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   <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>
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   <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>
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   <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>
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   <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>
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   <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>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>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>
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   <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>
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   <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>
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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>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>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-23T15:56:17Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>フォルムアルデヒド深遠探査（A Formaldehyde Deep Field）</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>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>
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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>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>
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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>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>
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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>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>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
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   <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>
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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>
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   <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>
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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>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>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <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>
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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>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>
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   <news:genres>Blog</news:genres>
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  <news:news>
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   <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>
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   <news:genres>Blog</news:genres>
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  <news:news>
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   <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>
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   <news:genres>Blog</news:genres>
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   <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>
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   <news:genres>Blog</news:genres>
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  <news:news>
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   <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>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
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    <news:language>ja</news:language>
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   <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>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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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>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>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>学習による重み付け（Learning to Weight for Text Classification）</news:title>
   <news:publication_date>2026-08-23T13:17:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <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>
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 <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>
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 <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>
  </news:news>
 </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>
   <news:publication_date>2026-08-23T11:29:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <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>
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 </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>
   <news:title>胸部疾患の局在化のためのマスク化変分潜在表現（InfoMask: Masked Variational Latent Representation to Localize Chest Disease）</news:title>
   <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>
  <loc>https://aibr.jp/archives/726286</loc>
  <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>
  <loc>https://aibr.jp/archives/726284</loc>
  <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>
  <loc>https://aibr.jp/archives/726282</loc>
  <lastmod>2026-08-23T07:04:51Z</lastmod>
  <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>
  </news:news>
 </url>
 <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>
 </url>
 <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>
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   <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>
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   <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>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/726140</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>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>
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 </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>
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   <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>
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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>2026-08-22T21:08:25Z</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>
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   <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>
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   <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>
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   <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>
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 </url>
 <url>
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  <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>
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   <news:genres>Blog</news:genres>
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 </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>
   <news:publication_date>2026-08-22T16:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726066</loc>
  <lastmod>2026-08-22T16:37:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化された非線形変数選択（Structured Nonlinear Variable Selection）</news:title>
   <news:publication_date>2026-08-22T16:37:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726064</loc>
  <lastmod>2026-08-22T16:37:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド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>
   <news:publication_date>2026-08-22T16:37:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726062</loc>
  <lastmod>2026-08-22T16:36:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-08-22T16:36:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726060</loc>
  <lastmod>2026-08-22T16:36:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-08-22T16:36:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726058</loc>
  <lastmod>2026-08-22T16:36:10Z</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>
   <news:publication_date>2026-08-22T16:36:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726056</loc>
  <lastmod>2026-08-22T15:44:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-08-22T15:44:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726054</loc>
  <lastmod>2026-08-22T15:44:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-08-22T15:44:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726052</loc>
  <lastmod>2026-08-22T15:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-08-22T15:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726050</loc>
  <lastmod>2026-08-22T15:43:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
   <news:publication_date>2026-08-22T15:43:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726048</loc>
  <lastmod>2026-08-22T15:43:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習済み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>
   <news:publication_date>2026-08-22T15:43:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726046</loc>
  <lastmod>2026-08-22T15:43:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分ラベル付きネットワークデータの分類とLogistic Network Lasso（Classifying Partially Labeled Networked Data via Logistic Network Lasso）</news:title>
   <news:publication_date>2026-08-22T15:43:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726044</loc>
  <lastmod>2026-08-22T15:43:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かなデータから信頼できる事例を選ぶ方法（A method on selecting reliable samples based on fuzziness in positive and unlabeled learning）</news:title>
   <news:publication_date>2026-08-22T15:43:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726042</loc>
  <lastmod>2026-08-22T14:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線ネットワークにおける干渉予測（Interference Prediction in Wireless Networks: Stochastic Geometry meets Recursive Filtering）</news:title>
   <news:publication_date>2026-08-22T14:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726040</loc>
  <lastmod>2026-08-22T14:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ主導の機械学習システム設計（Data Science and Digital Systems: The 3Ds of Machine Learning Systems Design）</news:title>
   <news:publication_date>2026-08-22T14:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726038</loc>
  <lastmod>2026-08-22T14:51:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの写真実写的顔ディテール合成 (Photo-Realistic Facial Details Synthesis From Single Image)</news:title>
   <news:publication_date>2026-08-22T14:51:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726036</loc>
  <lastmod>2026-08-22T14:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いたベイズ推論の高速化（Accelerated Bayesian inference using deep learning）</news:title>
   <news:publication_date>2026-08-22T14:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726034</loc>
  <lastmod>2026-08-22T14:50:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オランダF3地震データセット：地震解釈の機械学習向け新公開データセット（Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation）</news:title>
   <news:publication_date>2026-08-22T14:50:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726032</loc>
  <lastmod>2026-08-22T14:50:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アクティブスタッキングによる心拍数推定（Active Stacking for Heart Rate Estimation）</news:title>
   <news:publication_date>2026-08-22T14:50:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726030</loc>
  <lastmod>2026-08-22T13:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロ構造画像から物性を予測するデータ駆動手法（Data-Driven Microstructure Property Relations）</news:title>
   <news:publication_date>2026-08-22T13:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726028</loc>
  <lastmod>2026-08-22T13:46:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルエッジコンピューティングにおける計算複製の活用（Exploiting Computation Replication for Mobile Edge Computing）</news:title>
   <news:publication_date>2026-08-22T13:46:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726026</loc>
  <lastmod>2026-08-22T13:46:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽のテンポと調（キー）推定を軸方向フィルタ付きCNNで解く（Musical Tempo and Key Estimation using Convolutional Neural Networks with Directional Filters）</news:title>
   <news:publication_date>2026-08-22T13:46:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726024</loc>
  <lastmod>2026-08-22T13:45:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク再構築とコミュニティ検出（Network reconstruction and community detection from dynamics）</news:title>
   <news:publication_date>2026-08-22T13:45:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/726022</loc>
  <lastmod>2026-08-22T13:45:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模インタラクティブ物体セグメンテーションと人間アノテータ（Large-scale interactive object segmentation with human annotators）</news:title>
   <news:publication_date>2026-08-22T13:45:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726020</loc>
  <lastmod>2026-08-22T13:45:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何学に着想を得た決定ベース攻撃（A geometry-inspired decision-based attack）</news:title>
   <news:publication_date>2026-08-22T13:45:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726018</loc>
  <lastmod>2026-08-22T13:45:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライブ映像における顔のピクセレーション手法の実装と評価（Pixelation is NOT Done in Videos Yet）</news:title>
   <news:publication_date>2026-08-22T13:45:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726016</loc>
  <lastmod>2026-08-22T12:53:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスモーダル部分空間学習：カーネル相関最大化と識別構造保持（Cross-modal Subspace Learning via Kernel Correlation Maximization and Discriminative Structure Preserving）</news:title>
   <news:publication_date>2026-08-22T12:53:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726014</loc>
