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   <news:title>3D点対応の深層登録を同時に解く3DRegNet（3DRegNet: A Deep Neural Network for 3D Point Registration）</news:title>
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   <news:title>マルチグリッド予測フィルタフローによる教師なし動画学習（Multigrid Predictive Filter Flow for Unsupervised Learning on Videos）</news:title>
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   <news:title>地下区間でのスマートフォン位置推定（SubwayPS: Towards Smartphone Positioning in Underground Public Transportation Systems）</news:title>
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   <news:title>拡張ニューラル常微分方程式（Augmented Neural ODEs）</news:title>
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   <news:title>単眼3D物体検出と形状再構築の統合（Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstruction）</news:title>
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   <news:title>うつ病の言語的・非言語的信号を統合して推定する手法（The Verbal and Non Verbal Signals of Depression - Combining Acoustics, Text and Visuals for Estimating Depression Level）</news:title>
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   <news:title>Mizarを加速する学習による節（clause）誘導（Hammering Mizar by Learning Clause Guidance）</news:title>
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    <news:language>ja</news:language>
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   <news:title>ラウタム正則化による半教師付き転移学習（Lautum Regularization for Semi-supervised Transfer 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>無病胸部X線を安全にふるい分ける深層転移学習（Identifying disease-free chest X-ray images with deep transfer learning）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>行動駆動型弱教師あり物体検出（Activity Driven Weakly Supervised Object Detection）</news:title>
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    <news:language>ja</news:language>
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   <news:title>MVX-Net: マルチモーダルVoxelNetによる3D物体検出の先駆け（MVX-Net: Multimodal VoxelNet for 3D Object Detection）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>ジャンプ回帰の逐次適応設計（Sequential Adaptive Design for Jump Regression Estimation）</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>医用画像におけるドメイン適応と一般化の強力なベースライン（A Strong Baseline for Domain Adaptation and Generalization in Medical Imaging）</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>異種ゲノムデータから臨床転帰を学習する（Learning Clinical Outcomes from Heterogeneous Genomic Data Sources）</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>主観的構成要素の回帰ラベル生成におけるトリプレット埋め込み（Generating Labels for Regression of Subjective Constructs using Triplet Embeddings）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>注釈（アノテーション）効率を高める画像間変換による半教師ありセグメンテーション（Towards annotation-efficient segmentation via image-to-image translation）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>System Level Synthesis（System Level Synthesis）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>吸収線変動と連続光変化の関係：イオン化変化が駆動するBAL準星の吸収線変動（Ionization driven intrinsic absorption line variability of BAL quasars in the Stripe 82 region）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-25T12:37:07Z</lastmod>
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    <news:language>ja</news:language>
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   <news:title>100万時間の音声データで学んだこと（LESSONS FROM BUILDING ACOUSTIC MODELS WITH A MILLION HOURS OF SPEECH）</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>注意深い模倣による単語埋め込みの改善（Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts）</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>原子スケール表現とテンソル性質の統計学習（Atomic-scale representation and statistical learning of tensorial properties）</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>人体部位学習に向けたモデルフリー歩容認識（TOWARDS HUMAN BODY-PART LEARNING FOR MODEL-FREE GAIT RECOGNITION）</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>高赤方偏移銀河の存在量予測とファジィ暗黒物質の検証（Predictions for the Abundance of High-redshift Galaxies in a Fuzzy Dark Matter Universe）</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>生成-識別補完学習（Generative-Discriminative Complementary Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/727080</loc>
  <lastmod>2026-08-25T11:44:06Z</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>パルケス観測による銀河のH I質量関数の洞察（The H I mass function in the Parkes H I Zone of Avoidance survey）</news:title>
   <news:publication_date>2026-08-25T11:44:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>原始技能の学習と一般化――堅牢な二腕マニピュレーションに向けて（Learning and Generalisation of Primitive Skills: Towards Robust Dual-arm Manipulation）</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>α星Aの中心核の性質：金属量組成が及ぼす影響（On the nature of the core of α Centauri A: the impact of the metallicity mixture）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ランダム配線ニューラルネットワークの画像認識への応用（Exploring Randomly Wired Neural Networks for Image Recognition）</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>学習した分子表現による性質予測の解析（Analyzing Learned Molecular Representations for Property Prediction）</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>
   </news:publication>
   <news:title>ニューラル論理ネットワークによる学習アルゴリズム（Learning Algorithms via Neural Logic Networks）</news:title>
   <news:publication_date>2026-08-25T10:51:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727068</loc>
  <lastmod>2026-08-25T10:42:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルモデルの数学的推論能力の分析（Analysing Mathematical Reasoning Abilities of Neural Models）</news:title>
   <news:publication_date>2026-08-25T10:42:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727066</loc>
  <lastmod>2026-08-25T10:42:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク侵入検知のための能動学習（Active Learning for Network Intrusion Detection）</news:title>
   <news:publication_date>2026-08-25T10:42:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727064</loc>
  <lastmod>2026-08-25T10:41:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Weisfeiler-Lemanの高次表現をスケーラブルにする手法（Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings）</news:title>
   <news:publication_date>2026-08-25T10:41:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727062</loc>
  <lastmod>2026-08-25T10:41:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小規模データ向けのエンドツーエンド視覚音声認識（End-to-End Visual Speech Recognition for Small-Scale Datasets）</news:title>
   <news:publication_date>2026-08-25T10:41:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727060</loc>
  <lastmod>2026-08-25T10:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声のノイズ除去を変えるパラメトリック再合成（SPEECH DENOISING BY PARAMETRIC RESYNTHESIS）</news:title>
   <news:publication_date>2026-08-25T10:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727058</loc>
  <lastmod>2026-08-25T10:40:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語誘発EEGデータの理解：ファインチューンした言語モデルで予測する（Understanding language-elicited EEG data by predicting it from a fine-tuned language model）</news:title>
   <news:publication_date>2026-08-25T10:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727056</loc>
  <lastmod>2026-08-25T09:49:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸目的関数に対する確率的勾配降下法の収束速度（Convergence rates for the stochastic gradient descent method for non-convex objective functions）</news:title>
   <news:publication_date>2026-08-25T09:49:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727054</loc>
  <lastmod>2026-08-25T09:48:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動によるパラメータ化偏微分方程式の近似（Data driven approximation of parametrized PDEs by Reduced Basis and Neural Networks）</news:title>
   <news:publication_date>2026-08-25T09:48:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727052</loc>
  <lastmod>2026-08-25T09:48:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FEAFA: 顔表情分析と3D顔アニメーションのための高精度注釈データセット（FEAFA: A Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animation）</news:title>
   <news:publication_date>2026-08-25T09:48:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727050</loc>
  <lastmod>2026-08-25T09:47:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Synthetic Learner による時系列処置効果の推定（Synthetic learner: Model-Free Inference on Treatments over Time）</news:title>
   <news:publication_date>2026-08-25T09:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727048</loc>
  <lastmod>2026-08-25T09:47:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動による意味空間導出の有効性（Effectiveness of Data-Driven Induction of Semantic Spaces）</news:title>
   <news:publication_date>2026-08-25T09:47:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727046</loc>
  <lastmod>2026-08-25T09:46:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガイド付き超解像をピクセル対ピクセル変換として考える（Guided Super-Resolution as Pixel-to-Pixel Transformation）</news:title>
   <news:publication_date>2026-08-25T09:46:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727044</loc>
  <lastmod>2026-08-25T09:46:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語ベクトル空間の概念可視化（Neural Vector Conceptualization for Word Vector Space Interpretation）</news:title>
   <news:publication_date>2026-08-25T09:46:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727042</loc>
  <lastmod>2026-08-25T08:54:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定量位相顕微鏡によるがん細胞の空間署名（Quantitative Phase Microscopy Spatial Signatures of Cancer Cells）</news:title>
   <news:publication_date>2026-08-25T08:54:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727040</loc>
  <lastmod>2026-08-25T08:46:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で位相転移を解き明かす（Unveiling phase transitions with machine learning）</news:title>
   <news:publication_date>2026-08-25T08:46:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727038</loc>
  <lastmod>2026-08-25T08:45:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストからリアルな画像を作るための意味分離（Semantics Disentangling for Text-to-Image Generation）</news:title>
   <news:publication_date>2026-08-25T08:45:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727036</loc>
  <lastmod>2026-08-25T08:45:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー応答予測のための操作認識ニューラルネットワーク（Operation-aware Neural Networks for User Response Prediction）</news:title>
   <news:publication_date>2026-08-25T08:45:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727034</loc>
  <lastmod>2026-08-25T08:44:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BCMA-ES IIの再検討（BCMA-ES II: revisiting Bayesian CMA-ES）</news:title>
   <news:publication_date>2026-08-25T08:44:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727032</loc>
  <lastmod>2026-08-25T08:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク指向チャネル状態情報の量子化（Task Oriented Channel State Information Quantization）</news:title>
   <news:publication_date>2026-08-25T08:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727030</loc>
  <lastmod>2026-08-25T08:43:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈依存ニューラル原形復元のための訓練データ拡張（Training Data Augmentation for Context-Sensitive Neural Lemmatization Using Inflection Tables and Raw Text）</news:title>
   <news:publication_date>2026-08-25T08:43:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727028</loc>
  <lastmod>2026-08-25T07:52:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆引き辞書のための多義語ベクトル埋め込みの活用（Using Multi-Sense Vector Embeddings for Reverse Dictionaries）</news:title>
   <news:publication_date>2026-08-25T07:52:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727026</loc>
  <lastmod>2026-08-25T07:51:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチアームド・バンディットの実務応用サーベイ（A Survey on Practical Applications of Multi-Armed and Contextual Bandits）</news:title>
   <news:publication_date>2026-08-25T07:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727024</loc>
  <lastmod>2026-08-25T07:51:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非剛体点群整合の学習的アプローチ（Non-Rigid Point Set Registration Networks）</news:title>
   <news:publication_date>2026-08-25T07:51:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727022</loc>
  <lastmod>2026-08-25T07:50:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈と属性に基づく密なキャプショニング（Context and Attribute Grounded Dense Captioning）</news:title>
   <news:publication_date>2026-08-25T07:50:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727020</loc>
  <lastmod>2026-08-25T07:50:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス・属性・カテゴリの協調埋め込みによる画像検索（Cooperative Embeddings for Instance, Attribute and Category Retrieval）</news:title>
   <news:publication_date>2026-08-25T07:50:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727018</loc>
  <lastmod>2026-08-25T07:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BCMA-ESのベイズ的再解釈が示す最適化戦略の本質（BCMA-ES: A Bayesian approach to CMA-ES）</news:title>
   <news:publication_date>2026-08-25T07:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727016</loc>
  <lastmod>2026-08-25T07:49:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠縁の楕円銀河で起きたType II超新星の謎（SN 2016hil – A TYPE II SUPERNOVA IN THE REMOTE OUTSKIRTS OF AN ELLIPTICAL HOST AND ITS ORIGIN）</news:title>
   <news:publication_date>2026-08-25T07:49:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727014</loc>
  <lastmod>2026-08-25T06:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの活性化空間の幾何構造（On Geometric Structure of Activation Spaces in Neural Networks）</news:title>
   <news:publication_date>2026-08-25T06:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727012</loc>
  <lastmod>2026-08-25T06:58:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>橋梁コンクリート欠陥のためのメタ学習によるCNN設計（Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the CODEBRIM Dataset）</news:title>
   <news:publication_date>2026-08-25T06:58:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727010</loc>
  <lastmod>2026-08-25T06:58:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレベル空間プーリング特徴による美的評価の高精度化（Effective Aesthetics Prediction with Multi-level Spatially Pooled Features）</news:title>
   <news:publication_date>2026-08-25T06:58:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727008</loc>
  <lastmod>2026-08-25T06:56:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベリングを越えて：クラスタリングでマルウェアファミリーのネットワーク行動プロファイルを構築する（Beyond Labeling: Using Clustering to Build Network Behavioral Profiles of Malware Families）</news:title>
   <news:publication_date>2026-08-25T06:56:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727006</loc>
  <lastmod>2026-08-25T06:56:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResNetがなぜ効くのか（Why ResNet Works? Residuals Generalize）</news:title>
   <news:publication_date>2026-08-25T06:56:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727004</loc>
  <lastmod>2026-08-25T06:56:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン内構造を活用した容易な転移学習（EASY TRANSFER LEARNING BY EXPLOITING INTRA-DOMAIN STRUCTURES）</news:title>
   <news:publication_date>2026-08-25T06:56:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727002</loc>
  <lastmod>2026-08-25T06:56:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>赤方偏移z≈4星形成銀河の紫外線スペクトル傾斜βと恒星集団（The UV spectral slope beta and stellar population of most active star-forming galaxies at z∼4）</news:title>
   <news:publication_date>2026-08-25T06:56:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/727000</loc>
  <lastmod>2026-08-25T06:04:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしニューラルマスクビームフォーミングの訓練（Unsupervised training of neural mask-based beamforming）</news:title>
   <news:publication_date>2026-08-25T06:04:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726998</loc>
  <lastmod>2026-08-25T06:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像文脈でテキスト内部の表現を助ける手法（Aiding Intra-Text Representations with Visual Context for Multimodal Named Entity Recognition）</news:title>
   <news:publication_date>2026-08-25T06:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726996</loc>
  <lastmod>2026-08-25T06:04:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジを残す画像平滑化のベンチマーク（A Benchmark for Edge-Preserving Image Smoothing）</news:title>
   <news:publication_date>2026-08-25T06:04:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726994</loc>
  <lastmod>2026-08-25T06:03:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル情報を活かしたクラスベースのドメイン適応手法（Looking back at Labels: A Class based Domain Adaptation Technique）</news:title>
   <news:publication_date>2026-08-25T06:03:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726992</loc>
  <lastmod>2026-08-25T06:03:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴選択とアンサンブル分類器に基づく効率的侵入検知システムの構築（Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier）</news:title>
   <news:publication_date>2026-08-25T06:03:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726990</loc>
  <lastmod>2026-08-25T06:03:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホログラフィック・インフレーションの提案（Holographic Inflation）</news:title>
   <news:publication_date>2026-08-25T06:03:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726988</loc>
  <lastmod>2026-08-25T06:03:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河団のSZEスケーリングとIa型超新星による距離双対性検証（Galaxy cluster Sunyaev-Zel&amp;#039;dovich effect scaling-relation and type Ia supernova observations as a test for the cosmic distance duality relation）</news:title>
   <news:publication_date>2026-08-25T06:03:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726986</loc>
  <lastmod>2026-08-25T05:12:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層ごとの相関を用いたニューラルネットワークの不確実性評価（Correlated Parameters to Accurately Measure Uncertainty in Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-25T05:12:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726984</loc>
  <lastmod>2026-08-25T05:11:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点注釈のみで群衆内の検出とカウントを同時に行う手法（Point in, Box out: Beyond Counting Persons in Crowds）</news:title>
   <news:publication_date>2026-08-25T05:11:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726982</loc>
  <lastmod>2026-08-25T05:11:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無監視人物再識別のための条件付き敵対的ネットワーク（CANU-ReID: A Conditional Adversarial Network for Unsupervised person Re-Identification）</news:title>
   <news:publication_date>2026-08-25T05:11:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726980</loc>
