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   <news:title>属性情報に基づくゼロショットドメイン適応（Zero-shot Domain Adaptation Based on Attribute Information）</news:title>
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   <news:title>高次元における最尤推定の最適性と有界凸回帰の検証（Optimality of Maximum Likelihood for Log-Concave Density Estimation and Bounded Convex Regression）</news:title>
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   <news:title>銀河中心研究の次の10年を描く（Envisioning the next decade of Galactic Center science）</news:title>
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   <news:title>銀河ハローの中間年齢集団の欠如（The intermediate age population of the Galactic halo）</news:title>
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   <news:title>少数のシフトだけで十分である：効率的な畳み込みニューラルネットワーク設計（All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification）</news:title>
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   <news:title>再生可能エネルギーの時空間シナリオ予測（Forecasting Spatio-Temporal Renewable Scenarios: a Deep Generative Approach）</news:title>
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   <news:title>Stokes流懸濁液のシミュレーション高速化（Machine learning acceleration of simulations of Stokesian suspensions）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>タスク志向の設計を深層強化学習で実現する手法（Task-oriented Design through Deep Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>予測に直結する特徴量ランキングの柔軟な枠組み（A flexible model-free prediction-based framework for feature ranking）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>構文を取り込む新しいSRL手法：SupertagsによるSyntax-aware Neural Semantic Role Labeling with Supertags (Syntax-aware Neural Semantic Role Labeling with Supertags)</news:title>
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   <news:title>AutoMLコンペの設計と成果（AutoML @ NeurIPS 2018 challenge: Design and Results）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>組織画像から予後を予測する無教師学習の試み（TOWARDS UNSUPERVISED CANCER SUBTYPING: PREDICTING PROGNOSIS USING A HISTOLOGIC VISUAL DICTIONARY）</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>グラフクラスタリングの解像度パラメータを学習する方法（Learning Resolution Parameters for Graph Clustering）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-17T12:41:22Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>時間領域における特徴集約を学習する手法（Learning Feature Aggregation in Temporal Domain for Re-Identification）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-17T12:41:10Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>シミュレーションから実環境へゼロショットで移行する自動運転制御（Zero-Shot Autonomous Vehicle Policy Transfer: From Simulation to Real-World via Adversarial Learning）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>非負ローカルスパースコーディングによるサブスペースクラスタリング（Non-Negative Local Sparse Coding for Subspace Clustering）</news:title>
   <news:publication_date>2026-08-17T11:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:title>“Hang in there”：共感的応答を要する投稿の自動検出（“Hang in there”: Lexical and visual analysis to identify posts warranting empathetic responses）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>視覚的にもっと自然なVRの把持（A Visually Plausible Grasping System for Object Manipulation and Interaction in Virtual Reality Environments）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-17T11:38:30Z</lastmod>
  <news:news>
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    <news:language>ja</news:language>
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   <news:title>原始星系の組み立てにおける変動性（Variability in the Assembly of Protostellar Systems）</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>修正的な人間フィードバックからガウス方策を学ぶ（Learning Gaussian Policies from Corrective Human Feedback）</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>信頼性を重視したカーネルスパースコーディングと辞書学習（Conﬁdent Kernel Sparse Coding and Dictionary 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>Alfvén波のチャーピングと高速イオン損失の機械学習解析（Machine learning characterisation of Alfvénic and sub-Alfvénic chirping and correlation with fast ion loss at NSTX）</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>ディープフィードフォワードを用いた流体の縮約モデル構築（Construction of Reduced Order Models for Fluid Flows Using Deep Feedforward Neural Networks）</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>ゲーム開発で学ぶプログラミング概念（Teaching Programming Concepts by Developing Games）</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>線形化されたベンジャミン方程式の可制御性と安定化（On the Controllability and Stabilization of the Linearized Benjamin Equation on a Periodic Domain）</news:title>
   <news:publication_date>2026-08-17T10:45:27Z</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>
   </news:publication>
   <news:title>宇宙天気における機械学習の挑戦（The Challenge of Machine Learning in Space Weather）</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>継続的に学習するシステムの参照アーキテクチャ（Continual Learning in Practice）</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>建物エネルギー管理における強化学習の総覧（A Review of Reinforcement Learning for Autonomous Building Energy Management）</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:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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  <lastmod>2026-08-17T05:11:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認証済みユーザーの特徴と予測手法（What sets Verified Users apart? Insights, Analysis and Prediction of Verified Users on Twitter）</news:title>
   <news:publication_date>2026-08-17T05:11:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724071</loc>
  <lastmod>2026-08-17T05:11:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目的指向行動と変分予測符号化による視覚注意とワーキングメモリの動的統合（Goal-Directed Behavior under Variational Predictive Coding）</news:title>
   <news:publication_date>2026-08-17T05:11:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724069</loc>
  <lastmod>2026-08-17T05:10:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴を凝縮して整列させる教師なしドメイン適応（Learning Condensed and Aligned Features for Unsupervised Domain Adaptation Using Label Propagation）</news:title>
   <news:publication_date>2026-08-17T05:10:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724067</loc>
  <lastmod>2026-08-17T05:10:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RFループ内での深層学習を組み込む無線機器のリアルタイム化（Big Data Goes Small: Real-Time Spectrum-Driven Embedded Wireless Networking Through Deep Learning in the RF Loop）</news:title>
   <news:publication_date>2026-08-17T05:10:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724065</loc>
  <lastmod>2026-08-17T05:10:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列医用画像解析による知能的医用画像分析（Parallel Medical Imaging for Intelligent Medical Image Analysis: Concepts, Methods, and Applications）</news:title>
   <news:publication_date>2026-08-17T05:10:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724063</loc>
  <lastmod>2026-08-17T05:09:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歴史文書の正規化における少数例学習とゼロショット学習の実証（Few-Shot and Zero-Shot Learning for Historical Text Normalization）</news:title>
   <news:publication_date>2026-08-17T05:09:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724061</loc>
  <lastmod>2026-08-17T04:18:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程とベイズ最適化の金融応用（Financial Applications of Gaussian Processes and Bayesian Optimization）</news:title>
   <news:publication_date>2026-08-17T04:18:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724059</loc>
  <lastmod>2026-08-17T04:18:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散データにおける条件付き独立性検定（Testing Conditional Independence on Discrete Data using Stochastic Complexity）</news:title>
   <news:publication_date>2026-08-17T04:18:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724057</loc>
  <lastmod>2026-08-17T04:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地中鉱山における発破作業による岩盤挙動の数値モデリング (NUMERICAL MODELING OF ROCKMASS BEHAVIOUR DUE TO BLASTING OPERATIONS IN UNDERGROUND MINES)</news:title>
   <news:publication_date>2026-08-17T04:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724055</loc>
  <lastmod>2026-08-17T04:16:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン人間行動認識に階層化隠れマルコフモデルを用いる（Online Human Activity Recognition Employing Hierarchical Hidden Markov Models）</news:title>
   <news:publication_date>2026-08-17T04:16:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724053</loc>
  <lastmod>2026-08-17T04:16:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習アーキテクチャによる攻撃的言語分析（Offensive Language Analysis using Deep Learning Architecture）</news:title>
   <news:publication_date>2026-08-17T04:16:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724051</loc>
  <lastmod>2026-08-17T04:16:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次モンテカルロの要素（Elements of Sequential Monte Carlo）</news:title>
   <news:publication_date>2026-08-17T04:16:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724049</loc>
  <lastmod>2026-08-17T04:15:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主成分分析に基づくマルチビュー深層表現による画像分類（Image Classification base on PCA of Multi-view Deep Representation）</news:title>
   <news:publication_date>2026-08-17T04:15:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724047</loc>
  <lastmod>2026-08-17T03:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー効率の高い物体検出を実現するSpiking‑YOLO（Spiking‑YOLO: Spiking Neural Network for Energy‑Efficient Object Detection）</news:title>
   <news:publication_date>2026-08-17T03:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724045</loc>
  <lastmod>2026-08-17T03:23:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師ありセルフトaught深層学習による指骨セグメンテーション（Semi-Supervised Self-Taught Deep Learning for Finger Bones Segmentation）</news:title>
   <news:publication_date>2026-08-17T03:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724043</loc>
  <lastmod>2026-08-17T03:23:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブミリ波で作る宇宙の3次元地図（The case for a ‘sub-millimeter SDSS’: a 3D map of galaxy evolution to z ≈10）</news:title>
   <news:publication_date>2026-08-17T03:23:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724041</loc>
  <lastmod>2026-08-17T03:22:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス内分割によるオープンセット認識（Open-Set Recognition Using Intra-Class Splitting）</news:title>
   <news:publication_date>2026-08-17T03:22:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724039</loc>
  <lastmod>2026-08-17T03:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークのパラドックス：類似でありながら異なり、異なりながら類似である（Paradox in Deep Neural Networks: Similar yet Different while Different yet Similar）</news:title>
   <news:publication_date>2026-08-17T03:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724037</loc>
  <lastmod>2026-08-17T03:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SmartEDA: 自動化された探索的データ解析が変える現場（SmartEDA: An R Package for Automated Exploratory Data Analysis）</news:title>
   <news:publication_date>2026-08-17T03:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724035</loc>
  <lastmod>2026-08-17T03:21:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識における閉塞指向コンパクトテンプレート学習（Occlusion-guided compact template learning for ensemble deep network-based pose-invariant face recognition）</news:title>
   <news:publication_date>2026-08-17T03:21:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724033</loc>
  <lastmod>2026-08-17T02:30:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフにおける予測と説明のための相互作用埋め込み（Interaction Embeddings for Prediction and Explanation in Knowledge Graphs）</news:title>
   <news:publication_date>2026-08-17T02:30:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724031</loc>
  <lastmod>2026-08-17T02:29:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミャンマー語の音節ベースニューラル固有表現抽出（Syllable-Based Neural Named Entity Recognition for Myanmar Language）</news:title>
