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   <news:title>Kymatioによるスキャッタリング変換の実装と実用性（Kymatio: Scattering Transforms in Python）</news:title>
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   <news:title>CamLoc: リソース制約のあるスマートカメラでの姿勢推定に基づく歩行者位置検出（CamLoc: Pedestrian Location Detection from Pose Estimation on Resource-constrained Smart-cameras）</news:title>
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   <news:title>ラプラスカーネルにおける最小ノルム補間の一貫性は高次元現象である（Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon）</news:title>
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   <news:title>クラス認識型敵対的合成による胸部CTの肺結節合成（CLASS-AWARE ADVERSARIAL LUNG NODULE SYNTHESIS IN CT IMAGES）</news:title>
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   <news:title>対話に基づく会議スケジューリングの強化学習（MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>芸術表現における物体認識のための教師なしスタイル適応（Artistic Object Recognition by Unsupervised Style Adaptation）</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>カテーテル室からの循環器入院予測（Forecasting Cardiology Admissions from Catheterization Laboratory）</news:title>
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   <news:title>現代機械学習実践とバイアス‑バリアンスの再考（Reconciling Modern Machine Learning Practice and the Bias-Variance Trade-off）</news:title>
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   <news:title>プロキシを用いた高次元での転移学習（Predicting with Proxies: Transfer Learning in High Dimension）</news:title>
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   <news:title>塩ドームのノイズ耐性検出と追跡（Noise-robust detection and tracking of salt domes in postmigrated volumes using texture, tensors, and subspace learning）</news:title>
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   <news:title>スケーラブルなスパース変分ガウス過程によるGAM（Scalable GAM using sparse variational Gaussian processes）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>深層手指姿勢推定を組み合わせたタッチ可能プロジェクタ深度システム（Enhanced Touchable Projector-depth System with Deep Hand Pose Estimation）</news:title>
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   <news:title>高密度核物質中の重クォークからのグルオン放出（Gluon emission from heavy quarks in dense nuclear matter）</news:title>
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   <news:title>幅（Width）がもたらす最適化の転移：Basinsの消失について（On the Benefit of Width for Neural Networks: Disappearance of Basins）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>マルチバリアントMRIバイオマーカーがアルツハイマー様認知機能障害をより良く予測する（Multivariate MR Biomarkers Better Predict Cognitive Dysfunction in Mouse Models of Alzheimer’s Disease）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>スケッチのための点群多列Point-CNN（Multi-column Point-CNN for Sketch Segmentation）</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>分散確率的勾配法の連続時間解析（A continuous-time analysis of distributed stochastic gradient）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>重みの対称性が深層ニューラルネットワークにもたらす効率化（Exploring Weight Symmetry in Deep Neural Networks）</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>UAVによる車両検出：Faster R-CNNとYOLOv3の比較（Car Detection using Unmanned Aerial Vehicles: Comparison between Faster R-CNN and YOLOv3）</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>カスケード拡散を扱う変分トポロジカルニューラルモデル（A Variational Topological Neural Model for Cascade-based Diffusion in Networks）</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>物体指向の予測と計画による物理相互作用の思考（Reasoning about Physical Interactions with Object-Oriented Prediction and Planning）</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>スペクトル制御によるGANの計算と一般化の改善（On Computation and Generalization of GANs with Spectrum Control）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>知識蒸留による深層ニューラルネットワークの可解釈化（Improving the Interpretability of Deep Neural Networks with Knowledge Distillation）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>がん薬感受性予測の深層学習的前進（tCNNS: Convolutional Neural Networks for Drug Response Prediction）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Wikibook-BotによるWikipedia本の自動生成（Wikibook-Bot - Automatic Generation of a Wikipedia Book）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像ラベルのみからの粗から細への意味セグメンテーション（Coarse-to-fine Semantic Segmentation from Image-level Labels）</news:title>
   <news:publication_date>2026-07-22T03:33:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/714540</loc>
  <lastmod>2026-07-22T03:24:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-22T03:24:33Z</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>パッシブ・アグレッシブ学習と制御（Passive-Aggressive Learning and Control）</news:title>
   <news:publication_date>2026-07-22T03:24:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発散トライアングルによる生成器・エネルギー型・推論モデルの共同学習（Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model）</news:title>
   <news:publication_date>2026-07-22T03:24:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識表現学習の定量的レビュー（Knowledge Representation Learning: A Quantitative Review）</news:title>
   <news:publication_date>2026-07-22T03:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714532</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>カリカチュアで明らかになる顔表現の構造（Deep Convolutional Neural Networks in the Face of Caricature: Identity and Image Revealed）</news:title>
   <news:publication_date>2026-07-22T03:23:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714530</loc>
  <lastmod>2026-07-22T03:23:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス意識型画像変換の実務的意義（INSTAGAN: INSTANCE-AWARE IMAGE-TO-IMAGE TRANSLATION）</news:title>
   <news:publication_date>2026-07-22T03:23:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714528</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>ハイパーグラフのクラスタリング：モジュラリティ最大化アプローチ（Hypergraph Clustering: A Modularity Maximization Approach）</news:title>
   <news:publication_date>2026-07-22T02:32:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714526</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>構造化スパース性に基づく信号分類の新枠組み（Structured Sparsity Models for Classification）</news:title>
   <news:publication_date>2026-07-22T02:31:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714524</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>文単位の事前学習と言語モデリングを超えて（Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling）</news:title>
   <news:publication_date>2026-07-22T02:31:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714522</loc>
  <lastmod>2026-07-22T02:31:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散版CMA-ESの提案（A discrete version of CMA-ES）</news:title>
   <news:publication_date>2026-07-22T02:31:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714520</loc>
  <lastmod>2026-07-22T02:31:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-22T02:31:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714518</loc>
  <lastmod>2026-07-22T02:30:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Clickbait検出チャレンジが示した実務的教訓（The Clickbait Challenge 2017: Towards a Regression Model for Clickbait Strength）</news:title>
   <news:publication_date>2026-07-22T02:30:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714516</loc>
  <lastmod>2026-07-22T02:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セミパラメトリック差の差分法と高次元制御変数（Semiparametric Difference-in-Differences with Potentially Many Control Variables）</news:title>
   <news:publication_date>2026-07-22T02:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714514</loc>
  <lastmod>2026-07-22T01:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による適応的画像サンプリングとXRF再構成への応用（Adaptive Image Sampling using Deep Learning and its Application on X-Ray Fluorescence Image Reconstruction）</news:title>
   <news:publication_date>2026-07-22T01:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714512</loc>
  <lastmod>2026-07-22T01:39:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-22T01:39:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714510</loc>
  <lastmod>2026-07-22T01:38:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープビルボード：物理世界での自動運転テスト（DeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems）</news:title>
   <news:publication_date>2026-07-22T01:38:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714508</loc>
  <lastmod>2026-07-22T01:37:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波（mmWave）ネットワークにおけるバックホール容量制約への深層強化学習による対処（Dealing with Limited Backhaul Capacity in Millimeter Wave Systems: A Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-07-22T01:37:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714506</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>自動化されたストリーム学習の適応戦略（Automated Adaptation Strategies for Stream Learning）</news:title>
   <news:publication_date>2026-07-22T01:37:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714504</loc>
  <lastmod>2026-07-22T01:37:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による量子断熱アルゴリズム設計（Quantum Adiabatic Algorithm Design using Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-22T01:37:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714502</loc>
  <lastmod>2026-07-22T01:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドラウプナー波の早期検出に向けた深層学習の適用（Early Detection of the Draupner Wave Using Deep Learning）</news:title>
   <news:publication_date>2026-07-22T01:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714500</loc>
  <lastmod>2026-07-22T00:45:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きな時間変動を持つタイムラプス動画の未来フレーム意味セグメンテーション（Future frame semantic segmentation of time-lapsed videos with large temporal displacement）</news:title>
   <news:publication_date>2026-07-22T00:45:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714498</loc>
  <lastmod>2026-07-22T00:45:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相制約に基づくホームオモルフィック自己符号化の限界と指針（Topological Constraints on Homeomorphic Auto-Encoding）</news:title>
   <news:publication_date>2026-07-22T00:45:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714496</loc>
  <lastmod>2026-07-22T00:45:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的にパラメータ化された分布でGANを評価する意味（Evaluating Generative Adversarial Networks on Explicitly Parameterized Distributions）</news:title>
   <news:publication_date>2026-07-22T00:45:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714494</loc>
  <lastmod>2026-07-22T00:44:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dポイントカプセルネットワーク（3D Point Capsule Networks）</news:title>
   <news:publication_date>2026-07-22T00:44:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714492</loc>
  <lastmod>2026-07-22T00:44:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-22T00:44:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714490</loc>
  <lastmod>2026-07-22T00:44:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-22T00:44:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714488</loc>
  <lastmod>2026-07-22T00:43:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バグ修正から学ぶソースコードの変異生成（Learning How to Mutate Source Code from Bug-Fixes）</news:title>
   <news:publication_date>2026-07-22T00:43:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714486</loc>
  <lastmod>2026-07-21T23:53:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SMPLRによる3D人体姿勢と形状復元（SMPLR: Deep SMPL reverse for 3D human pose and shape recovery）</news:title>
   <news:publication_date>2026-07-21T23:53:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714484</loc>
  <lastmod>2026-07-21T23:52:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-21T23:52:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714482</loc>
  <lastmod>2026-07-21T23:52:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフ・ザ・グリッドモデルに基づく深層学習（OFF-THE-GRID MODEL BASED DEEP LEARNING (O-MODL)）</news:title>
   <news:publication_date>2026-07-21T23:52:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/714480</loc>
  <lastmod>2026-07-21T23:52:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis（Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714478</loc>
  <lastmod>2026-07-21T23:52:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3次元幾何整合性で学ぶ半教師ありセマンティックセグメンテーション（S4-Net: Geometry-Consistent Semi-Supervised Semantic Segmentation）</news:title>
   <news:publication_date>2026-07-21T23:52:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714476</loc>
  <lastmod>2026-07-21T23:51:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表面ネットワークと一般被覆（Surface Networks via General Covers）</news:title>
   <news:publication_date>2026-07-21T23:51:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-07-21T23:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/714472</loc>
  <lastmod>2026-07-21T23:00:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載エッジコンピューティングと深層強化学習（Vehicular Edge Computing via Deep Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-07-21T23:00:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク認識型生成的不確実性による分布外入力への堅牢性（Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty）</news:title>