  <lastmod>2026-08-25T05:10:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HoloGANが切り拓く「2D画像からの3D理解」の自動化（HoloGAN: Unsupervised Learning of 3D Representations From Natural Images）</news:title>
   <news:publication_date>2026-08-25T05:10:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726978</loc>
  <lastmod>2026-08-25T05:10:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークを用いた変分強化サンプリング（NEURAL NETWORKS BASED VARIATIONALLY ENHANCED SAMPLING）</news:title>
   <news:publication_date>2026-08-25T05:10:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726976</loc>
  <lastmod>2026-08-25T05:10:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からの3次元姿勢推定を生成と序列で解く（Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking）</news:title>
   <news:publication_date>2026-08-25T05:10:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726974</loc>
  <lastmod>2026-08-25T04:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実用的に情報量を高めるテキスト生成（Pragmatically Informative Text Generation）</news:title>
   <news:publication_date>2026-08-25T04:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726972</loc>
  <lastmod>2026-08-25T04:18:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球状閉じ込めH+2の基底状態と励起状態の振る舞い（Spherically confined H+2: 2Σ+g and 2Σ+u states）</news:title>
   <news:publication_date>2026-08-25T04:18:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726970</loc>
  <lastmod>2026-08-25T04:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィードバック駆動の布ストリップ折り畳み（Feedback-based Fabric Strip Folding）</news:title>
   <news:publication_date>2026-08-25T04:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726968</loc>
  <lastmod>2026-08-25T04:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスター環境における厚いディスクの起源（The Fornax 3D project: Thick disks in a cluster environment）</news:title>
   <news:publication_date>2026-08-25T04:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726966</loc>
  <lastmod>2026-08-25T04:17:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンセット話者識別における識別型ニューラルネットワークの検証（Experiments on Open-Set Speaker Identification with Discriminatively Trained Neural Networks）</news:title>
   <news:publication_date>2026-08-25T04:17:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726964</loc>
  <lastmod>2026-08-25T04:17:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PCA風オートエンコーダ（A PCA-LIKE AUTOENCODER）</news:title>
   <news:publication_date>2026-08-25T04:17:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726962</loc>
  <lastmod>2026-08-25T04:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Reinforcement Learningによるパーティショニングアドバイザの学習（Learning a Partitioning Advisor with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-25T04:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726960</loc>
  <lastmod>2026-08-25T03:25:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層メトリック学習に基づくハッシュネットワークによるリモートセンシング画像検索（Metric-Learning based Deep Hashing Network for Content Based Retrieval of Remote Sensing Images）</news:title>
   <news:publication_date>2026-08-25T03:25:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726958</loc>
  <lastmod>2026-08-25T03:25:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中心線深度に基づく強化学習による左心耳開口部局在化（Centerline Depth World for Reinforcement Learning-based Left Atrial Appendage Orifice Localization）</news:title>
   <news:publication_date>2026-08-25T03:25:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726956</loc>
  <lastmod>2026-08-25T03:24:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調型セルラーUAVインターネットの協力技術（Cooperation Techniques for A Cellular Internet of Unmanned Aerial Vehicles）</news:title>
   <news:publication_date>2026-08-25T03:24:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726954</loc>
  <lastmod>2026-08-25T03:23:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNS-Morph：TorのためのUDPベースのブートストラッププロトコル（DNS-Morph: UDP-Based Bootstrapping Protocol For Tor）</news:title>
   <news:publication_date>2026-08-25T03:23:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726952</loc>
  <lastmod>2026-08-25T03:23:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層サリエンシーモデルに対する敵対的攻撃（Adversarial Attacks against Deep Saliency Models）</news:title>
   <news:publication_date>2026-08-25T03:23:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726950</loc>
  <lastmod>2026-08-25T03:23:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BPPart と BPMax：塩基対カウントモデルによるRNA-RNA相互作用の分割関数と構造予測 (BPPart and BPMax: RNA-RNA Interaction Partition Function and Structure Prediction for the Base Pair Counting Model)</news:title>
   <news:publication_date>2026-08-25T03:23:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726948</loc>
  <lastmod>2026-08-25T03:23:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エントロピーサーチで最適化するエネルギーベースのスイングアップ制御（Enhancement of Energy-Based Swing-Up Controller via Entropy Search）</news:title>
   <news:publication_date>2026-08-25T03:23:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726946</loc>
  <lastmod>2026-08-25T02:31:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GC-MSピーク整列を深層学習で自動化する手法（Peak Alignment of Gas Chromatography-Mass Spectrometry Data with Deep Learning）</news:title>
   <news:publication_date>2026-08-25T02:31:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726944</loc>
  <lastmod>2026-08-25T02:31:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界上に生成して異常を見抜くアプローチ（Fence GAN: Towards Better Anomaly Detection）</news:title>
   <news:publication_date>2026-08-25T02:31:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726942</loc>
  <lastmod>2026-08-25T02:30:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化化学療法スケジューリングの数値比較（Personalized Cancer Chemotherapy Schedule: a numerical comparison of performance and robustness in model-based and model-free scheduling methodologies）</news:title>
   <news:publication_date>2026-08-25T02:30:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726940</loc>
  <lastmod>2026-08-25T02:30:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス条件付きオートエンコーダによるオープンセット認識（C2AE: Class Conditioned Auto-Encoder for Open-set Recognition）</news:title>
   <news:publication_date>2026-08-25T02:30:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726938</loc>
  <lastmod>2026-08-25T02:30:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散学習における通信削減のためのネスト付きディザ量子化（Nested Dithered Quantization for Communication Reduction in Distributed Training）</news:title>
   <news:publication_date>2026-08-25T02:30:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726936</loc>
  <lastmod>2026-08-25T02:29:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>12誘導心電図の自動診断に向けた深層ニューラルネットワークの実装（Automatic diagnosis of the 12-lead ECG using a deep neural network）</news:title>
   <news:publication_date>2026-08-25T02:29:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726934</loc>
  <lastmod>2026-08-25T02:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>期待モデルによる計画（Planning with Expectation Models）</news:title>
   <news:publication_date>2026-08-25T02:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726932</loc>
  <lastmod>2026-08-25T01:38:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>意味を手がかりにした骨格ベース行動認識（Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition）</news:title>
   <news:publication_date>2026-08-25T01:38:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726930</loc>
  <lastmod>2026-08-25T01:37:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-25T01:37:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726928</loc>
  <lastmod>2026-08-25T01:37:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データがなくても学べる学生ネットワークの作り方（Data-Free Learning of Student Networks）</news:title>
   <news:publication_date>2026-08-25T01:37:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726926</loc>
  <lastmod>2026-08-25T01:37:04Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語推論の最新動向（Recent Advances in Natural Language Inference: A Survey）</news:title>
   <news:publication_date>2026-08-25T01:37:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726924</loc>
  <lastmod>2026-08-25T01:36:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AIに照明推定を学習させる手法（DeepLight: Learning Illumination for Unconstrained Mobile Mixed Reality）</news:title>
   <news:publication_date>2026-08-25T01:36:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726922</loc>
  <lastmod>2026-08-25T01:36:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートホームの安全アクセスにおける人物識別と可視要約（Person Identification with Visual Summary for a Safe Access to a Smart Home）</news:title>
   <news:publication_date>2026-08-25T01:36:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726920</loc>
  <lastmod>2026-08-25T01:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理空間の位相構造に対する操作主義的アプローチ（Operational approach to the topological structure of the physical space）</news:title>
   <news:publication_date>2026-08-25T01:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726918</loc>
  <lastmod>2026-08-25T00:44:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Barista：効率的でスケーラブルなサーバーレス深層学習予測提供システム（BARISTA: Efficient and Scalable Serverless Serving System for Deep Learning Prediction Services）</news:title>
   <news:publication_date>2026-08-25T00:44:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726916</loc>
  <lastmod>2026-08-25T00:44:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アディティブ製造部品向け2.5D深層学習MBIRによるX線CT再構成（X-Ray CT Reconstruction of Additively Manufactured Parts using 2.5D Deep Learning MBIR）</news:title>
   <news:publication_date>2026-08-25T00:44:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726914</loc>
  <lastmod>2026-08-25T00:43:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Curls &amp;amp; Wheyによるブラックボックス敵対的攻撃の改良（Curls &amp;amp; Whey: Boosting Black-Box Adversarial Attacks）</news:title>
   <news:publication_date>2026-08-25T00:43:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726912</loc>
  <lastmod>2026-08-25T00:43:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的サブスペース降下法（Stochastic Subspace Descent）</news:title>
   <news:publication_date>2026-08-25T00:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726910</loc>
  <lastmod>2026-08-25T00:43:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Contrastive Predictive Codingに基づく話者認証特徴量（Contrastive Predictive Coding Based Feature for Automatic Speaker Verification）</news:title>
   <news:publication_date>2026-08-25T00:43:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726908</loc>
  <lastmod>2026-08-25T00:43:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スムースな積分布の混合モデル学習（Learning Mixtures of Smooth Product Distributions: Identifiability and Algorithm）</news:title>
   <news:publication_date>2026-08-25T00:43:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726906</loc>
  <lastmod>2026-08-25T00:42:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>帯域割当モデルの認知的管理と事例ベース推論（Cognitive Management of Bandwidth Allocation Models with Case-Based Reasoning – Evidences Towards Dynamic BAM Reconfiguration）</news:title>
   <news:publication_date>2026-08-25T00:42:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726904</loc>
  <lastmod>2026-08-24T23:51:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ない実演で学べる模倣学習の切り札：Generative Predecessor Models（GPRIL）（Generative Predecessor Models for Sample-Efficient Imitation Learning）</news:title>
   <news:publication_date>2026-08-24T23:51:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726902</loc>
  <lastmod>2026-08-24T23:50:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル構造予測における近似推論手法のベンチマーク（Benchmarking Approximate Inference Methods for Neural Structured Prediction）</news:title>
   <news:publication_date>2026-08-24T23:50:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726900</loc>
  <lastmod>2026-08-24T23:50:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模かつ異種混在の修復可能システムに対する信頼性解析手法の統合（Analysis of Large Heterogeneous Repairable System Reliability Data with Static System Attributes and Dynamic Sensor Measurement in Big Data Environment）</news:title>
   <news:publication_date>2026-08-24T23:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726898</loc>
  <lastmod>2026-08-24T23:49:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ScriptNet: 静的解析に基づく悪性JavaScript検出（ScriptNet: Neural Static Analysis for Malicious JavaScript Detection）</news:title>
   <news:publication_date>2026-08-24T23:49:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726896</loc>
  <lastmod>2026-08-24T23:49:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>余剰変数がRNNの臨床予測性能に与える影響（The Impact of Extraneous Variables on the Performance of Recurrent Neural Network Models in Clinical Tasks）</news:title>
   <news:publication_date>2026-08-24T23:49:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726894</loc>
  <lastmod>2026-08-24T23:49:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterを用いたサイバー脅威検出の深層学習（Cyberthreat Detection from Twitter using Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-24T23:49:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726892</loc>
  <lastmod>2026-08-24T23:49:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HYPE: 人間の目で評価する生成モデルの基準（HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models）</news:title>
   <news:publication_date>2026-08-24T23:49:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726890</loc>
  <lastmod>2026-08-24T22:57:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-24T22:57:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726888</loc>
  <lastmod>2026-08-24T22:56:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列磁気共鳴画像再構成における深層学習の到達点（Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction）</news:title>
   <news:publication_date>2026-08-24T22:56:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726886</loc>
  <lastmod>2026-08-24T22:56:39Z</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・インダストリアル・エスピオナージ（Deep Industrial Espionage）</news:title>
   <news:publication_date>2026-08-24T22:56:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726884</loc>
  <lastmod>2026-08-24T22:56:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ全体を数値化して比較する技術の革新（Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity）</news:title>
   <news:publication_date>2026-08-24T22:56:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726882</loc>
  <lastmod>2026-08-24T22:56:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物性指向埋め込みによる材料探索の枠組み（Property-aimed embedding: a machine learning framework for material discovery）</news:title>
   <news:publication_date>2026-08-24T22:56:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726880</loc>
  <lastmod>2026-08-24T22:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>創造性に着想を得たゼロショット学習（Creativity Inspired Zero-Shot Learning）</news:title>
   <news:publication_date>2026-08-24T22:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726878</loc>
  <lastmod>2026-08-24T22:55:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指紋の固定長表現 — 深層ネットワークとドメイン知識による革新 (Fingerprints: Fixed Length Representation via Deep Networks and Domain Knowledge)</news:title>
   <news:publication_date>2026-08-24T22:55:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726876</loc>
  <lastmod>2026-08-24T22:04:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中性子スキンが示す核物質方程式と中性子星への示唆（Neutron skins as laboratory constraints on properties of neutron stars and on what we can learn from heavy ion fragmentation reactions）</news:title>
   <news:publication_date>2026-08-24T22:04:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726874</loc>
  <lastmod>2026-08-24T21:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記号的回帰による高速で汎用的な多体間相互作用ポテンシャルの発見（Fast, accurate, and transferable many-body interatomic potentials by symbolic regression）</news:title>
   <news:publication_date>2026-08-24T21:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726872</loc>
  <lastmod>2026-08-24T21:56:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層フェノタイピングの方法論と知識抽象化（Digging Deeper: Methodologies for High-Content Phenotyping and Knowledge-Abstraction in C. elegans）</news:title>
   <news:publication_date>2026-08-24T21:56:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726870</loc>
  <lastmod>2026-08-24T21:56:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2次元ラジアルcine MRIに対する時空間スライス学習によるアンダーサンプリングアーチファクト低減（Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI with Limited Training Data）</news:title>
   <news:publication_date>2026-08-24T21:56:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726868</loc>
  <lastmod>2026-08-24T21:55:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期の視覚的自己位置推定のためのマッチング可能な画像変換の学習（Learning Matchable Image Transformations for Long-term Metric Visual Localization）</news:title>
   <news:publication_date>2026-08-24T21:55:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726866</loc>
  <lastmod>2026-08-24T21:55:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepCloudによるデータ駆動生成デザイン（DeepCloud）</news:title>
   <news:publication_date>2026-08-24T21:55:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726864</loc>
  <lastmod>2026-08-24T21:54:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転の確率的回帰とクォータニオン平均を用いた深層マルチヘッドネットワーク（Probabilistic Regression of Rotations using Quaternion Averaging and a Deep Multi-Headed Network）</news:title>
   <news:publication_date>2026-08-24T21:54:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726862</loc>
  <lastmod>2026-08-24T21:03:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BIRADS特徴を組み込んだ半教師あり深層学習による乳房超音波診断の実用化展望（BIRADS Features-Oriented Semi-supervised Deep Learning for Breast Ultrasound Computer-Aided Diagnosis）</news:title>
   <news:publication_date>2026-08-24T21:03:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726860</loc>
  <lastmod>2026-08-24T21:03:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多モーダルスパース分類器による思春期脳年齢推定（Multimodal Sparse Classifier for Adolescent Brain Age Prediction）</news:title>
   <news:publication_date>2026-08-24T21:03:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726858</loc>
  <lastmod>2026-08-24T21:02:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知遷移モデル下の決定的MDPにおける効率的かつ安全な探索（Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models）</news:title>