   <news:publication_date>2026-08-17T02:29:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724029</loc>
  <lastmod>2026-08-17T02:29:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超大型望遠鏡を用いたダークマターの性質検証（Testing the Nature of Dark Matter with Extremely Large Telescopes）</news:title>
   <news:publication_date>2026-08-17T02:29:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724027</loc>
  <lastmod>2026-08-17T02:28:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再プログラマブルな電気光学的非線形活性化関数（Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks）</news:title>
   <news:publication_date>2026-08-17T02:28:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724025</loc>
  <lastmod>2026-08-17T02:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的に学習するGANによる楽曲生成の実践と意義（Progressive Generative Adversarial Binary Networks for Music Generation）</news:title>
   <news:publication_date>2026-08-17T02:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724023</loc>
  <lastmod>2026-08-17T02:28:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランクテンソルグリッドによる画像補完（Low-rank Tensor Grid for Image Completion）</news:title>
   <news:publication_date>2026-08-17T02:28:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724021</loc>
  <lastmod>2026-08-17T02:28:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平方井戸ポテンシャルによる核天体物理学的融合反応の解釈（Potential model for nuclear astrophysical fusion reactions with a square-well potential）</news:title>
   <news:publication_date>2026-08-17T02:28:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724019</loc>
  <lastmod>2026-08-17T01:35:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高エネルギー物理における機械学習の適用（Machine Learning Solutions for High Energy Physics）</news:title>
   <news:publication_date>2026-08-17T01:35:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724017</loc>
  <lastmod>2026-08-17T01:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈対応学習によるニューラル機械翻訳（Context-Aware Learning for Neural Machine Translation）</news:title>
   <news:publication_date>2026-08-17T01:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724015</loc>
  <lastmod>2026-08-17T01:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイト単位深層ニューラルネットワークの活性解析（Activation Analysis of a Byte-Based Deep Neural Network for Malware Classification）</news:title>
   <news:publication_date>2026-08-17T01:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724013</loc>
  <lastmod>2026-08-17T01:32:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化医用画像解析の深層学習革新（Deep Learning for Automated Medical Image Analysis）</news:title>
   <news:publication_date>2026-08-17T01:32:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724011</loc>
  <lastmod>2026-08-17T01:31:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lq安定性のための指数的エフロン–スタイン不等式（An Exponential Efron-Stein Inequality for Lq Stable Learning Rules）</news:title>
   <news:publication_date>2026-08-17T01:31:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724009</loc>
  <lastmod>2026-08-17T01:31:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実践的な多忠実度ベイズ最適化によるハイパーパラメータ探索（Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning）</news:title>
   <news:publication_date>2026-08-17T01:31:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724007</loc>
  <lastmod>2026-08-17T01:31:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一RGB画像から複雑トポロジーのメッシュを生成する骨格ブリッジ学習（A Skeleton-bridged Deep Learning Approach for Generating Meshes of Complex Topologies from Single RGB Images）</news:title>
   <news:publication_date>2026-08-17T01:31:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724005</loc>
  <lastmod>2026-08-17T00:39:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移適応学習の10年サーベイ（Transfer Adaptation Learning: A Decade Survey）</news:title>
   <news:publication_date>2026-08-17T00:39:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724003</loc>
  <lastmod>2026-08-17T00:39:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なセマンティックセグメンテーションのための知識適応（Knowledge Adaptation for Efficient Semantic Segmentation）</news:title>
   <news:publication_date>2026-08-17T00:39:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724001</loc>
  <lastmod>2026-08-17T00:39:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習によるアイス状態の生成（Generation of ice states through deep reinforcement learning）</news:title>
   <news:publication_date>2026-08-17T00:39:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723999</loc>
  <lastmod>2026-08-17T00:38:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リングオシレーターネットワークを用いたハードウェアトロイ検出と教師あり学習の比較（Supervised Machine Learning Techniques for Trojan Detection with Ring Oscillator Network）</news:title>
   <news:publication_date>2026-08-17T00:38:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723997</loc>
  <lastmod>2026-08-17T00:38:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチクラス動的OD需要の推定（Estimating multi-class dynamic origin-destination demand through a forward-backward algorithm on computational graphs）</news:title>
   <news:publication_date>2026-08-17T00:38:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723995</loc>
  <lastmod>2026-08-17T00:37:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間変動する特徴量を扱う可証明学習アルゴリズム（Provably Correct Learning Algorithms in the Presence of Time-Varying Features Using a Variational Perspective）</news:title>
   <news:publication_date>2026-08-17T00:37:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723993</loc>
  <lastmod>2026-08-17T00:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低消費電力識別型深層信念ネットワークのための近似計算フレームワーク（AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks）</news:title>
   <news:publication_date>2026-08-17T00:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723991</loc>
  <lastmod>2026-08-16T23:45:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Log-Likelihood Ratio Quantization（Deep Log-Likelihood Ratio Quantization）</news:title>
   <news:publication_date>2026-08-16T23:45:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723989</loc>
  <lastmod>2026-08-16T23:45:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎化されたスパース加法モデル（Generalized Sparse Additive Models）</news:title>
   <news:publication_date>2026-08-16T23:45:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723987</loc>
  <lastmod>2026-08-16T23:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不規則間隔データに対するウェーブレット回帰と加法モデル（Wavelet regression and additive models for irregularly spaced data）</news:title>
   <news:publication_date>2026-08-16T23:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723985</loc>
  <lastmod>2026-08-16T22:51:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株価バー画像を使ったCNNによるアルゴリズム取引モデル（Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-16T22:51:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723983</loc>
  <lastmod>2026-08-16T22:40:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LEAPによる辺性質の学習（Learning Edge Properties in Graphs from Path Aggregations）</news:title>
   <news:publication_date>2026-08-16T22:40:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723981</loc>
  <lastmod>2026-08-16T22:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ彩色問題とDeep Learningの邂逅（Graph Colouring Meets Deep Learning: Effective Graph Neural Network Models for Combinatorial Problems）</news:title>
   <news:publication_date>2026-08-16T22:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723979</loc>
  <lastmod>2026-08-16T22:39:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮ビデオ品質向上のための品質ゲート付きConvLSTM（Quality-Gated Convolutional LSTM for Enhancing Compressed Video）</news:title>
   <news:publication_date>2026-08-16T22:39:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723977</loc>
  <lastmod>2026-08-16T22:39:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球近傍の超新星爆発が示す証拠と示唆（Near-Earth Supernova Explosions: Evidence, Implications, and Opportunities）</news:title>
   <news:publication_date>2026-08-16T22:39:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723975</loc>
  <lastmod>2026-08-16T22:38:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波リズムの出現：EEGデータのモデル解釈（Emergence of Brain Rhythms: Model Interpretation of EEG Data）</news:title>
   <news:publication_date>2026-08-16T22:38:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723973</loc>
  <lastmod>2026-08-16T21:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既知の相互作用だけで薬物相互作用を予測する手法の提案（Detecting drug-drug interactions using artificial neural networks and classic graph similarity measures）</news:title>
   <news:publication_date>2026-08-16T21:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723971</loc>
  <lastmod>2026-08-16T21:46:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モノラル音声改善と認識のギャップを埋める（Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling）</news:title>
   <news:publication_date>2026-08-16T21:46:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723969</loc>
  <lastmod>2026-08-16T21:46:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助的学習による壊滅的忘却の克服（Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay）</news:title>
   <news:publication_date>2026-08-16T21:46:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723967</loc>
  <lastmod>2026-08-16T21:45:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い可逆変換で分散MCMCを速く正確にする手法（Embarrassingly parallel MCMC using deep invertible transformations）</news:title>
   <news:publication_date>2026-08-16T21:45:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723965</loc>
  <lastmod>2026-08-16T21:44:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類における意図しないバイアスを多面的に測る指標群（Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification）</news:title>
   <news:publication_date>2026-08-16T21:44:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723963</loc>
  <lastmod>2026-08-16T21:44:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GOGGLESによる自動画像ラベリング（GOGGLES: Automatic Image Labeling with Affinity Coding）</news:title>
   <news:publication_date>2026-08-16T21:44:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723961</loc>
  <lastmod>2026-08-16T21:44:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EDGES低周波スペクトルにおける赤方偏移した21cm信号（THE REDSHIFTED 21-CM SIGNAL IN THE EDGES LOW-BAND SPECTRUM）</news:title>
   <news:publication_date>2026-08-16T21:44:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723959</loc>
  <lastmod>2026-08-16T20:52:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層Seq2Seqを用いた高速Text-to-Speech（Deep Text-to-Speech System with Seq2Seq Model）</news:title>
   <news:publication_date>2026-08-16T20:52:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723957</loc>
  <lastmod>2026-08-16T20:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模交通信号制御のためのマルチエージェント深層強化学習（Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control）</news:title>
   <news:publication_date>2026-08-16T20:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723955</loc>
  <lastmod>2026-08-16T20:52:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NASAのSDOミッションから作られた機械学習用データセットの意義（A Machine Learning Dataset Prepared From the NASA Solar Dynamics Observatory Mission）</news:title>
   <news:publication_date>2026-08-16T20:52:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723953</loc>
  <lastmod>2026-08-16T20:51:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>巨大衝突の現場で使える機械学習モデル（Realistic On-The-Fly Outcomes of Planetary Collisions: Machine Learning Applied to Simulations of Giant Impacts）</news:title>