  <lastmod>2026-08-22T12:53:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stacked Monte Carloを用いたオプション価格評価の分散削減（STACKED MONTE CARLO FOR OPTION PRICING）</news:title>
   <news:publication_date>2026-08-22T12:53:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726012</loc>
  <lastmod>2026-08-22T12:52:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RecSys-DANによるクロスドメイン推薦の実務的意義（RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems）</news:title>
   <news:publication_date>2026-08-22T12:52:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726010</loc>
  <lastmod>2026-08-22T12:51:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>どこを見ればよいかを学ぶ―IHC画像スコアリングに対する注目モデル（Learning Where to See: A Novel Attention Model for Automated Immunohistochemical Scoring）</news:title>
   <news:publication_date>2026-08-22T12:51:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726008</loc>
  <lastmod>2026-08-22T12:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高精度なインスタンス認識型セマンティック3Dマップの構築（High-quality Instance-aware Semantic 3D Map Using RGB-D Camera）</news:title>
   <news:publication_date>2026-08-22T12:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726006</loc>
  <lastmod>2026-08-22T12:51:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙データからICMEを自動検出する深層学習法（Automatic detection of Interplanetary Coronal Mass Ejections from in-situ data: a deep learning approach）</news:title>
   <news:publication_date>2026-08-22T12:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726004</loc>
  <lastmod>2026-08-22T12:51:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間的一貫性を備えた深度予測と意味理解の統合（Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach）</news:title>
   <news:publication_date>2026-08-22T12:51:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726002</loc>
  <lastmod>2026-08-22T11:59:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的テンソルネットワークによる教師あり学習モデル（Generative Tensor Network Classification Model for Supervised Machine Learning）</news:title>
   <news:publication_date>2026-08-22T11:59:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/726000</loc>
  <lastmod>2026-08-22T11:49:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>いつ量子コンピュータは実用化するのか（When will we have a quantum computer?）</news:title>
   <news:publication_date>2026-08-22T11:49:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725998</loc>
  <lastmod>2026-08-22T11:49:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超音波検査データの拡張で機械学習が超人性能を示す（Augmented Ultrasonic Data for Machine Learning）</news:title>
   <news:publication_date>2026-08-22T11:49:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725996</loc>
  <lastmod>2026-08-22T11:47:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械間相互運用性と機械間翻訳モデル（Interoperability and machine-to-machine translation model with mappings to machine learning tasks）</news:title>
   <news:publication_date>2026-08-22T11:47:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725994</loc>
  <lastmod>2026-08-22T11:47:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒト表現型と遺伝子の関係を大規模に作る手法（A Silver Standard Corpus of Human Phenotype-Gene Relations）</news:title>
   <news:publication_date>2026-08-22T11:47:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725992</loc>
  <lastmod>2026-08-22T11:47:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小規模データセット向け画像分類器の改善：学習率適応による高速化と精度向上（Improving image classifiers for small datasets by learning rate adaptations）</news:title>
   <news:publication_date>2026-08-22T11:47:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725990</loc>
  <lastmod>2026-08-22T11:47:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多声部歌唱合成をGANで実現する試み（WGANSing: A Multi-Voice Singing Voice Synthesizer Based on the Wasserstein-GAN）</news:title>
   <news:publication_date>2026-08-22T11:47:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725988</loc>
  <lastmod>2026-08-22T10:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン表現による知識グラフ埋め込み（Domain Representation for Knowledge Graph Embedding）</news:title>
   <news:publication_date>2026-08-22T10:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725986</loc>
  <lastmod>2026-08-22T10:44:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル非教師ありハッシングによる高速クロスモーダル検索（Unsupervised Multi-modal Hashing for Cross-Modal Retrieval）</news:title>
   <news:publication_date>2026-08-22T10:44:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725984</loc>
  <lastmod>2026-08-22T10:43:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外科ナビゲーション向けソフト組織挙動の学習（Learning Soft Tissue Behavior of Organs for Surgical Navigation with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-22T10:43:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725982</loc>
  <lastmod>2026-08-22T10:42:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Autoencoding Binary Classifiersによる教師付き異常検出の革新（Autoencoding Binary Classifiers for Supervised Anomaly Detection）</news:title>
   <news:publication_date>2026-08-22T10:42:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725980</loc>
  <lastmod>2026-08-22T10:42:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的グラフ回帰の理論と実装的示唆（On the Theory of Dynamic Graph Regression Problem）</news:title>
   <news:publication_date>2026-08-22T10:42:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725978</loc>
  <lastmod>2026-08-22T10:42:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽器トランジェントを学習する条件付けRNN（Conditioning a Recurrent Neural Network to synthesize musical instrument transients）</news:title>
   <news:publication_date>2026-08-22T10:42:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725976</loc>
  <lastmod>2026-08-22T10:42:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケールCNNと動的トリプレットロスによる生物音響分類の進展（Multiscale CNN based Deep Metric Learning for Bioacoustic Classification）</news:title>
   <news:publication_date>2026-08-22T10:42:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725974</loc>
  <lastmod>2026-08-22T09:50:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>影除去を学習するMask-ShadowGAN（Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data）</news:title>
   <news:publication_date>2026-08-22T09:50:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725972</loc>
  <lastmod>2026-08-22T09:50:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点予測を取り込む確率的負荷予測の二段階フレームワーク（Probabilistic Load Forecasting via Point Forecast Feature Integration）</news:title>
   <news:publication_date>2026-08-22T09:50:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725970</loc>
  <lastmod>2026-08-22T09:49:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化された畳み込みと効率的な言語認識（Generalized Convolution and Efficient Language Recognition）</news:title>
   <news:publication_date>2026-08-22T09:49:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725968</loc>
  <lastmod>2026-08-22T09:49:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる集約レベルにおける短期負荷予測と予測可能性の解析（Short-term Load Forecasting at Different Aggregation Levels with Predictability Analysis）</news:title>
   <news:publication_date>2026-08-22T09:49:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725966</loc>
  <lastmod>2026-08-22T09:49:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド密度汎関数の最適化におけるベイズ最適化の応用（Bayesian optimization for tuning and selecting hybrid-density functionals）</news:title>
   <news:publication_date>2026-08-22T09:49:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725964</loc>
  <lastmod>2026-08-22T09:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AlphaXによるニューラルアーキテクチャ探索（AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search）</news:title>
   <news:publication_date>2026-08-22T09:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725962</loc>
  <lastmod>2026-08-22T09:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ量子化に対するニューラルネットワークの頑健性（Robustness of Neural Networks to Parameter Quantization）</news:title>
   <news:publication_date>2026-08-22T09:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725960</loc>
  <lastmod>2026-08-22T08:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ルールベースエージェントの失敗シナリオ生成（Failure-Scenario Maker for Rule-Based Agent using Multi-agent Adversarial Reinforcement Learning and its Application to Autonomous Driving）</news:title>
   <news:publication_date>2026-08-22T08:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725958</loc>
  <lastmod>2026-08-22T08:48:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による非並列コーパスでの文章スタイル変換（Reinforcement Learning Based Text Style Transfer without Parallel Training Corpus）</news:title>
   <news:publication_date>2026-08-22T08:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725956</loc>
  <lastmod>2026-08-22T08:47:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工ヒューマン最適化（Artificial Human Optimization）分野の出発点（Novel Artificial Human Optimization Field Algorithms – The Beginning）</news:title>
   <news:publication_date>2026-08-22T08:47:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725954</loc>
  <lastmod>2026-08-22T08:47:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数グローバル記述子の組合せによる画像検索改善（Combination of Multiple Global Descriptors for Image Retrieval）</news:title>
   <news:publication_date>2026-08-22T08:47:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725952</loc>
  <lastmod>2026-08-22T08:45:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔ランドマーク検出における意味的一致の追求（Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection）</news:title>
   <news:publication_date>2026-08-22T08:45:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725950</loc>
  <lastmod>2026-08-22T08:45:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復平均の重み付けによる鞍点問題解法（Increasing iterate averaging for solving saddle-point problems）</news:title>
   <news:publication_date>2026-08-22T08:45:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725948</loc>
  <lastmod>2026-08-22T08:45:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造情報を用いたドメイン適応によるセマンティックセグメンテーションの強化（All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation）</news:title>
   <news:publication_date>2026-08-22T08:45:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725946</loc>
  <lastmod>2026-08-22T07:53:03Z</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結果の異常を検知するアラームシステム（An Alarm System for Segmentation Algorithm Based on Shape Model）</news:title>
   <news:publication_date>2026-08-22T07:53:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725944</loc>
  <lastmod>2026-08-22T07:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デバイス上で学ぶ未登録語の連合学習（Federated Learning Of Out-Of-Vocabulary Words）</news:title>
   <news:publication_date>2026-08-22T07:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725942</loc>
  <lastmod>2026-08-22T07:52:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>翻訳で見落とす最適化機会（Lost in translation: Exposing hidden compiler optimization opportunities）</news:title>
   <news:publication_date>2026-08-22T07:52:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725940</loc>
  <lastmod>2026-08-22T07:51:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応可能なソフトウェアの性能モデルにおける再訓練型と増分学習の比較（On Using Retrained and Incremental Machine Learning for Modeling Performance of Adaptable Software: An Empirical Comparison）</news:title>
   <news:publication_date>2026-08-22T07:51:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725938</loc>
  <lastmod>2026-08-22T07:51:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固有値と一般化固有値問題のチュートリアル（Eigenvalue and Generalized Eigenvalue Problems: Tutorial）</news:title>
   <news:publication_date>2026-08-22T07:51:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725936</loc>
  <lastmod>2026-08-22T07:51:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続行動空間におけるQ学習とCross-Entropy Guided Policies（Q-Learning for Continuous Actions with Cross-Entropy Guided Policies）</news:title>
   <news:publication_date>2026-08-22T07:51:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725934</loc>
  <lastmod>2026-08-22T07:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応型自動脅威認識による手荷物CT解析の革新（An Approach for Adaptive Automatic Threat Recognition Within 3D Computed Tomography Images for Baggage Security Screening）</news:title>
   <news:publication_date>2026-08-22T07:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725932</loc>
  <lastmod>2026-08-22T06:50:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしドメイン適応とゼロショット視覚認識の統合 (Unifying Unsupervised Domain Adaptation and Zero-Shot Visual Recognition)</news:title>
   <news:publication_date>2026-08-22T06:50:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725930</loc>
  <lastmod>2026-08-22T06:50:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非差別的意思決定のための最適かつ公正な決定木の学習（Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making）</news:title>
   <news:publication_date>2026-08-22T06:50:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725928</loc>
  <lastmod>2026-08-22T06:49:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>白箱（ホワイトボックス）攻撃に対するランダム化離散化による防御（Defending against Whitebox Adversarial Attacks via Randomized Discretization）</news:title>
   <news:publication_date>2026-08-22T06:49:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725926</loc>
  <lastmod>2026-08-22T06:49:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応型ネットワークによる動きぼけ除去 (Motion Deblurring with an Adaptive Network)</news:title>
   <news:publication_date>2026-08-22T06:49:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725924</loc>
  <lastmod>2026-08-22T06:49:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カプセルネットワークの情報希薄化を抑える実践的改善法（Reducing the dilution: An analysis of the information sensitiveness of capsule network with a practical improvement method）</news:title>
   <news:publication_date>2026-08-22T06:49:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725922</loc>