   <news:publication_date>2026-07-21T23:00:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714468</loc>
  <lastmod>2026-07-21T23:00:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ探索空間によるニューラルアーキテクチャ探索の拡張（Neural Architecture Search Over a Graph Search Space）</news:title>
   <news:publication_date>2026-07-21T23:00:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714466</loc>
  <lastmod>2026-07-21T22:59:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層分離で高速化する分散深層学習（Stanza: Layer Separation for Distributed Training in Deep Learning）</news:title>
   <news:publication_date>2026-07-21T22:59:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714464</loc>
  <lastmod>2026-07-21T22:59:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低遅延でプライバシーを守る推論の実現（Low Latency Privacy Preserving Inference）</news:title>
   <news:publication_date>2026-07-21T22:59:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714462</loc>
  <lastmod>2026-07-21T22:59:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークを用いたグレースケール画像の自動色付け（Sampling using Neural Networks for colorizing the grayscale images）</news:title>
   <news:publication_date>2026-07-21T22:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714460</loc>
  <lastmod>2026-07-21T22:59:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース非負CANDECOMP/PARAFAC分解の比較研究（Sparse Nonnegative CANDECOMP/PARAFAC Decomposition in Block Coordinate Descent Framework: A Comparison Study）</news:title>
   <news:publication_date>2026-07-21T22:59:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714458</loc>
  <lastmod>2026-07-21T22:07:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低コスト自動医療診断デバイスの試作（Low-Cost Device Prototype for Automatic Medical Diagnosis Using Deep Learning Methods）</news:title>
   <news:publication_date>2026-07-21T22:07:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714456</loc>
  <lastmod>2026-07-21T21:49:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳領域とディスレクシアの相関・分類のための特徴量と機械学習（Features and Machine Learning for Correlating and Classifying between Brain Areas and Dyslexia）</news:title>
   <news:publication_date>2026-07-21T21:49:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714454</loc>
  <lastmod>2026-07-21T21:49:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データマニフォールドの双線形モデリングによる動的MRI復元（Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery）</news:title>
   <news:publication_date>2026-07-21T21:49:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714452</loc>
  <lastmod>2026-07-21T21:49:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フロンティア市場における修正版Black‑Scholesと機械学習による株価予測（Predicting the Stock Price of Frontier Markets Using Modified Black‑Scholes Option Pricing Model and Machine Learning）</news:title>
   <news:publication_date>2026-07-21T21:49:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714450</loc>
  <lastmod>2026-07-21T21:48:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的敵対的ユーザモデルによる強化学習推薦（Generative Adversarial User Model for Reinforcement Learning Based Recommendation System）</news:title>
   <news:publication_date>2026-07-21T21:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714448</loc>
  <lastmod>2026-07-21T21:48:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制御語彙の埋め込みで捉えるトランスレーショナル科学（Identifying translational science through embeddings of controlled vocabularies）</news:title>
   <news:publication_date>2026-07-21T21:48:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714446</loc>
  <lastmod>2026-07-21T21:48:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重ニューラル・カウンターファクチュアル後悔最小化（Double Neural Counterfactual Regret Minimization）</news:title>
   <news:publication_date>2026-07-21T21:48:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714444</loc>
  <lastmod>2026-07-21T20:56:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠隔教師あり学習におけるクロスリレーション・クロスバッグ注意機構（Cross-relation Cross-bag Attention for Distantly-supervised Relation Extraction）</news:title>
   <news:publication_date>2026-07-21T20:56:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714442</loc>
  <lastmod>2026-07-21T20:56:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜画像を用いた糖尿病性網膜症の早期検出と重症度評価（Deep Learning based Early Detection and Grading of Diabetic Retinopathy Using Retinal Fundus Images）</news:title>
   <news:publication_date>2026-07-21T20:56:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714440</loc>
  <lastmod>2026-07-21T20:55:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生体表面の登録精度向上のためのフォワードプロパゲーション（Eyes on the Prize: Improving Biological Surface Registration via Forward Propagation）</news:title>
   <news:publication_date>2026-07-21T20:55:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714438</loc>
  <lastmod>2026-07-21T20:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>システムレベル熱流体シミュレーションにおける誤差推定とメッシュ・モデル最適化のデータ駆動フレームワーク（A Data-driven Framework for Error Estimation and Mesh-Model Optimization in System-level Thermal-Hydraulic Simulation）</news:title>
   <news:publication_date>2026-07-21T20:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714436</loc>
  <lastmod>2026-07-21T20:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速データ駆動型MPCを実現する線形化ガウス過程（Linearized Gaussian Processes for Fast Data-driven Model Predictive Control）</news:title>
   <news:publication_date>2026-07-21T20:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714434</loc>
  <lastmod>2026-07-21T20:55:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習可能な動的生成モデルと交互時系列逆伝播（Learning Dynamic Generator Model by Alternating Back-Propagation Through Time）</news:title>
   <news:publication_date>2026-07-21T20:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714432</loc>
  <lastmod>2026-07-21T20:55:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユークリッド空間データの階層クラスタリング改良（Hierarchical Clustering for Euclidean Data）</news:title>
   <news:publication_date>2026-07-21T20:55:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714430</loc>
  <lastmod>2026-07-21T20:04:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察データ下での交絡除去強化学習（Deconfounding Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-21T20:04:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714428</loc>
  <lastmod>2026-07-21T20:03:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QuickSelによる迅速な選択性学習（QuickSel: Quick Selectivity Learning with Mixture Models）</news:title>
   <news:publication_date>2026-07-21T20:03:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714426</loc>
  <lastmod>2026-07-21T20:03:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間ライトシートの自己修復（Self-healing of space-time light sheets）</news:title>
   <news:publication_date>2026-07-21T20:03:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714424</loc>
  <lastmod>2026-07-21T20:02:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BlinkMLによる高速かつ確率的保証付きの学習（BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees）</news:title>
   <news:publication_date>2026-07-21T20:02:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714422</loc>
  <lastmod>2026-07-21T20:02:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画からの2D→3D顔復元による虚偽検出（Deception Detection by 2D-to-3D Face Reconstruction from Videos）</news:title>
   <news:publication_date>2026-07-21T20:02:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714420</loc>
  <lastmod>2026-07-21T20:02:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負データのための一般化スコアマッチング（Generalized Score Matching for Non-Negative Data）</news:title>
   <news:publication_date>2026-07-21T20:02:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714418</loc>
  <lastmod>2026-07-21T20:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新しい骨格ベース表現による3D人体動作認識（Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-21T20:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714416</loc>
  <lastmod>2026-07-21T19:10:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ℓ0,∞に基づく畳み込みスパースコーディングへの貪欲法（A Greedy Approach to ℓ0,∞Based Convolutional Sparse Coding）</news:title>
   <news:publication_date>2026-07-21T19:10:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714414</loc>
  <lastmod>2026-07-21T19:10:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性オートエンコーダによる圧縮表現学習（Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization）</news:title>
   <news:publication_date>2026-07-21T19:10:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714412</loc>
  <lastmod>2026-07-21T19:10:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースな暗黙的フィードバックに対する深層アイテムベース協調フィルタリング（Deep Item-based Collaborative Filtering for Sparse Implicit Feedback）</news:title>
   <news:publication_date>2026-07-21T19:10:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714410</loc>
  <lastmod>2026-07-21T19:09:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号化投影からのライトフィールド再構築を統一的に扱う学習フレームワーク（A Unified Learning Based Framework for Light Field Reconstruction from Coded Projections）</news:title>
   <news:publication_date>2026-07-21T19:09:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714408</loc>
  <lastmod>2026-07-21T19:09:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己学習型スマートコントラクトの可能性（Toward a self-learned Smart Contracts）</news:title>
   <news:publication_date>2026-07-21T19:09:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714406</loc>
  <lastmod>2026-07-21T19:08:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフデータに対する敵対的攻撃と防御の概観（Adversarial Attack and Defense on Graph Data）</news:title>
   <news:publication_date>2026-07-21T19:08:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714404</loc>
  <lastmod>2026-07-21T19:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業プロセスのパラメータ予測に関する機械学習の実用化（Prediction of Industrial Process Parameters using Artificial Intelligence Algorithms）</news:title>
   <news:publication_date>2026-07-21T19:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714402</loc>
  <lastmod>2026-07-21T18:17:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模多言語文センテンス埋め込みによるゼロショット転移の実現（Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond）</news:title>
   <news:publication_date>2026-07-21T18:17:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714400</loc>
  <lastmod>2026-07-21T18:11:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在変数モデリングによる生成概念表現（Latent Variable Modeling for Generative Concept Representations and Deep Generative Models）</news:title>
   <news:publication_date>2026-07-21T18:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714398</loc>
  <lastmod>2026-07-21T18:11:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生涯事実学習（Exploring the Challenges towards Lifelong Fact Learning）</news:title>
   <news:publication_date>2026-07-21T18:11:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714396</loc>
  <lastmod>2026-07-21T18:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤観測ネットワークにおける最尤推定とグラフマッチング（Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks）</news:title>
   <news:publication_date>2026-07-21T18:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714394</loc>
  <lastmod>2026-07-21T18:10:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSSTによるキロノヴァの偶発的検出がもたらす変化（Serendipitous Discoveries of Kilonovae in the LSST Main Survey: Maximising Detections of Sub-Threshold Gravitational Wave Events）</news:title>
   <news:publication_date>2026-07-21T18:10:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714392</loc>
  <lastmod>2026-07-21T18:10:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓移植患者の詳細な心機能解析を可能にする計算モデルの応用（Deep phenotyping of cardiac function in heart transplant patients using cardiovascular systems models）</news:title>
   <news:publication_date>2026-07-21T18:10:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714390</loc>
  <lastmod>2026-07-21T18:09:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分画像解析に機械学習を適用する比較研究（Machine Learning on Difference Image Analysis: A comparison of methods for transient detection）</news:title>
   <news:publication_date>2026-07-21T18:09:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714388</loc>
  <lastmod>2026-07-21T17:18:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数アクセスネットワーク上の疎なGGMの構造学習（Structure Learning of Sparse GGMs over Multiple Access Networks）</news:title>
   <news:publication_date>2026-07-21T17:18:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714386</loc>
  <lastmod>2026-07-21T17:17:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助ニューラルネットワークで週末・祝日を扱う隣接（アジョイント）ネットワーク（Using an Ancillary Neural Network to Capture Weekends and Holidays in an Adjoint Neural Network Architecture for Intelligent Building Management）</news:title>
   <news:publication_date>2026-07-21T17:17:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714384</loc>