   <news:publication_date>2026-08-16T20:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723951</loc>
  <lastmod>2026-08-16T20:51:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話と転移学習による実用的意味解析（Practical Semantic Parsing for Spoken Language Understanding）</news:title>
   <news:publication_date>2026-08-16T20:51:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723949</loc>
  <lastmod>2026-08-16T20:51:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再電離期の宇宙の相転移をLyαで解き明かす（Unveiling the Phase Transition of the Universe During the Reionization Epoch with Lyα）</news:title>
   <news:publication_date>2026-08-16T20:51:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723947</loc>
  <lastmod>2026-08-16T20:51:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>普遍的な変分量子計算の実現可能性（Universal Variational Quantum Computation）</news:title>
   <news:publication_date>2026-08-16T20:51:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723945</loc>
  <lastmod>2026-08-16T19:59:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小マゼラン雲の個別恒星を用いたTP-AGB段階の制約（Constraining the thermally-pulsing asymptotic giant branch phase with resolved stellar populations in the Small Magellanic Cloud）</news:title>
   <news:publication_date>2026-08-16T19:59:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723943</loc>
  <lastmod>2026-08-16T19:49:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マニフォールド上の行列因子分解としてのクラスタリングの再考（Revisiting clustering as matrix factorisation on the Stiefel manifold）</news:title>
   <news:publication_date>2026-08-16T19:49:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723941</loc>
  <lastmod>2026-08-16T19:49:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ割当モデル：非負テンソル分解とトピックモデルのための逐次モンテカルロ推論（Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Pólya Urns）</news:title>
   <news:publication_date>2026-08-16T19:49:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723939</loc>
  <lastmod>2026-08-16T19:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経剪定による継続学習（Continual Learning via Neural Pruning）</news:title>
   <news:publication_date>2026-08-16T19:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723937</loc>
  <lastmod>2026-08-16T19:47:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>conLSH：文脈を使ってノイズの多い長リードをマッピングする新しいハッシュ法（conLSH: Context based Locality Sensitive Hashing for Mapping of noisy SMRT Reads）</news:title>
   <news:publication_date>2026-08-16T19:47:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723935</loc>
  <lastmod>2026-08-16T19:47:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチメッセンジャー天文学の展望（Opportunities for Multimessenger Astronomy in the 2020s）</news:title>
   <news:publication_date>2026-08-16T19:47:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723933</loc>
  <lastmod>2026-08-16T19:47:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NGC 1533、IC 2038、IC 2039：ドラード群の相互作用する三重銀河（VEGAS: NGC 1533, IC 2038 and IC 2039: an interacting triplet in the Dorado group）</news:title>
   <news:publication_date>2026-08-16T19:47:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723931</loc>
  <lastmod>2026-08-16T18:55:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークのスケーリング—キャパシティ配分の視点（Scaling up deep neural networks: a capacity allocation perspective）</news:title>
   <news:publication_date>2026-08-16T18:55:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723929</loc>
  <lastmod>2026-08-16T18:55:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的コミュニケーションにおける語用論的推論と視覚的抽象化（Pragmatic inference and visual abstraction enable contextual flexibility during visual communication）</news:title>
   <news:publication_date>2026-08-16T18:55:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723927</loc>
  <lastmod>2026-08-16T18:55:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で送信アンテナを賢く選ぶ：Massive MIMO-GSMにおける実証的改善（Transmit Antenna Selection for Massive MIMO-GSM with Machine Learning）</news:title>
   <news:publication_date>2026-08-16T18:55:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723925</loc>
  <lastmod>2026-08-16T18:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層ニューラルネットワークの平均場解析（Mean Field Analysis of Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-16T18:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723923</loc>
  <lastmod>2026-08-16T18:53:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M33に対する新規深部JVLA電波サーベイ（A NEW, DEEP JVLA RADIO SURVEY OF M33）</news:title>
   <news:publication_date>2026-08-16T18:53:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723921</loc>
  <lastmod>2026-08-16T18:53:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反応学習戦略が変える反復ゲームの設計（REACTIVE LEARNING STRATEGIES FOR ITERATED GAMES）</news:title>
   <news:publication_date>2026-08-16T18:53:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723919</loc>
  <lastmod>2026-08-16T18:53:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理知識とAIを賢く組み合わせる（Physics Enhanced Artificial Intelligence）</news:title>
   <news:publication_date>2026-08-16T18:53:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723917</loc>
  <lastmod>2026-08-16T18:01:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタラクティブ知覚によるアフォーダンス地図の構築（Building an Affordances Map with Interactive Perception）</news:title>
   <news:publication_date>2026-08-16T18:01:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723915</loc>
  <lastmod>2026-08-16T17:53:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lγ-PageRankによる半教師あり学習（Lγ-PageRank for Semi-Supervised Learning）</news:title>
   <news:publication_date>2026-08-16T17:53:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723913</loc>
  <lastmod>2026-08-16T17:53:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子エンタングルメントスイッチの確率解析（On the Stochastic Analysis of a Quantum Entanglement Switch）</news:title>
   <news:publication_date>2026-08-16T17:53:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723911</loc>
  <lastmod>2026-08-16T17:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡散K平均法による多様体クラスタリング（Diffusion K-means clustering on manifolds: provable exact recovery via semidefinite relaxations）</news:title>
   <news:publication_date>2026-08-16T17:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723909</loc>
  <lastmod>2026-08-16T17:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース深層強化学習による機械の「描画学習」(Learning to Paint With Model-based Deep Reinforcement Learning)</news:title>
   <news:publication_date>2026-08-16T17:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723907</loc>
  <lastmod>2026-08-16T17:52:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子設計のための深層学習レビュー（Deep learning for molecular design – a review of the state of the art）</news:title>
   <news:publication_date>2026-08-16T17:52:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723905</loc>
  <lastmod>2026-08-16T17:51:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Accuracy BoosterによるCNN性能向上（Accuracy Booster: Performance Boosting using Feature Map Re-calibration）</news:title>
   <news:publication_date>2026-08-16T17:51:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723903</loc>
  <lastmod>2026-08-16T17:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TensorFlowによるHPC評価と実運用への含意（An Evaluation of TensorFlow Performance in HPC Applications）</news:title>
   <news:publication_date>2026-08-16T17:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723901</loc>
  <lastmod>2026-08-16T17:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子エネルギー写像によるニューラルネットワークポテンシャルの検証（Atomic energy mapping of neural network potential）</news:title>
   <news:publication_date>2026-08-16T17:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723899</loc>
  <lastmod>2026-08-16T17:00:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SleepNetによる自動睡眠解析（SleepNet: Automated sleep analysis via dense convolutional neural network using physiological time series）</news:title>
   <news:publication_date>2026-08-16T17:00:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723897</loc>
  <lastmod>2026-08-16T16:58:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークによる関係推論とニューロモーフィック逆伝播学習（A Spiking Network for Inference of Relations Trained with Neuromorphic Backpropagation）</news:title>
   <news:publication_date>2026-08-16T16:58:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723895</loc>
  <lastmod>2026-08-16T16:58:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベラー・ホット表現による脳波（EEG）てんかん性短時間活動の検出（Labeler-hot Detection of EEG Epileptic Transients）</news:title>
   <news:publication_date>2026-08-16T16:58:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723893</loc>
  <lastmod>2026-08-16T16:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>源を差し引いた宇宙赤外背景の背後にある集団（Populations behind the source-subtracted cosmic infrared background anisotropies）</news:title>
   <news:publication_date>2026-08-16T16:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723891</loc>
  <lastmod>2026-08-16T16:58:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>所定性能制御を用いた方策改良で時相論理タスクを満たす（Prescribed Performance Control Guided Policy Improvement for Satisfying Signal Temporal Logic Tasks）</news:title>
   <news:publication_date>2026-08-16T16:58:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723889</loc>
  <lastmod>2026-08-16T16:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフライン署名検証における多表現学習とマルチロス・スナップショットアンサンブル（Multi-Representational Learning for Offline Signature Verification using Multi-Loss Snapshot Ensemble of CNNs）</news:title>
   <news:publication_date>2026-08-16T16:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723887</loc>
  <lastmod>2026-08-16T16:05:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPMF: 信頼と嗜好の分割に基づく行列分解型推薦アルゴリズム（SPMF: A Social Trust and Preference Segmentation–based Matrix Factorization Recommendation Algorithm）</news:title>
   <news:publication_date>2026-08-16T16:05:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723885</loc>
  <lastmod>2026-08-16T16:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Recurrent Q-LearningとDeep Q-Learningの比較（Deep Recurrent Q-Learning vs Deep Q-Learning on a simple Partially Observable Markov Decision Process with Minecraft）</news:title>
   <news:publication_date>2026-08-16T16:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723883</loc>
  <lastmod>2026-08-16T16:04:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル流解析を超音波とCNNで実現する可能性（Demonstration of Vector Flow Imaging using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-16T16:04:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723881</loc>
  <lastmod>2026-08-16T16:04:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル保存埋め込みによる類似度学習（Similarity Learning via Kernel Preserving Embedding）</news:title>
   <news:publication_date>2026-08-16T16:04:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723879</loc>
  <lastmod>2026-08-16T16:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習のための勾配降下ベース最適化アルゴリズム（Gradient Descent based Optimization Algorithms for Deep Learning Models Training）</news:title>
   <news:publication_date>2026-08-16T16:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723877</loc>
  <lastmod>2026-08-16T16:04:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Manifold Mixupによる文字認識の改善（Manifold Mixup improves text recognition with CTC loss）</news:title>
   <news:publication_date>2026-08-16T16:04:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723875</loc>
  <lastmod>2026-08-16T15:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InceptionGCNによる疾病予測の新地平（InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction）</news:title>