   <news:publication_date>2026-08-24T21:02:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726856</loc>
  <lastmod>2026-08-24T21:01:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な情報隠蔽機構を機械学習で設計する（Optimal Obfuscation Mechanisms via Machine Learning）</news:title>
   <news:publication_date>2026-08-24T21:01:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726854</loc>
  <lastmod>2026-08-24T21:01:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的最適処置配分（Dynamically Optimal Treatment Allocation）</news:title>
   <news:publication_date>2026-08-24T21:01:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726852</loc>
  <lastmod>2026-08-24T21:01:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Updates-Leak: オンライン学習におけるデータ漏洩攻撃の実態（Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning）</news:title>
   <news:publication_date>2026-08-24T21:01:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726850</loc>
  <lastmod>2026-08-24T21:01:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン・オフライン実験による方策探索のベイズ最適化（Bayesian Optimization for Policy Search via Online-Offline Experimentation）</news:title>
   <news:publication_date>2026-08-24T21:01:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726848</loc>
  <lastmod>2026-08-24T20:09:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク・ソフトオプション学習（Multitask Soft Option Learning）</news:title>
   <news:publication_date>2026-08-24T20:09:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726846</loc>
  <lastmod>2026-08-24T20:09:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Equivariant Multi-View Networks（Equivariant Multi-View Networks）</news:title>
   <news:publication_date>2026-08-24T20:09:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726844</loc>
  <lastmod>2026-08-24T20:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索停止を学習する手法とその意義（Learning to Stop in Structured Prediction for Neural Machine Translation）</news:title>
   <news:publication_date>2026-08-24T20:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726842</loc>
  <lastmod>2026-08-24T20:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>領域的同質性による防御モデル転倒を狙う攻撃（Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses）</news:title>
   <news:publication_date>2026-08-24T20:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726840</loc>
  <lastmod>2026-08-24T20:07:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模バッチ最適化による高速BERT学習（Large Batch Optimization for Deep Learning: Training BERT in 76 Minutes）</news:title>
   <news:publication_date>2026-08-24T20:07:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726838</loc>
  <lastmod>2026-08-24T20:07:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterにおける感情分析の分散表現アプローチ（Twitter Sentiment Analysis using Distributed Word and Sentence Representation）</news:title>
   <news:publication_date>2026-08-24T20:07:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726836</loc>
  <lastmod>2026-08-24T20:07:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝的に進化させたガウスカーネルによる感情分析（SENTIMENT ANALYSIS WITH GENETICALLY EVOLVED GAUSSIAN KERNELS）</news:title>
   <news:publication_date>2026-08-24T20:07:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726834</loc>
  <lastmod>2026-08-24T19:15:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>導かれたメタ・ポリシー探索（Guided Meta-Policy Search）</news:title>
   <news:publication_date>2026-08-24T19:15:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726832</loc>
  <lastmod>2026-08-24T19:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット自己監督による物体セグメンテーション（Robot-Supervised Learning for Object Segmentation）</news:title>
   <news:publication_date>2026-08-24T19:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726830</loc>
  <lastmod>2026-08-24T19:14:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートビルディングにおける機械学習とビッグデータの活用（Leveraging Machine Learning and Big Data for Smart Buildings: A Comprehensive Survey）</news:title>
   <news:publication_date>2026-08-24T19:14:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726828</loc>
  <lastmod>2026-08-24T19:13:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LUTNetが示すFPGAソフトロジック再考（LUTNet: Rethinking Inference in FPGA Soft Logic）</news:title>
   <news:publication_date>2026-08-24T19:13:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726826</loc>
  <lastmod>2026-08-24T19:13:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による肺炎の早期診断 (Early Diagnosis of Pneumonia with Deep Learning)</news:title>
   <news:publication_date>2026-08-24T19:13:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726824</loc>
  <lastmod>2026-08-24T19:13:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像中のバイアス信号を制御する方法（Controlling for Biasing Signals in Images for Prognostic Models: Survival Predictions for Lung Cancer with Deep Learning）</news:title>
   <news:publication_date>2026-08-24T19:13:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726822</loc>
  <lastmod>2026-08-24T19:13:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散メトロポリスサンプラーと最適並列性（Distributed Metropolis Sampler with Optimal Parallelism）</news:title>
   <news:publication_date>2026-08-24T19:13:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726820</loc>
  <lastmod>2026-08-24T18:21:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SAS画像セグメンテーションにおける可能性主義的手法の比較（Comparison of Possibilistic Fuzzy Local Information C-Means and Possibilistic K-Nearest Neighbors for Synthetic Aperture Sonar Image Segmentation）</news:title>
   <news:publication_date>2026-08-24T18:21:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726818</loc>
  <lastmod>2026-08-24T18:21:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コードスタイル自動修正ツールの実務的意義（STYLE-ANALYZER: fixing code style inconsistencies with interpretable unsupervised algorithms）</news:title>
   <news:publication_date>2026-08-24T18:21:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726816</loc>
  <lastmod>2026-08-24T18:20:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>略語の文脈解読を完全自動化する手法（Unsupervised Abbreviation Disambiguation）</news:title>
   <news:publication_date>2026-08-24T18:20:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726814</loc>
  <lastmod>2026-08-24T18:20:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット視覚のための軽量マルチタスク指標の提案（The RGB-D Triathlon: Towards Agile Visual Toolboxes for Robots）</news:title>
   <news:publication_date>2026-08-24T18:20:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726812</loc>
  <lastmod>2026-08-24T18:20:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D 深層学習の頑健性（Robustness of 3D Deep Learning in an Adversarial Setting）</news:title>
   <news:publication_date>2026-08-24T18:20:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726810</loc>
  <lastmod>2026-08-24T18:19:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球面上のU-Netが脳表面解析を変える（Spherical U-Net on Cortical Surfaces: Methods and Applications）</news:title>
   <news:publication_date>2026-08-24T18:19:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726808</loc>
  <lastmod>2026-08-24T18:19:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超音波ブラインドスティックによる自立支援（Ultrasonic Blind Stick For Completely Blind People To Avoid Any Kind Of Obstacles）</news:title>
   <news:publication_date>2026-08-24T18:19:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726806</loc>
  <lastmod>2026-08-24T17:27:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表面科学と触媒における原子スケール機械学習の実装（An Atomistic Machine Learning Package for Surface Science and Catalysis）</news:title>
   <news:publication_date>2026-08-24T17:27:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726804</loc>
  <lastmod>2026-08-24T17:27:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Key.Netによる特徴点検出の再考（Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters）</news:title>
   <news:publication_date>2026-08-24T17:27:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726802</loc>
  <lastmod>2026-08-24T17:26:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間特徴空間を制限することで実現する敵対的防御（Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-24T17:26:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726800</loc>
  <lastmod>2026-08-24T17:25:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意義に応じた情報ボトルネックによるドメイン適応セマンティックセグメンテーション（Significance-aware Information Bottleneck for Domain Adaptive Semantic Segmentation）</news:title>
   <news:publication_date>2026-08-24T17:25:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726798</loc>
  <lastmod>2026-08-24T17:25:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的残差粗視化（Adversarial-Residual-Coarse-Graining）</news:title>
   <news:publication_date>2026-08-24T17:25:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726796</loc>
  <lastmod>2026-08-24T17:25:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tree Search Networkによるスパース回帰の革新（Tree Search Network for Sparse Regression）</news:title>
   <news:publication_date>2026-08-24T17:25:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726794</loc>
  <lastmod>2026-08-24T17:25:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィルタの非線形集約による画像ノイズ除去の改善（Non-linear aggregation of filters to improve image denoising）</news:title>
   <news:publication_date>2026-08-24T17:25:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726792</loc>
  <lastmod>2026-08-24T16:33:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習を組み込む安全クリティカルシステムの工学的課題（Engineering problems in machine learning systems）</news:title>
   <news:publication_date>2026-08-24T16:33:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726790</loc>
  <lastmod>2026-08-24T16:33:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DefectNetによる不均衡データ上の多クラス欠陥検出（DEFECTNET: MULTI-CLASS FAULT DETECTION ON HIGHLY-IMBALANCED DATASETS）</news:title>
   <news:publication_date>2026-08-24T16:33:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726788</loc>
  <lastmod>2026-08-24T16:32:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密集領域における精密検出の手法（Precise Detection in Densely Packed Scenes）</news:title>
   <news:publication_date>2026-08-24T16:32:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726786</loc>
  <lastmod>2026-08-24T16:31:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>果物認識のための畳み込みニューラルネットワークによる分類器の実装（Implementation of Fruits Recognition Classifier using Convolutional Neural Network Algorithm）</news:title>
   <news:publication_date>2026-08-24T16:31:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726784</loc>
  <lastmod>2026-08-24T16:31:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者不均衡な音声コーパスを用いたマルチスピーカニューラル音声合成の学習 (Training Multi-Speaker Neural Text-to-Speech Systems using Speaker-Imbalanced Speech Corpora)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-24T16:31:20Z</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>2026-08-24T16:31:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726780</loc>
  <lastmod>2026-08-24T16:31:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度認識型ビデオフレーム補間（Depth-Aware Video Frame Interpolation）</news:title>
   <news:publication_date>2026-08-24T16:31:07Z</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>意味を持つエッジで追う単眼カメラ位置推定（Semantic Nearest Neighbor Fields for Monocular Edge Visual-Odometry）</news:title>
   <news:publication_date>2026-08-24T15:39:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726776</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>TG-PSMによるトラフィック変形と追跡防止（Tunable Greedy Packet Sequence Morphing Based on Trace Clustering）</news:title>
   <news:publication_date>2026-08-24T15:39:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726774</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>GANをGANで学習する試み（GAN You Do the GAN GAN?）</news:title>
   <news:publication_date>2026-08-24T15:38:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726772</loc>
  <lastmod>2026-08-24T15:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テレコムにおける顧客解約予測（Customer churn prediction in telecom using machine learning in big data platform）</news:title>
   <news:publication_date>2026-08-24T15:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726770</loc>
  <lastmod>2026-08-24T15:38:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドと機械を組み合わせた多項目スクリーニング（Combining Crowd and Machines for Multi-predicate Item Screening）</news:title>
   <news:publication_date>2026-08-24T15:38:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726768</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>JSIS3Dによる3D点群の意味・個体同時分割（JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds）</news:title>
   <news:publication_date>2026-08-24T15:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726766</loc>
  <lastmod>2026-08-24T15:37:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化多チャネルによる敵対的攻撃耐性の強化（Defending against adversarial attacks by randomized diversification）</news:title>
   <news:publication_date>2026-08-24T15:37:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726764</loc>
  <lastmod>2026-08-24T14:46:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム特徴の力と限界（On the Power and Limitations of Random Features for Understanding Neural Networks）</news:title>
   <news:publication_date>2026-08-24T14:46:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726762</loc>
  <lastmod>2026-08-24T14:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工衛星画像における建造物計数の深層学習と注意重み付け（DEEP BUILT-STRUCTURE COUNTING IN SATELLITE IMAGERY USING ATTENTION BASED RE-WEIGHTING）</news:title>
   <news:publication_date>2026-08-24T14:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726760</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>単一屋外画像からのエンドツーエンドタイムラプス生成（End-to-End Time-Lapse Video Synthesis from a Single Outdoor Image）</news:title>
   <news:publication_date>2026-08-24T14:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726758</loc>
  <lastmod>2026-08-24T14:25:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチホップ知識経路で人間の欲求を解き明かす（Ranking and Selecting Multi-Hop Knowledge Paths to Better Predict Human Needs）</news:title>
   <news:publication_date>2026-08-24T14:25:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726756</loc>
  <lastmod>2026-08-24T14:25:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内容重み付け深層画像圧縮（Learning Content-Weighted Deep Image Compression）</news:title>
   <news:publication_date>2026-08-24T14:25:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726754</loc>
  <lastmod>2026-08-24T14:24:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Learn2MACによるURLLC向けオンライン学習型多元接続（Learn2MAC: Online Learning Multiple Access for URLLC Applications）</news:title>
   <news:publication_date>2026-08-24T14:24:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726752</loc>
  <lastmod>2026-08-24T14:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化を使った確率モデル推論の頑健化（Robust Optimisation Monte Carlo）</news:title>
   <news:publication_date>2026-08-24T14:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726750</loc>
  <lastmod>2026-08-24T13:33:27Z</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/726748</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>臨床時系列解析における転移学習の実践的示唆（Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-24T13:33:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726746</loc>
  <lastmod>2026-08-24T13:33:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模交通標識検出・認識のための深層学習（Deep Learning for Large-Scale Traffic-Sign Detection and Recognition）</news:title>
   <news:publication_date>2026-08-24T13:33:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726744</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>ユーザー生成コンテンツにおける音楽エンティティ認識 (Recognizing Musical Entities in User-generated Content)</news:title>
   <news:publication_date>2026-08-24T13:32:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726742</loc>
  <lastmod>2026-08-24T13:32:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制御可能な特徴空間による画像復元（CFSNet: Toward a Controllable Feature Space for Image Restoration）</news:title>
   <news:publication_date>2026-08-24T13:32:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726740</loc>
  <lastmod>2026-08-24T13:32:16Z</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>
  <loc>https://aibr.jp/archives/726738</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>単一画像の反射（リフレクション）除去におけるミスアライメント学習とネットワーク強化（Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726736</loc>
  <lastmod>2026-08-24T12:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-24T12:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726734</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:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726732</loc>
  <lastmod>2026-08-24T12:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個々のユニットが果たす相対的寄与の可視化（Relative Attributing Propagation）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726730</loc>
  <lastmod>2026-08-24T12:28:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResUNet-aによる高解像度空中画像の意味セグメンテーション（ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data）</news:title>
   <news:publication_date>2026-08-24T12:28:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726728</loc>
  <lastmod>2026-08-24T12:28:45Z</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分散電力制御（Distributed Power Control for Large Energy Harvesting Networks: A Multi-Agent Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-08-24T12:28:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726726</loc>
  <lastmod>2026-08-24T12:28:25Z</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>2026-08-24T12:28:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726724</loc>
  <lastmod>2026-08-24T12:27:47Z</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>2026-08-24T12:27:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726722</loc>
  <lastmod>2026-08-24T11:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adaptive Bayesian Linear Regression for Automated Machine Learning（Adaptive Bayesian Linear Regression for Automated Machine Learning）</news:title>
   <news:publication_date>2026-08-24T11:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726720</loc>