  <lastmod>2026-07-21T17:17:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>製造業の大規模マルチストリーム監視と診断の統合手法（Large Multistream Data Analytics for Monitoring and Diagnostics in Manufacturing Systems）</news:title>
   <news:publication_date>2026-07-21T17:17:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714382</loc>
  <lastmod>2026-07-21T17:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模機械学習のための確率的信頼領域不完全ニュートン法（Stochastic Trust Region Inexact Newton Method for Large-scale Machine Learning）</news:title>
   <news:publication_date>2026-07-21T17:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714380</loc>
  <lastmod>2026-07-21T17:16:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図（ECG）セグメンテーションと誤り訂正の実践的示唆（ECG Segmentation by Neural Networks: Errors and Correction）</news:title>
   <news:publication_date>2026-07-21T17:16:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714378</loc>
  <lastmod>2026-07-21T17:16:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Androidマルウェア検出における深層学習の応用レビュー（A Review on The Use of Deep Learning in Android Malware Detection）</news:title>
   <news:publication_date>2026-07-21T17:16:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714376</loc>
  <lastmod>2026-07-21T17:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実顕微鏡画像のノイズ特性に合わせたデータセットとその示唆（A Poisson-Gaussian Denoising Dataset with Real Fluorescence Microscopy Images）</news:title>
   <news:publication_date>2026-07-21T17:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714374</loc>
  <lastmod>2026-07-21T16:24:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報量に基づく物体アノテーション選択（INFORMATIVE OBJECT ANNOTATIONS）</news:title>
   <news:publication_date>2026-07-21T16:24:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714372</loc>
  <lastmod>2026-07-21T16:24:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏ったデータで「学ばせない」ための訓練法（Learning Not to Learn: Training Deep Neural Networks with Biased Data）</news:title>
   <news:publication_date>2026-07-21T16:24:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714370</loc>
  <lastmod>2026-07-21T16:23:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子化対話言語モデルが変えたもの（Quantized-Dialog Language Model for Goal-Oriented Conversational Systems）</news:title>
   <news:publication_date>2026-07-21T16:23:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714368</loc>
  <lastmod>2026-07-21T16:23:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地下鉄到着表示が乗客数に与える影響（The Impact of Countdown Clocks on Subway Ridership in New York City）</news:title>
   <news:publication_date>2026-07-21T16:23:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714366</loc>
  <lastmod>2026-07-21T16:23:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医用画像における文脈選択的注意を用いた領域提案ネットワーク（Region Proposal Networks with Contextual Selective Attention for Real-Time Organ Detection）</news:title>
   <news:publication_date>2026-07-21T16:23:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714364</loc>
  <lastmod>2026-07-21T16:22:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるアンテナ選択が変える無信頼リレーネットワーク（Machine Learning-Based Antenna Selection in Untrusted Relay Networks）</news:title>
   <news:publication_date>2026-07-21T16:22:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714362</loc>
  <lastmod>2026-07-21T16:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的解析レポートをそのまま使うマルウェア検出の実務フレームワーク（MalDy: Portable, Data-Driven Malware Detection using Natural Language Processing and Machine Learning Techniques on Behavioral Analysis Reports）</news:title>
   <news:publication_date>2026-07-21T16:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714360</loc>
  <lastmod>2026-07-21T15:31:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数の大きな地震イメージから地層境界を追跡する手法（Multi-resolution neural networks for tracking seismic horizons from few training images）</news:title>
   <news:publication_date>2026-07-21T15:31:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714358</loc>
  <lastmod>2026-07-21T15:13:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現実世界でロボットに歩かせる学習（Learning to Walk via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-21T15:13:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714356</loc>
  <lastmod>2026-07-21T15:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短いヒングリッシュ文の筆者帰属における教師あり学習法の考察（An Investigation of Supervised Learning Methods for Authorship Attribution in Short Hinglish Texts using Char &amp;amp; Word N-grams）</news:title>
   <news:publication_date>2026-07-21T15:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714354</loc>
  <lastmod>2026-07-21T15:12:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DUNEでの非標準ニュートリノ相互作用（NSI）と可変ビームによるパラメータ相関の可視化（Correlations and degeneracies among the NSI parameters with tunable beams at DUNE）</news:title>
   <news:publication_date>2026-07-21T15:12:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714352</loc>
  <lastmod>2026-07-21T15:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未教師付ドメイン適応のためのCORAL+（THE CORAL+ ALGORITHM FOR UNSUPERVISED DOMAIN ADAPTATION OF PLDA）</news:title>
   <news:publication_date>2026-07-21T15:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714350</loc>
  <lastmod>2026-07-21T15:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチエージェント強化学習によるマーケットメイクの最適化（Optimizing Market Making using Multi-Agent Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-21T15:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714348</loc>
  <lastmod>2026-07-21T15:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層顔属性解析の総覧（A Survey of Deep Facial Attribute Analysis）</news:title>
   <news:publication_date>2026-07-21T15:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714346</loc>
  <lastmod>2026-07-21T14:20:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハッシュベースニューラルネットの理論的理解（Towards a Theoretical Understanding of Hashing-Based Neural Nets）</news:title>
   <news:publication_date>2026-07-21T14:20:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714344</loc>
  <lastmod>2026-07-21T14:19:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による電磁反演（Deep learning electromagnetic inversion with convolutional neural networks）</news:title>
   <news:publication_date>2026-07-21T14:19:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714342</loc>
  <lastmod>2026-07-21T14:19:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム剪定が示す深層畳み込みニューラルネットワークの可塑性（Studying the Plasticity in Deep Convolutional Neural Networks using Random Pruning）</news:title>
   <news:publication_date>2026-07-21T14:19:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714340</loc>
  <lastmod>2026-07-21T14:19:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習を使った増強系列タグ付けシステムの新概念（A New Concept of Deep Reinforcement Learning based Augmented General Sequence Tagging System）</news:title>
   <news:publication_date>2026-07-21T14:19:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714338</loc>
  <lastmod>2026-07-21T14:18:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー定義音声語のfew-shot学習の検討（An Investigation of Few-Shot Learning in Spoken Term Classification）</news:title>
   <news:publication_date>2026-07-21T14:18:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714336</loc>
  <lastmod>2026-07-21T14:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソース表現を逐次洗練するNMTの提案（Learning to Refine Source Representations for Neural Machine Translation）</news:title>
   <news:publication_date>2026-07-21T14:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714334</loc>
  <lastmod>2026-07-21T14:18:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意図検出とスロット抽出のためのBi-model RNNセマンティックフレーム解析（A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling）</news:title>
   <news:publication_date>2026-07-21T14:18:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714332</loc>
  <lastmod>2026-07-21T13:27:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D PersonVLADによる全長動画のグローバル表現学習（3D PersonVLAD: Learning Deep Global Representations for Video-based Person Re-identification）</news:title>
   <news:publication_date>2026-07-21T13:27:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714330</loc>
  <lastmod>2026-07-21T13:26:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RegNetによる画像間ポーズ推定の最適化学習（RegNet: Learning the Optimization of Direct Image-to-Image Pose Registration）</news:title>
   <news:publication_date>2026-07-21T13:26:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714328</loc>
  <lastmod>2026-07-21T13:26:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多版本プログラミングに着想を得た音声敵対的入力の検出手法（A Multiversion Programming Inspired Approach to Detecting Audio Adversarial Examples）</news:title>
   <news:publication_date>2026-07-21T13:26:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714326</loc>
  <lastmod>2026-07-21T13:25:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的オンライン勾配降下法の問い合わせ複雑度改善（Dynamic Online Gradient Descent with Improved Query Complexity）</news:title>
   <news:publication_date>2026-07-21T13:25:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714324</loc>
  <lastmod>2026-07-21T13:25:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関属性を考慮した応用駆動型プライバシー保護データ公開 (Application-driven Privacy-preserving Data Publishing with Correlated Attributes)</news:title>
   <news:publication_date>2026-07-21T13:25:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714322</loc>
  <lastmod>2026-07-21T13:25:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分ラベル付きデータを用いた深層畳み込みGANによる食品認識（Deep Convolutional Generative Adversarial Network Based Food Recognition Using Partially Labeled Data）</news:title>
   <news:publication_date>2026-07-21T13:25:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714320</loc>
  <lastmod>2026-07-21T13:25:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コインテレーション・ペアのポートフォリオ最適化（Portfolio Optimization for Cointelated Pairs: SDEs vs Machine Learning）</news:title>
   <news:publication_date>2026-07-21T13:25:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714318</loc>
  <lastmod>2026-07-21T12:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>指紋画像生成における接続性重視GAN（Finger-GAN: Generating Realistic Fingerprint Images Using Connectivity Imposed GAN）</news:title>
   <news:publication_date>2026-07-21T12:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714316</loc>
  <lastmod>2026-07-21T12:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的専門家混合モデルにおけるドロップアウト正則化（DROPOUT REGULARIZATION IN HIERARCHICAL MIXTURE OF EXPERTS）</news:title>
   <news:publication_date>2026-07-21T12:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714314</loc>
  <lastmod>2026-07-21T12:33:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動き選択的予測による映像フレーム合成（Motion Selective Prediction for Video Frame Synthesis）</news:title>
   <news:publication_date>2026-07-21T12:33:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714312</loc>
  <lastmod>2026-07-21T12:33:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アベル133領域のX線点源カタログ（A Catalog of X-Ray Point Sources in the Abell 133 Region）</news:title>
   <news:publication_date>2026-07-21T12:33:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714310</loc>
  <lastmod>2026-07-21T12:33:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム多項式の低次数近似 (Low Degree Approximation of Random Polynomials)</news:title>
   <news:publication_date>2026-07-21T12:33:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714308</loc>
  <lastmod>2026-07-21T12:32:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合次数スペクトルクラスタリング（Mixed-Order Spectral Clustering for Networks）</news:title>
   <news:publication_date>2026-07-21T12:32:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714306</loc>
  <lastmod>2026-07-21T12:32:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム深層ニューラルネットワークは単純関数にバイアスを持つ（Random deep neural networks are biased towards simple functions）</news:title>
   <news:publication_date>2026-07-21T12:32:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714304</loc>
  <lastmod>2026-07-21T11:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ拡張のためのシーケンス間学習（Sequence to Sequence Learning for Query Expansion）</news:title>
   <news:publication_date>2026-07-21T11:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714302</loc>
  <lastmod>2026-07-21T11:41:56Z</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参加者不確実性対応の共同深層学習（Privacy-Preserving Collaborative Deep Learning with Unreliable Participants）</news:title>
   <news:publication_date>2026-07-21T11:41:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714300</loc>
  <lastmod>2026-07-21T11:41:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期株価ボラティリティ予測のためのマルチモーダル深層学習（Multimodal deep learning for short-term stock volatility prediction）</news:title>
   <news:publication_date>2026-07-21T11:41:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714298</loc>