  <lastmod>2026-08-22T06:49:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度数値表現が変えるDNNの実用性（Performance-Efficiency Trade-off of Low-Precision Numerical Formats in Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-22T06:49:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725920</loc>
  <lastmod>2026-08-22T05:57:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像から便を識別する深層学習の試み（Augmenting Gastrointestinal Health: A Deep Learning Approach to Human Stool Recognition and Characterization in Macroscopic Images）</news:title>
   <news:publication_date>2026-08-22T05:57:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725918</loc>
  <lastmod>2026-08-22T05:57:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TSKファジィと機械学習の機能同値性が示す実務への示唆（On the Functional Equivalence of TSK Fuzzy Systems to Neural Networks, Mixture of Experts, CART, and Stacking Ensemble Regression）</news:title>
   <news:publication_date>2026-08-22T05:57:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725916</loc>
  <lastmod>2026-08-22T05:56:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的表面最適化と対数密度推定（General Probabilistic Surface Optimization and Log Density Estimation）</news:title>
   <news:publication_date>2026-08-22T05:56:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725914</loc>
  <lastmod>2026-08-22T05:55:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム条件付分布による分布的推論の体系化（The Random Conditional Distribution For Higher-Order Probabilistic Inference）</news:title>
   <news:publication_date>2026-08-22T05:55:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725912</loc>
  <lastmod>2026-08-22T05:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺内における局在化のための深層学習（Deep Learning for Localization in the Lung）</news:title>
   <news:publication_date>2026-08-22T05:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725910</loc>
  <lastmod>2026-08-22T05:55:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文エンコーダーにおける社会的バイアスの測定（On Measuring Social Biases in Sentence Encoders）</news:title>
   <news:publication_date>2026-08-22T05:55:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725908</loc>
  <lastmod>2026-08-22T05:54:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Machine learningと物理科学の接点（Machine learning and the physical sciences）</news:title>
   <news:publication_date>2026-08-22T05:54:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725906</loc>
  <lastmod>2026-08-22T05:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Shannonエントロピーに基づく質問埋め込み（Question Embeddings Based on Shannon Entropy）</news:title>
   <news:publication_date>2026-08-22T05:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725904</loc>
  <lastmod>2026-08-22T05:03:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像から学習データを作る画素平均化法（A Novel Pixel-Averaging Technique for Extracting Training Data from a Single Image, Used in ML-Based Image Enlargement）</news:title>
   <news:publication_date>2026-08-22T05:03:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725902</loc>
  <lastmod>2026-08-22T05:03:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gated Spatio-Temporal Energy Graphによる動画関係推論（Video Relationship Reasoning using Gated Spatio-Temporal Energy Graph）</news:title>
   <news:publication_date>2026-08-22T05:03:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725900</loc>
  <lastmod>2026-08-22T05:02:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現データを用いた生存予測のトピックモデリング手法（Gene Expression based Survival Prediction for Cancer Patients – A Topic Modeling Approach）</news:title>
   <news:publication_date>2026-08-22T05:02:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725898</loc>
  <lastmod>2026-08-22T05:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勝つことがすべてではない：ゲーム開発を支える知的エージェントの活用（Winning Isn’t Everything: Enhancing Game Development with Intelligent Agents）</news:title>
   <news:publication_date>2026-08-22T05:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725896</loc>
  <lastmod>2026-08-22T05:01:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子コンピューティングの次の一手（Next Steps in Quantum Computing: Computer Science’s Role）</news:title>
   <news:publication_date>2026-08-22T05:01:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725894</loc>
  <lastmod>2026-08-22T05:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Geometry-Awareなカリキュラム学習による単眼視覚オドメトリの習得（Learning Monocular Visual Odometry through Geometry-Aware Curriculum Learning）</news:title>
   <news:publication_date>2026-08-22T05:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725892</loc>
  <lastmod>2026-08-22T04:10:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽とダンスで学ぶ具現化された意味（Learning embodied semantics via music and dance）</news:title>
   <news:publication_date>2026-08-22T04:10:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725890</loc>
  <lastmod>2026-08-22T04:09:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークで学ぶロボット群の分散制御器学習 (Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks)</news:title>
   <news:publication_date>2026-08-22T04:09:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725888</loc>
  <lastmod>2026-08-22T04:09:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆最適計画による空域運用学習（Inverse Optimal Planning for Air Traffic Control）</news:title>
   <news:publication_date>2026-08-22T04:09:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725886</loc>
  <lastmod>2026-08-22T04:08:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロバッチ学習における重み標準化とバッチ・チャンネル正規化（Micro-Batch Training with Batch-Channel Normalization and Weight Standardization）</news:title>
   <news:publication_date>2026-08-22T04:08:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725884</loc>
  <lastmod>2026-08-22T04:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DUNE-PRISMによる軽質暗黒物質探索の新戦略（Hunting On- and Off-Axis for Light Dark Matter with DUNE-PRISM）</news:title>
   <news:publication_date>2026-08-22T04:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725882</loc>
  <lastmod>2026-08-22T04:08:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダークマター密度場からハローを描く物理的に動機付けられたニューラルネットワーク（Painting halos from cosmic density fields of dark matter with physically motivated neural networks）</news:title>
   <news:publication_date>2026-08-22T04:08:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725880</loc>
  <lastmod>2026-08-22T04:08:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>K2データにおける深層学習での系外惑星同定（Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data）</news:title>
   <news:publication_date>2026-08-22T04:08:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/725878</loc>
  <lastmod>2026-08-22T03:14:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴量の依存を考慮した個別予測説明の改良（Explaining Individual Predictions When Features Are Dependent: More Accurate Approximations to Shapley Values）</news:title>
   <news:publication_date>2026-08-22T03:14:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725876</loc>
  <lastmod>2026-08-22T03:14:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー生成コンテンツの差分プライバシー表現学習（dpUGC: Learn Differentially Private Representation for User Generated Contents）</news:title>
   <news:publication_date>2026-08-22T03:14:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725874</loc>
  <lastmod>2026-08-22T02:22:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CODAによるスケール認識型敵対的密度適応による物体カウント改善（CODA: COUNTING OBJECTS VIA SCALE-AWARE ADVERSARIAL DENSITY ADAPTION）</news:title>
   <news:publication_date>2026-08-22T02:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725872</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>多面的な社会的影響を深く捉える二重グラフ注意ネットワーク（Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems）</news:title>
   <news:publication_date>2026-08-22T02:21:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725870</loc>
  <lastmod>2026-08-22T02:20:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的コンテクストを用いたスケール適応型密特徴（Scale-Adaptive Neural Dense Features: Learning via Hierarchical Context Aggregation）</news:title>
   <news:publication_date>2026-08-22T02:20:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725868</loc>
  <lastmod>2026-08-22T02:20:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生物から学ぶ「自己学習する知能」の枠組み（A Conceptual Bio-Inspired Framework for the Evolution of Artificial General Intelligence）</news:title>
   <news:publication_date>2026-08-22T02:20:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725866</loc>
  <lastmod>2026-08-22T02:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショット学習に基づく人体活動認識（Few-Shot Learning-Based Human Activity Recognition）</news:title>
   <news:publication_date>2026-08-22T02:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725864</loc>
  <lastmod>2026-08-22T02:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共同手-物体姿勢推定の一般化されたフィードバックループ（Generalized Feedback Loop for Joint Hand-Object Pose Estimation）</news:title>
   <news:publication_date>2026-08-22T02:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725862</loc>
  <lastmod>2026-08-22T01:28:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み強化学習のための深層オートエンコーダ活用（On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-22T01:28:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725860</loc>
  <lastmod>2026-08-22T01:27:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サレー市における子どもの脆弱性の可視化（Understanding Childhood Vulnerability in The City of Surrey）</news:title>
   <news:publication_date>2026-08-22T01:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725858</loc>
  <lastmod>2026-08-22T01:27:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LogBarrier擾乱攻撃の実践的解説 (THE LOGBARRIER ADVERSARIAL ATTACK)</news:title>
   <news:publication_date>2026-08-22T01:27:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725856</loc>
  <lastmod>2026-08-22T01:26:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>おおまかな確率的保証に基づくナッシュ均衡学習（Probably Approximately Correct Nash Equilibrium Learning）</news:title>
   <news:publication_date>2026-08-22T01:26:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725854</loc>
  <lastmod>2026-08-22T01:26:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一細胞アプローチによる細胞競合の解析（Single-cell approaches to cell competition: high-throughput imaging, machine learning and simulations）</news:title>
   <news:publication_date>2026-08-22T01:26:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725852</loc>
  <lastmod>2026-08-22T01:26:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所直交分解による高速内積探索の実務的解説（Local Orthogonal Decomposition for Maximum Inner Product Search）</news:title>
   <news:publication_date>2026-08-22T01:26:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725843</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>コードスイッチング音声・言語処理の包括的レビュー（A Survey of Code-switched Speech and Language Processing）</news:title>
   <news:publication_date>2026-08-22T00:34:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725841</loc>
  <lastmod>2026-08-22T00:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-22T00:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725839</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-22T00:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725837</loc>
  <lastmod>2026-08-22T00:32:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンゴ葉の病害識別のための領域注目型深層畳み込みニューラルネットワーク（Apple Leaf Disease Identification through Region-of-Interest-Aware Deep Convolutional Neural Network）</news:title>
   <news:publication_date>2026-08-22T00:32:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725835</loc>
  <lastmod>2026-08-22T00:32:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識CNNの雑音耐性トレーニングパラダイム（Noise-Tolerant Paradigm for Training Face Recognition CNNs）</news:title>
   <news:publication_date>2026-08-22T00:32:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725833</loc>
  <lastmod>2026-08-22T00:31:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形システム同定のサンプル複雑度下限（Sample Complexity Lower Bounds for Linear System Identification）</news:title>
   <news:publication_date>2026-08-22T00:31:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725831</loc>
  <lastmod>2026-08-22T00:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測・ノイズ下でカオス的力学を学習するEM様手法（EM-like Learning Chaotic Dynamics from Noisy and Partial Observations）</news:title>
   <news:publication_date>2026-08-22T00:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725829</loc>
  <lastmod>2026-08-21T23:39:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配ハミルトニアンモンテカルロによる非凸最適化の収束解析（Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Learning）</news:title>
   <news:publication_date>2026-08-21T23:39:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725827</loc>
  <lastmod>2026-08-21T23:38:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合デモンストレーションからのマルチモーダル方策学習（Learning a Multi-Modal Policy via Imitating Demonstrations with Mixed Behaviors）</news:title>
   <news:publication_date>2026-08-21T23:38:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725825</loc>
  <lastmod>2026-08-21T23:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>降水パラメータ化のデータ駆動アプローチ（A Data-Driven Approach to Precipitation Parameterizations Using Convolutional Encoder-Decoder Neural Networks）</news:title>
   <news:publication_date>2026-08-21T23:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725823</loc>
  <lastmod>2026-08-21T23:37:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>政策論争における内生的連携形成（Endogenous Coalition Formation in Policy Debates）</news:title>
   <news:publication_date>2026-08-21T23:37:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725821</loc>
  <lastmod>2026-08-21T23:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多数のセンサーとアクチュエータで知覚と制御を成し遂げる考え方（Perceptual Control with Large Feature and Actuator Networks）</news:title>
   <news:publication_date>2026-08-21T23:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725819</loc>
