmod>2026-07-06T22:53:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチユーザーVR360の遅延制御とQoE重視の深層学習支援マルチキャスト枠組み（Taming the latency in multi-user VR 360◦: A QoE-aware deep learning-aided multicast framework）</news:title>
   <news:publication_date>2026-07-06T22:53:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708927</loc>
  <lastmod>2026-07-06T22:53:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Siamese Networksとベイズ最適化による動画物体追跡の統合手法（Deep Siamese Networks with Bayesian non-Parametrics for Video Object Tracking）</news:title>
   <news:publication_date>2026-07-06T22:53:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708925</loc>
  <lastmod>2026-07-06T22:52:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>荷電流深非弾性散乱における準排他的重クォーク生成（Semi-Exclusive Heavy Quark Production in Charged-Current Deep Inelastic Scattering）</news:title>
   <news:publication_date>2026-07-06T22:52:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708923</loc>
  <lastmod>2026-07-06T22:51:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠距離歩行者検出を改善する深層生成とSSDの統合（Deep Learning based Pedestrian Detection at Distance in Smart Cities）</news:title>
   <news:publication_date>2026-07-06T22:51:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708921</loc>
  <lastmod>2026-07-06T22:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度画像を特権情報として用いるRGBベースの3D手指姿勢推定（RGB-based 3D Hand Pose Estimation via Privileged Learning with Depth Images）</news:title>
   <news:publication_date>2026-07-06T22:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708919</loc>
  <lastmod>2026-07-06T21:59:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>引用の役割と出典位置を同時に学習するニューラル手法（Neural Multi-Task Learning for Citation Function and Provenance）</news:title>
   <news:publication_date>2026-07-06T21:59:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708917</loc>
  <lastmod>2026-07-06T21:59:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>性別認識と年齢推定のための転移学習（Transfer Learning with Deep CNNs for Gender Recognition and Age Estimation）</news:title>
   <news:publication_date>2026-07-06T21:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708915</loc>
  <lastmod>2026-07-06T21:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル差分を探索価値に変える方策最適化（Policy Optimization with Model-based Explorations）</news:title>
   <news:publication_date>2026-07-06T21:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708913</loc>
  <lastmod>2026-07-06T21:58:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sparkエコシステム概観と実務への示唆（A Survey on Spark Ecosystem for Big Data Processing）</news:title>
   <news:publication_date>2026-07-06T21:58:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708911</loc>
  <lastmod>2026-07-06T21:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換領域に基づく多重線形動的システム（Transform-Based Multilinear Dynamical System for Tensor Time Series Analysis）</news:title>
   <news:publication_date>2026-07-06T21:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708909</loc>
  <lastmod>2026-07-06T21:58:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布差異最大化による画像プライバシー保護（Distribution Discrepancy Maximization for Image Privacy Preserving）</news:title>
   <news:publication_date>2026-07-06T21:58:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708907</loc>
  <lastmod>2026-07-06T21:58:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライブ映像で動く高精度顔認識の実装（Implementation of Robust Face Recognition System Using Live Video Feed Based on CNN）</news:title>
   <news:publication_date>2026-07-06T21:58:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708905</loc>
  <lastmod>2026-07-06T21:06:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能性のための正則化された敵対的生成例（Regularized adversarial examples for model interpretability）</news:title>
   <news:publication_date>2026-07-06T21:06:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708903</loc>
  <lastmod>2026-07-06T21:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>整形手術と変装による顔変化に対する照合手法（On Matching Faces with Alterations due to Plastic Surgery and Disguise）</news:title>
   <news:publication_date>2026-07-06T21:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708901</loc>
  <lastmod>2026-07-06T21:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種組み込み機器上でのDNN推論最適化：RLによるプリミティブ選択探索（Learning to infer: RL-based search for DNN primitive selection on Heterogeneous Embedded Systems）</news:title>
   <news:publication_date>2026-07-06T21:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708899</loc>
  <lastmod>2026-07-06T21:05:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>詳細GPUシミュレータによる機械学習ワークロード解析（Analyzing Machine Learning Workloads Using a Detailed GPU Simulator）</news:title>
   <news:publication_date>2026-07-06T21:05:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708897</loc>
  <lastmod>2026-07-06T21:05:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分ディリクレ枠組みによる異常検知（A Variational Dirichlet Framework for Out-of-Distribution Detection）</news:title>
   <news:publication_date>2026-07-06T21:05:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708895</loc>
  <lastmod>2026-07-06T21:04:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN-QP：勾配消失とLipschitz制約を同時に回避する新しいGAN枠組み (GAN-QP: A Novel GAN Framework without Gradient Vanishing and Lipschitz Constraint)</news:title>
   <news:publication_date>2026-07-06T21:04:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708893</loc>