  <lastmod>2026-07-21T11:40:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Tensor-TrainによるLSTM圧縮で単一チャネル音声強調を実現する（Tensor-Train Long Short-Term Memory for Monaural Speech Enhancement）</news:title>
   <news:publication_date>2026-07-21T11:40:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714296</loc>
  <lastmod>2026-07-21T11:40:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>X線タンパク質結晶の画像分類（Classification of X-Ray Protein Crystallization Using Deep Convolutional Neural Networks with a Finder Module）</news:title>
   <news:publication_date>2026-07-21T11:40:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714294</loc>
  <lastmod>2026-07-21T11:40:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンデマンド動画配信のためのディスパッチ学習（On-Demand Video Dispatch Networks: A Scalable End-to-End Learning Approach）</news:title>
   <news:publication_date>2026-07-21T11:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714292</loc>
  <lastmod>2026-07-21T11:40:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノロボットを用いた多発性がん検出の最適化視点（Nanorobots-assisted Detection of Multifocal Cancer: A Multimodal Optimization Perspective）</news:title>
   <news:publication_date>2026-07-21T11:40:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714290</loc>
  <lastmod>2026-07-21T10:49:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合再帰ネットワークによるマルチ入力視覚解析（Coupled Recurrent Network (CRN)）</news:title>
   <news:publication_date>2026-07-21T10:49:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714288</loc>
  <lastmod>2026-07-21T10:48:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によるバイオセンシングで腫瘍標的を直接狙う（Biosensing-by-learning Direct Targeting Strategy for Enhanced Tumor Sensitization）</news:title>
   <news:publication_date>2026-07-21T10:48:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714286</loc>
  <lastmod>2026-07-21T10:48:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味忠実度指標を用いた学習型顔画像圧縮（Learning based Facial Image Compression with Semantic Fidelity Metric）</news:title>
   <news:publication_date>2026-07-21T10:48:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714284</loc>
  <lastmod>2026-07-21T10:48:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声に対する敵対的攻撃の検出法：Noise Flooding（Noise Flooding for Detecting Audio Adversarial Examples Against Automatic Speech Recognition）</news:title>
   <news:publication_date>2026-07-21T10:48:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714282</loc>
  <lastmod>2026-07-21T10:48:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模過負荷MIMO向け学習可能射影勾配検出器（Trainable Projected Gradient Detector for Massive Overloaded MIMO Channels: Data-driven Tuning Approach）</news:title>
   <news:publication_date>2026-07-21T10:48:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714280</loc>
  <lastmod>2026-07-21T10:47:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーミュテーション・フェーズ防御（Permutation Phase Defense）</news:title>
   <news:publication_date>2026-07-21T10:47:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714278</loc>
  <lastmod>2026-07-21T10:47:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模単一細胞トランスクリプトームの並列クラスタリング手法（Parallel Clustering of Single Cell Transcriptomic Data with Split-Merge Sampling on Dirichlet Process Mixtures）</news:title>
   <news:publication_date>2026-07-21T10:47:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714276</loc>
  <lastmod>2026-07-21T09:56:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジとクラウドを分担する推論最適化の実践（JALAD: Joint Accuracy- and Latency-Aware Deep Structure Decoupling for Edge-Cloud Execution）</news:title>
   <news:publication_date>2026-07-21T09:56:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714274</loc>
  <lastmod>2026-07-21T09:55:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デュセンベリーの消費理論：慣習・学習・ラチェティング（Duesenberry’s Theory of Consumption: Habit, Learning, and Ratcheting）</news:title>
   <news:publication_date>2026-07-21T09:55:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714272</loc>
  <lastmod>2026-07-21T09:47:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トポロジカル保護の局所破綻を探る：充填因子依存の頑健な量子ホール非圧縮相の進化（Probing breakdown of topological protection: Filling-factor-dependent evolution of robust quantum Hall incompressible phases）</news:title>
   <news:publication_date>2026-07-21T09:47:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714270</loc>
  <lastmod>2026-07-21T09:47:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメインオントロジーから構築するニューラル意味解析器 (Building a Neural Semantic Parser from a Domain Ontology)</news:title>
   <news:publication_date>2026-07-21T09:47:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714268</loc>
  <lastmod>2026-07-21T09:45:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attention Branch Networkによる視覚説明と性能向上の統合（Attention Branch Network: Learning of Attention Mechanism for Visual Explanation）</news:title>
   <news:publication_date>2026-07-21T09:45:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714266</loc>
  <lastmod>2026-07-21T09:45:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TransNFCM：カテゴリ条件付き翻訳で捉えるファッション互換性（TransNFCM: Translation-Based Neural Fashion Compatibility Modeling）</news:title>
   <news:publication_date>2026-07-21T09:45:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714264</loc>
  <lastmod>2026-07-21T09:45:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レコメンダー向け深層オートエンコーダのパラメータ影響分析（Deep Autoencoder for Recommender Systems: Parameter Influence Analysis）</news:title>
   <news:publication_date>2026-07-21T09:45:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714262</loc>
  <lastmod>2026-07-21T08:54:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過学習パラメータ化された非線形学習：勾配降下が最短経路を取るのか（Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?）</news:title>
   <news:publication_date>2026-07-21T08:54:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714260</loc>
  <lastmod>2026-07-21T08:54:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Incomplete Multi-view Learningのための共同埋め込み学習と低ランク近似の枠組み（Joint Embedding Learning and Low-Rank Approximation: A Framework for Incomplete Multi-view Learning）</news:title>
   <news:publication_date>2026-07-21T08:54:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714258</loc>
  <lastmod>2026-07-21T08:54:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差密結合ネットワークによる画像復元（Residual Dense Network for Image Restoration）</news:title>
   <news:publication_date>2026-07-21T08:54:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714256</loc>
  <lastmod>2026-07-21T08:53:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク化エージェントのための側情報を用いた堅牢な拡散再帰最小二乗アルゴリズムの研究 (STUDY OF ROBUST DIFFUSION RECURSIVE LEAST SQUARES ALGORITHMS WITH SIDE INFORMATION FOR NETWORKED AGENTS)</news:title>
   <news:publication_date>2026-07-21T08:53:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714254</loc>
  <lastmod>2026-07-21T08:52:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化に声を与える手法（The Voice of Optimization）</news:title>
   <news:publication_date>2026-07-21T08:52:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714252</loc>
  <lastmod>2026-07-21T08:52:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>健康ツイートのクラスタリングのための深層表現学習（Deep Representation Learning for Clustering of Health Tweets）</news:title>
   <news:publication_date>2026-07-21T08:52:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714250</loc>
  <lastmod>2026-07-21T08:52:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショット時系列行動検出のためのSimilarity R-C3D（Similarity R-C3D for Few-shot Temporal Activity Detection）</news:title>
   <news:publication_date>2026-07-21T08:52:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714248</loc>
  <lastmod>2026-07-21T08:01:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーケンサー：シーケンス学習によるエンドツーエンドのプログラム修復（SEQUENCER: Sequence-to-Sequence Learning for End-to-End Program Repair）</news:title>
   <news:publication_date>2026-07-21T08:01:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714246</loc>
  <lastmod>2026-07-21T07:52:06Z</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時代の量子化学（Quantum Chemistry in the Age of Quantum Computing）</news:title>
   <news:publication_date>2026-07-21T07:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714244</loc>
  <lastmod>2026-07-21T07:51:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセンタートラフィック制御のための強化学習プロトタイピング基盤（Iroko: A Framework to Prototype Reinforcement Learning for Data Center Traffic Control）</news:title>
   <news:publication_date>2026-07-21T07:51:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714242</loc>
  <lastmod>2026-07-21T07:51:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VMAV-Cによる注意ベースのモデルベース強化学習（VMAV-C: A Deep Attention-based Reinforcement Learning Algorithm for Model-based Control）</news:title>
   <news:publication_date>2026-07-21T07:51:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714240</loc>
  <lastmod>2026-07-21T07:50:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病気予測のための自己注意付きグラフ畳み込み（SELF-ATTENTION EQUIPPED GRAPH CONVOLUTIONS FOR DISEASE PREDICTION）</news:title>
   <news:publication_date>2026-07-21T07:50:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714238</loc>
  <lastmod>2026-07-21T07:50:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無限木上のビッグデータ情報再構成（Big Data Information Reconstruction on an Infinite Tree for a 4×4-state Asymmetric Model with Community Effects）</news:title>
   <news:publication_date>2026-07-21T07:50:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714236</loc>
  <lastmod>2026-07-21T07:50:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォーマット認識型学習とFuzz生成（Format-aware Learn&amp;amp;Fuzz: Deep Test Data Generation for Efficient Fuzzing）</news:title>
   <news:publication_date>2026-07-21T07:50:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714234</loc>
  <lastmod>2026-07-21T06:59:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>P-V臨界現象とEinstein–Horndeski重力における黒洞の相転移（P-V criticality in the extended phase space of black holes in Einstein-Horndeski gravity）</news:title>
   <news:publication_date>2026-07-21T06:59:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714232</loc>
  <lastmod>2026-07-21T06:59:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-21T06:59:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714230</loc>
  <lastmod>2026-07-21T06:59:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量パーシステンスランドスケープ（Multiparameter Persistence Landscapes）</news:title>
   <news:publication_date>2026-07-21T06:59:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714228</loc>
  <lastmod>2026-07-21T06:59:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-21T06:59:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714226</loc>
  <lastmod>2026-07-21T06:58:55Z</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>2026-07-21T06:58:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714224</loc>
  <lastmod>2026-07-21T06:58:47Z</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>2026-07-21T06:58:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714222</loc>
  <lastmod>2026-07-21T06:58:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>隠れボトムを伴う三体束縛状態の予言（Possible bound states with hidden bottom from ¯K(∗)B(∗) ¯B(∗) systems）</news:title>
   <news:publication_date>2026-07-21T06:58:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714220</loc>
  <lastmod>2026-07-21T06:07:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MMD-GANの訓練改善と反発損失関数（IMPROVING MMD-GAN TRAINING WITH REPULSIVE LOSS FUNCTION）</news:title>
   <news:publication_date>2026-07-21T06:07:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714218</loc>
  <lastmod>2026-07-21T06:07:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループを保存するラベル埋め込みによるマルチラベル分類（Group Preserving Label Embedding for Multi-Label Classification）</news:title>
   <news:publication_date>2026-07-21T06:07:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714216</loc>
  <lastmod>2026-07-21T06:06:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ単位のディープ・ホワイトニングとカラー変換による画像翻訳（Image-to-Image Translation via Group-wise Deep Whitening-and-Coloring Transformation）</news:title>
   <news:publication_date>2026-07-21T06:06:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714214</loc>
  <lastmod>2026-07-21T06:06:27Z</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>2026-07-21T06:06:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714212</loc>
  <lastmod>2026-07-21T06:06:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化ゼロショット学習のための適応的信頼度平滑化（Adaptive Confidence Smoothing for Generalized Zero-Shot Learning）</news:title>
   <news:publication_date>2026-07-21T06:06:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714210</loc>