  <lastmod>2026-08-21T23:37:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主に非循環有向ネットワークの地平線ダイナミクス（Network Horizon Dynamics I: Qualitative Aspects）</news:title>
   <news:publication_date>2026-08-21T23:37:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725817</loc>
  <lastmod>2026-08-21T22:45:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MetaPruningによる自動チャネルプルーニング（MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning）</news:title>
   <news:publication_date>2026-08-21T22:45:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725815</loc>
  <lastmod>2026-08-21T22:45:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>呼吸位相検出のための畳み込みニューラルネットワーク（Convolutional neural network for breathing phase detection in lung sounds）</news:title>
   <news:publication_date>2026-08-21T22:45:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725813</loc>
  <lastmod>2026-08-21T22:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的特徴から学ぶ少数ショット分類（Learning from Adversarial Features for Few-Shot Classification）</news:title>
   <news:publication_date>2026-08-21T22:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725811</loc>
  <lastmod>2026-08-21T22:44:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノ機械振動子のレーザー冷却でゼロ点エネルギーへ到達（Laser cooling of a nanomechanical oscillator to the zero-point energy）</news:title>
   <news:publication_date>2026-08-21T22:44:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725809</loc>
  <lastmod>2026-08-21T22:44:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期言語発達の計算論的・ロボティクスモデルの概観（Computational and Robotic Models of Early Language Development: A Review）</news:title>
   <news:publication_date>2026-08-21T22:44:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725807</loc>
  <lastmod>2026-08-21T22:43:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズを前提にしたベクトル空間の整列（Aligning Vector-spaces with Noisy Supervised Lexicons）</news:title>
   <news:publication_date>2026-08-21T22:43:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725805</loc>
  <lastmod>2026-08-21T21:52:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>精度への道：機械学習で加速するシリコンのab initioシミュレーション（The road to accuracy: machine-learning-accelerated silicon ab initio simulations）</news:title>
   <news:publication_date>2026-08-21T21:52:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725803</loc>
  <lastmod>2026-08-21T21:52:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マニフォールド基準で導く転移学習（Manifold Criterion Guided Transfer Learning）</news:title>
   <news:publication_date>2026-08-21T21:52:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725801</loc>
  <lastmod>2026-08-21T21:52:29Z</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>2026-08-21T21:52:29Z</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>ファイルのエントロピー信号と機械学習による電子文書内悪性コードの検出（Capturing the symptoms of malicious code in electronic documents by file’s entropy signal combined with Machine learning）</news:title>
   <news:publication_date>2026-08-21T21:51:42Z</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>音声から顔を生成する技術の要点（WAV2PIX: SPEECH-CONDITIONED FACE GENERATION USING GENERATIVE ADVERSARIAL NETWORKS）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブマイクロ秒で動く高性能DNNをFPGAへ実装する手法（Implementation of high-performance, sub-microsecond deep neural networks on FPGAs for trigger applications）</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>偏光から学ぶ深層形状推定（Deep Shape from Polarization）</news:title>
   <news:publication_date>2026-08-21T21:51:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LOGAN: 潜在的過完備空間における非対応形状変換（LOGAN: Unpaired Shape Transform in Latent Overcomplete Space）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶を使って高速化するモバイル映像物体検出（Looking Fast and Slow: Memory-Guided Mobile Video Object Detection）</news:title>
   <news:publication_date>2026-08-21T21:00:05Z</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>
   </news:publication>
   <news:title>DeepRED: Deep Image PriorとREDを組み合わせた画像逆問題の新展開（DeepRED: Deep Image Prior Powered by RED）</news:title>
   <news:publication_date>2026-08-21T20:59:45Z</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>学習されたカーネルを用いるダウンスケーリングによる非均一単一画像のデブラー（Down-Scaling with Learned Kernels in Multi-Scale Deep Neural Networks for Non-Uniform Single Image Deblurring）</news:title>
   <news:publication_date>2026-08-21T20:59:23Z</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>空間減衰文脈による顕著物体検出の統合的手法（SAC-Net: Spatial Attenuation Context for Salient Object Detection）</news:title>
   <news:publication_date>2026-08-21T20:59:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725781</loc>
  <lastmod>2026-08-21T20:59:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波で指の個別動作を読み取るためのアンサンブル学習（An Ensemble Learning Based Classification of Individual Finger Movement from EEG）</news:title>
   <news:publication_date>2026-08-21T20:59:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725779</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>深層無監督ドメイン適応の高速化（Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning）</news:title>
   <news:publication_date>2026-08-21T20:58:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期的アニーリングスケジュールによるKL消失の抑制（Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing）</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>ImageNetの学習済み分類層を活かす転移学習の再考（Enhanced Transfer Learning with ImageNet Trained Classification Layer）</news:title>
   <news:publication_date>2026-08-21T19:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク特化型埋め込み変換とアテンションネットワークによる複数の人口統計属性予測（Predicting Multiple Demographic Attributes with Task Specific Embedding Transformation and Attention Network）</news:title>
   <news:publication_date>2026-08-21T19:56:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習とセグメンテーション情報をGANで組み合わせた学習データ非依存の画像登録（COMBINING TRANSFER LEARNING AND SEGMENTATION INFORMATION WITH GANS FOR TRAINING DATA INDEPENDENT IMAGE REGISTRATION）</news:title>
   <news:publication_date>2026-08-21T19:55:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-21T19:55:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Iris R-CNNによる非協調環境下の虹彩分割（Iris R-CNN: Accurate Iris Segmentation in Non-cooperative Environment）</news:title>
   <news:publication_date>2026-08-21T19:55:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>任意ショット学習のための特徴生成フレームワーク（f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning）</news:title>
   <news:publication_date>2026-08-21T19:54:59Z</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>異種表現で言語と知識をつなぐ手法（Connecting Language and Knowledge with Heterogeneous Representations for Neural Relation Extraction）</news:title>
   <news:publication_date>2026-08-21T19:04:10Z</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>サイクル一貫性を用いた画像→キャプションのエンドツーエンド学習（End-to-End Learning Using Cycle Consistency for Image-to-Caption Transformations）</news:title>
   <news:publication_date>2026-08-21T18:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T18:52:47Z</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>2026-08-21T18:52:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-21T18:52:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T18:52:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差非局所注意ネットワークによる画像復元（Residual Non-Local Attention Networks for Image Restoration）</news:title>
   <news:publication_date>2026-08-21T18:52:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T18:51:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>査読理解のための論証マイニング（Argument Mining for Understanding Peer Reviews）</news:title>
   <news:publication_date>2026-08-21T18:51:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725751</loc>
  <lastmod>2026-08-21T18:51:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁気共鳻画像再構成のための変換学習（Transform Learning for Magnetic Resonance Image Reconstruction: From Model-based Learning to Building Neural Networks）</news:title>
   <news:publication_date>2026-08-21T18:51:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T18:00:02Z</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>2026-08-21T17:59:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>真のバッチ弟子学習と深層サクセッサーフィーチャー（Truly Batch Apprenticeship Learning with Deep Successor Features）</news:title>
   <news:publication_date>2026-08-21T17:59:39Z</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>確率ジャンプ線形系の安全な学習ベース制御（Safe Learning-Based Control of Stochastic Jump Linear Systems: a Distributionally Robust Approach）</news:title>
   <news:publication_date>2026-08-21T17:58:37Z</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>多クラス組織病理画像分類のための畳み込みニューラルネットワーク（Convolutional Neural Networks for Multi-class Histopathology Image Classification）</news:title>
   <news:publication_date>2026-08-21T17:58:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725741</loc>
  <lastmod>2026-08-21T17:58:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lasso Weighted k-meansが示す高次元クラスタリングの新基準（A Strongly Consistent Sparse k-means Clustering with Direct l1 Penalization on Variable Weights）</news:title>
   <news:publication_date>2026-08-21T17:58:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T17:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ResNet型畳み込みニューラルネットワークの近似と非パラメトリック推定（Approximation and Non-parametric Estimation of ResNet-type Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-21T17:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T17:06:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの堅牢性の形式化（A Formalization of Robustness for Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-21T17:06:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-21T17:06:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-21T17:05:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>合成データと半教師あり学習で小規模・不均衡データを活用する手法（Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-21T17:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別的部分グラフ学習によるネットワーク状態予測（Discriminative Subgraph Learning via Sparse Self-Representation）</news:title>
   <news:publication_date>2026-08-21T17:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725727</loc>
  <lastmod>2026-08-21T17:04:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SNR適応型ID-OCTAによる血管可視化の精度向上（SNR-adaptive ID-OCTA）</news:title>
   <news:publication_date>2026-08-21T17:04:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725725</loc>
  <lastmod>2026-08-21T17:03:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速アップリンク割当てとNOMAへのFederated Learning応用（Fast Uplink Grant for NOMA: a Federated Learning based Approach）</news:title>
   <news:publication_date>2026-08-21T17:03:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725723</loc>
  <lastmod>2026-08-21T16:12:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルによる近似クエリ処理（Approximate Query Processing for Data Exploration using Deep Generative Models）</news:title>
   <news:publication_date>2026-08-21T16:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725721</loc>
  <lastmod>2026-08-21T16:12:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル認識型関数混合ネットワークによる分光超解像（Pixel-aware Deep Function-mixture Network for Spectral Super-Resolution）</news:title>
   <news:publication_date>2026-08-21T16:12:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725719</loc>
  <lastmod>2026-08-21T16:12:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多属性選択率推定における深層学習の応用（Multi-Attribute Selectivity Estimation Using Deep Learning）</news:title>
   <news:publication_date>2026-08-21T16:12:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725717</loc>
  <lastmod>2026-08-21T16:11:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段階圧縮によるニューラルネットワークの効率化（MUSCO: Multi-Stage Compression of neural networks）</news:title>
   <news:publication_date>2026-08-21T16:11:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725715</loc>
  <lastmod>2026-08-21T16:11:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木星の大赤斑の深さを探る（Determining the depth of Jupiter’s Great Red Spot with Juno: a Slepian approach）</news:title>
   <news:publication_date>2026-08-21T16:11:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725713</loc>
  <lastmod>2026-08-21T16:11:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタ整列を教師で促す手法（Cluster Alignment with a Teacher for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-08-21T16:11:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725711</loc>
  <lastmod>2026-08-21T16:10:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高変形ソフト粒子の圧縮挙動とジャミング後の力学（Soft grain compression: beyond the jamming point）</news:title>
   <news:publication_date>2026-08-21T16:10:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725709</loc>
  <lastmod>2026-08-21T15:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深海面における非相互作用重力波の理論的展開（Non-interacting gravity waves on the surface of a deep fluid）</news:title>
   <news:publication_date>2026-08-21T15:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725707</loc>
  <lastmod>2026-08-21T15:19:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者抽出ニューラルネットワークの最適化（Optimization of Speaker Extraction Neural Network with Magnitude and Temporal Spectrum Approximation Loss）</news:title>
   <news:publication_date>2026-08-21T15:19:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725705</loc>
  <lastmod>2026-08-21T15:19:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な製品埋め込みに基づく深層レコメンダーエンジン（Deep recommender engine based on efficient product embeddings neural pipeline）</news:title>
   <news:publication_date>2026-08-21T15:19:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725703</loc>
  <lastmod>2026-08-21T15:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間量子化を用いた変分推論による敵対的耐性（Variational Inference with Latent Space Quantization for Adversarial Resilience）</news:title>
   <news:publication_date>2026-08-21T15:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725701</loc>