  <lastmod>2026-07-06T21:04:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値混合モデルに関する情報理論的下界（Information Theoretic Bounds on Optimal Worst-case Error in Binary Mixture Identification）</news:title>
   <news:publication_date>2026-07-06T21:04:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708891</loc>
  <lastmod>2026-07-06T20:12:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化マップを用いた強化学習における知識の貯蔵と転移（Self-Organizing Maps for Storage and Transfer of Knowledge in Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-06T20:12:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708889</loc>
  <lastmod>2026-07-06T20:12:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像とGPSの検証を下から照合する手法（Image-to-GPS Verification Through A Bottom-Up Pattern Matching Network）</news:title>
   <news:publication_date>2026-07-06T20:12:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708887</loc>
  <lastmod>2026-07-06T20:12:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習モデルの理解を深める—適切な解像度で重要特徴を特定する手法（Understanding Learned Models by Identifying Important Features at the Right Resolution）</news:title>
   <news:publication_date>2026-07-06T20:12:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708885</loc>
  <lastmod>2026-07-06T20:11:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全な訓練データで学ぶ深層学習による画像修復（Deep Learning with Inaccurate Training Data for Image Restoration）</news:title>
   <news:publication_date>2026-07-06T20:11:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708883</loc>
  <lastmod>2026-07-06T20:11:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RePrによる畳み込みフィルタの改良訓練（RePr: Improved Training of Convolutional Filters）</news:title>
   <news:publication_date>2026-07-06T20:11:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708881</loc>
  <lastmod>2026-07-06T20:10:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CIFAR10で見る深層ニューラルネットワークと人間の視覚認識の比較（CIFAR10 to Compare Visual Recognition Performance between Deep Neural Networks and Humans）</news:title>
   <news:publication_date>2026-07-06T20:10:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708879</loc>
  <lastmod>2026-07-06T20:10:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主要作物の非生物的ストレス誘導遺伝子におけるシグナル配列の予測（Prediction of Signal Sequences in Abiotic Stress Inducible Genes from Main Crops by Association Rule Mining）</news:title>
   <news:publication_date>2026-07-06T20:10:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708877</loc>
  <lastmod>2026-07-06T19:19:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センサー駆動の確率的グラフによる大規模電力系モデリング（Probabilistic Graphs for Sensor Data-driven Modelling of Power Systems at Scale）</news:title>
   <news:publication_date>2026-07-06T19:19:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708875</loc>
  <lastmod>2026-07-06T19:19:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepConsensus: 多層の特徴の合意で揺らぎに強い画像分類を実現する（DeepConsensus: using the consensus of features from multiple layers to attain robust image classification）</news:title>
   <news:publication_date>2026-07-06T19:19:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708873</loc>
  <lastmod>2026-07-06T19:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>より高品質なスタイル転送を実現するGLStyleNet（GLStyleNet: Higher Quality Style Transfer Combining Global and Local Pyramid Features）</news:title>
   <news:publication_date>2026-07-06T19:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708871</loc>
  <lastmod>2026-07-06T19:17:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロジェクト型実験授業での学びを探る—学生のリフレクションを用いた評価（Using reflections to explore student learning during the project component of an advanced laboratory course）</news:title>
   <news:publication_date>2026-07-06T19:17:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708869</loc>
  <lastmod>2026-07-06T19:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカルRGB-to-CAD対応関係を学習して物体姿勢を推定する手法（Learning Local RGB-to-CAD Correspondences for Object Pose Estimation）</news:title>
   <news:publication_date>2026-07-06T19:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708867</loc>
  <lastmod>2026-07-06T19:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理タスクにおける不確実性の定量化（Quantifying Uncertainties in Natural Language Processing Tasks）</news:title>
   <news:publication_date>2026-07-06T19:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708865</loc>
  <lastmod>2026-07-06T19:16:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ的交差性フェアネスの評価（Bayesian Modeling of Intersectional Fairness: The Variance of Bias）</news:title>
   <news:publication_date>2026-07-06T19:16:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708855</loc>
  <lastmod>2026-07-06T18:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Determinantal Point Processes（Deep Determinantal Point Processes）</news:title>
   <news:publication_date>2026-07-06T18:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708853</loc>
  <lastmod>2026-07-06T18:15:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PointConvによる3D点群向け深層畳み込みネットワーク（PointConv: Deep Convolutional Networks on 3D Point Clouds）</news:title>
   <news:publication_date>2026-07-06T18:15:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708851</loc>
  <lastmod>2026-07-06T18:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TTSにおける表現混合法（Representation Mixing for TTS Synthesis）</news:title>
   <news:publication_date>2026-07-06T18:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708849</loc>