  <lastmod>2026-08-24T11:35:51Z</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>2026-08-24T11:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726718</loc>
  <lastmod>2026-08-24T11:34:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡な産業時系列に対するGANベースの故障診断手法（A Novel GAN-based Fault Diagnosis Approach for Imbalanced Industrial Time Series）</news:title>
   <news:publication_date>2026-08-24T11:34:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726716</loc>
  <lastmod>2026-08-24T11:34:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-24T11:34:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726714</loc>
  <lastmod>2026-08-24T11:34:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数ソースの弱教師付き学習による注目領域検出（Multi-source weak supervision for saliency detection）</news:title>
   <news:publication_date>2026-08-24T11:34:22Z</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>高次元ハイパースペクトル画像の深層クラスタリングとクラス内距離制約（Deep Clustering With Intra-class Distance Constraint for Hyperspectral Images）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー疎再構成同調埋め込みによる次元削減（Co-regularized Multi-view Sparse Reconstruction Embedding for Dimension Reduction）</news:title>
   <news:publication_date>2026-08-24T11:32:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726708</loc>
  <lastmod>2026-08-24T10:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セグメンテーション協調による弱教師付き物体検出（Weakly Supervised Object Detection with Segmentation Collaboration）</news:title>
   <news:publication_date>2026-08-24T10:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726706</loc>
  <lastmod>2026-08-24T10:29:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型自己符号化器による階層的画像圧縮（Layered Image Compression using Scalable Auto-encoder）</news:title>
   <news:publication_date>2026-08-24T10:29:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726704</loc>
  <lastmod>2026-08-24T10:17:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全データに対する差分位相コントラストCTの深層学習再構成フレームワーク（A Deep Learning Reconstruction Framework for Differential Phase-Contrast Computed Tomography with Incomplete Data）</news:title>
   <news:publication_date>2026-08-24T10:17:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726702</loc>
  <lastmod>2026-08-24T10:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的な人物再識別における可視性認識型部位特徴学習（Perceive Where to Focus: Learning Visibility-aware Part-level Features for Partial Person Re-identiﬁcation）</news:title>
   <news:publication_date>2026-08-24T10:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726700</loc>
  <lastmod>2026-08-24T10:17:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュースメディアの信頼性と政治的イデオロギーを同時に推定する手法（Multi-Task Ordinal Regression for Jointly Predicting the Trustworthiness and the Leading Political Ideology of News Media）</news:title>
   <news:publication_date>2026-08-24T10:17:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726698</loc>
  <lastmod>2026-08-24T10:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を切り分ける無監督異常検知（Unsupervised Contextual Anomaly Detection using Joint Deep Variational Generative Models）</news:title>
   <news:publication_date>2026-08-24T10:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726696</loc>
  <lastmod>2026-08-24T09:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界単一画像超解像の新基準と新モデル（Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model）</news:title>
   <news:publication_date>2026-08-24T09:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726694</loc>
  <lastmod>2026-08-24T09:24:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間アンサンブル学習と予測不確実性の校正（Adaptive Ensemble Learning of Spatiotemporal Processes with Calibrated Predictive Uncertainty）</news:title>
   <news:publication_date>2026-08-24T09:24:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726692</loc>
  <lastmod>2026-08-24T09:24:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期マニータスキングランタイムの比較研究（A Comparative Study of Asynchronous Many–Tasking Runtimes: Cilk, Charm++, ParalleX and AM++）</news:title>
   <news:publication_date>2026-08-24T09:24:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726690</loc>
  <lastmod>2026-08-24T09:24:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二相流レジーム予測に向けたLSTMベース深層再帰型ニューラルネットワーク（Two-phase flow regime prediction using LSTM based deep recurrent neural network）</news:title>
   <news:publication_date>2026-08-24T09:24:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726688</loc>
  <lastmod>2026-08-24T09:23:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野菜切断タスクの意味的埋め込み空間の学習（Learning Semantic Embedding Spaces for Slicing Vegetables）</news:title>
   <news:publication_date>2026-08-24T09:23:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726686</loc>
  <lastmod>2026-08-24T09:23:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続イベント列の要約と系列エピソードの統計モデル（Summarizing Event Sequences with Serial Episodes: A Statistical Model and an Application）</news:title>
   <news:publication_date>2026-08-24T09:23:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726684</loc>
  <lastmod>2026-08-24T08:32:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形文脈バンディットにおけるほぼ最小最大レグレット（Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits）</news:title>
   <news:publication_date>2026-08-24T08:32:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726682</loc>
  <lastmod>2026-08-24T08:25:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半透明水彩顔料混色の予測モデル（PREDICTION MODEL FOR SEMITRANSPARENT WATERCOLOR PIGMENT MIXTURES USING DEEP LEARNING WITH A DATASET OF TRANSMITTANCE AND REFLECTANCE）</news:title>
   <news:publication_date>2026-08-24T08:25:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726680</loc>
  <lastmod>2026-08-24T08:25:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WiFiで人体を「見る」技術の衝撃（Person-in-WiFi: Fine-grained Person Perception using WiFi）</news:title>
   <news:publication_date>2026-08-24T08:25:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726678</loc>
  <lastmod>2026-08-24T08:25:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーツ単位で生成するGANの設計と意義（COCO-GAN: Generation by Parts via Conditional Coordinating）</news:title>
   <news:publication_date>2026-08-24T08:25:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726676</loc>
  <lastmod>2026-08-24T08:23:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似ダイナミクスをもつロボット間の知識転移による高精度即興軌道追従 (Knowledge Transfer Between Robots with Similar Dynamics for High-Accuracy Impromptu Trajectory Tracking)</news:title>
   <news:publication_date>2026-08-24T08:23:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726674</loc>
  <lastmod>2026-08-24T08:23:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境との相互作用が不可欠である分離表現学習の再定義（Symmetry-Based Disentangled Representation Learning requires Interaction with Environments）</news:title>
   <news:publication_date>2026-08-24T08:23:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726672</loc>
  <lastmod>2026-08-24T08:23:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイアス制御を組み込んだ敵対的学習による人物再識別の改良（Person Re-identification with Bias-controlled Adversarial Training）</news:title>
   <news:publication_date>2026-08-24T08:23:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726670</loc>
  <lastmod>2026-08-24T07:30:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>署名認証を一変させるSiamese-CNN手法（OSVNet: Convolutional Siamese Network for Writer Independent Online Signature Verification）</news:title>
   <news:publication_date>2026-08-24T07:30:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726668</loc>
  <lastmod>2026-08-24T07:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ルール制約付き深層強化学習によるレーンチェンジ意思決定（Lane Change Decision-making through Deep Reinforcement Learning with Rule-based Constraints）</news:title>
   <news:publication_date>2026-08-24T07:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726666</loc>
  <lastmod>2026-08-24T07:30:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MortonNetによる点群の自己教師あり局所特徴学習（MortonNet: Self-Supervised Learning of Local Features in 3D Point Clouds）</news:title>
   <news:publication_date>2026-08-24T07:30:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726664</loc>
  <lastmod>2026-08-24T07:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平滑スプラインと条件付きガウスグラフィカルモデルを組み合わせた半パラメトリック密度推定（Combining Smoothing Spline with Conditional Gaussian Graphical Model for Density and Graph Estimation）</news:title>
   <news:publication_date>2026-08-24T07:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726662</loc>
  <lastmod>2026-08-24T07:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒト視覚に着想を得た注意機構で知覚重視型超解像の損失指標を改善する（A HVS-inspired Attention to Improve Loss Metrics for CNN-based Perception-Oriented Super-Resolution）</news:title>
   <news:publication_date>2026-08-24T07:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726660</loc>
  <lastmod>2026-08-24T07:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電圧品質時系列分類における畳み込みニューラルネットワーク（Voltage Quality Time Series Classification using Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-24T07:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726658</loc>
  <lastmod>2026-08-24T07:29:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしで安定な3Dキーポイントを学習する手法の要点（USIP: Unsupervised Stable Interest Point Detection from 3D Point Clouds）</news:title>
   <news:publication_date>2026-08-24T07:29:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726656</loc>
  <lastmod>2026-08-24T06:38:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データの非パラメトリック密度推定（Nonparametric Density Estimation for High-Dimensional Data – Algorithms and Applications）</news:title>
   <news:publication_date>2026-08-24T06:38:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726654</loc>
  <lastmod>2026-08-24T06:38:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>境界に着目したマルチフォーカス画像合成（BOUNDARY AWARE MULTI-FOCUS IMAGE FUSION USING DEEP NEURAL NETWORK）</news:title>
   <news:publication_date>2026-08-24T06:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726652</loc>
  <lastmod>2026-08-24T06:37:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SIFT記述子を用いた回転不変な畳み込みニューラルネットワーク（Exploiting SIFT Descriptor for Rotation Invariant Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-24T06:37:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726650</loc>
  <lastmod>2026-08-24T06:37:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を考慮する機械翻訳（Machine translation considering context information using Encoder-Decoder model）</news:title>
   <news:publication_date>2026-08-24T06:37:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726648</loc>
  <lastmod>2026-08-24T06:37:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的特徴空間の適応的調整によるゼロショット認識の改善（ADAPTIVE ADJUSTMENT WITH SEMANTIC FEATURE SPACE FOR ZERO-SHOT RECOGNITION）</news:title>
   <news:publication_date>2026-08-24T06:37:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726646</loc>
  <lastmod>2026-08-24T06:36:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EE-AEによる排他性強化型自己符号化器（EE-AE: Exclusivity Enhanced Autoencoder）</news:title>
   <news:publication_date>2026-08-24T06:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726644</loc>
  <lastmod>2026-08-24T06:36:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定常時系列の非パラメトリック漸近解析（Asymptotic nonparametric statistical analysis of stationary time series）</news:title>
   <news:publication_date>2026-08-24T06:36:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726642</loc>
  <lastmod>2026-08-24T05:45:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続的年齢解析の普遍的変分フレームワーク（UVA: A Universal Variational Framework for Continuous Age Analysis）</news:title>
   <news:publication_date>2026-08-24T05:45:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726640</loc>
  <lastmod>2026-08-24T05:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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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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 <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:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-24T05:43:28Z</news:publication_date>
   <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:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-24T04:51:23Z</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>
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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:publication_date>2026-08-24T04:00:00Z</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:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>GraSPyによるグラフ統計ライブラリ（GraSPy: Graph Statistics in Python）</news:title>
   <news:publication_date>2026-08-24T03:59:09Z</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>2026-08-24T03:59:03Z</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>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news: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>
   <news:title>深層強化学習による高速道路自動運転の実用性（Autonomous Highway Driving using Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-24T03:06:05Z</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>
  </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>電子–イオン衝突器が拓く核内パートン分布の精密化（Nuclear Parton Distributions from Lepton-Nucleus Scattering and the Impact of an Electron-Ion Collider）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </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: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>2026-08-24T02:11:53Z</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>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-24T02:09:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-24T02:09:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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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: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>
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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>
  <loc>https://aibr.jp/archives/726566</loc>
  <lastmod>2026-08-24T01:08:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>印刷写真を使ったカラーカンスタンシーデータセット生成（CroP: Color Constancy Benchmark Dataset Generator）</news:title>
   <news:publication_date>2026-08-24T01:08:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726564</loc>
  <lastmod>2026-08-24T01:07:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的堅牢性とモデル圧縮を両立する道（Adversarial Robustness vs. Model Compression, or Both?）</news:title>
   <news:publication_date>2026-08-24T01:07:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726562</loc>
  <lastmod>2026-08-24T01:07:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>論理プログラムによる関係表現学習（Learning Relational Representations with Auto-encoding Logic Programs）</news:title>
   <news:publication_date>2026-08-24T01:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726560</loc>
  <lastmod>2026-08-24T01:07:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前処理を減らし現場データで強くなる前進：T2強調MRIにおける前立腺領域分割のクロスデータセット評価（CNN-based Prostate Zonal Segmentation on T2-weighted MR Images: A Cross-dataset Study）</news:title>
   <news:publication_date>2026-08-24T01:07:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726558</loc>
  <lastmod>2026-08-24T00:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感覚データの確率的予測と生成的敵対ネットワーク（Probabilistic Forecasting of Sensory Data with Generative Adversarial Networks – ForGAN）</news:title>
   <news:publication_date>2026-08-24T00:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726556</loc>
  <lastmod>2026-08-24T00:15:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデータでより学ぶ：GANベースの医療画像拡張（Learning More with Less: GAN-based Medical Image Augmentation）</news:title>
   <news:publication_date>2026-08-24T00:15:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726554</loc>
  <lastmod>2026-08-24T00:14:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一ビットADCs環境下のMIMO受信での頑健なデータ検出（Robust Data Detection for MIMO Systems with One-Bit ADCs: A Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-08-24T00:14:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726552</loc>
  <lastmod>2026-08-24T00:14:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意のぼかしカーネルに対応する深層プラグアンドプレイス超解像（Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels）</news:title>
   <news:publication_date>2026-08-24T00:14:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726550</loc>
  <lastmod>2026-08-24T00:14:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック語の再ランク付けによる解釈性向上（Re-Ranking Words to Improve Interpretability of Automatically Generated Topics）</news:title>
   <news:publication_date>2026-08-24T00:14:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726548</loc>
  <lastmod>2026-08-24T00:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>静電容量式心電図の雑音除去のための深層ニューラルネットワーク（Deep Network for Capacitive ECG Denoising）</news:title>
   <news:publication_date>2026-08-24T00:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726546</loc>
  <lastmod>2026-08-24T00:13:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層残差ネットワークに対する証明可能な防御（A Provable Defense for Deep Residual Networks）</news:title>
   <news:publication_date>2026-08-24T00:13:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726544</loc>
  <lastmod>2026-08-23T23:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳を模した深層再帰強化学習による模擬自動運転エージェント（Towards Brain-inspired System: Deep Recurrent Reinforcement Learning for Simulated Self-driving Agent）</news:title>
   <news:publication_date>2026-08-23T23:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726542</loc>
  <lastmod>2026-08-23T23:22:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FPGA内蔵ECCによるアンダーボルティング障害の緩和評価（Evaluating Built-in ECC of FPGA on-chip Memories for the Mitigation of Undervolting Faults）</news:title>
   <news:publication_date>2026-08-23T23:22:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726540</loc>
  <lastmod>2026-08-23T23:22:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反射材を含む合成画像での物体検出器の学習（Training Object Detectors on Synthetic Images Containing Reflecting Materials）</news:title>
   <news:publication_date>2026-08-23T23:22:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726538</loc>