  <lastmod>2026-08-21T15:17:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HAXMLNetが示す極端多ラベル分類の新潮流（HAXMLNet: Hierarchical Attention Network for Extreme Multi-Label Text Classification）</news:title>
   <news:publication_date>2026-08-21T15:17:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725699</loc>
  <lastmod>2026-08-21T15:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床テキストにおける最短依存経路ベースのLSTMによる関係抽出（Relation extraction between the clinical entities based on the shortest dependency path based LSTM）</news:title>
   <news:publication_date>2026-08-21T15:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725697</loc>
  <lastmod>2026-08-21T15:17:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>要約生成を特徴量化してフェイクニュース検出を改善する手法（Neural Abstractive Text Summarization and Fake News Detection）</news:title>
   <news:publication_date>2026-08-21T15:17:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725695</loc>
  <lastmod>2026-08-21T14:24:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB画像を入力とするマップレスロボット航法のサンプル効率化（Using RGB Image as Visual Input for Mapless Robot Navigation）</news:title>
   <news:publication_date>2026-08-21T14:24:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725693</loc>
  <lastmod>2026-08-21T14:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブルセンサの弱ラベルデータから活動を見つける注意機構CNN（Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors）</news:title>
   <news:publication_date>2026-08-21T14:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725691</loc>
  <lastmod>2026-08-21T14:24:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限仮説クラス下のオンライン学習における改善された誤り境界（Algorithms and Improved bounds for online learning under finite hypothesis class）</news:title>
   <news:publication_date>2026-08-21T14:24:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725689</loc>
  <lastmod>2026-08-21T14:22:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KPTransferによるキーポイント部分集合間ドメイン転移の実用的意義（KPTransfer: improved performance and faster convergence from keypoint subset-wise domain transfer in human pose estimation）</news:title>
   <news:publication_date>2026-08-21T14:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725687</loc>
  <lastmod>2026-08-21T14:22:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SRGAN: トレーニングデータが結果を決める（SRGAN: Training Dataset Matters）</news:title>
   <news:publication_date>2026-08-21T14:22:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725685</loc>
  <lastmod>2026-08-21T14:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素値PolSARデータの効率的利用—マルチタスク深層学習フレームワーク（Efficiently utilizing complex-valued PolSAR image data via a multi-task deep learning framework）</news:title>
   <news:publication_date>2026-08-21T14:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725683</loc>
  <lastmod>2026-08-21T14:21:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散機械学習ジョブのオーケストレーションを実現するTonY（TonY: An Orchestrator for Distributed Machine Learning Jobs）</news:title>
   <news:publication_date>2026-08-21T14:21:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725680</loc>
  <lastmod>2026-08-21T13:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>sharpDARTS：より高速で高精度なDifferentiable Architecture Search（sharpDARTS: Faster and More Accurate Differentiable Architecture Search）</news:title>
   <news:publication_date>2026-08-21T13:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725678</loc>
  <lastmod>2026-08-21T13:29:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散再帰型オートエンコーダによる拡張可能な画像圧縮（DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression）</news:title>
   <news:publication_date>2026-08-21T13:29:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725676</loc>
  <lastmod>2026-08-21T13:29:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変換に応答する表現の教師なし学習（AVT: Unsupervised Learning of Transformation-Equivariant Representations by Autoencoding Variational Transformations）</news:title>
   <news:publication_date>2026-08-21T13:29:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725674</loc>
  <lastmod>2026-08-21T13:28:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実環境向けの長距離ニューラル航行ポリシー（Long Range Neural Navigation Policies for the Real World）</news:title>
   <news:publication_date>2026-08-21T13:28:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725672</loc>
  <lastmod>2026-08-21T13:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時相論理に導かれた安全強化学習と制御バリア関数（Temporal Logic Guided Safe Reinforcement Learning Using Control Barrier Functions）</news:title>
   <news:publication_date>2026-08-21T13:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725670</loc>
  <lastmod>2026-08-21T13:28:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺結節検出のためのエンドツーエンド統合フレームワーク（AN END-TO-END FRAMEWORK FOR INTEGRATED PULMONARY NODULE DETECTION AND FALSE POSITIVE REDUCTION）</news:title>
   <news:publication_date>2026-08-21T13:28:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725668</loc>
  <lastmod>2026-08-21T13:28:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺葉自動分割における深層学習の実用化可能性（AUTOMATIC PULMONARY LOBE SEGMENTATION USING DEEP LEARNING）</news:title>
   <news:publication_date>2026-08-21T13:28:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725666</loc>
  <lastmod>2026-08-21T12:36:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StartNet：ストリーミング映像における行動開始検出の実時間化（StartNet: Online Detection of Action Start in Untrimmed Videos）</news:title>
   <news:publication_date>2026-08-21T12:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725664</loc>
  <lastmod>2026-08-21T12:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシー学習器に対するデータ汚染攻撃と防御（Data Poisoning against Differentially-Private Learners: Attacks and Defenses）</news:title>
   <news:publication_date>2026-08-21T12:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725662</loc>
  <lastmod>2026-08-21T12:36:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン最適化による学習と制御の新枠組み（Online Optimisation for Online Learning and Control – From No-Regret to Generalised Error Convergence）</news:title>
   <news:publication_date>2026-08-21T12:36:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725660</loc>
  <lastmod>2026-08-21T12:35:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協働型言語学習SNSにおける書記能力評価の提案（Toward the Evaluation of Written Proficiency on a Collaborative Social Network for Learning Languages: Yask）</news:title>
   <news:publication_date>2026-08-21T12:35:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725658</loc>
  <lastmod>2026-08-21T12:35:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能力に基づくカリキュラム学習で変わる機械翻訳の学習効率（Competence-based Curriculum Learning for Neural Machine Translation）</news:title>
   <news:publication_date>2026-08-21T12:35:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725656</loc>
  <lastmod>2026-08-21T12:35:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中性子星とブラックホールの時間領域研究：X線によるコンパクト天体の同定（Time Domain Studies of Neutron Star and Black Hole Populations: X-ray Identification of Compact Object Types）</news:title>
   <news:publication_date>2026-08-21T12:35:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725654</loc>
  <lastmod>2026-08-21T12:34:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高効率4接合太陽電池の設計と評価（Novel High Efficiency Quadruple Junction Solar Cell with Current Matching and Quantum Efficiency Simulations）</news:title>
   <news:publication_date>2026-08-21T12:34:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725652</loc>
  <lastmod>2026-08-21T11:43:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HouseExpo：学習ベースの移動ロボット研究を加速する大規模2D室内レイアウトデータセット（HouseExpo: A Large-scale 2D Indoor Layout Dataset for Learning-based Algorithms on Mobile Robots）</news:title>
   <news:publication_date>2026-08-21T11:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725650</loc>
  <lastmod>2026-08-21T11:43:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による時間位相アンラッピング（Temporal phase unwrapping using deep learning）</news:title>
   <news:publication_date>2026-08-21T11:43:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725648</loc>
  <lastmod>2026-08-21T11:42:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルな差分プライバシーと認証付き堅牢性を両立する手法（Scalable Differential Privacy with Certified Robustness in Adversarial Learning）</news:title>
   <news:publication_date>2026-08-21T11:42:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725646</loc>
  <lastmod>2026-08-21T11:41:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜OCT画像の疾患情報を残す意味的ノイズ除去（Semantic denoising autoencoders for retinal optical coherence tomography）</news:title>
   <news:publication_date>2026-08-21T11:41:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725644</loc>
  <lastmod>2026-08-21T11:41:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識に基づく応答生成の深化（Knowledge-Grounded Response Generation with Deep Attentional Latent-Variable Model）</news:title>
   <news:publication_date>2026-08-21T11:41:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725642</loc>
  <lastmod>2026-08-21T11:41:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィードバックネットワークによる画像超解像の新展開（Feedback Network for Image Super-Resolution）</news:title>
   <news:publication_date>2026-08-21T11:41:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725640</loc>
  <lastmod>2026-08-21T11:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>材料間の類似度測定と「Distinctiveness」の重視（Measuring the Similarity between Materials with an Emphasis on the Materials’ Distinctiveness）</news:title>
   <news:publication_date>2026-08-21T11:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725638</loc>
  <lastmod>2026-08-21T10:49:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Coin.AIによる有用作業の証明スキーム（Coin.AI: A Proof-of-Useful-Work Scheme for Blockchain-Based Distributed Deep Learning）</news:title>
   <news:publication_date>2026-08-21T10:49:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725636</loc>
  <lastmod>2026-08-21T10:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BitSplit-Netによるマルチビット深層ニューラルネットワーク (BitSplit-Net: Multi-bit Deep Neural Network with Bitwise Activation Function)</news:title>
   <news:publication_date>2026-08-21T10:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725634</loc>
  <lastmod>2026-08-21T10:48:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Guided Complement Entropyがもたらす「防御を追加しない」堅牢化（Improving Adversarial Robustness via Guided Complement Entropy）</news:title>
   <news:publication_date>2026-08-21T10:48:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725632</loc>
  <lastmod>2026-08-21T10:48:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動による予測保全と不確実性推定（Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models）</news:title>
   <news:publication_date>2026-08-21T10:48:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725630</loc>
  <lastmod>2026-08-21T10:47:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インターネットが変える市場調査と意思決定（Role of the internet in marketing research and business decision-making）</news:title>
   <news:publication_date>2026-08-21T10:47:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725628</loc>
  <lastmod>2026-08-21T10:47:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値分類における半準パラメトリックな不確かさ境界（Semi-Parametric Uncertainty Bounds for Binary Classification）</news:title>
   <news:publication_date>2026-08-21T10:47:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725626</loc>
  <lastmod>2026-08-21T10:47:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深さ情報で合成データの弱点を埋める（What Synthesis is Missing: Depth Adaptation Integrated with Weak Supervision for Indoor Scene Parsing）</news:title>
   <news:publication_date>2026-08-21T10:47:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725624</loc>
  <lastmod>2026-08-21T09:55:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Auto-ReID: 人物再識別向け部分認識ConvNetを自動探索する手法（Auto-ReID: Searching for a Part-Aware ConvNet for Person Re-Identification）</news:title>
   <news:publication_date>2026-08-21T09:55:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725622</loc>
  <lastmod>2026-08-21T09:54:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進展的DNN圧縮：ADMMを用いた超高率の重み剪定と量子化の実現（Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM）</news:title>
   <news:publication_date>2026-08-21T09:54:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725620</loc>
  <lastmod>2026-08-21T09:54:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な水中画像強調による視覚認知の改善（Fast Underwater Image Enhancement for Improved Visual Perception）</news:title>
   <news:publication_date>2026-08-21T09:54:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725618</loc>
  <lastmod>2026-08-21T09:53:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律操作のためのシーン理解と深層学習（Scene Understanding for Autonomous Manipulation with Deep Learning）</news:title>
   <news:publication_date>2026-08-21T09:53:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725616</loc>
  <lastmod>2026-08-21T09:53:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>写真写実的スタイル転送を一変させた波形レット補正（Photorealistic Style Transfer via Wavelet Transforms）</news:title>
   <news:publication_date>2026-08-21T09:53:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725614</loc>
  <lastmod>2026-08-21T09:53:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TTRに基づく報酬で学ぶ強化学習（TTR-Based Reward for Reinforcement Learning with Implicit Model Priors）</news:title>
   <news:publication_date>2026-08-21T09:53:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725612</loc>
  <lastmod>2026-08-21T09:52:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PMLによるクラウド向け汎用アクセス制御言語の提案（PML: An Interpreter-Based Access Control Policy Language for Web Services）</news:title>
   <news:publication_date>2026-08-21T09:52:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725610</loc>
  <lastmod>2026-08-21T09:01:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオをロボットの命令語へ変換する技術の本質（V2CNet: A Deep Learning Framework to Translate Videos to Commands for Robotic Manipulation）</news:title>