   <news:publication_date>2026-08-16T15:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723873</loc>
  <lastmod>2026-08-16T15:13:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙マイクロ波背景放射のスペクトル歪みが切り拓く新たな観測窓（Spectral Distortions of the CMB as a Probe of Inflation, Recombination, Structure Formation and Particle Physics）</news:title>
   <news:publication_date>2026-08-16T15:13:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723871</loc>
  <lastmod>2026-08-16T15:12:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様な画像補完（Pluralistic Image Completion）</news:title>
   <news:publication_date>2026-08-16T15:12:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723869</loc>
  <lastmod>2026-08-16T15:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散深層学習によるマルチサイトCT血腫セグメンテーションの実務的示唆（Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury）</news:title>
   <news:publication_date>2026-08-16T15:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723867</loc>
  <lastmod>2026-08-16T15:11:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期的不整合と知識蒸留による単眼深度推定の改良（Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-08-16T15:11:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723865</loc>
  <lastmod>2026-08-16T15:11:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈性から推論へ――汎用近似器の推定フレームワーク（From interpretability to inference: an estimation framework for universal approximators）</news:title>
   <news:publication_date>2026-08-16T15:11:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723863</loc>
  <lastmod>2026-08-16T15:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二人の大統領を分ける確率的決闘（A probabilistic duel to distinguish two presidents）</news:title>
   <news:publication_date>2026-08-16T15:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723861</loc>
  <lastmod>2026-08-16T14:20:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>センター間で学習した滑らかさの事前分布による変分ベイズ脳組織セグメンテーション（A cross-center smoothness prior for variational Bayesian brain tissue segmentation）</news:title>
   <news:publication_date>2026-08-16T14:20:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723859</loc>
  <lastmod>2026-08-16T14:20:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代表性サンプリングによるミニバッチSGD高速化（Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling）</news:title>
   <news:publication_date>2026-08-16T14:20:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723857</loc>
  <lastmod>2026-08-16T14:19:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感覚皮質が示す「学びながら覚える」の因果的役割（A causal role of sensory cortices in behavioral benefits of &amp;#039;learning by doing&amp;#039;）</news:title>
   <news:publication_date>2026-08-16T14:19:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723855</loc>
  <lastmod>2026-08-16T14:19:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>訓練データの部分的シャッフルで言語モデルを改善する手法（Partially Shuffling the Training Data to Improve Language Models）</news:title>
   <news:publication_date>2026-08-16T14:19:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723853</loc>
  <lastmod>2026-08-16T14:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>十代が本物のサイバーセキュリティツールで学んだこと（Gathering Insights from Teenagers’ Hacking Experience with Authentic Cybersecurity Tools）</news:title>
   <news:publication_date>2026-08-16T14:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723851</loc>
  <lastmod>2026-08-16T14:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ分布駆動の自動回路近似法（Automated Circuit Approximation Method Driven by Data Distribution）</news:title>
   <news:publication_date>2026-08-16T14:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723849</loc>
  <lastmod>2026-08-16T14:18:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ基準学習による高速かつ高精度なニューラル中国語分かち書きの実装（Towards Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning）</news:title>
   <news:publication_date>2026-08-16T14:18:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723847</loc>
  <lastmod>2026-08-16T13:26:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アップリンク大規模MIMOにおける半ブラインドなチャネル・信号推定（Semi-Blind Channel-and-Signal Estimation for Uplink Massive MIMO With Channel Sparsity）</news:title>
   <news:publication_date>2026-08-16T13:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723845</loc>
  <lastmod>2026-08-16T13:25:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラジオとX線で探る宇宙の衝撃波─宇宙間ガスの可視化に向けた観測戦略（Detecting shocked intergalactic gas with X-ray and radio observations）</news:title>
   <news:publication_date>2026-08-16T13:25:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723843</loc>
  <lastmod>2026-08-16T13:25:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fisher-Bures型敵対的グラフ畳み込みネットワーク（Fisher-Bures Adversary Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-16T13:25:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723841</loc>
  <lastmod>2026-08-16T13:24:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語を2進数で表す新手法が変えたテキスト分類（An Innovative Word Encoding Method For Text Classification Using Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-16T13:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723839</loc>
  <lastmod>2026-08-16T13:24:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UCCA意味グラフを構成木へ変換する解析法（UCCA Graph Parsing as Constituent Tree Parsing）</news:title>
   <news:publication_date>2026-08-16T13:24:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723837</loc>
  <lastmod>2026-08-16T13:24:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルによる決定的予測と逆レンダリングへの応用（Deep Generative Models: Deterministic Prediction with an Application in Inverse Rendering）</news:title>
   <news:publication_date>2026-08-16T13:24:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723835</loc>
  <lastmod>2026-08-16T13:24:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Eコマースにおける個別広告効果の推定 (Estimating Individual Advertising Effect in E-Commerce)</news:title>
   <news:publication_date>2026-08-16T13:24:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723833</loc>
  <lastmod>2026-08-16T12:32:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークに対する敵対的攻撃は防げるか（Can Adversarial Network Attack be Defended?）</news:title>
   <news:publication_date>2026-08-16T12:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723831</loc>
  <lastmod>2026-08-16T12:31:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>干渉軽減による超高信頼・低遅延無線通信の実現（Interference Mitigation for Ultrareliable Low-Latency Wireless Communication）</news:title>
   <news:publication_date>2026-08-16T12:31:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723829</loc>
  <lastmod>2026-08-16T12:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>屋外・実世界での耳認証の実力を測る挑戦（The Unconstrained Ear Recognition Challenge 2019）</news:title>
   <news:publication_date>2026-08-16T12:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723827</loc>
  <lastmod>2026-08-16T12:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HetConvによる異種カーネル畳み込み（HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs）</news:title>
   <news:publication_date>2026-08-16T12:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723825</loc>
  <lastmod>2026-08-16T12:29:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門家の状態列を活用したハイブリッド強化学習（Hybrid Reinforcement Learning with Expert State Sequences）</news:title>
   <news:publication_date>2026-08-16T12:29:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723823</loc>
  <lastmod>2026-08-16T12:29:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>触覚で操るロボット操作（Manipulation by Feel: Touch-Based Control with Deep Predictive Models）</news:title>
   <news:publication_date>2026-08-16T12:29:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723821</loc>
  <lastmod>2026-08-16T12:28:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非並列データを用いた歌声変換の実践（SINGING VOICE CONVERSION WITH NON-PARALLEL DATA）</news:title>
   <news:publication_date>2026-08-16T12:28:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723819</loc>
  <lastmod>2026-08-16T11:37:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アライメントに基づくマッチングネットワークが開くワンショット分類とオープンセット認識の地平（ALIGNMENT BASED MATCHING NETWORKS FOR ONE-SHOT CLASSIFICATION AND OPEN-SET RECOGNITION）</news:title>
   <news:publication_date>2026-08-16T11:37:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723817</loc>
  <lastmod>2026-08-16T11:37:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二者零和ゲームにおけるエージェント合理性の大規模学習（Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games）</news:title>
   <news:publication_date>2026-08-16T11:37:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723815</loc>
  <lastmod>2026-08-16T11:36:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間認識型非局所注意機構によるファッションランドマーク検出（Spatial-Aware Non-Local Attention for Fashion Landmark Detection）</news:title>
   <news:publication_date>2026-08-16T11:36:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723813</loc>
  <lastmod>2026-08-16T11:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>資産価格付けにおける深層学習の実用革命（Deep Learning in Asset Pricing）</news:title>
   <news:publication_date>2026-08-16T11:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723811</loc>
  <lastmod>2026-08-16T11:36:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期宇宙の明るいクエーサーとその宿主銀河（The First Luminous Quasars and Their Host Galaxies）</news:title>
   <news:publication_date>2026-08-16T11:36:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723809</loc>
  <lastmod>2026-08-16T11:35:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OpenStreetMapを用いた走行環境理解の可用性の探究（Exploring OpenStreetMap Availability for Driving Environment Understanding）</news:title>
   <news:publication_date>2026-08-16T11:35:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723807</loc>
  <lastmod>2026-08-16T11:35:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共形シンプレクティックと相対論的最適化（Conformal Symplectic and Relativistic Optimization）</news:title>
   <news:publication_date>2026-08-16T11:35:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723805</loc>
  <lastmod>2026-08-16T10:44:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の重力波検出器グリッチを迅速に見つけ出す手法（Classifying the unknown: discovering novel gravitational-wave detector glitches using similarity learning）</news:title>
   <news:publication_date>2026-08-16T10:44:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723803</loc>
  <lastmod>2026-08-16T10:44:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチバンド観測が開くブラックホール連星研究の新局面（What We Can Learn From Multi-Band Observations of Black Hole Binaries）</news:title>
   <news:publication_date>2026-08-16T10:44:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723801</loc>
  <lastmod>2026-08-16T10:44:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>出力分布のずれを「距離」で測る：Sliced Wasserstein Discrepancyによるドメイン適応（Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-08-16T10:44:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723799</loc>
  <lastmod>2026-08-16T10:43:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間データにおける興味ある高密度領域の探索（Exploration of Interesting Dense Regions in Spatial Data）</news:title>
   <news:publication_date>2026-08-16T10:43:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723797</loc>
  <lastmod>2026-08-16T10:43:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>尤度なしMCMCを可能にする近似比推定器の実装と意義（Likelihood-free Markov chain Monte Carlo with Amortized Approximate Ratio Estimators）</news:title>
   <news:publication_date>2026-08-16T10:43:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723795</loc>