  <lastmod>2026-07-21T06:06:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種混在アドホックネットワークにおける安定割当のためのマルチプレイヤー多腕バンディット（Multi-player Multi-armed Bandits for Stable Allocation in Heterogeneous Ad-Hoc Networks）</news:title>
   <news:publication_date>2026-07-21T06:06:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714208</loc>
  <lastmod>2026-07-21T06:05:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不規則な画像文字を一体的に読むTextNet（TextNet: Irregular Text Reading from Images with an End-to-End Trainable Network）</news:title>
   <news:publication_date>2026-07-21T06:05:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714206</loc>
  <lastmod>2026-07-21T05:14:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-21T05:14:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714204</loc>
  <lastmod>2026-07-21T05:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二変量因果推論のベイズモデル（A Bayesian Model for Bivariate Causal Inference）</news:title>
   <news:publication_date>2026-07-21T05:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714202</loc>
  <lastmod>2026-07-21T05:13:49Z</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>2026-07-21T05:13:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714200</loc>
  <lastmod>2026-07-21T05:13:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結合解析辞書学習による逆変換の帰納学習（Coupled Analysis Dictionary Learning to inductively learn inversion: Application to real-time reconstruction of Biomedical signals）</news:title>
   <news:publication_date>2026-07-21T05:13:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714198</loc>
  <lastmod>2026-07-21T05:13:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データマッピングと並列化t-SNE（Big Data Mapping with parallelized t-SNE）</news:title>
   <news:publication_date>2026-07-21T05:13:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714196</loc>
  <lastmod>2026-07-21T05:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>設計パターン検出のための可解なソフトウェア表現：Feature Maps（Feature Maps: A Comprehensible Software Representation for Design Pattern Detection）</news:title>
   <news:publication_date>2026-07-21T05:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714194</loc>
  <lastmod>2026-07-21T05:12:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚に基づく深度マップ超解像の提案（Perceptual Deep Depth Super-Resolution）</news:title>
   <news:publication_date>2026-07-21T05:12:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714192</loc>
  <lastmod>2026-07-21T04:21:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一様安定性アルゴリズムの一般化境界（Generalization Bounds for Uniformly Stable Algorithms）</news:title>
   <news:publication_date>2026-07-21T04:21:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714190</loc>
  <lastmod>2026-07-21T04:21:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モーメントマッチングによるニューラル機械翻訳の訓練（Moment Matching Training for Neural Machine Translation）</news:title>
   <news:publication_date>2026-07-21T04:21:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714188</loc>
  <lastmod>2026-07-21T04:21:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の皮質信号を用いたRNNデコーダの高性能化（Recurrent Neural Network Decoders for 2D Cursor Control）</news:title>
   <news:publication_date>2026-07-21T04:21:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714186</loc>
  <lastmod>2026-07-21T04:20:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-07-21T04:20:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>賢く推測する：ラベルのみのブラックボックス敵対的攻撃に対する偏ったサンプリング（Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks）</news:title>
   <news:publication_date>2026-07-21T04:20:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714182</loc>
  <lastmod>2026-07-21T04:20:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>筆者適応型畳み込みニューラルネットワークによる簡潔なHMMベース手書き中国語認識（Writer-Aware CNN for Parsimonious HMM-Based Offline Handwritten Chinese Text Recognition）</news:title>
   <news:publication_date>2026-07-21T04:20:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714180</loc>
  <lastmod>2026-07-21T04:19:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間変化する有向グラフ上での非ベイズ的社会学習における自己確信の増加（On Increasing Self-Confidence in Non-Bayesian Social Learning over Time-Varying Directed Graphs）</news:title>
   <news:publication_date>2026-07-21T04:19:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714178</loc>
  <lastmod>2026-07-21T03:28:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空画像からの地表面日射量推定のための深層学習（Deep Learning for Inferring the Surface Solar Irradiance from Sky Imagery）</news:title>
   <news:publication_date>2026-07-21T03:28:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714176</loc>
  <lastmod>2026-07-21T03:28:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Au+Au衝突におけるオープンチャームハドロン生成の測定（Open charm hadron production at STAR）</news:title>
   <news:publication_date>2026-07-21T03:28:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714174</loc>
  <lastmod>2026-07-21T03:28:08Z</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・テレスコープの探索的データ解析（Exploratory Data Analysis of a Network Telescope）</news:title>
   <news:publication_date>2026-07-21T03:28:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714172</loc>
  <lastmod>2026-07-21T03:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルパーシステンス：深層ニューラルネットワークの構造的複雑性指標（NEURAL PERSISTENCE: A COMPLEXITY MEASURE FOR DEEP NEURAL NETWORKS USING ALGEBRAIC TOPOLOGY）</news:title>
   <news:publication_date>2026-07-21T03:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714170</loc>
  <lastmod>2026-07-21T03:27:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>列部分集合選択のための決定点過程（A determinantal point process for column subset selection）</news:title>
   <news:publication_date>2026-07-21T03:27:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714168</loc>
  <lastmod>2026-07-21T03:26:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化と電力制御のための強化学習（Reinforcement Learning for Self Organization and Power Control of Two-Tier Heterogeneous Networks）</news:title>
   <news:publication_date>2026-07-21T03:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714166</loc>
  <lastmod>2026-07-21T03:26:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>A-Optimal Projectionの量子アルゴリズムと量子回路（Quantum algorithm and quantum circuit for A-Optimal Projection: dimensionality reduction）</news:title>
   <news:publication_date>2026-07-21T03:26:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714164</loc>
  <lastmod>2026-07-21T02:35:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ラベルで高精度なトラフィック分類を達成する方法（How to Achieve High Classification Accuracy with Just a Few Labels: A Semi-supervised Approach Using Sampled Packets）</news:title>
   <news:publication_date>2026-07-21T02:35:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714162</loc>
  <lastmod>2026-07-21T02:34:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブリティッシュコロンビア沿岸の降雨パターン検出（Detecting British Columbia Coastal Rainfall Patterns by Clustering Gaussian Processes）</news:title>
   <news:publication_date>2026-07-21T02:34:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714160</loc>
  <lastmod>2026-07-21T02:34:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>いつコミュニケーションすべきかを学ぶ方法（LEARNING WHEN TO COMMUNICATE AT SCALE IN MULTIAGENT COOPERATIVE AND COMPETITIVE TASKS）</news:title>
   <news:publication_date>2026-07-21T02:34:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714158</loc>
  <lastmod>2026-07-21T02:34:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン専門家の反復フィードバックを容易にする多目的アンタイムルールマイニングシステム（A Multi-Objective Anytime Rule Mining System to Ease Iterative Feedback from Domain Experts）</news:title>
   <news:publication_date>2026-07-21T02:34:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714156</loc>
  <lastmod>2026-07-21T02:34:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス類似性を活かしたニューラルネット耐性強化（Leveraging Class Similarity to Improve Deep Neural Network Robustness）</news:title>
   <news:publication_date>2026-07-21T02:34:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714154</loc>
  <lastmod>2026-07-21T02:34:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水質情報のリアルタイム伝達を会話型言語モデルで実現する試み（Water quality information dissemination at real-time in South Africa using language modelling）</news:title>
   <news:publication_date>2026-07-21T02:34:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714152</loc>
  <lastmod>2026-07-21T02:33:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現学習で離散選択モデルを強化する（Enhancing Discrete Choice Models with Representation Learning）</news:title>
   <news:publication_date>2026-07-21T02:33:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714150</loc>
  <lastmod>2026-07-21T01:42:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子多体系における構造的複雑性の測定（Surveying structural complexity in quantum many-body systems）</news:title>
   <news:publication_date>2026-07-21T01:42:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714148</loc>
  <lastmod>2026-07-21T01:42:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ分解のためのエンドツーエンド学習（End-to-end Learning for Graph Decomposition）</news:title>
   <news:publication_date>2026-07-21T01:42:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714146</loc>
  <lastmod>2026-07-21T01:41:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rankin–Cohen 演算子の逆変換とホログラフィック変換（INVERSION OF RANKIN–COHEN OPERATORS VIA HOLOGRAPHIC TRANSFORM）</news:title>
   <news:publication_date>2026-07-21T01:41:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714144</loc>
  <lastmod>2026-07-21T01:41:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所群における矮小銀河の星形成史の再構築（The Local Group Dwarf Galaxies: The Star Formation Histories derived using the Long Period Variable Stars）</news:title>
   <news:publication_date>2026-07-21T01:41:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714142</loc>
  <lastmod>2026-07-21T01:41:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>γ-カプセルネットワークによる耐敵対性と説明可能性の向上（Increasing the adversarial robustness and explainability of capsule networks with γ-capsules）</news:title>
   <news:publication_date>2026-07-21T01:41:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714140</loc>
  <lastmod>2026-07-21T01:40:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人の示範で学ぶ自動運転の効率化（Parallelized Interactive Machine Learning on Autonomous Vehicles）</news:title>
   <news:publication_date>2026-07-21T01:40:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714138</loc>
  <lastmod>2026-07-21T01:40:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローレンツブーストネットワークによる自律的特徴工学（Lorentz Boost Networks: Autonomous Physics-Inspired Feature Engineering）</news:title>
   <news:publication_date>2026-07-21T01:40:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714136</loc>
  <lastmod>2026-07-21T00:49:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽系外縁天体の大規模探索を提案する深堀観測計画（Deep Drilling Fields for Solar System Science）</news:title>
   <news:publication_date>2026-07-21T00:49:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714134</loc>
  <lastmod>2026-07-21T00:49:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層化ベイズネットワークにおける推論手法の拡張（Inference in Graded Bayesian Networks）</news:title>
   <news:publication_date>2026-07-21T00:49:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714132</loc>
  <lastmod>2026-07-21T00:49:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプリングされた非線形動的システムの非線形ロバストフィルタリング（Nonlinear Robust Filtering of Sampled-Data Dynamical Systems）</news:title>
   <news:publication_date>2026-07-21T00:49:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714130</loc>
  <lastmod>2026-07-21T00:48:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Prior Visual Relationshipを用いたシーングラフ推論による視覚的質問応答（Scene Graph Reasoning with Prior Visual Relationship for Visual Question Answering）</news:title>
   <news:publication_date>2026-07-21T00:48:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714128</loc>
  <lastmod>2026-07-21T00:48:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的受理器における計算手法の実装と意義（Computations in Stochastic Acceptors）</news:title>
   <news:publication_date>2026-07-21T00:48:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714126</loc>
  <lastmod>2026-07-21T00:47:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AVRA: MRI画像からの萎縮自動視覚評価（Automatic Visual Ratings of Atrophy from MRI images using Recurrent Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-21T00:47:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714124</loc>
  <lastmod>2026-07-21T00:47:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過去の走査から学ぶ：新規構造を検出する断層再構成（LEARNING FROM PAST SCANS: TOMOGRAPHIC RECONSTRUCTION TO DETECT NEW STRUCTURES）</news:title>
   <news:publication_date>2026-07-21T00:47:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714122</loc>