   <news:publication_date>2026-08-21T09:01:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725608</loc>
  <lastmod>2026-08-21T09:00:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Residual Pyramid Learningによるシングルショット分割の実務的示唆（Residual Pyramid Learning for Single-Shot Semantic Segmentation）</news:title>
   <news:publication_date>2026-08-21T09:00:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725606</loc>
  <lastmod>2026-08-21T09:00:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルシフト下の正則化学習がもたらす実務的価値（Regularized Learning for Domain Adaptation under Label Shifts）</news:title>
   <news:publication_date>2026-08-21T09:00:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725604</loc>
  <lastmod>2026-08-21T08:59:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データの欠損値補完（Imputation in time series）</news:title>
   <news:publication_date>2026-08-21T08:59:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725602</loc>
  <lastmod>2026-08-21T08:59:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数クラスの生成的過剰サンプリング（Generative Adversarial Minority Oversampling）</news:title>
   <news:publication_date>2026-08-21T08:59:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725600</loc>
  <lastmod>2026-08-21T08:59:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般人向けの強化学習説明の実証研究（Explaining Reinforcement Learning to Mere Mortals: An Empirical Study）</news:title>
   <news:publication_date>2026-08-21T08:59:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725598</loc>
  <lastmod>2026-08-21T08:58:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門家知識を組み込む機械学習（Expert-Augmented Machine Learning）</news:title>
   <news:publication_date>2026-08-21T08:58:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725596</loc>
  <lastmod>2026-08-21T08:07:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンボリック回帰を用いた強化学習の価値関数構築（Symbolic Regression Methods for Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-21T08:07:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725594</loc>
  <lastmod>2026-08-21T08:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河から塵（ほこり）はどう逃げるのか（How does dust escape galaxies?）</news:title>
   <news:publication_date>2026-08-21T08:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725592</loc>
  <lastmod>2026-08-21T08:07:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CUR分解とその摂動解析が示す低ランク行列近似の安定性（CUR Decompositions, Approximations, and Perturbations）</news:title>
   <news:publication_date>2026-08-21T08:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725590</loc>
  <lastmod>2026-08-21T08:06:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布系状態推定のための物理認識ニューラルネットワーク（Physics-Aware Neural Networks for Distribution System State Estimation）</news:title>
   <news:publication_date>2026-08-21T08:06:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725588</loc>
  <lastmod>2026-08-21T08:06:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軸索の伝導速度がネットワークのリズムを変える可能性（Axonal Conduction Velocity Impacts Neuronal Network Oscillations）</news:title>
   <news:publication_date>2026-08-21T08:06:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725586</loc>
  <lastmod>2026-08-21T08:06:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分可能プログラミングによるテンソルネットワーク最適化（Differentiable Programming Tensor Networks）</news:title>
   <news:publication_date>2026-08-21T08:06:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725584</loc>
  <lastmod>2026-08-21T08:05:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイジアン深層学習のためのデータ拡張（Data Augmentation for Bayesian Deep Learning）</news:title>
   <news:publication_date>2026-08-21T08:05:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725582</loc>
  <lastmod>2026-08-21T07:13:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>z∼8でのHβ+[O III]輝度関数と銀河特性（The GREATS Hβ+[O III] Luminosity Function and Galaxy Properties at z ∼8: Walking the Way of JWST）</news:title>
   <news:publication_date>2026-08-21T07:13:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725580</loc>
  <lastmod>2026-08-21T07:13:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希薄な宇宙の流入—Lyα放射銀河におけるIGM降着の観測的証拠（Probing IGM accretion onto faint Lyα emitters at z ∼2.8）</news:title>
   <news:publication_date>2026-08-21T07:13:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725578</loc>
  <lastmod>2026-08-21T07:12:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GroomRLによるジェットグルーミングの強化学習化（GroomRL: Jet Grooming through Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-21T07:12:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725576</loc>
  <lastmod>2026-08-21T07:12:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fog Roboticsによるロボット学習と表面片付けの実用化（A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering）</news:title>
   <news:publication_date>2026-08-21T07:12:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725574</loc>
  <lastmod>2026-08-21T07:11:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンザフライ学習で得られる機械学習力場によるハイブリッドペロブスカイトの相転移（Phase transitions of hybrid perovskites simulated by machine-learning force fields trained on-the-fly with Bayesian inference）</news:title>
   <news:publication_date>2026-08-21T07:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725572</loc>
  <lastmod>2026-08-21T07:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者に依存しない表現を学習するための敵対的手法（TOWARDS ADVERSARIAL LEARNING OF SPEAKER-INVARIANT REPRESENTATION FOR SPEECH EMOTION RECOGNITION）</news:title>
   <news:publication_date>2026-08-21T07:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725570</loc>
  <lastmod>2026-08-21T07:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間に聞き取れない音声敵対的事例の構築と堅牢化（Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition）</news:title>
   <news:publication_date>2026-08-21T07:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725568</loc>
  <lastmod>2026-08-21T06:19:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手持ちWEMIを用いた目標検出アルゴリズムの比較（Comparison of Hand-held WEMI Target Detection Algorithms）</news:title>
   <news:publication_date>2026-08-21T06:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725566</loc>
  <lastmod>2026-08-21T06:19:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限エネルギー空間と測度論的ラプラシアンの整理（LAPLACE OPERATORS IN FINITE ENERGY AND DISSIPATION SPACES）</news:title>
   <news:publication_date>2026-08-21T06:19:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725564</loc>
  <lastmod>2026-08-21T06:19:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Monte Carlo Neural Fictitious Self-Playによる不完全情報ゲームの近似ナッシュ均衡獲得（Monte Carlo Neural Fictitious Self-Play）</news:title>
   <news:publication_date>2026-08-21T06:19:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725562</loc>
  <lastmod>2026-08-21T06:18:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非マルコフ確率過程に対する機械学習によるメモリカーネルの閉じ込み (Machine learning memory kernels as closure for non-Markovian stochastic processes)</news:title>
   <news:publication_date>2026-08-21T06:18:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725560</loc>
  <lastmod>2026-08-21T06:17:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜疾患の同時自動検出を目指した深層学習システムの評価 (Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration)</news:title>
   <news:publication_date>2026-08-21T06:17:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725558</loc>
  <lastmod>2026-08-21T06:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化文書における表理解（Table understanding in structured documents）</news:title>
   <news:publication_date>2026-08-21T06:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725556</loc>
  <lastmod>2026-08-21T06:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習手法で宇宙線反陽子フラックスにおけるダークマター信号を探る（Investigating the dark matter signal in the cosmic ray antiproton flux with the machine learning method）</news:title>
   <news:publication_date>2026-08-21T06:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725554</loc>
  <lastmod>2026-08-21T05:24:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復的な強化学習による二足歩行スキル設計（Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie）</news:title>
   <news:publication_date>2026-08-21T05:24:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725552</loc>
  <lastmod>2026-08-21T05:24:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>類似した形態特徴を持つ細胞の識別におけるゴーストサイトメトリーの応用 (Use of Ghost Cytometry to Differentiate Cells with Similar Gross Morphologic Characteristics)</news:title>
   <news:publication_date>2026-08-21T05:24:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725550</loc>
  <lastmod>2026-08-21T05:24:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電力市場におけるリスク最小化の機械学習アプローチ（A Machine Learning approach to Risk Minimisation in Electricity Markets with Coregionalized Sparse Gaussian Processes）</news:title>
   <news:publication_date>2026-08-21T05:24:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725548</loc>
  <lastmod>2026-08-21T05:23:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁化ダイナミクスを学習する（Learning magnetization dynamics）</news:title>
   <news:publication_date>2026-08-21T05:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725546</loc>
  <lastmod>2026-08-21T05:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多体系のエンタングルメント深度を装置非依存に評価する手法の最適化（Optimization of device-independent witnesses of entanglement depth from two-body correlators）</news:title>
   <news:publication_date>2026-08-21T05:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725544</loc>
  <lastmod>2026-08-21T05:23:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全確率的制御の感度と安全性（Sensitivity and safety of fully probabilistic control）</news:title>
   <news:publication_date>2026-08-21T05:23:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725542</loc>
  <lastmod>2026-08-21T05:22:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平性の目に見えない力（The invisible power of fairness. How machine learning shapes democracy）</news:title>
   <news:publication_date>2026-08-21T05:22:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725540</loc>
  <lastmod>2026-08-21T04:31:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OODIDAによる分散データ分析の迅速なプロトタイピング（Facilitating Rapid Prototyping in the Distributed Data Analytics Platform OODIDA via Active-Code Replacement）</news:title>
   <news:publication_date>2026-08-21T04:31:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725538</loc>
  <lastmod>2026-08-21T04:31:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小売の多次元売上に対する最適結合予測（Optimal Combination Forecasts on Retail Multi-Dimensional Sales Data）</news:title>
   <news:publication_date>2026-08-21T04:31:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725536</loc>
  <lastmod>2026-08-21T04:30:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Aggregated Deep Local Featuresによるリモートセンシング画像検索の合理化（Aggregated Deep Local Features for Remote Sensing Image Retrieval）</news:title>
   <news:publication_date>2026-08-21T04:30:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725534</loc>
  <lastmod>2026-08-21T04:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固体・真空界面におけるイオン液体の構造と拡散挙動に関する分子動力学シミュレーションの知見（Insights from Molecular Dynamics Simulations on Structural Organization and Diffusive Dynamics of an Ionic Liquid at Solid and Vacuum Interfaces）</news:title>
   <news:publication_date>2026-08-21T04:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725532</loc>
  <lastmod>2026-08-21T04:29:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>薄膜金属の結晶核の構造と形態（Structure and Morphology of Crystalline Nuclei arising in a Crystallizing Liquid Metallic Film）</news:title>
   <news:publication_date>2026-08-21T04:29:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725530</loc>
  <lastmod>2026-08-21T04:29:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>透過壁環境での前面レーダー画像の歪みを軽減するノイズ除去オートエンコーダ（Mitigation of Through-Wall Distortions of Frontal Radar Images using Denoising Autoencoders）</news:title>
   <news:publication_date>2026-08-21T04:29:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725528</loc>
  <lastmod>2026-08-21T04:28:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓画像解析における分離表現学習（Disentangled representation learning in cardiac image analysis）</news:title>
   <news:publication_date>2026-08-21T04:28:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725526</loc>
  <lastmod>2026-08-21T03:37:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストクラスタリングのエンドツーエンドニューラルネットワークフレームワーク (An end-to-end Neural Network Framework for Text Clustering)</news:title>
   <news:publication_date>2026-08-21T03:37:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725524</loc>
  <lastmod>2026-08-21T03:37:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチベイズ最適化のための獲得関数サンプリング（Sampling Acquisition Functions for Batch Bayesian Optimization）</news:title>
   <news:publication_date>2026-08-21T03:37:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725522</loc>
  <lastmod>2026-08-21T03:36:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>金属スクラップ選別にAIを持ち込む（ARTIFICIAL INTELLIGENCE-BASED PROCESS FOR METAL SCRAP SORTING）</news:title>
   <news:publication_date>2026-08-21T03:36:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725520</loc>
  <lastmod>2026-08-21T03:35:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延シナプス可塑性で学ぶ（Learning with Delayed Synaptic Plasticity）</news:title>
   <news:publication_date>2026-08-21T03:35:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725518</loc>
  <lastmod>2026-08-21T03:35:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群レベルfMRI解析のための制約付きICA‑EMDモデル (A constrained ICA-EMD Model for Group Level fMRI Analysis)</news:title>
   <news:publication_date>2026-08-21T03:35:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725516</loc>
  <lastmod>2026-08-21T03:35:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化を用いた高速ベイズ的不確実性推定と低減（Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution Network）</news:title>