  <lastmod>2026-08-16T10:43:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一巡で高次元データを圧縮して学ぶ手法の要点と応用（One-Pass Sparsified Gaussian Mixtures）</news:title>
   <news:publication_date>2026-08-16T10:43:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723793</loc>
  <lastmod>2026-08-16T10:42:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚情報からロボット操作を学ぶ「Affordance」表現の実用化（Affordance Learning for End-to-End Visuomotor Robot Control）</news:title>
   <news:publication_date>2026-08-16T10:42:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723791</loc>
  <lastmod>2026-08-16T09:51:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一深度画像からの逐次ビュー補間による高精度3Dシーン補完（Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image）</news:title>
   <news:publication_date>2026-08-16T09:51:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723789</loc>
  <lastmod>2026-08-16T09:51:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なテンソル二重クラスタリングのアルゴリズム（Algorithms for an Efficient Tensor Biclustering）</news:title>
   <news:publication_date>2026-08-16T09:51:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723787</loc>
  <lastmod>2026-08-16T09:50:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>β3-IRTが変える評価の視点（β3-IRT: A New Item Response Model and its Applications）</news:title>
   <news:publication_date>2026-08-16T09:50:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723785</loc>
  <lastmod>2026-08-16T09:50:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な共謀フリー教授法（Optimal Collusion-Free Teaching）</news:title>
   <news:publication_date>2026-08-16T09:50:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723783</loc>
  <lastmod>2026-08-16T09:50:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載通信における深層学習ベースの資源割当方式 (A Deep Learning Based Resource Allocation Scheme in Vehicular Communication Systems)</news:title>
   <news:publication_date>2026-08-16T09:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723781</loc>
  <lastmod>2026-08-16T09:50:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多項分布ランダムフォレスト：一貫性とプライバシー保存への一歩（Multinomial Random Forest: Toward Consistency and Privacy-Preservation）</news:title>
   <news:publication_date>2026-08-16T09:50:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723779</loc>
  <lastmod>2026-08-16T09:49:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースの法線フィルタリングによるメッシュノイズ除去（NormalNet: Learning-based Normal Filtering for Mesh Denoising）</news:title>
   <news:publication_date>2026-08-16T09:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723777</loc>
  <lastmod>2026-08-16T08:58:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力不確実性を低次元で伝播させる実務的指針（Uncertainty Propagation in Deep Neural Network Using Active Subspace）</news:title>
   <news:publication_date>2026-08-16T08:58:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723775</loc>
  <lastmod>2026-08-16T08:58:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ化されたガウス過程のスケーラブル表現（Scalable Grouped Gaussian Processes via Direct Cholesky Functional Representations）</news:title>
   <news:publication_date>2026-08-16T08:58:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723773</loc>
  <lastmod>2026-08-16T08:57:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子診療録における固有表現認識：ルールベースと機械学習アプローチの比較（Named Entity Recognition for Electronic Health Records: A Comparison of Rule-based and Machine Learning Approaches）</news:title>
   <news:publication_date>2026-08-16T08:57:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723771</loc>
  <lastmod>2026-08-16T08:57:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限定角度CTのシノグラム補完手法（A Sinogram Inpainting Method based on Generative Adversarial Network for Limited-angle Computed Tomography）</news:title>
   <news:publication_date>2026-08-16T08:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723769</loc>
  <lastmod>2026-08-16T08:57:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相再構成を深めるDeep Griffin–Lim Iteration（DEEP GRIFFIN–LIM ITERATION）</news:title>
   <news:publication_date>2026-08-16T08:57:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723767</loc>
  <lastmod>2026-08-16T08:57:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングを使った位相制御とOAMビーム生成（Deep learning-based phase control method for coherent beam combining and its application in generating orbital angular momentum beams）</news:title>
   <news:publication_date>2026-08-16T08:57:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723765</loc>
  <lastmod>2026-08-16T08:56:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主観的視覚属性の深層ロバスト予測（Deep Robust Subjective Visual Property Prediction in Crowdsourcing）</news:title>
   <news:publication_date>2026-08-16T08:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723763</loc>
  <lastmod>2026-08-16T08:05:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Haar特徴に基づくカスケード分類器を用いた対象認識と追跡（Object recognition and tracking using Haar-like Features Cascade Classifiers: Application to a quad-rotor UAV）</news:title>
   <news:publication_date>2026-08-16T08:05:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723761</loc>
  <lastmod>2026-08-16T08:05:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内積操作による分散SGDの破壊（Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation）</news:title>
   <news:publication_date>2026-08-16T08:05:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723759</loc>
  <lastmod>2026-08-16T08:05:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepTagRec：コンテンツとユーザ関係を統合したタグ推薦フレームワーク（DeepTagRec: A Content-cum-User based Tag Recommendation Framework for Stack Overflow）</news:title>
   <news:publication_date>2026-08-16T08:05:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723757</loc>
  <lastmod>2026-08-16T08:04:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律ロボットにおける自己適応を可能にする機械学習と定量的プランニング（Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots）</news:title>
   <news:publication_date>2026-08-16T08:04:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723755</loc>
  <lastmod>2026-08-16T08:04:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膝MRIの自動セグメンテーション（Automated Segmentation of Knee MRI using Hierarchical Classifiers and Just Enough Interaction based Learning: Data from Osteoarthritis Initiative）</news:title>
   <news:publication_date>2026-08-16T08:04:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723753</loc>
  <lastmod>2026-08-16T08:04:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習に基づく3D/4D膝MRI領域分割の新手法（Learning-Based Cost Functions for 3D and 4D Multi-Surface Multi-Object Segmentation of Knee MRI）</news:title>
   <news:publication_date>2026-08-16T08:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723751</loc>
  <lastmod>2026-08-16T08:04:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期フェデレーテッド最適化の実践的意義（ASYNCHRONOUS FEDERATED OPTIMIZATION）</news:title>
   <news:publication_date>2026-08-16T08:04:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723749</loc>
  <lastmod>2026-08-16T07:13:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長方形バウンディング過程による効率的な空間分割（Rectangular Bounding Process）</news:title>
   <news:publication_date>2026-08-16T07:13:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723747</loc>
  <lastmod>2026-08-16T07:13:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Shape2Motionによる単一3D形状からの可動部解析（Shape2Motion: Joint Analysis of Motion Parts and Attributes from 3D Shapes）</news:title>
   <news:publication_date>2026-08-16T07:13:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723745</loc>
  <lastmod>2026-08-16T07:13:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバストな対数損失分類における公平性の統合（Fairness for Robust Log Loss Classification）</news:title>
   <news:publication_date>2026-08-16T07:13:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723743</loc>
  <lastmod>2026-08-16T07:12:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電磁過渡事象の原因同定のための時空間特徴学習（Cause Identification of Electromagnetic Transient Events using Spatiotemporal Feature Learning）</news:title>
   <news:publication_date>2026-08-16T07:12:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723741</loc>
  <lastmod>2026-08-16T07:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー2D/3D剛体位置合わせの実務的意義（Multiview 2D/3D Rigid Registration via a Point-Of-Interest Network for Tracking and Triangulation）</news:title>
   <news:publication_date>2026-08-16T07:12:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723739</loc>
  <lastmod>2026-08-16T07:12:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティクスを保つ敵対的攻撃（Semantics Preserving Adversarial Attacks）</news:title>
   <news:publication_date>2026-08-16T07:12:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723737</loc>
  <lastmod>2026-08-16T07:12:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダイナミックメッセージ表示が運転行動を変える仕組み（Comprehensive Analysis of Dynamic Message Sign Impact on Driver Behavior: A Random Forest Approach）</news:title>
   <news:publication_date>2026-08-16T07:12:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723735</loc>
  <lastmod>2026-08-16T06:20:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GNNExplainerによるグラフニューラルネットワークの説明生成（GNNExplainer: Generating Explanations for Graph Neural Networks）</news:title>
   <news:publication_date>2026-08-16T06:20:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723733</loc>
  <lastmod>2026-08-16T06:19:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNの構造とショートカットを同時に進化させるハイブリッドGA-PSO（A Hybrid GA-PSO Method for Evolving Architecture and Short Connections of Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-16T06:19:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723731</loc>
  <lastmod>2026-08-16T06:19:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負カーネルスパースコーディングによる動作データ分類（Non-Negative Kernel Sparse Coding for the Classification of Motion Data）</news:title>
   <news:publication_date>2026-08-16T06:19:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723729</loc>
  <lastmod>2026-08-16T06:18:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人は教えるか、ただ動くか――目的学習における人モデルの誤指定を問う（Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective Learning）</news:title>
   <news:publication_date>2026-08-16T06:18:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723727</loc>
  <lastmod>2026-08-16T06:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーンメモリトランスフォーマーによる長期タスクへの応用（Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks）</news:title>
   <news:publication_date>2026-08-16T06:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723725</loc>
  <lastmod>2026-08-16T06:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepPoolによるライドシェア最適化（DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-16T06:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723723</loc>
  <lastmod>2026-08-16T06:17:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像から高速に反射を抑える凸最適化手法（Fast Single Image Reflection Suppression via Convex Optimization）</news:title>
   <news:publication_date>2026-08-16T06:17:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723721</loc>
  <lastmod>2026-08-16T05:25:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多流（マルチストリーム）時系列データの先読みを可能にするFPCAベースの非パラメトリック手法（Functional Principal Component Analysis for Extrapolating Multi-stream Longitudinal Data）</news:title>
   <news:publication_date>2026-08-16T05:25:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723719</loc>
  <lastmod>2026-08-16T05:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量ガウス畳み込み過程を用いる共変モデルの変分推論（Variational Inference of Joint Models using Multivariate Gaussian Convolution Processes）</news:title>
   <news:publication_date>2026-08-16T05:25:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723717</loc>