  <lastmod>2026-07-20T23:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼映像から学ぶエピポーラ幾何に基づくマルチビュー深度と自己運動の学習 (Epipolar Geometry based Learning of Multi-view Depth and Ego-Motion from Monocular Sequences)</news:title>
   <news:publication_date>2026-07-20T23:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714120</loc>
  <lastmod>2026-07-20T23:56:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2D LiDARを用いた車両姿勢検出のための効率的なL字フィッティング手法 (An Efficient L-Shape Fitting Method for Vehicle Pose Detection with 2D LiDAR)</news:title>
   <news:publication_date>2026-07-20T23:56:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714118</loc>
  <lastmod>2026-07-20T23:56:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形復元写像を伴う有限次元符号化スキームの学習（Learning finite-dimensional coding schemes with nonlinear reconstruction maps）</news:title>
   <news:publication_date>2026-07-20T23:56:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714116</loc>
  <lastmod>2026-07-20T23:55:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバルニュースのバイラル予測とコミュニティ解析（Scalable prediction of global online media news virality）</news:title>
   <news:publication_date>2026-07-20T23:55:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714114</loc>
  <lastmod>2026-07-20T23:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学フロントエンドによる畳み込みニューラルネットワークの実装（An Optical Frontend for a Convolutional Neural Network）</news:title>
   <news:publication_date>2026-07-20T23:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714112</loc>
  <lastmod>2026-07-20T23:55:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの圧縮で医療向けAIを軽量化する（Artificial neural networks condensation: A strategy to facilitate adaption of machine learning in medical settings by reducing computational burden）</news:title>
   <news:publication_date>2026-07-20T23:55:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714110</loc>
  <lastmod>2026-07-20T23:55:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デコーダ入力を強化した非自己回帰型ニューラル機械翻訳（Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input）</news:title>
   <news:publication_date>2026-07-20T23:55:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714108</loc>
  <lastmod>2026-07-20T23:04:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスアーキテクチャ命令埋め込みモデルによるバイナリ解析の革新（A Cross-Architecture Instruction Embedding Model for Natural Language Processing-Inspired Binary Code Analysis）</news:title>
   <news:publication_date>2026-07-20T23:04:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714106</loc>
  <lastmod>2026-07-20T23:04:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルデータの文脈を取り込む埋め込み改良（Improving Context-Aware Semantic Relationships in Sparse Mobile Datasets）</news:title>
   <news:publication_date>2026-07-20T23:04:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714104</loc>
  <lastmod>2026-07-20T23:03:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合メンバーシップ再帰ニューラルネットワーク（Mixed Membership Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-20T23:03:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714102</loc>
  <lastmod>2026-07-20T23:03:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層クラスタリングで捉えるフレーミングを考慮した合理的無関心の効用関数推定（Estimating Rationally Inattentive Utility Functions with Deep Clustering for Framing - Applications in YouTube Engagement Dynamics）</news:title>
   <news:publication_date>2026-07-20T23:03:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714100</loc>
  <lastmod>2026-07-20T23:03:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル法における分布に依存しない不確実性定量（Distribution-Free Uncertainty Quantification for Kernel Methods by Gradient Perturbations）</news:title>
   <news:publication_date>2026-07-20T23:03:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714098</loc>
  <lastmod>2026-07-20T23:03:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知能チュータリングシステムの包括的歴史調査と最近の展開（Intelligent Tutoring Systems: A Comprehensive Historical Survey with Recent Developments）</news:title>
   <news:publication_date>2026-07-20T23:03:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714096</loc>
  <lastmod>2026-07-20T23:02:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セグメンタルな出力分布一致を用いた教師なし音声認識（UNSUPERVISED SPEECH RECOGNITION VIA SEGMENTAL EMPIRICAL OUTPUT DISTRIBUTION MATCHING）</news:title>
   <news:publication_date>2026-07-20T23:02:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714094</loc>
  <lastmod>2026-07-20T22:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VAEは本当に「新しいもの」を生み出せるか（Can VAEs Generate Novel Examples?）</news:title>
   <news:publication_date>2026-07-20T22:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714092</loc>
  <lastmod>2026-07-20T22:11:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超軽量ボゾンによる確率的重力波背景の初探索（A first search for a stochastic gravitational-wave background from ultralight bosons）</news:title>
   <news:publication_date>2026-07-20T22:11:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714090</loc>
  <lastmod>2026-07-20T22:10:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース言語における部分文字列類似性を活用した文書分類（Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification）</news:title>
   <news:publication_date>2026-07-20T22:10:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714088</loc>
  <lastmod>2026-07-20T22:10:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>K33フリーイジングモデルの推論とサンプリング（Inference and Sampling of K33-free Ising Models）</news:title>
   <news:publication_date>2026-07-20T22:10:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714086</loc>
  <lastmod>2026-07-20T22:09:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>G292.0+1.8のショックを受けた外層と周囲物質の詳細X線マッピング（Detailed X-ray Mapping of the Shocked Ejecta and Circumstellar Medium in G292.0+1.8）</news:title>
   <news:publication_date>2026-07-20T22:09:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714084</loc>
  <lastmod>2026-07-20T22:09:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルを用いた部分サンプリングFourier Ptychography（Deep Ptych: Subsampled Fourier Ptychography using Generative Priors）</news:title>
   <news:publication_date>2026-07-20T22:09:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714082</loc>
  <lastmod>2026-07-20T22:09:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬駆動の軽い教師あり学習で構造化予測を実現する方法（Search-Guided, Lightly-Supervised Training of Structured Prediction Energy Networks）</news:title>
   <news:publication_date>2026-07-20T22:09:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714080</loc>
  <lastmod>2026-07-20T21:18:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタアーキテクチャ探索の実務意義（Meta Architecture Search）</news:title>
   <news:publication_date>2026-07-20T21:18:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714078</loc>
  <lastmod>2026-07-20T21:08:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶を使って現場で学ぶMPC：オンライン学習で安定性保証を得る方法（Online learning with stability guarantees: A memory-based real-time model predictive controller）</news:title>
   <news:publication_date>2026-07-20T21:08:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714076</loc>
  <lastmod>2026-07-20T21:07:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TaxoGenによる無監督トピック階層の構築（TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clustering）</news:title>
   <news:publication_date>2026-07-20T21:07:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714074</loc>
  <lastmod>2026-07-20T21:07:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>30日再入院予測におけるニューラルネットワーク対ロジスティック回帰（Neural networks versus Logistic regression for 30 days all-cause readmission prediction）</news:title>
   <news:publication_date>2026-07-20T21:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714072</loc>
  <lastmod>2026-07-20T21:07:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超低遅延・高信頼通信（URLLC）のリスク対応資源配分と機械学習の役割（Risk-Aware Resource Allocation for URLLC）</news:title>
   <news:publication_date>2026-07-20T21:07:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714070</loc>
  <lastmod>2026-07-20T21:07:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム価格プログラムにおける動的需要応答モデルの学習 (Learning Dynamical Demand Response Model in Real-Time Pricing Program)</news:title>
   <news:publication_date>2026-07-20T21:07:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714068</loc>
  <lastmod>2026-07-20T21:06:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ計算クラスタの機械学習によるタスク失敗予測（Bioinformatics Computational Cluster Batch Task Profiling with Machine Learning for Failure Prediction）</news:title>
   <news:publication_date>2026-07-20T21:06:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714066</loc>
  <lastmod>2026-07-20T20:15:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペクトル画像の空間・スペクトル両面を用いた次元削減（Dimensionality Reduction of Hyperspectral Imagery Based on Spatial-spectral Manifold Learning）</news:title>
   <news:publication_date>2026-07-20T20:15:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714064</loc>
  <lastmod>2026-07-20T20:15:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エスケープルーム：階層的強化学習のための構成可能なテストベッド（Escape Room: A Configurable Testbed for Hierarchical Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-20T20:15:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714062</loc>
  <lastmod>2026-07-20T20:14:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アイスホッケー動画における姿勢と光学フローを用いた行動認識（Temporal Hockey Action Recognition via Pose and Optical Flows）</news:title>
   <news:publication_date>2026-07-20T20:14:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714060</loc>
  <lastmod>2026-07-20T20:14:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-20T20:14:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714058</loc>
  <lastmod>2026-07-20T20:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レビュー対象の縮小：変更セット削減のための指摘予測（Shrinking Code Review Changesets through Remark Prediction）</news:title>
   <news:publication_date>2026-07-20T20:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714056</loc>
  <lastmod>2026-07-20T20:13:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別データに対する普遍的な教師あり学習（Universal Supervised Learning for Individual Data）</news:title>
   <news:publication_date>2026-07-20T20:13:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714054</loc>
  <lastmod>2026-07-20T20:13:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットのフットプリンティングを可能にするツールaztarna（aztarna: robot footprinting tool）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714052</loc>
  <lastmod>2026-07-20T19:22:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた固有表現抽出の概観（A Survey on Deep Learning for Named Entity Recognition）</news:title>
   <news:publication_date>2026-07-20T19:22:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714050</loc>
  <lastmod>2026-07-20T19:14:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム射影層を用いた深層ネットワークの訓練（Training Deep Networks with Random Projection Layer）</news:title>
   <news:publication_date>2026-07-20T19:14:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714048</loc>
  <lastmod>2026-07-20T19:13:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Modified Causal Forestsによる異質な因果効果推定（Modified Causal Forests for Estimating Heterogeneous Causal Effects）</news:title>
   <news:publication_date>2026-07-20T19:13:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714046</loc>
  <lastmod>2026-07-20T19:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者とフレーズ情報を符号化する微分可能なスーパーベクター抽出（Differentiable Supervector Extraction for Encoding Speaker and Phrase Information in Text Dependent Speaker Verification）</news:title>
   <news:publication_date>2026-07-20T19:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714044</loc>
  <lastmod>2026-07-20T19:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>舌下静脈の自動セグメンテーション（FULLY AUTOMATIC SEGMENTATION OF SUBLINGUAL VEINS FROM RETRAINED U-NET MODEL FOR FEW NEAR INFRARED IMAGES）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714042</loc>
  <lastmod>2026-07-20T19:12:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-20T19:12:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714040</loc>
  <lastmod>2026-07-20T19:11:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層不確実性定量化（Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting）</news:title>
   <news:publication_date>2026-07-20T19:11:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714038</loc>
  <lastmod>2026-07-20T18:20:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーム処理パイプラインの自動構成と自動スケーリング（Automatic configuration and scaling of stream processing pipelines）</news:title>
   <news:publication_date>2026-07-20T18:20:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714036</loc>
  <lastmod>2026-07-20T18:20:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向コンテクスト分離ネットワークによる学習型スケーラブル画像圧縮（LEARNED SCALABLE IMAGE COMPRESSION WITH BIDIRECTIONAL CONTEXT DISENTANGLEMENT NETWORK）</news:title>