   <news:publication_date>2026-08-21T03:35:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725514</loc>
  <lastmod>2026-08-21T03:34:47Z</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>2026-08-21T03:34:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725512</loc>
  <lastmod>2026-08-21T02:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>化学組成のベイズ最適化とRFe12型磁石への応用（Bayesian optimization of chemical composition: a comprehensive framework and its application to RFe12-type magnet compounds）</news:title>
   <news:publication_date>2026-08-21T02:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725510</loc>
  <lastmod>2026-08-21T02:43:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配のみのラインサーチ（Gradient-only line searches: An Alternative to Probabilistic Line Searches）</news:title>
   <news:publication_date>2026-08-21T02:43:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725508</loc>
  <lastmod>2026-08-21T02:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル確率的予測による相互行動の解釈可能なモデル（Multi-modal Probabilistic Prediction of Interactive Behavior via an Interpretable Model）</news:title>
   <news:publication_date>2026-08-21T02:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725506</loc>
  <lastmod>2026-08-21T02:42:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙の正則化による高次元線形回帰（High-Dimensional Linear Regression via Implicit Regularization）</news:title>
   <news:publication_date>2026-08-21T02:42:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725504</loc>
  <lastmod>2026-08-21T02:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層フィクティシャス・プレイによる確率微分ゲームの解法（Deep Fictitious Play for Stochastic Differential Games）</news:title>
   <news:publication_date>2026-08-21T02:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725502</loc>
  <lastmod>2026-08-21T02:41:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーケンス分解によるマクロアクション強化学習（Macro Action Reinforcement Learning with Sequence Disentanglement using Variational Autoencoder）</news:title>
   <news:publication_date>2026-08-21T02:41:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725500</loc>
  <lastmod>2026-08-21T02:41:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段階目標抽象による深層階層強化学習推薦（Deep Hierarchical Reinforcement Learning Based Recommendations via Multi-goals Abstraction）</news:title>
   <news:publication_date>2026-08-21T02:41:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725498</loc>
  <lastmod>2026-08-21T01:50:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの3D顔再構成を2D画像で補助する学習法（3D Face Reconstruction from A Single Image Assisted by 2D Face Images in the Wild）</news:title>
   <news:publication_date>2026-08-21T01:50:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725496</loc>
  <lastmod>2026-08-21T01:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さなミニライゾトロンデータセットを乗り越える転移学習（Overcoming Small Minirhizotron Datasets Using Transfer Learning）</news:title>
   <news:publication_date>2026-08-21T01:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725494</loc>
  <lastmod>2026-08-21T01:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二分空間分割フォレスト（Binary Space Partitioning Forests）</news:title>
   <news:publication_date>2026-08-21T01:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725492</loc>
  <lastmod>2026-08-21T01:49:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Binary Space Partitioning-Tree Process（The Binary Space Partitioning-Tree Process）</news:title>
   <news:publication_date>2026-08-21T01:49:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725490</loc>
  <lastmod>2026-08-21T01:49:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習で解釈可能な決定木を学ぶ最適化手法（Optimization Methods for Interpretable Differentiable Decision Trees in Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-21T01:49:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725488</loc>
  <lastmod>2026-08-21T01:49:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MNMFを用いた教師なし音声強調とMVDRビームフォーミング（Unsupervised Speech Enhancement Based on Multichannel NMF-Informed Beamforming）</news:title>
   <news:publication_date>2026-08-21T01:49:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725486</loc>
  <lastmod>2026-08-21T01:48:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多モーダル画像の教師なし変形登録を離散表現で解く（Unsupervised Deformable Registration for Multi-Modal Images via Disentangled Representations）</news:title>
   <news:publication_date>2026-08-21T01:48:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725484</loc>
  <lastmod>2026-08-21T00:56:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光コヒーレンストモグラフィ（OCT）画像のスペックル低減のためのResNetベース汎用手法 (A RESNET-BASED UNIVERSAL METHOD FOR SPECKLE REDUCTION IN OPTICAL COHERENCE TOMOGRAPHY IMAGES)</news:title>
   <news:publication_date>2026-08-21T00:56:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725482</loc>
  <lastmod>2026-08-21T00:56:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>けいれんと非けいれんの分類に対する新規IndRNNアプローチ (A Novel Independent RNN Approach to Classification of Seizures against Non-seizures)</news:title>
   <news:publication_date>2026-08-21T00:56:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725480</loc>
  <lastmod>2026-08-21T00:55:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層多天体分光観測がLSSTのダークエネルギー研究を強化する（Deep Multi-object Spectroscopy to Enhance Dark Energy Science from LSST）</news:title>
   <news:publication_date>2026-08-21T00:55:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725478</loc>
  <lastmod>2026-08-21T00:55:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広域多天体分光観測がLSSTの暗黒エネルギー研究にもたらすもの（Wide-field Multi-object Spectroscopy to Enhance Dark Energy Science from LSST）</news:title>
   <news:publication_date>2026-08-21T00:55:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725476</loc>
  <lastmod>2026-08-21T00:55:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一天体の撮像と分光がLSSTの暗黒エネルギー研究を強化する（Single-object Imaging and Spectroscopy to Enhance Dark Energy Science from LSST）</news:title>
   <news:publication_date>2026-08-21T00:55:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725474</loc>
  <lastmod>2026-08-21T00:54:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散電子医療記録を用いた患者クラスタリングはフェデレーテッド機械学習の効率を改善する（Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records）</news:title>
   <news:publication_date>2026-08-21T00:54:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725472</loc>
  <lastmod>2026-08-21T00:54:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境における加重ワンショット・リッジ回帰の実務的意義（WONDER: Weighted one-shot distributed ridge regression in high dimensions）</news:title>
   <news:publication_date>2026-08-21T00:54:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725470</loc>
  <lastmod>2026-08-21T00:02:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DQNに基づくモデル内探索による効率的学習（DQN with Model-Based Exploration: Efficient Learning on Environments with Sparse Rewards）</news:title>
   <news:publication_date>2026-08-21T00:02:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725468</loc>
  <lastmod>2026-08-21T00:01:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成対抗学習による最適な構造化CNN剪定（Towards Optimal Structured CNN Pruning via Generative Adversarial Learning）</news:title>
   <news:publication_date>2026-08-21T00:01:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725466</loc>
  <lastmod>2026-08-21T00:00:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルデータ向け分離辞書の混合学習（Learning Mixtures of Separable Dictionaries for Tensor Data: Analysis and Algorithms）</news:title>
   <news:publication_date>2026-08-21T00:00:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725464</loc>
  <lastmod>2026-08-21T00:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HARDIの高速かつ高精度な再構成を実現する1Dエンコーダ・デコーダ畳み込みネットワーク（FAST AND ACCURATE RECONSTRUCTION OF HARDI USING A 1D ENCODER-DECODER CONVOLUTIONAL NETWORK）</news:title>
   <news:publication_date>2026-08-21T00:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725462</loc>
  <lastmod>2026-08-21T00:00:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワルファリン臨床用量アルゴリズムの適用範囲判定（A Computer-Aided System for Determining the Application Range of a Warfarin Clinical Dosing Algorithm Using Support Vector Machines with a Polynomial Kernel Function）</news:title>
   <news:publication_date>2026-08-21T00:00:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725460</loc>
  <lastmod>2026-08-20T23:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の生物医学データベースからアソシエーションルールとオントロジーを用いてメタデータ推奨を生成する方法（Using association rule mining and ontologies to generate metadata recommendations from multiple biomedical databases）</news:title>
   <news:publication_date>2026-08-20T23:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725458</loc>
  <lastmod>2026-08-20T23:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラ貼付ステッカーによる物理的攻撃（Adversarial camera stickers: A physical camera-based attack on deep learning systems）</news:title>
   <news:publication_date>2026-08-20T23:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725456</loc>
  <lastmod>2026-08-20T23:08:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間でU-Netを模倣する自己符号化器による骨盤骨セグメンテーション向上（Imitating U-Net Enhanced Autoencoders in Latent Space for Improved Pelvic Bone Segmentation in MRI）</news:title>
   <news:publication_date>2026-08-20T23:08:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725454</loc>
  <lastmod>2026-08-20T23:08:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙論と初期宇宙（Cosmology and the Early Universe）</news:title>
   <news:publication_date>2026-08-20T23:08:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725452</loc>
  <lastmod>2026-08-20T23:08:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散オフポリシーActor‑Criticと方策コンセンサス（Distributed off-Policy Actor-Critic Reinforcement Learning with Policy Consensus）</news:title>
   <news:publication_date>2026-08-20T23:08:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725450</loc>
  <lastmod>2026-08-20T23:07:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形フィルタリング総覧（The Hitchhiker’s Guide to Nonlinear Filtering）</news:title>
   <news:publication_date>2026-08-20T23:07:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725448</loc>
  <lastmod>2026-08-20T23:07:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続時間領域で学習可能な時系列整列手法：Trainable Time Warping（Trainable Time Warping: Aligning Time-Series in the Continuous-Time Domain）</news:title>
   <news:publication_date>2026-08-20T23:07:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725446</loc>
  <lastmod>2026-08-20T23:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット指示の効率的自然言語理解のためのコンパクト表現の推定 (Inferring Compact Representations for Efficient Natural Language Understanding of Robot Instructions)</news:title>
   <news:publication_date>2026-08-20T23:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725444</loc>
  <lastmod>2026-08-20T23:06:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ULMFitとバックトランスレーションによる少量データのテキスト分類（Low Resource Text Classification with ULMFit and Backtranslation）</news:title>
   <news:publication_date>2026-08-20T23:06:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725442</loc>
  <lastmod>2026-08-20T22:15:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ系列MRIを用いた脳腫瘍検出と分類のDeep Radiomics（Deep Radiomics for Brain Tumor Detection and Classification from Multi-Sequence MRI）</news:title>
   <news:publication_date>2026-08-20T22:15:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725440</loc>
  <lastmod>2026-08-20T22:15:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチドメイン敵対学習が変える現場導入の常識（Multi-Domain Adversarial Learning）</news:title>
   <news:publication_date>2026-08-20T22:15:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725438</loc>
  <lastmod>2026-08-20T22:14:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化付き混合線形回帰モデルにおけるパラメータ推定の収束性（Convergence of Parameter Estimates for Regularized Mixed Linear Regression Models）</news:title>
   <news:publication_date>2026-08-20T22:14:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725436</loc>
  <lastmod>2026-08-20T22:14:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Top-1誤差に注目した較正済み不確実性推定（Calibrated Top-1 Uncertainty estimates for classification by score based models）</news:title>
   <news:publication_date>2026-08-20T22:14:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725434</loc>
  <lastmod>2026-08-20T22:13:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形状理解のためのSkelNetOnチャレンジ（SkelNetOn 2019: Dataset and Challenge on Deep Learning for Geometric Shape Understanding）</news:title>
   <news:publication_date>2026-08-20T22:13:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725432</loc>
  <lastmod>2026-08-20T22:13:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細胞同定のための確率的アトラス（A probabilistic atlas for cell identification）</news:title>
   <news:publication_date>2026-08-20T22:13:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725430</loc>
  <lastmod>2026-08-20T22:12:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高閾値活性化を用いた深層ネットワークの最下層復元（Recovering the Lowest Layer of Deep Networks with High Threshold Activations）</news:title>
   <news:publication_date>2026-08-20T22:12:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725428</loc>
  <lastmod>2026-08-20T21:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイクロステーショナリ過程のネットワークにおける正確なトポロジー学習（Exact Topology Learning in a Network of Cyclostationary Processes）</news:title>
   <news:publication_date>2026-08-20T21:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725426</loc>
  <lastmod>2026-08-20T21:21:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Penobscotデータセット：地震データで機械学習を育てる（Penobscot Dataset: Fostering Machine Learning Development for Seismic Interpretation）</news:title>
   <news:publication_date>2026-08-20T21:21:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725424</loc>