  <lastmod>2026-07-06T18:14:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>匿名性の深掘り：Quora質問の大規模分析（Deep Dive into Anonymity: A Large Scale Analysis of Quora Questions）</news:title>
   <news:publication_date>2026-07-06T18:14:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708847</loc>
  <lastmod>2026-07-06T18:14:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴と抽象行動を学習して一般化計画を計算する（Learning Features and Abstract Actions for Computing Generalized Plans）</news:title>
   <news:publication_date>2026-07-06T18:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708845</loc>
  <lastmod>2026-07-06T18:14:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動ソースコード要約の改善（Improving Automatic Source Code Summarization via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-06T18:14:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708843</loc>
  <lastmod>2026-07-06T18:13:59Z</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進化の加速（Accelerating the Evolution of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-06T18:13:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708841</loc>
  <lastmod>2026-07-06T17:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙ベクトルの非教師型後処理とコンセプタ反転（Unsupervised Post-processing of Word Vectors via Conceptor Negation）</news:title>
   <news:publication_date>2026-07-06T17:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708839</loc>
  <lastmod>2026-07-06T17:22:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形文表現における共通談話バイアスの補正（Correcting the Common Discourse Bias in Linear Representation of Sentences using Conceptors）</news:title>
   <news:publication_date>2026-07-06T17:22:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708837</loc>
  <lastmod>2026-07-06T17:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ共有によるマルチエージェント運転行動学習の設計（Parameter Sharing Reinforcement Learning Architecture for Multi Agent Driving Behaviors）</news:title>
   <news:publication_date>2026-07-06T17:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/708835</loc>
  <lastmod>2026-07-06T17:20:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:title>時空散乱ネットワークによる電磁逆設計と断層撮影（Space-Time Scattering Network for Electromagnetic Inverse Design and Tomography）</news:title>
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   <news:title>多エージェント強化学習における言語規約の自発的出現（Emergence of linguistic conventions in multi-agent reinforcement learning）</news:title>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>深層スパース符号化に基づく分類器は転移可能な敵対的例に頑健である（Classifiers Based on Deep Sparse Coding Architectures are Robust to Deep Learning Transferable Examples）</news:title>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ニューラルネットワークのロバストネス評価の統計的アプローチ（A Statistical Approach to Assessing Neural Network Robustness）</news:title>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:title>データ部分集合を用いた高速かつ貪欲なガウス過程のスパース化手法（A Fast and Greedy Subset-of-Data (SoD) Scheme for Sparsification in Gaussian processes）</news:title>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:title>再帰的スパース擬似入力ガウス過程SARSA（Recursive Sparse Pseudo-input Gaussian Process SARSA）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>エルゴード推論が開く並列化の扉（The Theory and Algorithm of Ergodic Inference）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>分布値データに対するBatch Self Organizing Mapと変数・成分の自動重み付け（Batch Self Organizing maps for distributional data with automatic weighting of variables and components）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>視覚だけで触覚を推定する研究（Sequential Image-based Attention Network for Inferring Force Estimation without Haptic Sensor）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>スタッキング型深層解析ネットワークの実務的理解（Stacking-Based Deep Neural Network: Deep Analytic Network for Pattern Classification）</news:title>
   <news:publication_date>2026-07-06T16:26:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>質量分析からの化学構造同定を部分構造で解く（Chemical Structure Elucidation from Mass Spectrometry by Matching Substructures）</news:title>
   <news:publication_date>2026-07-06T16:26:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>動的グラフにおけるリンク予測によるレコメンデーションの改良（Link Prediction in Dynamic Graphs for Recommendation）</news:title>
   <news:publication_date>2026-07-06T15:35:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/708811</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>注意機構を用いたWi‑Fiネットワークにおける歩行動作と方向の認識（Attention-based Walking Gait and Direction Recognition in Wi‑Fi Networks）</news:title>
   <news:publication_date>2026-07-06T15:34:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>人の識別と体格指数（Person Identification and Body Mass Index: A Deep Learning-Based Study on Micro-Dopplers）</news:title>
   <news:publication_date>2026-07-06T15:34:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>因果的な3D CNNのための再帰畳み込み（Recurrent Convolutions for Causal 3D CNNs）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>単調性分類の総覧（Monotonic classification: an overview on algorithms, performance measures and data sets）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-06T15:32:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>限定的楽観が後悔を減らす——割引和ゲームにおける最小後悔のアルゴリズム（The Impatient May Use Limited Optimism to Minimize Regret）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-06T15:32:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>キャッシュ占有チャネルによる堅牢なウェブサイト識別（Robust Website Fingerprinting Through the Cache Occupancy Channel）</news:title>
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   <news:genres>Blog</news:genres>
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