   <news:publication_date>2026-07-20T18:20:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714034</loc>
  <lastmod>2026-07-20T18:20:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元逆問題に挑む深層自己回帰ニューラルネットワーク（Deep autoregressive neural networks for high-dimensional inverse problems in groundwater contaminant source identification）</news:title>
   <news:publication_date>2026-07-20T18:20:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714032</loc>
  <lastmod>2026-07-20T18:19:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的グラフ表現学習と自己注意ネットワーク（DYNAMIC GRAPH REPRESENTATION LEARNING VIA SELF-ATTENTION NETWORKS）</news:title>
   <news:publication_date>2026-07-20T18:19:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714030</loc>
  <lastmod>2026-07-20T18:19:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>化学反応の生成物予測をグラフ操作で学ぶ（GRAPH TRANSFORMATION POLICY NETWORK FOR CHEMICAL REACTION PREDICTION）</news:title>
   <news:publication_date>2026-07-20T18:19:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714028</loc>
  <lastmod>2026-07-20T18:19:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称オラクル問題の量子クエリ複雑性（Quantum query complexity of symmetric oracle problems）</news:title>
   <news:publication_date>2026-07-20T18:19:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714026</loc>
  <lastmod>2026-07-20T18:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PMU時系列データの画像埋め込みによる過渡事象分類（Image Embedding of PMU Data for Deep Learning towards Transient Disturbance Classification）</news:title>
   <news:publication_date>2026-07-20T18:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714024</loc>
  <lastmod>2026-07-20T17:27:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データ解析のための分散逐次法（Distributed sequential method for analyzing massive data）</news:title>
   <news:publication_date>2026-07-20T17:27:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714022</loc>
  <lastmod>2026-07-20T17:27:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能的逐次割付の意思決定最適化（Functional Sequential Treatment Allocation）</news:title>
   <news:publication_date>2026-07-20T17:27:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714020</loc>
  <lastmod>2026-07-20T17:27:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙プラズマにおける斥磁（Diamagnetic）場状態の理論的発見（Diamagnetic field states in cosmological plasmas）</news:title>
   <news:publication_date>2026-07-20T17:27:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714018</loc>
  <lastmod>2026-07-20T17:26:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>占有グリッドマップの多段予測（Multi-Step Prediction of Occupancy Grid Maps with Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-07-20T17:26:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714016</loc>
  <lastmod>2026-07-20T17:26:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースワンタイムグラブサンプリングによる内点抽出（Sparse One-Time Grab Sampling of Inliers）</news:title>
   <news:publication_date>2026-07-20T17:26:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714014</loc>
  <lastmod>2026-07-20T17:25:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差注意ネットワークによる手骨年齢推定（RESIDUAL ATTENTION BASED NETWORK FOR HAND BONE AGE ASSESSMENT）</news:title>
   <news:publication_date>2026-07-20T17:25:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714012</loc>
  <lastmod>2026-07-20T17:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランサムウェア検知に対する回復力の評価（Towards resilient machine learning for ransomware detection）</news:title>
   <news:publication_date>2026-07-20T17:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714010</loc>
  <lastmod>2026-07-20T16:34:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>砂漠の一粒の砂は何か（What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models）</news:title>
   <news:publication_date>2026-07-20T16:34:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714008</loc>
  <lastmod>2026-07-20T16:33:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層音声視覚モデルの実証的解析（An Empirical Analysis of Deep Audio-Visual Models for Speech Recognition）</news:title>
   <news:publication_date>2026-07-20T16:33:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714006</loc>
  <lastmod>2026-07-20T16:33:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置バイアス推定による公正なランキング学習（Position Bias Estimation for Unbiased Learning-to-Rank in eCommerce Search）</news:title>
   <news:publication_date>2026-07-20T16:33:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714004</loc>
  <lastmod>2026-07-20T16:33:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残響音から部屋を識別する終端学習（End-to-End Classification of Reverberant Rooms using DNNs）</news:title>
   <news:publication_date>2026-07-20T16:33:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714002</loc>
  <lastmod>2026-07-20T16:32:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスターロスによる人物再識別（Cluster Loss for Person Re-Identification）</news:title>
   <news:publication_date>2026-07-20T16:32:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/714000</loc>
  <lastmod>2026-07-20T16:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QuCumberによる波動関数再構築（QuCumber: wavefunction reconstruction with neural networks）</news:title>
   <news:publication_date>2026-07-20T16:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713998</loc>
  <lastmod>2026-07-20T16:32:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識ベース自動化治療計画と3次元GANの登場（Knowledge-based automated planning with three-dimensional generative adversarial networks）</news:title>
   <news:publication_date>2026-07-20T16:32:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713996</loc>
  <lastmod>2026-07-20T15:41:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置ずれ衛星画像の変化検出のための正準相関分析（Canonical Correlation Analysis for Misaligned Satellite Image Change Detection）</news:title>
   <news:publication_date>2026-07-20T15:41:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713994</loc>
  <lastmod>2026-07-20T15:41:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラウンド削減と厳密コミュニケーション複雑性の新知見（Round elimination in exact communication complexity）</news:title>
   <news:publication_date>2026-07-20T15:41:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713992</loc>
  <lastmod>2026-07-20T15:40:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可視画像と熱画像の融合による熱赤外画像の解像度向上（Multimodal Sensor Fusion In Single Thermal image Super-Resolution）</news:title>
   <news:publication_date>2026-07-20T15:40:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713990</loc>
  <lastmod>2026-07-20T15:39:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェブデータから学ぶ利点：教師なし物体ローカリゼーションの価値（Learning from Web Data: the Benefit of Unsupervised Object Localization）</news:title>
   <news:publication_date>2026-07-20T15:39:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713988</loc>
  <lastmod>2026-07-20T15:39:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚と音声を結ぶ記号的帰納バイアス（Symbolic inductive bias for visually grounded learning of spoken language）</news:title>
   <news:publication_date>2026-07-20T15:39:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713986</loc>
  <lastmod>2026-07-20T15:39:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Persistence Bag-of-Wordsによるトポロジカルデータ解析（Persistence Bag-of-Words for Topological Data Analysis）</news:title>
   <news:publication_date>2026-07-20T15:39:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713984</loc>
  <lastmod>2026-07-20T15:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チュリウムドープドYSOにおける深く持続するスペクトルホールの医用イメージングへの可能性（Deep and persistent spectral holes in thulium-doped yttrium orthosilicate for imaging applications）</news:title>
   <news:publication_date>2026-07-20T15:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713982</loc>
  <lastmod>2026-07-20T14:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デンドログラムから学ぶ表現学習（LEARNING REPRESENTATIONS FROM DENDROGRAMS）</news:title>
   <news:publication_date>2026-07-20T14:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713980</loc>
  <lastmod>2026-07-20T14:47:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クォーク・グルーオン識別の実用性と導入視点（Quark-Gluon Tagging: Machine Learning vs Detector）</news:title>
   <news:publication_date>2026-07-20T14:47:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713978</loc>
  <lastmod>2026-07-20T14:47:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ショット認識のための合成表現学習（Learning Compositional Representations for Few-Shot Recognition）</news:title>
   <news:publication_date>2026-07-20T14:47:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713976</loc>
  <lastmod>2026-07-20T14:46:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子深部での最適同期—資源と基礎的限界（Optimal synchronization deep in the quantum regime: resource and fundamental limit）</news:title>
   <news:publication_date>2026-07-20T14:46:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713974</loc>
  <lastmod>2026-07-20T14:46:44Z</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におけるオープンソースソフトウェアの位置づけ（Open source software in quantum computing）</news:title>
   <news:publication_date>2026-07-20T14:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713972</loc>
  <lastmod>2026-07-20T14:46:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的開示制御の未来（The future of statistical disclosure control）</news:title>
   <news:publication_date>2026-07-20T14:46:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/713970</loc>
  <lastmod>2026-07-20T14:46:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Webナビゲーション学習の実用的指針（Learning to Navigate the Web）</news:title>
   <news:publication_date>2026-07-20T14:46:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713968</loc>
  <lastmod>2026-07-20T13:55:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Swift J0746.3-1608の本性：中間極（Intermediate Polar）としての状態変化の解明（The true nature of Swift J0746.3-1608: a possible Intermediate Polar showing accretion state changes）</news:title>
   <news:publication_date>2026-07-20T13:55:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713966</loc>
  <lastmod>2026-07-20T13:54:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェネレーティブ敵対ネットワークを用いた地球物理データの勾配ベース決定論的反転は実現可能か？（Gradient-based deterministic inversion of geophysical data with Generative Adversarial Networks: is it feasible?）</news:title>
   <news:publication_date>2026-07-20T13:54:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713964</loc>
  <lastmod>2026-07-20T13:54:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生態データに基づく機械学習分類の比較（Ecological Data Analysis Based on Machine Learning Algorithms）</news:title>
   <news:publication_date>2026-07-20T13:54:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713962</loc>
  <lastmod>2026-07-20T13:53:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的粗密深層カーネルネットワークによる衛星画像の効率的変化検出（Cascaded Coarse-to-Fine Deep Kernel Networks for Efficient Satellite Image Change Detection）</news:title>
   <news:publication_date>2026-07-20T13:53:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713960</loc>
  <lastmod>2026-07-20T13:53:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークにおけるニューロモジュレーション導入による適応的行動学習（Introducing Neuromodulation in Deep Neural Networks to Learn Adaptive Behaviours）</news:title>
   <news:publication_date>2026-07-20T13:53:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713958</loc>
  <lastmod>2026-07-20T13:53:07Z</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・モデリングの実務的理解（Simulation Modeling）</news:title>
   <news:publication_date>2026-07-20T13:53:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713956</loc>
  <lastmod>2026-07-20T13:52:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多スケール拡張残差畳み込みネットワークによる画像ノイズ除去（A Multiscale Image Denoising Algorithm Based On Dilated Residual Convolution Network）</news:title>
   <news:publication_date>2026-07-20T13:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713954</loc>
  <lastmod>2026-07-20T13:02:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>巨大共鳴の微細構造が教えるもの（FINE STRUCTURE OF GIANT RESONANCES: WHAT CAN BE LEARNED）</news:title>
   <news:publication_date>2026-07-20T13:02:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713952</loc>
  <lastmod>2026-07-20T13:01:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習の観点から見た生成モデル（Generative Models from the perspective of Continual Learning）</news:title>
   <news:publication_date>2026-07-20T13:01:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713950</loc>
  <lastmod>2026-07-20T12:53:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>金属の液中レーザーアブレーション（Laser-induced ablation of metal in liquid）</news:title>
   <news:publication_date>2026-07-20T12:53:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713948</loc>
  <lastmod>2026-07-20T12:53:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3DSRnetによる動画超解像の実務的意義（3DSRnet: Video Super-resolution using 3D Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-20T12:53:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713946</loc>