  <lastmod>2026-08-16T05:25:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>日次電力取引におけるスプレッド密度推定と蓄電運用の最適化（Estimating Dynamic Conditional Spread Densities to Optimise Daily Storage Trading of Electricity）</news:title>
   <news:publication_date>2026-08-16T05:25:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723715</loc>
  <lastmod>2026-08-16T05:24:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BayesODによる物体検出の不確実性推定（BayesOD: A Bayesian Approach for Uncertainty Estimation in Deep Object Detectors）</news:title>
   <news:publication_date>2026-08-16T05:24:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T05:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>漸進的過剰緩和Q学習（Successive Over-Relaxation Q-Learning）</news:title>
   <news:publication_date>2026-08-16T04:32:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T04:32:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T04:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>直交結合によるワッサースタイン距離推定の改良（Orthogonal Estimation of Wasserstein Distances）</news:title>
   <news:publication_date>2026-08-16T04:31:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>情報理論的手法による汎化誤差の確率的上界の強化（Strengthened Information-theoretic Bounds on the Generalization Error）</news:title>
   <news:publication_date>2026-08-16T04:30:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T03:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T03:38:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T03:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T03:36:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T03:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T02:43:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T02:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T02:42:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T02:42:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723669</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>Stiefel上の制約付き勾配降下による量子グラフィカルモデルの学習 (Learning Quantum Graphical Models using Constrained Gradient Descent on the Stiefel Manifold)</news:title>
   <news:publication_date>2026-08-16T02:42:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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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>Skew-Fit：状態を網羅する自己監督型強化学習（Skew-Fit: State-Covering Self-Supervised Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-16T01:50:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723663</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>2026-08-16T01:42:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-16T01:41:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非コヒーレントMIMOの変調学習（Learning to Modulate for Non-coherent MIMO）</news:title>
   <news:publication_date>2026-08-16T01:41:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Learningを用いた2ウェイリレーネットワークの星座最適化（Deep Learning-Based Constellation Optimization for Physical Network Coding in Two-Way Relay Networks）</news:title>
   <news:publication_date>2026-08-16T01:41:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線からの年齢推定（Age prediction using a large chest X-ray dataset）</news:title>
   <news:publication_date>2026-08-16T01:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723655</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>NeuTra HMCによる悪いジオメトリの是正（NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport）</news:title>
   <news:publication_date>2026-08-16T01:40:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723653</loc>
  <lastmod>2026-08-16T01:40:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴フィードバックを持つ線形バンディット（Linear Bandits with Feature Feedback）</news:title>
   <news:publication_date>2026-08-16T01:40:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723651</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>画像のプライバシー予測を深層ニューラルネットワークで行う（Image Privacy Prediction Using Deep Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T00:48:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T00:48:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723645</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>2026-08-16T00:47:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/723641</loc>
  <lastmod>2026-08-16T00:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動するプライマリユーザ偽装攻撃の検出法（Primary User Emulation Attacks: A Detection Technique Based on Kalman Filter）</news:title>
   <news:publication_date>2026-08-16T00:47:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723639</loc>
  <lastmod>2026-08-16T00:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的雑音に強い生体認証の防御法（Robust Presentation Attack Detection through Unsupervised Adversarial Invariance）</news:title>
   <news:publication_date>2026-08-16T00:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723637</loc>
  <lastmod>2026-08-15T23:54:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模エネルギー収穫ネットワークのオンライン送信電力制御を深層学習で実現する（DEEP LEARNING BASED ONLINE POWER CONTROL FOR LARGE ENERGY HARVESTING NETWORKS）</news:title>
   <news:publication_date>2026-08-15T23:54:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723635</loc>
  <lastmod>2026-08-15T23:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星形成初期質量関数の変動が示す銀河進化への意味（Variations of the stellar Initial Mass Function in Semi-Analytic Models）</news:title>
   <news:publication_date>2026-08-15T23:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723633</loc>
  <lastmod>2026-08-15T23:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己対戦で学習する組合せ最適化エージェントの可能性（Learning Self-Game-Play Agents for Combinatorial Optimization Problems）</news:title>
   <news:publication_date>2026-08-15T23:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723631</loc>
  <lastmod>2026-08-15T23:53:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースJLによる特徴ハッシュの理解（Understanding Sparse JL for Feature Hashing）</news:title>
   <news:publication_date>2026-08-15T23:53:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723629</loc>
  <lastmod>2026-08-15T23:53:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠測データ下の正規化されないモデルに対するインピュテーション推定法（Imputation Estimators for Unnormalized Models with Missing Data）</news:title>
   <news:publication_date>2026-08-15T23:53:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723627</loc>
  <lastmod>2026-08-15T23:53:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転の頑健性と安全性を高める敵対的強化学習（Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-15T23:53:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723625</loc>
  <lastmod>2026-08-15T23:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RF給電バックスキャッタ通信における干渉回避ゲームの強化学習（Reinforcement Learning for Interference Avoidance Game in RF-Powered Backscatter Communications）</news:title>
   <news:publication_date>2026-08-15T23:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723623</loc>
  <lastmod>2026-08-15T23:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース変分ガウス過程回帰の収束速度に関する考察（Rates of Convergence for Sparse Variational Gaussian Process Regression）</news:title>
   <news:publication_date>2026-08-15T23:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723621</loc>
  <lastmod>2026-08-15T22:51:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的微分同相（位相保存）登録の教師なし学習（Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces）</news:title>
   <news:publication_date>2026-08-15T22:51:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723619</loc>
  <lastmod>2026-08-15T22:51:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>触覚で物体を識別する学習（Learning to Identify Object Instances by Touch: Tactile Recognition via Multimodal Matching）</news:title>
   <news:publication_date>2026-08-15T22:51:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723617</loc>
  <lastmod>2026-08-15T22:50:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2Dアイジンモデルの臨界温度推定を深層学習オートエンコーダで探る（The critical temperature of the 2D-Ising model through Deep Learning Autoencoders）</news:title>
   <news:publication_date>2026-08-15T22:50:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723615</loc>
  <lastmod>2026-08-15T22:50:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な深度推定のための2D畳み込みによるコストシグネチャ処理（Fast Deep Stereo with 2D Convolutional Processing of Cost Signatures）</news:title>
   <news:publication_date>2026-08-15T22:50:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723613</loc>
  <lastmod>2026-08-15T22:50:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誘導的転移によるニューラルアーキテクチャ最適化（Inductive Transfer for Neural Architecture Optimization）</news:title>
   <news:publication_date>2026-08-15T22:50:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723611</loc>
  <lastmod>2026-08-15T22:50:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い部分空間の変分推論による教師なしデータ補完（Unsupervised Data Imputation via Variational Inference of Deep Subspaces）</news:title>
   <news:publication_date>2026-08-15T22:50:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723609</loc>
  <lastmod>2026-08-15T21:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚情報と強化学習を組み合わせた皮膚診断支援の革新（Improving Skin Condition Classification with a Visual Symptom Checker Trained using Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-15T21:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723607</loc>
  <lastmod>2026-08-15T21:58:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三者対戦型GANによる難易度の高いサンプル生成と分類器強化（A Three-Player GAN: Generating Hard Samples To Improve Classification Networks）</news:title>
   <news:publication_date>2026-08-15T21:58:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723605</loc>
  <lastmod>2026-08-15T21:58:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GF-2高解像度衛星画像を用いたピクセルベースとオブジェクト指向分類の比較（Research on the pixel-based and object-oriented methods of urban feature extraction with GF-2 remote-sensing images）</news:title>
   <news:publication_date>2026-08-15T21:58:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723603</loc>
  <lastmod>2026-08-15T21:57:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深さはいつ効くのか――浅いモデルがある程度良ければ深さの利点は限定的か（Is Deeper Better only when Shallow is Good?）</news:title>
   <news:publication_date>2026-08-15T21:57:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723601</loc>
  <lastmod>2026-08-15T21:57:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱いラベルで路上景観セグメンテーションを強化する手法（On Boosting Semantic Street Scene Segmentation with Weak Supervision）</news:title>
   <news:publication_date>2026-08-15T21:57:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723599</loc>
  <lastmod>2026-08-15T21:57:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D複数物体生成の進化：Auto-Encoding Progressive GANs（Auto-Encoding Progressive Generative Adversarial Networks For 3D Multi Object Scenes）</news:title>
   <news:publication_date>2026-08-15T21:57:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723597</loc>
  <lastmod>2026-08-15T21:56:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デバイス・エッジ協調推論を高速化する2段階プルーニング（Improving Device-Edge Cooperative Inference of Deep Learning via 2-Step Pruning）</news:title>
   <news:publication_date>2026-08-15T21:56:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723595</loc>
  <lastmod>2026-08-15T21:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Support and Invertibility in Domain-Invariant Representations（Support and Invertibility in Domain-Invariant Representations）</news:title>
   <news:publication_date>2026-08-15T21:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723593</loc>