  <lastmod>2026-08-23T23:21:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>被験者横断の転移学習による人体行動認識（Cross-Subject Transfer Learning in Human Activity Recognition Systems using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-23T23:21:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726536</loc>
  <lastmod>2026-08-23T23:21:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称深層意味量子化による画像検索（Asymmetric Deep Semantic Quantization for Image Retrieval）</news:title>
   <news:publication_date>2026-08-23T23:21:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726534</loc>
  <lastmod>2026-08-23T23:21:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLとシステム研究の新境地（MLSys: The New Frontier of Machine Learning Systems）</news:title>
   <news:publication_date>2026-08-23T23:21:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726532</loc>
  <lastmod>2026-08-23T23:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的アプローチによる前方モデル学習：ライフゲームでの成果（A Local Approach to Forward Model Learning: Results on the Game of Life Game）</news:title>
   <news:publication_date>2026-08-23T23:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726530</loc>
  <lastmod>2026-08-23T22:28:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レーダー測定に基づく深層空間一貫占有地図（Deep, spatially coherent Occupancy Maps based on Radar Measurements）</news:title>
   <news:publication_date>2026-08-23T22:28:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726528</loc>
  <lastmod>2026-08-23T22:28:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市場操作をセキュリティ問題として捉える（Market Manipulation as a Security Problem）</news:title>
   <news:publication_date>2026-08-23T22:28:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726526</loc>
  <lastmod>2026-08-23T22:28:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン多目的回帰決定木と積み重ねリーフモデル（Online Multi-target regression trees with stacked leaf models）</news:title>
   <news:publication_date>2026-08-23T22:28:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726524</loc>
  <lastmod>2026-08-23T22:27:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かさを扱う証拠理論的深層逆センサモデル（Deep, spatially coherent Inverse Sensor Models with Uncertainty Incorporation using the evidential Framework）</news:title>
   <news:publication_date>2026-08-23T22:27:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726522</loc>
  <lastmod>2026-08-23T22:27:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的変分から決定的オートエンコーダへ（From Variational to Deterministic Autoencoders）</news:title>
   <news:publication_date>2026-08-23T22:27:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726520</loc>
  <lastmod>2026-08-23T22:27:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BaTiO3における強誘電体間転移の中間スケール起源（Mesoscopic Origin of Ferroelectric-Ferroelectric Transition in BaTiO3）</news:title>
   <news:publication_date>2026-08-23T22:27:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726518</loc>
  <lastmod>2026-08-23T22:26:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>登場人物の感情関係を機械に学習させる方法（Learning to Classify Emotional Relationships of Fictional Characters）</news:title>
   <news:publication_date>2026-08-23T22:26:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726516</loc>
  <lastmod>2026-08-23T21:35:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合分布を用いたオンライン分散削減（Online Variance Reduction with Mixtures）</news:title>
   <news:publication_date>2026-08-23T21:35:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726514</loc>
  <lastmod>2026-08-23T21:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声からの感情予測に対する注意機構付きエンドツーエンド多重課題学習（ATTENTION-AUGMENTED END-TO-END MULTI-TASK LEARNING FOR EMOTION PREDICTION FROM SPEECH）</news:title>
   <news:publication_date>2026-08-23T21:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726512</loc>
  <lastmod>2026-08-23T21:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分微分方程式に基づく家畜データ同化のための統計学習ツール（An innovative Statistical Learning Tool based on Partial Differential Equations for livestock Data Assimilation）</news:title>
   <news:publication_date>2026-08-23T21:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726510</loc>
  <lastmod>2026-08-23T21:25:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バグ報告の重複検出とクラスタリングを同時に学習する手法（Train One Get One Free: Partially Supervised Neural Network for Bug Report Duplicate Detection and Clustering）</news:title>
   <news:publication_date>2026-08-23T21:25:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726508</loc>
  <lastmod>2026-08-23T21:24:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フェルミラブの高速サイクロトロン導入による2.4MW化の設計（Rapid-Cycling Synchrotron for Multi-Megawatt Proton Facility at Fermilab）</news:title>
   <news:publication_date>2026-08-23T21:24:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726506</loc>
  <lastmod>2026-08-23T21:24:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Snore-GANsによるいびき音分類のための合成データ増強（Snore-GANs: Improving Automatic Snore Sound Classification with Synthesized Data）</news:title>
   <news:publication_date>2026-08-23T21:24:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726504</loc>
  <lastmod>2026-08-23T21:24:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MCTSに基づく自動交渉エージェント（MCTS-based Automated Negotiation Agent）</news:title>
   <news:publication_date>2026-08-23T21:24:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726502</loc>
  <lastmod>2026-08-23T20:33:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト読み上げと声質変換の統合学習（Joint training framework for text-to-speech and voice conversion using multi-source Tacotron and WaveNet）</news:title>
   <news:publication_date>2026-08-23T20:33:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726500</loc>
  <lastmod>2026-08-23T20:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前知識を組み込む「Informed Machine Learning」の体系化（Informed Machine Learning – A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems）</news:title>
   <news:publication_date>2026-08-23T20:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726498</loc>
  <lastmod>2026-08-23T20:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少量学習を用いた深層敵対的学習による動画ベース人物再識別（Few-Shot Deep Adversarial Learning for Video-based Person Re-identification）</news:title>
   <news:publication_date>2026-08-23T20:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726496</loc>
  <lastmod>2026-08-23T20:23:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル損失を用いたニューラル音声波形モデルの訓練（Training a Neural Speech Waveform Model using Spectral Losses of Short-Time Fourier Transform and Continuous Wavelet Transform）</news:title>
   <news:publication_date>2026-08-23T20:23:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726494</loc>
  <lastmod>2026-08-23T20:22:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度情報で手と物体を分離する実時間手法（DenseAttentionSeg: Segment Hands from Interacted Objects Using Depth Input）</news:title>
   <news:publication_date>2026-08-23T20:22:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726492</loc>
  <lastmod>2026-08-23T20:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUを用いた深層表現の分解と領域性（Deep Representation with ReLU Neural Networks）</news:title>
   <news:publication_date>2026-08-23T20:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726490</loc>
  <lastmod>2026-08-23T20:22:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MCMCベースの最尤学習によるエネルギーベースモデルの解剖（On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models）</news:title>
   <news:publication_date>2026-08-23T20:22:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726488</loc>
  <lastmod>2026-08-23T19:30:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの4Dスパシオ・アングラー一貫ライトフィールド合成（Synthesizing a 4D Spatio-Angular Consistent Light Field from a Single Image）</news:title>
   <news:publication_date>2026-08-23T19:30:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726486</loc>
  <lastmod>2026-08-23T19:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化入力とモジュール化による学習改善（Using Structured Input and Modularity for Improved Learning）</news:title>
   <news:publication_date>2026-08-23T19:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726484</loc>
  <lastmod>2026-08-23T19:30:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書からのキー情報抽出を高速にするCUTIE（CUTIE: Learning to Understand Documents with Convolutional Universal Text Information Extractor）</news:title>
   <news:publication_date>2026-08-23T19:30:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726482</loc>
  <lastmod>2026-08-23T19:29:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボル表現を学習させたニューラルネットの組合せ的汎化（Training neural networks to encode symbols enables combinatorial generalization）</news:title>
   <news:publication_date>2026-08-23T19:29:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726480</loc>
  <lastmod>2026-08-23T19:29:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FOFE-netによる知識ベース問答の簡潔かつ効果的な枠組み（A General FOFE-net Framework for Simple and Effective Question Answering over Knowledge Bases）</news:title>
   <news:publication_date>2026-08-23T19:29:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726478</loc>
  <lastmod>2026-08-23T19:29:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Local Aggregationによる視覚表現の教師なし学習（Local Aggregation for Unsupervised Learning of Visual Embeddings）</news:title>
   <news:publication_date>2026-08-23T19:29:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726476</loc>
  <lastmod>2026-08-23T19:28:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークへの方位情報付与（Lending Orientation to Neural Networks for Cross-view Geo-localization）</news:title>
   <news:publication_date>2026-08-23T19:28:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726474</loc>
  <lastmod>2026-08-23T18:37:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン専門家を対象としたユーザー中心設計による科学可視化研究（A User-centered Design Study in Scientific Visualization Targeting Domain Experts）</news:title>
   <news:publication_date>2026-08-23T18:37:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726472</loc>
  <lastmod>2026-08-23T18:37:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>食事ごとの血糖値予測の困難性（The Challenge of Predicting Meal-to-meal Blood Glucose Concentrations for Patients with Type I Diabetes）</news:title>
   <news:publication_date>2026-08-23T18:37:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726470</loc>
  <lastmod>2026-08-23T18:36:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度航空画像からの建物抽出を効率化するネットワーク（ESFNet: Efficient Network for Building Extraction from High-Resolution Aerial Images）</news:title>
   <news:publication_date>2026-08-23T18:36:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726468</loc>
  <lastmod>2026-08-23T18:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図を使った生体認証のための機械学習フレームワーク（A Machine Learning Framework for Biometric Authentication using Electrocardiogram）</news:title>
   <news:publication_date>2026-08-23T18:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726466</loc>
  <lastmod>2026-08-23T18:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量MRIとCNNによる前立腺病変分類の深堀り（A Deep Dive into Understanding Tumor Foci Classification using Multiparametric MRI Based on Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-23T18:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726464</loc>
  <lastmod>2026-08-23T18:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続的注意による良質な表現学習（Learning Good Representation via Continuous Attention）</news:title>
   <news:publication_date>2026-08-23T18:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726462</loc>
  <lastmod>2026-08-23T17:45:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メムトランジスタ交差配列を用いたメモリ内SVMフレームワーク（Neuromorphic In-Memory Computing Framework using Memtransistor Cross-bar based Support Vector Machines）</news:title>
   <news:publication_date>2026-08-23T17:45:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726460</loc>
  <lastmod>2026-08-23T17:44:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カリキュラムを用いた強化学習の改善（Improved Reinforcement Learning with Curriculum）</news:title>
   <news:publication_date>2026-08-23T17:44:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726458</loc>
  <lastmod>2026-08-23T17:44:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的ランジュバン法による対数凸密度からのサンプリング（Implicit Langevin Algorithms for Sampling From Log-concave Densities）</news:title>
   <news:publication_date>2026-08-23T17:44:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726456</loc>
  <lastmod>2026-08-23T17:43:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚質問応答の関係認識グラフ注意ネットワーク（Relation-Aware Graph Attention Network for Visual Question Answering）</news:title>
   <news:publication_date>2026-08-23T17:43:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726454</loc>
  <lastmod>2026-08-23T17:43:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一水中マイクロホンの多周波数振幅データによる深層学習源位定位（Deep-learning source localization using multi-frequency magnitude-only data）</news:title>
   <news:publication_date>2026-08-23T17:43:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726452</loc>
  <lastmod>2026-08-23T17:43:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>閉じチャネル分率の密度依存性の観測（Observation of the density dependence of the closed-channel fraction of a 6Li superfluid）</news:title>
   <news:publication_date>2026-08-23T17:43:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726450</loc>
  <lastmod>2026-08-23T17:43:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メッシュに基づく深層強化学習ポリシーの頑健性解析（Mesh-based Tools to Analyze Deep Reinforcement Learning Policies for Underactuated Biped Locomotion）</news:title>
   <news:publication_date>2026-08-23T17:43:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726448</loc>
  <lastmod>2026-08-23T16:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声に基づいた単語埋め込みによるA2W音声認識の改善（ACOUSTICALLY GROUNDED WORD EMBEDDINGS FOR IMPROVED ACOUSTICS-TO-WORD SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-08-23T16:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726446</loc>
  <lastmod>2026-08-23T16:51:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FrameNet: 単一RGB画像からの局所正準3Dフレーム推定（FrameNet: Learning Local Canonical Frames of 3D Surfaces from a Single RGB Image）</news:title>
   <news:publication_date>2026-08-23T16:51:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726444</loc>
  <lastmod>2026-08-23T16:51:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーパラメータ選択のコスト解析と実務的示唆（An analysis of the cost of hyper-parameter selection via split-sample validation, with applications to penalized regression）</news:title>
   <news:publication_date>2026-08-23T16:51:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726442</loc>
  <lastmod>2026-08-23T16:50:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超大規模グラフ埋め込みを可能にした仕組み（PyTorch‑BigGraph: A Large-scale Graph Embedding System）</news:title>
   <news:publication_date>2026-08-23T16:50:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726440</loc>
  <lastmod>2026-08-23T16:50:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意駆動型生成対抗ネットワークによる教師なし画像変換（Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation）</news:title>
   <news:publication_date>2026-08-23T16:50:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726438</loc>
  <lastmod>2026-08-23T16:50:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカル記述子に基づく画像対クラス距離の再考（Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning）</news:title>
   <news:publication_date>2026-08-23T16:50:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726436</loc>
  <lastmod>2026-08-23T16:50:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トーラス型オートエンコーダが示す潜在空間設計の新地平（Toroidal AutoEncoder）</news:title>
   <news:publication_date>2026-08-23T16:50:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726434</loc>
  <lastmod>2026-08-23T15:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像分類のための深層スパイキング畳み込みニューラルネットワーク（Deep Convolutional Spiking Neural Networks for Image Classification）</news:title>
   <news:publication_date>2026-08-23T15:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726432</loc>
  <lastmod>2026-08-23T15:58:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビット反転攻撃によるニューラルネット破壊（Bit-Flip Attack: Crushing Neural Network with Progressive Bit Search）</news:title>
   <news:publication_date>2026-08-23T15:58:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726430</loc>
  <lastmod>2026-08-23T15:57:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的な汚損と摂動に対するニューラルネットワークの堅牢性ベンチマーク（BENCHMARKING NEURAL NETWORK ROBUSTNESS TO COMMON CORRUPTIONS AND PERTURBATIONS）</news:title>
   <news:publication_date>2026-08-23T15:57:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726428</loc>
  <lastmod>2026-08-23T15:56:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声から電気喉頭波形への変換における敵対的近似推論（Adversarial Approximate Inference for Speech to Electroglottograph Conversion）</news:title>
   <news:publication_date>2026-08-23T15:56:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726426</loc>
  <lastmod>2026-08-23T15:56:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DEEP-FRIによる検証信頼度の改善（DEEP-FRI: Sampling Outside the Box Improves Soundness）</news:title>
   <news:publication_date>2026-08-23T15:56:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726424</loc>
  <lastmod>2026-08-23T15:56:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>iGenによる構成可能ソフトウェアの動的相互作用推論（iGen: Dynamic Interaction Inference for Configurable Software）</news:title>
   <news:publication_date>2026-08-23T15:56:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726422</loc>
  <lastmod>2026-08-23T15:56:17Z</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バリオン密度推定と等方性解析（Baryon density extraction and isotropy analysis of Cosmic Microwave Background using Deep Learning）</news:title>
   <news:publication_date>2026-08-23T15:56:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726420</loc>
  <lastmod>2026-08-23T15:04:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォルムアルデヒド深遠探査（A Formaldehyde Deep Field）</news:title>
   <news:publication_date>2026-08-23T15:04:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726418</loc>
  <lastmod>2026-08-23T15:04:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的ドメイン適応のための事例転移学習（Learning to Transfer Examples for Partial Domain Adaptation）</news:title>