  <lastmod>2026-08-20T21:20:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>システム全体を視野に入れた動的評価フレームワーク（A simulation based dynamic evaluation framework for system-wide algorithmic fairness）</news:title>
   <news:publication_date>2026-08-20T21:20:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725422</loc>
  <lastmod>2026-08-20T21:19:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種混合マルチタスク学習のためのマルチネットワーク自動構築に向けて（Towards automatic construction of multi-network models for heterogeneous multi-task learning）</news:title>
   <news:publication_date>2026-08-20T21:19:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725420</loc>
  <lastmod>2026-08-20T21:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエーサーのマイクロレンズ光度曲線解析に深層学習を用いる研究（Quasar microlensing light curve analysis using deep machine learning）</news:title>
   <news:publication_date>2026-08-20T21:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725418</loc>
  <lastmod>2026-08-20T21:19:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像のマルチラベル分類API比較とセマンティック評価の重要性（Comparison of State-of-the-Art Deep Learning APIs for Image Multi-Label Classification using Semantic Metrics）</news:title>
   <news:publication_date>2026-08-20T21:19:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725416</loc>
  <lastmod>2026-08-20T21:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sparse2Denseによる単眼SLAMの密な再構築（Sparse2Dense: From direct sparse odometry to dense 3D reconstruction）</news:title>
   <news:publication_date>2026-08-20T21:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725414</loc>
  <lastmod>2026-08-20T20:27:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ALMAスペクトロスコピー調査が示す分子ガスの宇宙進化（The ALMA Spectroscopic Survey in the Hubble Ultra Deep Field: Evolution of the molecular gas in CO-selected galaxies）</news:title>
   <news:publication_date>2026-08-20T20:27:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725412</loc>
  <lastmod>2026-08-20T20:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HUDFにおけるALMA分光調査が示した銀河ガスの実像（The ALMA Spectroscopic Survey in the HUDF: Nature and physical properties of gas-mass selected galaxies using MUSE spectroscopy）</news:title>
   <news:publication_date>2026-08-20T20:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725410</loc>
  <lastmod>2026-08-20T20:17:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HUDFにおけるALMA分光サーベイ：銀河のCO輝度関数と宇宙史を通じた分子ガス量の変遷（THE ALMA SPECTROSCOPIC SURVEY IN THE HUDF: CO LUMINOSITY FUNCTIONS AND THE MOLECULAR GAS CONTENT OF GALAXIES THROUGH COSMIC HISTORY）</news:title>
   <news:publication_date>2026-08-20T20:17:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725408</loc>
  <lastmod>2026-08-20T20:16:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズを「害さない」補間の理論 — 高次元線形回帰における無害な補間（Harmless interpolation of noisy data in regression）</news:title>
   <news:publication_date>2026-08-20T20:16:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725406</loc>
  <lastmod>2026-08-20T20:15:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HUDFにおけるALMA分光調査：銀河の分子ガス量とモデルとの乖離（The ALMA Spectroscopic Survey in the HUDF: the molecular gas content of galaxies and tensions with IllustrisTNG and the Santa Cruz SAM）</news:title>
   <news:publication_date>2026-08-20T20:15:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725404</loc>
  <lastmod>2026-08-20T20:15:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HUDFにおけるALMA分光観測：CO輝線と3mm連続体源（The ALMA Spectroscopic Survey in the HUDF: CO emission lines and 3 mm continuum sources）</news:title>
   <news:publication_date>2026-08-20T20:15:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725402</loc>
  <lastmod>2026-08-20T20:15:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転するブラックホールによる潮汐破壊の影響（Tidal disruptions by rotating black holes: effects of spin and impact parameter）</news:title>
   <news:publication_date>2026-08-20T20:15:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725400</loc>
  <lastmod>2026-08-20T19:22:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>摂動履歴探索による確率的線形バンディット（Perturbed-History Exploration in Stochastic Linear Bandits）</news:title>
   <news:publication_date>2026-08-20T19:22:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725398</loc>
  <lastmod>2026-08-20T19:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衝撃を受けたHMXにおけるメソスケールのエネルギー局在化のモデル化（Modeling meso-scale energy localization in shocked HMX, Part II: training machine-learned surrogate models for void shape and void-void interaction effects）</news:title>
   <news:publication_date>2026-08-20T19:22:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725396</loc>
  <lastmod>2026-08-20T19:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形ガウス近似メッセージ伝播の近似手法（ON APPROXIMATE NONLINEAR GAUSSIAN MESSAGE PASSING ON FACTOR GRAPHS）</news:title>
   <news:publication_date>2026-08-20T19:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725394</loc>
  <lastmod>2026-08-20T19:21:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>孤立波（ローグウェーブ）事象の持続時間解析（Lifetimes of rogue wave events in direct numerical simulations of deep-water irregular sea waves）</news:title>
   <news:publication_date>2026-08-20T19:21:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725392</loc>
  <lastmod>2026-08-20T19:21:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的システム同定の有限サンプル解析（Finite Sample Analysis of Stochastic System Identification）</news:title>
   <news:publication_date>2026-08-20T19:21:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725390</loc>
  <lastmod>2026-08-20T19:21:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度カメラとサンプルエントロピーによる歩行パターン解析（Exploratory studies of human gait changes using depth cameras and sample entropy）</news:title>
   <news:publication_date>2026-08-20T19:21:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725388</loc>
  <lastmod>2026-08-20T19:20:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク学習におけるタスク類似性学習の原理的アプローチ（A Principled Approach for Learning Task Similarity in Multitask Learning）</news:title>
   <news:publication_date>2026-08-20T19:20:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725386</loc>
  <lastmod>2026-08-20T18:29:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>走査プローブの状態認識を自動化するニューラルネットワーク群（Scanning Probe State Recognition With Multi-Class Neural Network Ensembles）</news:title>
   <news:publication_date>2026-08-20T18:29:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725384</loc>
  <lastmod>2026-08-20T18:28:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子グラフの階層的潜在表現：グループを明示するティア方式（Tiered Latent Representations and Latent Spaces for Molecular Graphs）</news:title>
   <news:publication_date>2026-08-20T18:28:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725382</loc>
  <lastmod>2026-08-20T18:28:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼動画からの衝突までの時間予測（Forecasting Time-to-Collision from Monocular Video: Feasibility, Dataset, and Challenges）</news:title>
   <news:publication_date>2026-08-20T18:28:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725380</loc>
  <lastmod>2026-08-20T18:27:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stripe 82深層画像による銀河のバルジ・ディスク分解カタログ（Bulge plus disc and Sérsic decomposition catalogues for 16,908 galaxies in the SDSS Stripe 82 co-adds）</news:title>
   <news:publication_date>2026-08-20T18:27:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725378</loc>
  <lastmod>2026-08-20T18:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別の快適温度を少ない問合せで学ぶ（Learning Personalized Thermal Preferences via Bayesian Active Learning with Unimodality Constraints）</news:title>
   <news:publication_date>2026-08-20T18:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725376</loc>
  <lastmod>2026-08-20T18:27:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予算制約下のエッジサービス配置と需要推定（Budget-constrained Edge Service Provisioning with Demand Estimation via Bandit Learning）</news:title>
   <news:publication_date>2026-08-20T18:27:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725374</loc>
  <lastmod>2026-08-20T18:27:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>狭い隙間をニューラルネットワークで飛行させる—エンドツーエンド計画と制御のアプローチ（Flying through a narrow gap using neural network: an end-to-end planning and control approach）</news:title>
   <news:publication_date>2026-08-20T18:27:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/725372</loc>
  <lastmod>2026-08-20T17:34:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再電離期に迫る――LAGERが示したz≈7のライマンα銀河の意味（LYMAN ALPHA GALAXIES IN THE EPOCH OF REIONIZATION）</news:title>
   <news:publication_date>2026-08-20T17:34:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/725370</loc>
  <lastmod>2026-08-20T17:34:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等変性を持つエンティティ関係ネットワーク（Equivariant Entity-Relationship Networks）</news:title>
   <news:publication_date>2026-08-20T17:34:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/725368</loc>
  <lastmod>2026-08-20T17:34:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別処方型サポートベクターマシンによる再入院抑止（Prescriptive Cluster-Dependent Support Vector Machines with an Application to Reducing Hospital Readmissions）</news:title>
   <news:publication_date>2026-08-20T17:34:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/725366</loc>
  <lastmod>2026-08-20T17:33:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在単体位相モデル：多視点クラスタリングと不確実性の可視化（Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification）</news:title>
   <news:publication_date>2026-08-20T17:33:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/725364</loc>
  <lastmod>2026-08-20T17:33:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データが乏しくても深層学習を使うための生成モデル（Generative Models For Deep Learning with Very Scarce Data）</news:title>
   <news:publication_date>2026-08-20T17:33:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725362</loc>
  <lastmod>2026-08-20T17:33:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>屋内廊下環境における単眼カメラを用いたUAV位置推定（Localization of Unmanned Aerial Vehicles in Corridor Environments using Deep Learning）</news:title>
   <news:publication_date>2026-08-20T17:33:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725360</loc>
  <lastmod>2026-08-20T17:32:49Z</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>2026-08-20T17:32:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725358</loc>
  <lastmod>2026-08-20T16:41:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ココエルシビティ、平滑性とバイアスが変える分散低減確率的勾配法（Cocoercivity, Smoothness and Bias in Variance-Reduced Stochastic Gradient Methods）</news:title>
   <news:publication_date>2026-08-20T16:41:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/725356</loc>
  <lastmod>2026-08-20T16:41:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非共有結合に対する量子機械学習補正が密度汎関数計算を変える（Non-covalent quantum machine learning corrections to density functionals）</news:title>
   <news:publication_date>2026-08-20T16:41:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725354</loc>
  <lastmod>2026-08-20T16:40:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HYDRAによる応力最小化型ハイパーボリック埋め込み（HYDRA: A METHOD FOR STRAIN-MINIMIZING HYPERBOLIC EMBEDDING OF NETWORK- AND DISTANCE-BASED DATA）</news:title>
   <news:publication_date>2026-08-20T16:40:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725352</loc>
  <lastmod>2026-08-20T16:40:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的時系列解析による薬物応答モデル化（Multi-Task Time Series Analysis applied to Drug Response Modelling）</news:title>
   <news:publication_date>2026-08-20T16:40:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725350</loc>
  <lastmod>2026-08-20T16:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>斜め落下する液滴の深い液槽への衝突（Oblique droplet impact onto a deep liquid pool）</news:title>
   <news:publication_date>2026-08-20T16:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725348</loc>
  <lastmod>2026-08-20T16:39:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市販サラダの微生物汚染評価のための統一スペクトル解析ワークフロー（A unified spectra analysis workflow for the assessment of microbial contamination of ready-to-eat green salads）</news:title>
   <news:publication_date>2026-08-20T16:39:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725346</loc>
  <lastmod>2026-08-20T15:48:41Z</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>2026-08-20T15:48:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725344</loc>
  <lastmod>2026-08-20T15:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られたデータで機械的聴覚を改善する方法（Improving Machine Hearing on Limited Data Sets）</news:title>
   <news:publication_date>2026-08-20T15:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725342</loc>
  <lastmod>2026-08-20T15:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話応答選択における階層的情報学習（Learning Multi-Level Information for Dialogue Response Selection）</news:title>
   <news:publication_date>2026-08-20T15:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725340</loc>
  <lastmod>2026-08-20T15:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込みと規則を反復学習する知識グラフ推論（Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning）</news:title>
   <news:publication_date>2026-08-20T15:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725338</loc>
  <lastmod>2026-08-20T15:47:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-20T15:47:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725336</loc>
  <lastmod>2026-08-20T15:47:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴でMCTSをバイアスする一般ゲームへの適用（Biasing MCTS with Features for General Games）</news:title>
   <news:publication_date>2026-08-20T15:47:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/725334</loc>
  <lastmod>2026-08-20T15:46:59Z</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>2026-08-20T15:46:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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