  <lastmod>2026-08-15T21:05:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳病変と解剖学の同時学習（Joint Learning of Brain Lesion and Anatomy Segmentation from Heterogeneous Datasets）</news:title>
   <news:publication_date>2026-08-15T21:05:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723591</loc>
  <lastmod>2026-08-15T21:05:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム行列を用いたワッサースタイン距離推定の改良（Random Matrix-Improved Estimation of the Wasserstein Distance between two Centered Gaussian Distributions）</news:title>
   <news:publication_date>2026-08-15T21:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723589</loc>
  <lastmod>2026-08-15T21:04:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量バイオメトリクスで再現するコード読解の認知指標（A Replication Study on Code Comprehension and Expertise using Lightweight Biometric Sensors）</news:title>
   <news:publication_date>2026-08-15T21:04:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723587</loc>
  <lastmod>2026-08-15T21:04:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実測データで学ぶ信号復調の深層学習（Deep Learning for Signal Demodulation in Physical Layer Wireless Communications: Prototype Platform, Open Dataset, and Analytics）</news:title>
   <news:publication_date>2026-08-15T21:04:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723585</loc>
  <lastmod>2026-08-15T21:04:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学イメージング装置の不確実性対応型性能評価（Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks）</news:title>
   <news:publication_date>2026-08-15T21:04:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723583</loc>
  <lastmod>2026-08-15T21:04:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLWeavingによるGLM高速化（Accelerating Generalized Linear Models with MLWeaving）</news:title>
   <news:publication_date>2026-08-15T21:04:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723581</loc>
  <lastmod>2026-08-15T20:13:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波動関数を幾何学で読み解く—2次元ターゲット空間からの一般化力学（On the geometrical hypotheses underlying wave functions and their emerging dynamics）</news:title>
   <news:publication_date>2026-08-15T20:13:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723579</loc>
  <lastmod>2026-08-15T20:13:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元イメージングバイオマーカーを用いた事象ベースモデルによる認知症の空間的進行推定（Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia）</news:title>
   <news:publication_date>2026-08-15T20:13:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723577</loc>
  <lastmod>2026-08-15T20:13:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中性子星データから状態方程式を推定する深層ニューラルネットワーク（Mapping neutron star data to the equation of state using the deep neural network）</news:title>
   <news:publication_date>2026-08-15T20:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723575</loc>
  <lastmod>2026-08-15T20:11:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lyapunov制約を用いた学習型制御器の設計フレームワーク（A framework of learning controller with Lyapunov-based constraint and application）</news:title>
   <news:publication_date>2026-08-15T20:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723573</loc>
  <lastmod>2026-08-15T20:11:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声駆動ジェスチャ生成の入出力表現解析 (Analyzing Input and Output Representations for Speech-Driven Gesture Generation)</news:title>
   <news:publication_date>2026-08-15T20:11:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723571</loc>
  <lastmod>2026-08-15T20:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接最適化問題に深層学習を当てる—駐車違反巡回の近似手法（Approximating Optimisation Solutions for Travelling Officer Problem with Customised Deep Learning Network）</news:title>
   <news:publication_date>2026-08-15T20:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T20:11:28Z</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>2026-08-15T20:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723567</loc>
  <lastmod>2026-08-15T19:19:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素値ゲーテッドオートエンコーダによる映像予測（Complex Valued Gated Auto-encoder for Video Frame Prediction）</news:title>
   <news:publication_date>2026-08-15T19:19:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723565</loc>
  <lastmod>2026-08-15T19:09:33Z</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>2026-08-15T19:09:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T19:09:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T19:08:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模グラフ上でのヒューリスティクス学習（Learning Heuristics over Large Graphs via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-15T19:08:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>知識を埋め込むルーティングでシーングラフ生成を強化する手法（Knowledge-Embedded Routing Network for Scene Graph Generation）</news:title>
   <news:publication_date>2026-08-15T19:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T19:08:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T19:08:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Small Data時代におけるファジィ分類器は不要か（Do we still need fuzzy classifiers for Small Data in the Era of Big Data?）</news:title>
   <news:publication_date>2026-08-15T19:07:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T18:16:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723551</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>証明可能なテンソルリング補完（Provable Tensor Ring Completion）</news:title>
   <news:publication_date>2026-08-15T18:15:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/723549</loc>
  <lastmod>2026-08-15T18:15:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T18:15:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T18:14:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T18:14:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>骨格軌跡に学習される規則性による映像異常検知（Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos）</news:title>
   <news:publication_date>2026-08-15T18:13:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T18:13:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習者の「混乱」を言語で特定する手法（An Identification of Learners’ Confusion through Language and Discourse Analysis）</news:title>
   <news:publication_date>2026-08-15T17:22:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T17:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T17:21:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T17:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T17:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T17:20:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723529</loc>
  <lastmod>2026-08-15T17:20:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723527</loc>
  <lastmod>2026-08-15T17:20:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T17:20:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T16:28:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>触覚ユーザインタフェースと実践学習による低侵襲手術トレーニング（Haptic User Interfaces and Practice-based Learning for Minimally Invasive Surgical Training）</news:title>
   <news:publication_date>2026-08-15T16:28:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T16:27:00Z</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>2026-08-15T16:27:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T16:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723517</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:publication_date>2026-08-15T16:26:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723515</loc>
  <lastmod>2026-08-15T16:26:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T16:26:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T16:25:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T15:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要領域を学習して効率的な経路計画を実現する（Learn and Link: Learning Critical Regions for Efficient Planning）</news:title>
   <news:publication_date>2026-08-15T15:34:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T15:32:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T14:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T14:38:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>協調エージェントの階層的教育方策学習（Learning Hierarchical Teaching Policies for Cooperative Agents）</news:title>
   <news:publication_date>2026-08-15T14:37:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T14:37:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T14:37:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴のホワイトニングと合意損失による非教師ありドメイン適応（Unsupervised Domain Adaptation using Feature-Whitening and Consensus Loss）</news:title>
   <news:publication_date>2026-08-15T13:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T13:45:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>帯域制約環境における協働ロボット探査のためのストリーミングシーンマップ（Streaming Scene Maps for Co-Robotic Exploration in Bandwidth Limited Environments）</news:title>
   <news:publication_date>2026-08-15T13:45:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723479</loc>
  <lastmod>2026-08-15T13:44:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多ホット圧縮ネットワーク埋め込み（Multi-Hot Compact Network Embedding）</news:title>
   <news:publication_date>2026-08-15T13:44:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T13:43:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723475</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>ENIGMA-NG：定理証明におけるニューラル＋勾配ブースト導入の実用化（ENIGMA-NG: Efficient Neural and Gradient-Boosted Inference Guidance for E⋆）</news:title>
   <news:publication_date>2026-08-15T13:43:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723473</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>2026-08-15T13:43:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T13:42:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723469</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>マルチタスク学習に基づく開かれた集合認識（Deep CNN-based Multi-task Learning for Open-Set Recognition）</news:title>
   <news:publication_date>2026-08-15T12:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723467</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>CLEVR-Dialogによる視覚対話の多段階推論評価の設計（CLEVR-Dialog: A Diagnostic Dataset for Multi-Round Reasoning in Visual Dialog）</news:title>
   <news:publication_date>2026-08-15T12:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723465</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>2026-08-15T12:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723463</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>2026-08-15T12:42:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723461</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>2026-08-15T12:41:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723459</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>2026-08-15T12:41:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723457</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>2026-08-15T12:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723455</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>2026-08-15T11:49:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723453</loc>
  <lastmod>2026-08-15T11:41:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>賢いアルゴリズムはハードウェア加速より有効か（SLIDE: In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems）</news:title>
   <news:publication_date>2026-08-15T11:41:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723451</loc>
  <lastmod>2026-08-15T11:41:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T11:40:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723447</loc>