   <news:publication_date>2026-08-23T15:04:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726416</loc>
  <lastmod>2026-08-23T15:03:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳インターフェースの情報理論的特徴変換学習（Information Theoretic Feature Transformation Learning for Brain Interfaces）</news:title>
   <news:publication_date>2026-08-23T15:03:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726414</loc>
  <lastmod>2026-08-23T15:03:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バリオンで描く：深層生成モデルを用いたガスの付加によるN体シミュレーション拡張（Painting with baryons: augmenting N-body simulations with gas using deep generative models）</news:title>
   <news:publication_date>2026-08-23T15:03:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726412</loc>
  <lastmod>2026-08-23T15:03:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注釈点を活用した高精度カウント手法（Counting with Focus for Free）</news:title>
   <news:publication_date>2026-08-23T15:03:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726410</loc>
  <lastmod>2026-08-23T15:02:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D全脳セグメンテーションの空間局所化ネットワークタイル（Spatially Localized Atlas Network Tiles）</news:title>
   <news:publication_date>2026-08-23T15:02:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726408</loc>
  <lastmod>2026-08-23T15:02:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FaSTGANによる高速動画物体セグメンテーション（Fast video object segmentation with Spatio-Temporal GANs）</news:title>
   <news:publication_date>2026-08-23T15:02:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726406</loc>
  <lastmod>2026-08-23T14:11:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BERTからのタスク固有知識の蒸留（Distilling Task-Specific Knowledge from BERT into Simple Neural Networks）</news:title>
   <news:publication_date>2026-08-23T14:11:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726404</loc>
  <lastmod>2026-08-23T14:11:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮革の自動欠陥セグメンテーション（Automatic Defect Segmentation on Leather with Deep Learning）</news:title>
   <news:publication_date>2026-08-23T14:11:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726402</loc>
  <lastmod>2026-08-23T14:11:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IMAEによるノイズ耐性学習の再考 — MAEの重み分散がもたらす意味（IMAE FOR NOISE-ROBUST LEARNING: MEAN ABSO-LUTE ERROR DOES NOT TREAT EXAMPLES EQUALLY AND GRADIENT MAGNITUDE’S VARIANCE MATTERS）</news:title>
   <news:publication_date>2026-08-23T14:11:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726400</loc>
  <lastmod>2026-08-23T14:11:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地理統計学のための近傍ニューラルネットワーク（Nearest-Neighbor Neural Networks for Geostatistics）</news:title>
   <news:publication_date>2026-08-23T14:11:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726398</loc>
  <lastmod>2026-08-23T14:10:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在クラス分析でARDSのサブフェノタイプを見つけ、機械学習予測を改善する（Using Latent Class Analysis to Identify ARDS Sub-phenotypes for Enhanced Machine Learning Predictive Performance）</news:title>
   <news:publication_date>2026-08-23T14:10:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726396</loc>
  <lastmod>2026-08-23T14:10:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程回帰を用いた効率的なパラメータ再構成（Using Gaussian process regression for efficient parameter reconstruction）</news:title>
   <news:publication_date>2026-08-23T14:10:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726394</loc>
  <lastmod>2026-08-23T14:10:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多数タスク学習とタスクルーティング（Many Task Learning with Task Routing）</news:title>
   <news:publication_date>2026-08-23T14:10:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726392</loc>
  <lastmod>2026-08-23T13:19:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的機械学習による自動化された調査コーダーの構築（Building Automated Survey Coders via Interactive Machine Learning）</news:title>
   <news:publication_date>2026-08-23T13:19:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726390</loc>
  <lastmod>2026-08-23T13:19:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトホロウキャピラリにおける高エネルギー紫外線分散波放射（High-energy ultraviolet dispersive-wave emission in compact hollow capillary systems）</news:title>
   <news:publication_date>2026-08-23T13:19:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726388</loc>
  <lastmod>2026-08-23T13:18:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シグネチャベース侵入検知にベイズ的仮説形成を拡張する（Extending Signature-based Intrusion Detection Systems With Bayesian Abductive Reasoning）</news:title>
   <news:publication_date>2026-08-23T13:18:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726386</loc>
  <lastmod>2026-08-23T13:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB-D合成視点の参照なし品質評価指標GANs-NQM（GANs-NQM: A Generative Adversarial Networks based No Reference Quality Assessment Metric for RGB-D Synthesized Views）</news:title>
   <news:publication_date>2026-08-23T13:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726384</loc>
  <lastmod>2026-08-23T13:17:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲーティング機構を導入したDNN埋め込みによる話者認証の改良（Deep Neural Network Embeddings with Gating Mechanisms for Text-Independent Speaker Verification）</news:title>
   <news:publication_date>2026-08-23T13:17:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726382</loc>
  <lastmod>2026-08-23T13:17:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる音声コーパス間の感情認識を安定して一般化する手法（Barking up the Right Tree: Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG)）</news:title>
   <news:publication_date>2026-08-23T13:17:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726380</loc>
  <lastmod>2026-08-23T13:17:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による重み付け（Learning to Weight for Text Classification）</news:title>
   <news:publication_date>2026-08-23T13:17:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726378</loc>
  <lastmod>2026-08-23T12:24:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化された適応重要度サンプリングの収束率（Convergence rates for optimised adaptive importance samplers）</news:title>
   <news:publication_date>2026-08-23T12:24:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726376</loc>
  <lastmod>2026-08-23T12:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1.6 kb/sのリアルタイム広帯域ニューラルボコーダ（A Real-Time Wideband Neural Vocoder at 1.6 kb/s Using LPCNet）</news:title>
   <news:publication_date>2026-08-23T12:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726374</loc>
  <lastmod>2026-08-23T12:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次統計量を使ったマルチタスク学習によるx-vector音声話者認証（Multi-Task Learning with High-Order Statistics for X-vector based Text-Independent Speaker Verification）</news:title>
   <news:publication_date>2026-08-23T12:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726372</loc>
  <lastmod>2026-08-23T12:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造と属性を統合するネットワーク埋め込みの実務的示唆（Multimodal Deep Network Embedding with Integrated Structure and Attribute Information）</news:title>
   <news:publication_date>2026-08-23T12:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726370</loc>
  <lastmod>2026-08-23T12:22:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化データの学習可能関数を数える（Counting the learnable functions of structured data）</news:title>
   <news:publication_date>2026-08-23T12:22:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726368</loc>
  <lastmod>2026-08-23T12:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のように記述する：画像キャプション生成における多様性の重要性（Describing like Humans: on Diversity in Image Captioning）</news:title>
   <news:publication_date>2026-08-23T12:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726366</loc>
  <lastmod>2026-08-23T12:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラミング概念と構文パターンの対応付けによるコード検索の改善（Crowd Sourced Data Analysis: Mapping of Programming Concepts to Syntactical Patterns）</news:title>
   <news:publication_date>2026-08-23T12:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726364</loc>
  <lastmod>2026-08-23T11:31:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己学習データの誤ラベル対処による低資源系列ラベリングの堅牢学習（Handling Noisy Labels for Robustly Learning from Self-Training Data for Low-Resource Sequence Labeling）</news:title>
   <news:publication_date>2026-08-23T11:31:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726362</loc>
  <lastmod>2026-08-23T11:31:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>翻訳モデルの診断手法の提案（Train, Sort, Explain: Learning to Diagnose Translation Models）</news:title>
   <news:publication_date>2026-08-23T11:31:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726360</loc>
  <lastmod>2026-08-23T11:31:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空中マニピュレーション：逆運動学、同定、RIC制御と実装 (Inverse Kinematics, Identification, RIC-based Control, and implementation of an Aerial Manipulator)</news:title>
   <news:publication_date>2026-08-23T11:31:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726358</loc>
  <lastmod>2026-08-23T11:29:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希土類低減永久磁石の計算設計（Computational Design of the Rare-Earth Reduced Permanent Magnets）</news:title>
   <news:publication_date>2026-08-23T11:29:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726356</loc>
  <lastmod>2026-08-23T11:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル活性化関数による学習の安定性と一般化の解析（On the Stability and Generalization of Learning with Kernel Activation Functions）</news:title>
   <news:publication_date>2026-08-23T11:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/726354</loc>
  <lastmod>2026-08-23T11:29:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経路最適化の正則化とデノイジングオートエンコーダ（Regularizing Trajectory Optimization with Denoising Autoencoders）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/726352</loc>
  <lastmod>2026-08-23T11:29:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラボリック近似に基づくラインサーチによるDNN最適化（Parabolic Approximation Line Search for DNNs）</news:title>
   <news:publication_date>2026-08-23T11:29:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726350</loc>
  <lastmod>2026-08-23T10:37:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>五重クォークと四重クォーク状態（Pentaquark and Tetraquark states）</news:title>
   <news:publication_date>2026-08-23T10:37:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726348</loc>
  <lastmod>2026-08-23T10:36:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ構造を学習するGNNの枠組み（Learning Discrete Structures for Graph Neural Networks）</news:title>
   <news:publication_date>2026-08-23T10:36:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726346</loc>
  <lastmod>2026-08-23T10:36:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基底ユークリッドノルムの最適次数学習による全変動(LEARNING OPTIMAL ORDERS OF THE UNDERLYING EUCLIDEAN NORM IN TOTAL VARIATION IMAGE DENOISING)</news:title>
   <news:publication_date>2026-08-23T10:36:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726344</loc>
  <lastmod>2026-08-23T10:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層流体表面における進行重力波の厳密解（Exact solution for progressive gravity waves on the surface of a deep fluid）</news:title>
   <news:publication_date>2026-08-23T10:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726342</loc>
  <lastmod>2026-08-23T10:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結合ダイナミカルシステムにおける構造学習と動的因果モデリング（Structure Learning in Coupled Dynamical Systems and Dynamic Causal Modelling）</news:title>
   <news:publication_date>2026-08-23T10:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726340</loc>
  <lastmod>2026-08-23T10:35:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンバランスな感情分類における談話マーカーを使った強化（Imbalanced Sentiment Classification Enhanced with Discourse Marker）</news:title>
   <news:publication_date>2026-08-23T10:35:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726338</loc>
  <lastmod>2026-08-23T10:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電波銀河の形状分類における転移学習の応用（Transfer learning for radio galaxy classification）</news:title>
   <news:publication_date>2026-08-23T10:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726336</loc>
  <lastmod>2026-08-23T09:44:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポスト真実時代のフェイクニュース抑止に向けたブロックチェーンの応用（Using Blockchain to Rein in The New Post-Truth World and Check The Spread of Fake News）</news:title>
   <news:publication_date>2026-08-23T09:44:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726334</loc>
  <lastmod>2026-08-23T09:44:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次意思決定のためのメタ学習サロゲートモデル（Meta-Learning surrogate models for sequential decision making）</news:title>
   <news:publication_date>2026-08-23T09:44:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726332</loc>
  <lastmod>2026-08-23T09:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中規模ソフトウェアコンサルティング企業における知識管理（Knowledge Management in Medium-Sized Software Consulting Companies）</news:title>
   <news:publication_date>2026-08-23T09:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726330</loc>
  <lastmod>2026-08-23T09:43:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像変換による分布シフトへの脆弱性に対処する手法（Addressing Model Vulnerability to Distributional Shifts over Image Transformation Sets）</news:title>
   <news:publication_date>2026-08-23T09:43:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726328</loc>
  <lastmod>2026-08-23T09:43:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可視光通信における雑音低減の実践的方法（A Noise Mitigation Approach for VLC Systems）</news:title>
   <news:publication_date>2026-08-23T09:43:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726326</loc>
  <lastmod>2026-08-23T09:42:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AED-Netによる異常事象検出（AED-Net: An Abnormal Event Detection Network）</news:title>
   <news:publication_date>2026-08-23T09:42:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726324</loc>
  <lastmod>2026-08-23T09:42:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Feature Intertwiner を用いた物体検出の新視点（FEATURE INTERTWINER FOR OBJECT DETECTION）</news:title>
   <news:publication_date>2026-08-23T09:42:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726322</loc>
  <lastmod>2026-08-23T08:50:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフカーネルの総覧（A Survey on Graph Kernels）</news:title>
   <news:publication_date>2026-08-23T08:50:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726320</loc>
  <lastmod>2026-08-23T08:50:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>談話マーカーを発掘する：教師なし文表現学習のために（Mining Discourse Markers for Unsupervised Sentence Representation Learning）</news:title>
   <news:publication_date>2026-08-23T08:50:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726318</loc>
  <lastmod>2026-08-23T08:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Feature-fusion Encoder-Decoder Network による肝病変自動セグメンテーション（FEATURE FUSION ENCODER DECODER NETWORK FOR AUTOMATIC LIVER LESION SEGMENTATION）</news:title>
   <news:publication_date>2026-08-23T08:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726316</loc>
  <lastmod>2026-08-23T08:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チェレンコフ検出器の高速シミュレーションにおける生成モデルの応用（Cherenkov Detectors Fast Simulation Using Neural Networks）</news:title>
   <news:publication_date>2026-08-23T08:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726314</loc>
  <lastmod>2026-08-23T08:50:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SRDGANによる実世界単一画像超解像のノイズ事前分布学習（SRDGAN: learning the noise prior for Super Resolution with Dual Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-23T08:50:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726312</loc>
  <lastmod>2026-08-23T08:49:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ADMET予測における飛躍的改善：PotentialNetによる深い特徴化（Step Change Improvement in ADMET Prediction with PotentialNet Deep Featurization）</news:title>
   <news:publication_date>2026-08-23T08:49:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726310</loc>
  <lastmod>2026-08-23T08:49:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱ラベル音響イベント検出の階層プーリング構造（Hierarchical Pooling Structure for Weakly Labeled Sound Event Detection）</news:title>
   <news:publication_date>2026-08-23T08:49:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726308</loc>
  <lastmod>2026-08-23T07:58:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワッサースタイン依存度による表現学習の新展開（Wasserstein Dependency Measure for Representation Learning）</news:title>
   <news:publication_date>2026-08-23T07:58:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726306</loc>
  <lastmod>2026-08-23T07:58:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガイダンスフレーム選択の学習による動画物体分割の改善（BubbleNets: Learning to Select the Guidance Frame in Video Object Segmentation by Deep Sorting Frames）</news:title>
   <news:publication_date>2026-08-23T07:58:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726304</loc>
  <lastmod>2026-08-23T07:58:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話における照応表現解決のための文脈的クエリ書き換え（A dataset for resolving referring expressions in spoken dialogue via contextual query rewrites (CQR))</news:title>
   <news:publication_date>2026-08-23T07:58:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726302</loc>
  <lastmod>2026-08-23T07:57:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層監督による非線形集約による顕著物体検出（DNA: Deeply-supervised Nonlinear Aggregation for Salient Object Detection）</news:title>
   <news:publication_date>2026-08-23T07:57:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726300</loc>
  <lastmod>2026-08-23T07:57:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心房細動を深層特徴と畳み込みネットワークで検出する手法（Atrial Fibrillation Detection Using Deep Features and Convolutional Networks）</news:title>
   <news:publication_date>2026-08-23T07:57:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726298</loc>
  <lastmod>2026-08-23T07:57:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型注意機構付き時系列畳み込みネットワークによる医療時系列分類（Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks）</news:title>
   <news:publication_date>2026-08-23T07:57:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726296</loc>
  <lastmod>2026-08-23T07:57:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションから実機へ：ドメインランダマイゼーションのパラメータ選定（How to pick the domain randomization parameters for sim-to-real transfer of reinforcement learning policies?）</news:title>