  <lastmod>2026-08-15T11:40:00Z</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>2026-08-15T11:40:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723445</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>2026-08-15T11:39:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T11:39:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>META-DATASET：少数例学習のためのデータセット群と新ベンチマーク（META-DATASET: A Dataset of Datasets for Learning to Learn from Few Examples）</news:title>
   <news:publication_date>2026-08-15T11:39:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T10:48:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723439</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>2026-08-15T10:47:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723437</loc>
  <lastmod>2026-08-15T10:47:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン特化の短文から自動で語彙体系を作る技術（Automatic Ontology Learning from Domain-Specific Short Unstructured Text Data）</news:title>
   <news:publication_date>2026-08-15T10:47:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T10:47:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T10:47:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Qiskitによる量子アルゴリズム入門（Introduction to Coding Quantum Algorithms: A Tutorial Series Using Qiskit）</news:title>
   <news:publication_date>2026-08-15T10:47:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T10:46:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/723283</loc>
  <lastmod>2026-08-15T00:32:28Z</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>2026-08-15T00:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723281</loc>
  <lastmod>2026-08-15T00:31:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズのある感染カスケードからのグラフ学習（Learning Graphs from Noisy Epidemic Cascades）</news:title>
   <news:publication_date>2026-08-15T00:31:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723279</loc>
  <lastmod>2026-08-15T00:31:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習のための世界モデルと疑似リハーサル（Continual Learning Using World Models for Pseudo-Rehearsal）</news:title>
   <news:publication_date>2026-08-15T00:31:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723277</loc>
  <lastmod>2026-08-15T00:30:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>成長グラフのための生成グラフ畳み込みネットワーク（Generative Graph Convolutional Network for Growing Graphs）</news:title>
   <news:publication_date>2026-08-15T00:30:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723275</loc>
  <lastmod>2026-08-15T00:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字レベルのテキスト正規化と因果的エンコーダ（A Character-Level Approach to the Text Normalization Problem Based on a New Causal Encoder）</news:title>
   <news:publication_date>2026-08-15T00:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723273</loc>
  <lastmod>2026-08-14T23:38:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IMEXnet – 順伝播で安定な深層ニューラルネットワーク（IMEXnet - A Forward Stable Deep Neural Network）</news:title>
   <news:publication_date>2026-08-14T23:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723271</loc>
  <lastmod>2026-08-14T23:38:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的自己回帰画像モデルと補助デコーダ（Hierarchical Autoregressive Image Models with Auxiliary Decoders）</news:title>
   <news:publication_date>2026-08-14T23:38:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723269</loc>
  <lastmod>2026-08-14T23:37:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Random Splinesによる点過程強度推定（Deep Random Splines for Point Process Intensity Estimation of Neural Population Data）</news:title>
   <news:publication_date>2026-08-14T23:37:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723267</loc>
  <lastmod>2026-08-14T23:36:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散オンライン凸最適化と時間変動結合不等式制約（Distributed Online Convex Optimization with Time-Varying Coupled Inequality Constraints）</news:title>
   <news:publication_date>2026-08-14T23:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723265</loc>
  <lastmod>2026-08-14T23:36:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BatchNormが学習を安定化する仕組みを読み解く（MEAN-FIELD ANALYSIS OF BATCH NORMALIZATION）</news:title>
   <news:publication_date>2026-08-14T23:36:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723263</loc>
  <lastmod>2026-08-14T23:36:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きGANによる油彩画生成（Conditional GANs For Painting Generation）</news:title>
   <news:publication_date>2026-08-14T23:36:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723261</loc>
  <lastmod>2026-08-14T23:35:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Buddy CompressionによるGPUメモリ拡張の実務的意義（Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs）</news:title>
   <news:publication_date>2026-08-14T23:35:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723259</loc>
  <lastmod>2026-08-14T22:44:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化型深層再帰的デノイジング自己符号化器による重力波信号の復元（Denoising Gravitational Waves with Enhanced Deep Recurrent Denoising Auto-Encoders）</news:title>
   <news:publication_date>2026-08-14T22:44:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723257</loc>
  <lastmod>2026-08-14T22:35:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>永続的学習下の文埋め込み整合が変える関係抽出の実務応用（Sentence Embedding Alignment for Lifelong Relation Extraction）</news:title>
   <news:publication_date>2026-08-14T22:35:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723255</loc>
  <lastmod>2026-08-14T22:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GanDef：GANベースの敵対的訓練防御（GanDef: A GAN based Adversarial Training Defense）</news:title>
   <news:publication_date>2026-08-14T22:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723253</loc>
  <lastmod>2026-08-14T22:33:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tactical Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation（Tactical Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation）</news:title>
   <news:publication_date>2026-08-14T22:33:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723251</loc>
  <lastmod>2026-08-14T22:33:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超新星スペクトル自動分類の深層学習（DASH: Deep Learning for the Automated Spectral Classification of Supernovae and their Hosts）</news:title>
   <news:publication_date>2026-08-14T22:33:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723249</loc>
  <lastmod>2026-08-14T22:33:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QCD因子分解のための機械学習テンプレート（Machine Learning Templates for QCD Factorization in the Search for Physics Beyond the Standard Model）</news:title>
   <news:publication_date>2026-08-14T22:33:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723247</loc>
  <lastmod>2026-08-14T22:32:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事後選択（ポストセレクション）による量子メトロロジーの優位性（Quantum Advantage in Postselected Metrology）</news:title>
   <news:publication_date>2026-08-14T22:32:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723245</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>Xbox Oneのデジタルフォレンジクス解析（Forensics Analysis of Xbox One Game Console）</news:title>
   <news:publication_date>2026-08-14T21:41:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723243</loc>
  <lastmod>2026-08-14T21:41:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列予測のための自己回帰畳み込み再帰ニューラルネットワーク（Autoregressive Convolutional Recurrent Neural Network）</news:title>
   <news:publication_date>2026-08-14T21:41:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723241</loc>
  <lastmod>2026-08-14T21:40:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係プーリングによるグラフ表現の強化（Relational Pooling for Graph Representations）</news:title>
   <news:publication_date>2026-08-14T21:40:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723239</loc>
  <lastmod>2026-08-14T21:40:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GRUNGE: 大規模な統一自動定理証明ベンチマーク（GRUNGE: A Grand Unified ATP Challenge）</news:title>
   <news:publication_date>2026-08-14T21:40:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723237</loc>
  <lastmod>2026-08-14T21:39:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全指向の深層強化学習：オンラインGaussian Process推定による探索ガイド（SAFETY-GUIDED DEEP REINFORCEMENT LEARNING VIA ONLINE GAUSSIAN PROCESS ESTIMATION）</news:title>
   <news:publication_date>2026-08-14T21:39:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723235</loc>
  <lastmod>2026-08-14T21:39:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知環境での視覚ナビゲーションにおける最適制御と学習の統合（Combining Optimal Control and Learning for Visual Navigation in Novel Environments）</news:title>
   <news:publication_date>2026-08-14T21:39:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723233</loc>
  <lastmod>2026-08-14T21:39:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデモから学ぶ人間行動のマルチモーダル表現（Learning multimodal representations for sample-efficient recognition of human actions）</news:title>
   <news:publication_date>2026-08-14T21:39:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723231</loc>
  <lastmod>2026-08-14T20:47:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層視覚顕著性モデルの理解と可視化（Understanding and Visualizing Deep Visual Saliency Models）</news:title>
   <news:publication_date>2026-08-14T20:47:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723229</loc>
  <lastmod>2026-08-14T20:47:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり注意アラインメントによる画像キャプション生成（Image captioning with weakly-supervised attention penalty）</news:title>
   <news:publication_date>2026-08-14T20:47:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723227</loc>
  <lastmod>2026-08-14T20:47:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D MRIからの前立腺セグメンテーション（Prostate Segmentation from 3D MRI using a Two-Stage Model and Variable-Input Based Uncertainty Measure）</news:title>
   <news:publication_date>2026-08-14T20:47:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723225</loc>
  <lastmod>2026-08-14T20:46:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像改ざん検出のハイブリッドLSTMとエンコーダ・デコーダ（Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries）</news:title>
   <news:publication_date>2026-08-14T20:46:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723223</loc>
  <lastmod>2026-08-14T20:46:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非微分モデルのための低レベル一次確率プログラミング言語（LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models）</news:title>
   <news:publication_date>2026-08-14T20:46:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723221</loc>
  <lastmod>2026-08-14T20:46:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一発で掴むための視覚——GQ-STNによるワンショット把持検出（GQ-STN: Optimizing One-Shot Grasp Detection based on Robustness Classifier）</news:title>
   <news:publication_date>2026-08-14T20:46:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723219</loc>
  <lastmod>2026-08-14T20:45:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キャビティ冷却による反強磁性マグノン間エンタングルメントの増強（Enhancement of antiferromagnetic magnon-magnon entanglement by cavity cooling）</news:title>
   <news:publication_date>2026-08-14T20:45:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723217</loc>
  <lastmod>2026-08-14T19:53:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KBQA: QAコーパスと知識ベースから学ぶ質問応答（KBQA: Learning Question Answering over QA Corpora and Knowledge Bases）</news:title>
   <news:publication_date>2026-08-14T19:53:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-14T19:45:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>標準コーダによるコーディング工数の定量化（The standard coder: a machine learning approach to measuring the effort required to produce source code change）</news:title>
   <news:publication_date>2026-08-14T19:45:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-14T19:45:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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