   <news:publication_date>2026-08-23T07:57:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726294</loc>
  <lastmod>2026-08-23T07:06:34Z</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>2026-08-23T07:06:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726292</loc>
  <lastmod>2026-08-23T07:06:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AutoSlimによるチャネル最適化の一撃（AutoSlim: Towards One-Shot Architecture Search for Channel Numbers）</news:title>
   <news:publication_date>2026-08-23T07:06:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726290</loc>
  <lastmod>2026-08-23T07:06:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸シナリオプログラムの事後確率境界と検証テスト（A Posteriori Probabilistic Bounds of Convex Scenario Programs with Validation Tests）</news:title>
   <news:publication_date>2026-08-23T07:06:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726288</loc>
  <lastmod>2026-08-23T07:05:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医用画像と機械学習の動向と展望 (Radiological images and machine learning: trends, perspectives, and prospects)</news:title>
   <news:publication_date>2026-08-23T07:05:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-23T07:05:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドベース会議のためのメディア処理資源割当機構（Resource Allocation Mechanism for Media Handling Services in Cloud Multimedia Conferencing）</news:title>
   <news:publication_date>2026-08-23T07:05:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-23T07:05:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多座標コストバランシングによる技能習得（Skill Acquisition via Automated Multi-Coordinate Cost Balancing）</news:title>
   <news:publication_date>2026-08-23T07:05:08Z</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>
   <news:title>因果性の視点から問うアルゴリズムの公平性（Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality）</news:title>
   <news:publication_date>2026-08-23T07:04:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726280</loc>
  <lastmod>2026-08-23T06:13:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WiFi指紋による屋内測位に対するRNNの適用（Recurrent Neural Networks For Accurate RSSI Indoor Localization）</news:title>
   <news:publication_date>2026-08-23T06:13:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726278</loc>
  <lastmod>2026-08-23T06:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多隠れ層リカレントニューラルネットワークと改良グレイウルフ最適化（A Multi Hidden Recurrent Neural Network with a Modified Grey Wolf Optimizer）</news:title>
   <news:publication_date>2026-08-23T06:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726276</loc>
  <lastmod>2026-08-23T06:03:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係性マッチングと適応・較正によるゼロショット画像認識（Zero-shot Image Recognition Using Relational Matching, Adaptation and Calibration）</news:title>
   <news:publication_date>2026-08-23T06:03:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726274</loc>
  <lastmod>2026-08-23T06:02:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線画像由来データの安定した予測（STABLE PREDICTION WITH RADIOMICS DATA）</news:title>
   <news:publication_date>2026-08-23T06:02:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726272</loc>
  <lastmod>2026-08-23T06:02:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークセキュリティ向け深層学習に対抗する敵対的手法の評価（Rallying Adversarial Techniques against Deep Learning for Network Security）</news:title>
   <news:publication_date>2026-08-23T06:02:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726270</loc>
  <lastmod>2026-08-23T06:02:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Inf-Convolutionによる非凸複合最適化の最適化（Optimization of Inf-Convolution Regularized Nonconvex Composite Problems）</news:title>
   <news:publication_date>2026-08-23T06:02:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726268</loc>
  <lastmod>2026-08-23T06:01:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超球面上で自己正規化活性化を用いたエコー・ステート・ネットワーク（Echo State Networks with Self-Normalizing Activations on the Hyper-Sphere）</news:title>
   <news:publication_date>2026-08-23T06:01:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726266</loc>
  <lastmod>2026-08-23T05:11:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外れ値に強い空間認識（Outlier-Robust Spatial Perception: Hardness, General-Purpose Algorithms, and Guarantees）</news:title>
   <news:publication_date>2026-08-23T05:11:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726264</loc>
  <lastmod>2026-08-23T05:11:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>早期停止を用いた勾配降下法はラベルノイズに対し理論的に頑健である（Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks）</news:title>
   <news:publication_date>2026-08-23T05:11:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726262</loc>
  <lastmod>2026-08-23T05:10:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGバイオメトリクスにおける敵対的深層学習 (Adversarial Deep Learning in EEG Biometrics)</news:title>
   <news:publication_date>2026-08-23T05:10:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726260</loc>
  <lastmod>2026-08-23T05:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星形成銀河Haro 11における恒星フィードバックの大規模影響（The impact of Stellar feedback from velocity-dependent ionized gas maps. – A MUSE view of Haro 11）</news:title>
   <news:publication_date>2026-08-23T05:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726258</loc>
  <lastmod>2026-08-23T05:10:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Laplace Landmark Localization（Laplace Landmark Localization）</news:title>
   <news:publication_date>2026-08-23T05:10:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726256</loc>
  <lastmod>2026-08-23T05:10:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像と文章の弱教師あり対応付けで語句を位置特定するAlign2Ground（Align2Ground: Weakly Supervised Phrase Grounding Guided by Image-Caption Alignment）</news:title>
   <news:publication_date>2026-08-23T05:10:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726254</loc>
  <lastmod>2026-08-23T05:09:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発話順序がクラウドソースされた感情アノテーションに及ぼす影響（MuSE-ING ON THE IMPACT OF UTTERANCE ORDERING ON CROWDSOURCED EMOTION ANNOTATIONS）</news:title>
   <news:publication_date>2026-08-23T05:09:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726252</loc>
  <lastmod>2026-08-23T04:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブレーンとブレインズ：深層強化学習で文字列空間を探索する（Branes with Brains: Exploring String Vacua with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-23T04:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726250</loc>
  <lastmod>2026-08-23T04:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的堅牢性と勾配解釈性の橋渡し（BRIDGING ADVERSARIAL ROBUSTNESS AND GRADIENT INTERPRETABILITY）</news:title>
   <news:publication_date>2026-08-23T04:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726248</loc>
  <lastmod>2026-08-23T04:18:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交互的多様体近接勾配法によるSparse PCAとSparse CCA（An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA）</news:title>
   <news:publication_date>2026-08-23T04:18:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726246</loc>
  <lastmod>2026-08-23T04:17:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のようにテキストを処理する — 視覚的に攻撃し護るNLPシステム（Text Processing Like Humans Do: Visually Attacking and Shielding NLP Systems）</news:title>
   <news:publication_date>2026-08-23T04:17:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726244</loc>
  <lastmod>2026-08-23T04:16:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続制御のための自己回帰ポリシー（Autoregressive Policies for Continuous Control Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-23T04:16:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726242</loc>
  <lastmod>2026-08-23T04:16:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現豊かな音声合成の潜在空間可視化と解釈（Visualization and Interpretation of Latent Spaces for Controlling Expressive Speech Synthesis through Audio Analysis）</news:title>
   <news:publication_date>2026-08-23T04:16:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726240</loc>
  <lastmod>2026-08-23T04:16:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制御理論的視点によるDouglas–Rachford分割法の解析とパラメータ選定（A Control-Theoretic Approach to Analysis and Parameter Selection of Douglas-Rachford Splitting）</news:title>
   <news:publication_date>2026-08-23T04:16:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726238</loc>
  <lastmod>2026-08-23T03:23:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期保有者の行動で予測する仮想財の寿命（From the Hands of an Early Adopter’s Avatar to Virtual Junkyards: Analysis of Virtual Goods’ Lifetime Survival）</news:title>
   <news:publication_date>2026-08-23T03:23:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726236</loc>
  <lastmod>2026-08-23T03:23:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群の局所記述子学習（DEEPPOINT3D: LEARNING DISCRIMINATIVE LOCAL DESCRIPTORS USING DEEP METRIC LEARNING ON 3D POINT CLOUDS）</news:title>
   <news:publication_date>2026-08-23T03:23:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726234</loc>
  <lastmod>2026-08-23T03:22:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的システムの簡潔な解析モデル構築（Constructing Parsimonious Analytic Models for Dynamic Systems via Symbolic Regression）</news:title>
   <news:publication_date>2026-08-23T03:22:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726232</loc>
  <lastmod>2026-08-23T03:22:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの初期化を見つめ直す（A Sober Look at Neural Network Initializations）</news:title>
   <news:publication_date>2026-08-23T03:22:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726230</loc>
  <lastmod>2026-08-23T03:21:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポルトガル南西・南沿岸の深海甲殻類底引き網漁業が海洋生態系に与える影響のモデリング（Modelling the impact of deep-water crustacean trawl fishery in the marine ecosystem off Portuguese Southwestern and South Coasts: I) the trophic web and trophic flows）</news:title>
   <news:publication_date>2026-08-23T03:21:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726228</loc>
  <lastmod>2026-08-23T03:21:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸スクエアルート損失回帰の高効率解法（A sparse semismooth Newton based proximal majorization-minimization algorithm for nonconvex square-root-loss regression problems）</news:title>
   <news:publication_date>2026-08-23T03:21:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726226</loc>
  <lastmod>2026-08-23T03:20:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からの2D→3Dリフティングによる3D物体検出（Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles）</news:title>
   <news:publication_date>2026-08-23T03:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726224</loc>
  <lastmod>2026-08-23T02:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コウモリアルゴリズムの大域収束解析（Global Convergence Analysis of the Bat Algorithm Using a Markovian Framework and Dynamical System Theory）</news:title>
   <news:publication_date>2026-08-23T02:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726222</loc>
  <lastmod>2026-08-23T02:29:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Import2vecによるライブラリ埋め込み学習（Import2vec: Learning Embeddings for Software Libraries）</news:title>
   <news:publication_date>2026-08-23T02:29:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726220</loc>
  <lastmod>2026-08-23T02:29:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディア信号で仮想通貨ニュースを感知する手法（Sensing Social Media Signals for Cryptocurrency News）</news:title>
   <news:publication_date>2026-08-23T02:29:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726218</loc>
  <lastmod>2026-08-23T02:29:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度顔画像の匿名化を両立する仕組み（k-Same-Siamese-GAN）</news:title>
   <news:publication_date>2026-08-23T02:29:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726216</loc>
  <lastmod>2026-08-23T02:29:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>掘削中の地質変化をリアルタイムで捉える手法（Real-time data-driven detection of the rock type alteration during a directional drilling）</news:title>
   <news:publication_date>2026-08-23T02:29:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726214</loc>
  <lastmod>2026-08-23T02:28:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続時間を扱う推薦グラフの新展開（Link Stream Graph for Temporal Recommendations）</news:title>
   <news:publication_date>2026-08-23T02:28:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726212</loc>
  <lastmod>2026-08-23T02:28:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像再構成を行わないイメージングサイトメトリー（Imaging cytometry without image reconstruction (ghost cytometry))</news:title>
   <news:publication_date>2026-08-23T02:28:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726210</loc>
  <lastmod>2026-08-23T01:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ショウジョウバエの社会行動フェノタイピングを2D+3DハイブリッドCNNで行う手法（Social Behavioral Phenotyping of Drosophila with a 2D-3D Hybrid CNN Framework）</news:title>
   <news:publication_date>2026-08-23T01:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/726208</loc>
  <lastmod>2026-08-23T01:37:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自発的な顔の微表情認識を3D時空間畳み込みで扱う（Spontaneous Facial Micro-Expression Recognition using 3D Spatiotemporal Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-23T01:37:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726206</loc>
  <lastmod>2026-08-23T01:37:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能なAIの落とし穴：加法的説明を信用するな（Do Not Trust Additive Explanations）</news:title>
   <news:publication_date>2026-08-23T01:37:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726204</loc>
  <lastmod>2026-08-23T01:36:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ化スパース行列乗算によるグラフ畳み込み高速化（Batched Sparse Matrix Multiplication for Accelerating Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-23T01:36:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726202</loc>
  <lastmod>2026-08-23T01:36:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みニューラルネットワークにおける非定型前処理の理解（Understanding Unconventional Preprocessors in Deep Convolutional Neural Networks for Face Identification）</news:title>
   <news:publication_date>2026-08-23T01:36:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726200</loc>
  <lastmod>2026-08-23T01:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ埋め込み相互作用視点から見る知識グラフ埋め込みの分析（Analyzing Knowledge Graph Embedding Methods from a Multi-Embedding Interaction Perspective）</news:title>
   <news:publication_date>2026-08-23T01:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/726198</loc>
  <lastmod>2026-08-23T01:36:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き運動伝播による自己教師あり学習（Self-Supervised Learning via Conditional Motion Propagation）</news:title>
   <news:publication_date>2026-08-23T01:36:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726196</loc>
  <lastmod>2026-08-23T00:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン教科書問題に対する学生の関与のネットワーク解析 (Network analyses of student engagement with online textbook problems)</news:title>
   <news:publication_date>2026-08-23T00:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726194</loc>
  <lastmod>2026-08-23T00:43:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙知識を用いない視覚に基づく言語から文意味表現を学ぶ（Learning semantic sentence representations from visually grounded language without lexical knowledge）</news:title>
   <news:publication_date>2026-08-23T00:43:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726192</loc>
  <lastmod>2026-08-23T00:43:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率進化の動的制御――深層強化学習による適応的薬剤投与（Dynamic Control of Stochastic Evolution: A Deep Reinforcement Learning Approach to Adaptively Targeting Emergent Drug Resistance）</news:title>
   <news:publication_date>2026-08-23T00:43:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726190</loc>
  <lastmod>2026-08-23T00:43:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2次元ケンドール形状の辞書学習（Dictionary Learning for Two-Dimensional Kendall Shapes）</news:title>
   <news:publication_date>2026-08-23T00:43:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726188</loc>
  <lastmod>2026-08-23T00:42:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様性と協調による少数ショット分類の恩恵（Diversity with Cooperation: Ensemble Methods for Few-Shot Classification）</news:title>
   <news:publication_date>2026-08-23T00:42:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726186</loc>
  <lastmod>2026-08-23T00:42:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段階テキスト正規化とマルチソース学習（Multilevel Text Normalization with Sequence-to-Sequence Networks and Multisource Learning）</news:title>
   <news:publication_date>2026-08-23T00:42:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726184</loc>
  <lastmod>2026-08-23T00:42:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化された勾配フリー敵対的攻撃の大規模化が示す既存攻撃による堅牢性の過大評価 (Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks)</news:title>
   <news:publication_date>2026-08-23T00:42:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726182</loc>
  <lastmod>2026-08-22T23:50:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>速度不変のタイムサーフェスによるイベントカメラのコーナー検出（Speed Invariant Time Surface for Learning to Detect Corner Points with Event-Based Cameras）</news:title>
   <news:publication_date>2026-08-22T23:50:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726180</loc>
  <lastmod>2026-08-22T23:50:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数情報源を能動的に使うベイズ求積法（Active Multi-Information Source Bayesian Quadrature）</news:title>
   <news:publication_date>2026-08-22T23:50:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726178</loc>
  <lastmod>2026-08-22T23:50:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的注意生成対抗ネットワークによるクロスドメイン感情分類（Hierarchical Attention Generative Adversarial Networks for Cross-domain Sentiment Classification）</news:title>
   <news:publication_date>2026-08-22T23:50:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726176</loc>
  <lastmod>2026-08-22T23:49:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自閉スペクトラム症（ASD）検出の新たな機械学習フレームワーク（A novel machine learning based framework for detection of Autism Spectrum Disorder (ASD))</news:title>
   <news:publication_date>2026-08-22T23:49:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726174</loc>
  <lastmod>2026-08-22T23:49:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎化されたオフポリシー・アクタークリティック（Generalized Off-Policy Actor-Critic）</news:title>
   <news:publication_date>2026-08-22T23:49:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726172</loc>
  <lastmod>2026-08-22T23:49:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rパッケージによる自動化EDAの現状と経営への示唆（The Landscape of R Packages for Automated Exploratory Data Analysis）</news:title>
   <news:publication_date>2026-08-22T23:49:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726170</loc>
  <lastmod>2026-08-22T23:48:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散基盤上での大規模深層学習：課題・技術・ツール（Scalable Deep Learning on Distributed Infrastructures: Challenges, Techniques and Tools）</news:title>
   <news:publication_date>2026-08-22T23:48:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726168</loc>
  <lastmod>2026-08-22T22:57:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語テキストを用いた画像検索：画像とテキストのクロスモーダル学習アプローチ（Image search using multilingual texts: a cross-modal learning approach between image and text）</news:title>
   <news:publication_date>2026-08-22T22:57:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726166</loc>
  <lastmod>2026-08-22T22:56:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変形可能カーネルネットワークによる深度マップのガイド付きアップサンプリング（Deformable Kernel Networks for Guided Depth Map Upsampling）</news:title>
   <news:publication_date>2026-08-22T22:56:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726164</loc>
  <lastmod>2026-08-22T22:55:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚情報を持つ文書からのマルチモーダル情報抽出を可能にするグラフ畳み込み（Graph Convolution for Multimodal Information Extraction from Visually Rich Documents）</news:title>
   <news:publication_date>2026-08-22T22:55:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726162</loc>
  <lastmod>2026-08-22T22:55:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数ホッピング通信に対する畳み込み攻撃（Convolution Attack on Frequency-Hopping by Full-Duplex Radios）</news:title>
   <news:publication_date>2026-08-22T22:55:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726160</loc>
  <lastmod>2026-08-22T22:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元でスパースな表現を使う利点（How Can We Be So Dense? The Benefits of Using Highly Sparse Representations）</news:title>
   <news:publication_date>2026-08-22T22:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726158</loc>
  <lastmod>2026-08-22T22:55:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元バスケット型アメリカンオプション評価における分散削減と機械学習の融合（Variance Reduction Applied to Machine Learning for Pricing Bermudan/American Options in High Dimension）</news:title>
   <news:publication_date>2026-08-22T22:55:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726156</loc>
  <lastmod>2026-08-22T22:55:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少データ問題と表現学習の総覧（Small Data Challenges in Big Data Era: A Survey of Recent Progress on Unsupervised and Semi-Supervised Methods）</news:title>
   <news:publication_date>2026-08-22T22:55:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726154</loc>
  <lastmod>2026-08-22T22:02:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度画像生成のためのAuto-Embedding GAN（Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis）</news:title>
   <news:publication_date>2026-08-22T22:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726152</loc>
  <lastmod>2026-08-22T22:02:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈要因を取り入れた経路選択モデルの高精度化（Improving Route Choice Models by Incorporating Contextual Factors via Knowledge Distillation）</news:title>
   <news:publication_date>2026-08-22T22:02:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726150</loc>
  <lastmod>2026-08-22T22:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラの色変換を真似ることで合成物を自然に見せる方法（Mimicking the In-Camera Color Pipeline for Camera-Aware Object Compositing）</news:title>
   <news:publication_date>2026-08-22T22:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726148</loc>
  <lastmod>2026-08-22T22:02:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>投擲ロボットの学習：任意物体を投げるTossingBot（TossingBot: Learning to Throw Arbitrary Objects with Residual Physics）</news:title>
   <news:publication_date>2026-08-22T22:02:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726146</loc>
  <lastmod>2026-08-22T22:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合マルチビューデータへの特徴選択（Feature Selection for Data Integration with Mixed Multi-View Data）</news:title>
   <news:publication_date>2026-08-22T22:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726144</loc>
  <lastmod>2026-08-22T22:01:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ない注釈で学ぶ深層共訓練による画像セグメンテーション（Deep Co-Training for Semi-Supervised Image Segmentation）</news:title>
   <news:publication_date>2026-08-22T22:01:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726142</loc>
  <lastmod>2026-08-22T22:01:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNの予測を「分解して説明する」手法の本質（On Attribution of Recurrent Neural Network Predictions via Additive Decomposition）</news:title>
   <news:publication_date>2026-08-22T22:01:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726140</loc>
  <lastmod>2026-08-22T21:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BAE-NETによる形状の共分割を促すブランチ型オートエンコーダ（BAE-NET: Branched Autoencoder for Shape Co-Segmentation）</news:title>
   <news:publication_date>2026-08-22T21:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726138</loc>
  <lastmod>2026-08-22T21:10:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量ロバスト推定の敵対的ロバストネス（On the Adversarial Robustness of Multivariate Robust Estimation）</news:title>
   <news:publication_date>2026-08-22T21:10:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726136</loc>
  <lastmod>2026-08-22T21:09:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震データ解釈におけるニューラルネットワークの実務応用（Neural-networks for geophysicists and their application to seismic data interpretation）</news:title>
   <news:publication_date>2026-08-22T21:09:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726134</loc>
  <lastmod>2026-08-22T21:08:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツイートの位置情報プライバシー侵害（Infringement of Tweets Geo-Location Privacy: an approach based on Graph Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-22T21:08:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726132</loc>
  <lastmod>2026-08-22T21:08:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組織学画像からの大腸癌診断：転移学習とCNNの比較検討（Colorectal cancer diagnosis from histology images: A comparative study）</news:title>
   <news:publication_date>2026-08-22T21:08:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726130</loc>
  <lastmod>2026-08-22T21:08:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集中型ベイズ実験計画のための層別多重重要度サンプリング（A layered multiple importance sampling scheme for focused optimal Bayesian experimental design）</news:title>
   <news:publication_date>2026-08-22T21:08:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726128</loc>
  <lastmod>2026-08-22T21:08:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル回帰におけるロバスト損失とIRLSによる最適化（Kernel based regression with robust loss function via iteratively reweighted least squares）</news:title>
   <news:publication_date>2026-08-22T21:08:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726126</loc>
  <lastmod>2026-08-22T20:16:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空撮における向き推定の汎化改善（Improved Generalization of Heading Direction Estimation for Aerial Filming Using Semi-Supervised Regression）</news:title>
   <news:publication_date>2026-08-22T20:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726124</loc>
  <lastmod>2026-08-22T20:16:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク化データにおける局所線形回帰（Localized Linear Regression in Networked Data）</news:title>
   <news:publication_date>2026-08-22T20:16:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726122</loc>
  <lastmod>2026-08-22T20:16:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低資源医用画像分類におけるCNN表現の評価（ON EVALUATING CNN REPRESENTATIONS FOR LOW RESOURCE MEDICAL IMAGE CLASSIFICATION）</news:title>
   <news:publication_date>2026-08-22T20:16:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726120</loc>
  <lastmod>2026-08-22T20:14:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化炭素ナノチューブに基づく可変ハイパーボリックメタマテリアル（Tunable Hyperbolic Metamaterials Based on Self-Assembled Carbon Nanotubes）</news:title>
   <news:publication_date>2026-08-22T20:14:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726118</loc>
  <lastmod>2026-08-22T20:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pix2Vex: 画像から形状を復元する滑らかな微分可能レンダラー（Pix2Vex: Image-to-Geometry Reconstruction using a Smooth Differentiable Renderer）</news:title>
   <news:publication_date>2026-08-22T20:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726116</loc>
  <lastmod>2026-08-22T20:14:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>せん断粒状断層における断続的摩擦ダイナミクスの機械学習解析（Machine Learning Reveals the State of Intermittent Frictional Dynamics in a Sheared Granular Fault）</news:title>
   <news:publication_date>2026-08-22T20:14:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726114</loc>
  <lastmod>2026-08-22T20:14:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きマルチソースTrAdaBoost（Weighted Multisource Tradaboost）</news:title>
   <news:publication_date>2026-08-22T20:14:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726112</loc>
  <lastmod>2026-08-22T19:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep segmentation networks predict survival of non-small cell lung cancer（Deep segmentation networks predict survival of non-small cell lung cancer）</news:title>
   <news:publication_date>2026-08-22T19:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726110</loc>
  <lastmod>2026-08-22T19:21:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多波長・多信号で迫るブラックホール合体の新展望（Multi-Messenger Astrophysics Opportunities with Stellar-Mass Binary Black Hole Mergers）</news:title>
   <news:publication_date>2026-08-22T19:21:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726108</loc>
  <lastmod>2026-08-22T19:21:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブルッフボディ上のランダム圧力場の動的モード分解（Dynamic mode decomposition of random pressure fields over bluff bodies）</news:title>
   <news:publication_date>2026-08-22T19:21:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726106</loc>
  <lastmod>2026-08-22T19:20:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスモーダルデータプログラミングによる迅速な医療機械学習（Cross-Modal Data Programming Enables Rapid Medical Machine Learning）</news:title>
   <news:publication_date>2026-08-22T19:20:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726104</loc>
  <lastmod>2026-08-22T19:20:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー保護を組み込んだ能動学習によるユーザー意図分類（Privacy-preserving Active Learning on Sensitive Data for User Intent Classification）</news:title>
   <news:publication_date>2026-08-22T19:20:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726102</loc>
  <lastmod>2026-08-22T19:20:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SuSiによる教師ありセルフオーガナイジングマップの実装と評価（SUSI: SUPERVISED SELF-ORGANIZING MAPS FOR REGRESSION AND CLASSIFICATION IN PYTHON）</news:title>
   <news:publication_date>2026-08-22T19:20:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726100</loc>
  <lastmod>2026-08-22T19:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー貯蔵の運用最適化を学ぶ：Deep Q-Networkによるリアルタイム制御（Energy Storage Management via Deep Q-Networks）</news:title>
   <news:publication_date>2026-08-22T19:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726098</loc>
  <lastmod>2026-08-22T18:27:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河の寄せ集め履歴を統合スペクトルから読み解く（A galaxy’s accretion history unveiled from its integrated spectrum）</news:title>
   <news:publication_date>2026-08-22T18:27:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726096</loc>
  <lastmod>2026-08-22T18:27:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移における被覆型活動銀河核の狭線領域の性質（Obscured AGN at 1.5 &amp;lt; z &amp;lt; 3.0 from the zCOSMOS-deep Survey）</news:title>
   <news:publication_date>2026-08-22T18:27:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726094</loc>
  <lastmod>2026-08-22T18:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分速単位の光学トランジェント探索が開く新領域（Probing the extragalactic fast transient sky at minute timescales with DECam）</news:title>
   <news:publication_date>2026-08-22T18:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726092</loc>
  <lastmod>2026-08-22T18:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移銀河の恒星金属量と質量の関係（The VANDELS survey: the stellar metallicities of star-forming galaxies at 2.5 &amp;lt; z &amp;lt; 5.0）</news:title>
   <news:publication_date>2026-08-22T18:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726090</loc>
  <lastmod>2026-08-22T18:24:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VANDELSサーベイが示す大質量休止銀河の形成史（The VANDELS survey: the star-formation histories of massive quiescent galaxies at 1.0 &amp;lt; z &amp;lt; 1.3）</news:title>
   <news:publication_date>2026-08-22T18:24:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726088</loc>
  <lastmod>2026-08-22T18:24:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>saVANtによるVAN強化（saVANt—VANs Enhanced by Importance and MCMC Sampling）</news:title>
   <news:publication_date>2026-08-22T18:24:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726086</loc>
  <lastmod>2026-08-22T18:23:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常軌跡検出を敵対的学習で行う手法（Adversarially Learned Abnormal Trajectory Classifier）</news:title>
   <news:publication_date>2026-08-22T18:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726084</loc>
  <lastmod>2026-08-22T17:32:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子特異的持続ホモロジーとタンパク質柔軟性解析への応用 (Atom-specific persistent homology and its application to protein flexibility analysis)</news:title>
   <news:publication_date>2026-08-22T17:32:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726082</loc>
  <lastmod>2026-08-22T17:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジで近リアルタイムに学習する物体検出の仕組み（RILOD: Near Real-Time Incremental Learning for Object Detection at the Edge）</news:title>
   <news:publication_date>2026-08-22T17:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726080</loc>
  <lastmod>2026-08-22T17:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転のためのマルチモーダルデータセットnuScenes（nuScenes: A multimodal dataset for autonomous driving）</news:title>
   <news:publication_date>2026-08-22T17:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726078</loc>
  <lastmod>2026-08-22T17:30:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン独立SVMによる脳デコーディングの転移学習（Domain Independent SVM for Transfer Learning in Brain Decoding）</news:title>
   <news:publication_date>2026-08-22T17:30:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726076</loc>
  <lastmod>2026-08-22T17:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習ネットワークをスパイキング化して耐性を高める（Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to Atari Breakout game）</news:title>
   <news:publication_date>2026-08-22T17:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726074</loc>
  <lastmod>2026-08-22T17:29:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正確で快適かつ人間らしい運転の学習（Learning Accurate, Comfortable and Human-like Driving）</news:title>
   <news:publication_date>2026-08-22T17:29:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726072</loc>
  <lastmod>2026-08-22T17:29:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>危機対応のためのツイート分類における深層学習とGloVeの有効性（Deep Learning and GloVe for Crisis Tweet Classification）</news:title>
   <news:publication_date>2026-08-22T17:29:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726070</loc>
  <lastmod>2026-08-22T16:38:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多項式時間でのShapley値近似による深層ニューラルネットワークの説明（Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Values Approximation）</news:title>
   <news:publication_date>2026-08-22T16:38:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726068</loc>
  <lastmod>2026-08-22T16:38:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非常に低解像度顔画像の照合とID保持型深層顔超解像ネットワーク（Verification of Very Low-Resolution Faces Using An Identity-Preserving Deep Face Super-resolution Network）</news:title>
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   <news:title>構造化された非線形変数選択（Structured Nonlinear Variable Selection）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>ハイブリッド古典量子線形方程式ソルバー（Hybrid classical-quantum linear solver using Noisy Intermediate-Scale Quantum machines）</news:title>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:title>回帰問題におけるTSKファジィシステム最適化（Optimize TSK Fuzzy Systems for Regression Problems: Mini-Batch Gradient Descent with Regularization, DropRule, and AdaBound）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>プロシューマー協力ゲームのスケーラビリティ改善（Improving the Scalability of a Prosumer Cooperative Game with K-Means Clustering）</news:title>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>バイアス補正が分散確率最適化に与える影響（On the Influence of Bias-Correction on Distributed Stochastic Optimization）</news:title>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>堅牢な5Gに向けて：LTEアップリンク妨害の実験的評価からの教訓（Towards Resilient 5G: Lessons Learned from Experimental Evaluations of LTE Uplink Jamming）</news:title>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>エッジ実装向けのディープデモザイシング（Deep Demosaicing for Edge Implementation）</news:title>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>安価な安静時EEGによる抑うつ検出の機械学習レビュー（Machine learning approaches in Detecting the Depression from Resting-state Electroencephalogram (EEG): A Review Study）</news:title>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>異種データセットにおけるワードスポッティングの信頼度評価（Exploring Confidence Measures for Word Spotting in Heterogeneous Datasets）</news:title>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:title>学習済み多様表現の組み合わせが実現する人間の知覚的類似性（High-Level Perceptual Similarity is Enabled by Learning Diverse Tasks）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-22T15:43:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-22T15:43:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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