  <lastmod>2026-07-20T12:52:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>夢を見るニューラルネットワークの厳密解析（Dreaming neural networks: rigorous results）</news:title>
   <news:publication_date>2026-07-20T12:52:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713944</loc>
  <lastmod>2026-07-20T12:52:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽子の部分分布関数における核不確実性（Nuclear Uncertainties in the Determination of Proton PDFs）</news:title>
   <news:publication_date>2026-07-20T12:52:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713942</loc>
  <lastmod>2026-07-20T12:52:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習とマルチタスク学習を組み合わせた薬物動態パラメータ予測（An Integrated Transfer Learning and Multitask Learning Approach for Pharmacokinetic Parameter Prediction）</news:title>
   <news:publication_date>2026-07-20T12:52:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713940</loc>
  <lastmod>2026-07-20T12:00:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランジュバン法が示す高次元推論の光と影（Marvels and pitfalls of the Langevin algorithm in noisy high-dimensional inference）</news:title>
   <news:publication_date>2026-07-20T12:00:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713938</loc>
  <lastmod>2026-07-20T12:00:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期ポテンシャルにおける連続時間ランダムウォーク（Continuous-time random walk for a particle in a periodic potential）</news:title>
   <news:publication_date>2026-07-20T12:00:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713936</loc>
  <lastmod>2026-07-20T11:59:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GaussianProcesses.jl によるJuliaでの非パラメトリックベイズ実装（GaussianProcesses.jl: A Nonparametric Bayes package for the Julia Language）</news:title>
   <news:publication_date>2026-07-20T11:59:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713934</loc>
  <lastmod>2026-07-20T11:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形写像の低ランク近似（Low-Rank Approximation of Linear Maps）</news:title>
   <news:publication_date>2026-07-20T11:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713932</loc>
  <lastmod>2026-07-20T11:58:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情を見つけて要約する統合モデル（A Multi-task Neural Approach for Emotion Attribution, Classification and Summarization）</news:title>
   <news:publication_date>2026-07-20T11:58:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713930</loc>
  <lastmod>2026-07-20T11:58:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NADPExによる時系列一貫性探索法（Neural Adaptive Dropout Policy Exploration）</news:title>
   <news:publication_date>2026-07-20T11:58:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713928</loc>
  <lastmod>2026-07-20T11:58:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LEAFAGEによる説明生成の実用性（LEAFAGE: Example-based and Feature importance-based Explanations for Black-box ML models）</news:title>
   <news:publication_date>2026-07-20T11:58:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713926</loc>
  <lastmod>2026-07-20T11:07:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NB-IoTネットワークにおけるリアルタイム最適化のための深層強化学習（Deep Reinforcement Learning for Real-Time Optimization in NB-IoT Networks）</news:title>
   <news:publication_date>2026-07-20T11:07:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713924</loc>
  <lastmod>2026-07-20T11:06:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>X線画像少数で学習したFaster R-CNNによる遠位橈骨骨折検出（Detection of distal radius fractures trained by a small set of X-ray images and Faster R-CNN）</news:title>
   <news:publication_date>2026-07-20T11:06:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713922</loc>
  <lastmod>2026-07-20T11:06:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ベイズネットにおける新しい学習アプローチ（A new approach to learning in Dynamic Bayesian Networks）</news:title>
   <news:publication_date>2026-07-20T11:06:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713920</loc>
  <lastmod>2026-07-20T11:05:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴ごとのバイアス増幅とその軽減（Feature-wise Bias Amplification）</news:title>
   <news:publication_date>2026-07-20T11:05:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713918</loc>
  <lastmod>2026-07-20T11:05:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャネル不一致と付加雑音下におけるデータ検出の教師なし学習アプローチ（An Unsupervised Learning Approach for Data Detection in the Presence of Channel Mismatch and Additive Noise）</news:title>
   <news:publication_date>2026-07-20T11:05:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713916</loc>
  <lastmod>2026-07-20T11:05:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>負荷予測研究の二次元分類と実務への適用法（Classification of load forecasting studies by forecasting problem to select load forecasting techniques and methodologies）</news:title>
   <news:publication_date>2026-07-20T11:05:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713914</loc>
  <lastmod>2026-07-20T11:05:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔のハリュシネーションとデータセットバイアスの再検討（Face Hallucination Revisited: An Exploratory Study on Dataset Bias）</news:title>
   <news:publication_date>2026-07-20T11:05:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713912</loc>
  <lastmod>2026-07-20T10:13:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的二重頑健勾配（Stochastic Doubly Robust Gradient）</news:title>
   <news:publication_date>2026-07-20T10:13:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713910</loc>
  <lastmod>2026-07-20T10:13:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>擬似シロー数（Pseudo Sylow numbers）</news:title>
   <news:publication_date>2026-07-20T10:13:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713908</loc>
  <lastmod>2026-07-20T10:13:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対なしの画像生成と生成潜在最近傍 (Non-Adversarial Image Synthesis with Generative Latent Nearest Neighbors)</news:title>
   <news:publication_date>2026-07-20T10:13:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713906</loc>
  <lastmod>2026-07-20T10:12:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物再検出の精度を高める4ストリーム・シアミーズCNN（A Deep Four-Stream Siamese Convolutional Neural Network with Joint Verification and Identification Loss for Person Re-detection）</news:title>
   <news:publication_date>2026-07-20T10:12:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713904</loc>
  <lastmod>2026-07-20T10:12:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチコンポーネント画像変換による深層ドメイン一般化（Multi-component Image Translation for Deep Domain Generalization）</news:title>
   <news:publication_date>2026-07-20T10:12:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713902</loc>
  <lastmod>2026-07-20T10:12:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COSINEによる大規模ネットワーク埋め込みの圧縮手法（COSINE: Compressive Network Embedding on Large-scale Information Networks）</news:title>
   <news:publication_date>2026-07-20T10:12:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713900</loc>
  <lastmod>2026-07-20T10:11:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoT向けブロックチェーンの活動プライバシー（On the Activity Privacy of Blockchain for IoT）</news:title>
   <news:publication_date>2026-07-20T10:11:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713898</loc>
  <lastmod>2026-07-20T09:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的グラフに対する適応的パターンマッチングと強化学習（Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs）</news:title>
   <news:publication_date>2026-07-20T09:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713896</loc>
  <lastmod>2026-07-20T09:20:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ網とニューラル網の表現力比較（On the Relative Expressiveness of Bayesian and Neural Networks）</news:title>
   <news:publication_date>2026-07-20T09:20:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713894</loc>
  <lastmod>2026-07-20T09:20:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密に意味的に整列された人物再識別（Densely Semantically Aligned Person Re-Identification）</news:title>
   <news:publication_date>2026-07-20T09:20:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713892</loc>
  <lastmod>2026-07-20T09:19:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人材採用における人物と職務の適合性強化（Enhancing Person-Job Fit for Talent Recruitment: An Ability-aware Neural Network Approach）</news:title>
   <news:publication_date>2026-07-20T09:19:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713890</loc>
  <lastmod>2026-07-20T09:19:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理におけるニューラル解析手法のサーベイ (Analysis Methods in Neural Language Processing: A Survey)</news:title>
   <news:publication_date>2026-07-20T09:19:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713888</loc>
  <lastmod>2026-07-20T09:19:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ChamNet: プラットフォームを意識した効率的ネットワーク設計（ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation）</news:title>
   <news:publication_date>2026-07-20T09:19:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713886</loc>
  <lastmod>2026-07-20T09:19:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データ解析のプリマルパスアルゴリズム（Primal path algorithm for compositional data analysis）</news:title>
   <news:publication_date>2026-07-20T09:19:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713884</loc>
  <lastmod>2026-07-20T08:28:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微視的カスケード予測のためのニューラル拡散モデル（Neural Diffusion Model for Microscopic Cascade Prediction）</news:title>
   <news:publication_date>2026-07-20T08:28:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713882</loc>
  <lastmod>2026-07-20T08:27:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スリマブルニューラルネットワークが変える現場の推論管理（Slimmable Neural Networks）</news:title>
   <news:publication_date>2026-07-20T08:27:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713880</loc>
  <lastmod>2026-07-20T08:26:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非専門家デモによる事前学習で深層強化学習のデータ効率を改善する手法（PRE-TRAINING WITH NON-EXPERT HUMAN DEMONSTRATION FOR DEEP REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-07-20T08:26:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713878</loc>
  <lastmod>2026-07-20T08:26:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回帰を用いたグローバル／ローカル二標本検定（Global and Local Two-Sample Tests via Regression）</news:title>
   <news:publication_date>2026-07-20T08:26:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713876</loc>
  <lastmod>2026-07-20T08:26:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチドメイン処理によるハイブリッドデノイジングによる音声強調（Multi-Domain Processing via Hybrid Denoising Networks for Speech Enhancement）</news:title>
   <news:publication_date>2026-07-20T08:26:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713874</loc>
  <lastmod>2026-07-20T08:26:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォンPPGと熱画像による瞬時ストレス推定（Instant Automated Inference of Perceived Mental Stress through Smartphone PPG and Thermal Imaging）</news:title>
   <news:publication_date>2026-07-20T08:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713872</loc>
  <lastmod>2026-07-20T08:25:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>眼底写真における深層学習と緑内障診療の比較（Deep Learning and Glaucoma Referral Features）</news:title>
   <news:publication_date>2026-07-20T08:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713870</loc>
  <lastmod>2026-07-20T07:35:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量レヴィ過程のキャリブレーションとニューラルネットワークによる推定（Calibrating Multivariate Lévy Processes with Neural Networks）</news:title>
   <news:publication_date>2026-07-20T07:35:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713868</loc>
  <lastmod>2026-07-20T07:25:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェフリー発散に基づくクラスタ妥当性指標（Cluster validity index based on Jeffrey divergence）</news:title>
   <news:publication_date>2026-07-20T07:25:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713866</loc>
  <lastmod>2026-07-20T07:25:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルクラウドソーシングによるセンサー選択と経路サービスへの応用（Mobile Crowdsourced Sensors Selection for Journey Services）</news:title>
   <news:publication_date>2026-07-20T07:25:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713864</loc>
  <lastmod>2026-07-20T07:24:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データレート重視の伝送戦略と深層学習自動エンコーダ（Data-Rate Driven Transmission Strategies for Deep Learning Based Communication Systems）</news:title>
   <news:publication_date>2026-07-20T07:24:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713862</loc>
  <lastmod>2026-07-20T07:23:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子回路の学習をハイブリッドで行う時代が来た（Training of Quantum Circuits on a Hybrid Quantum Computer）</news:title>
   <news:publication_date>2026-07-20T07:23:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713860</loc>
  <lastmod>2026-07-20T07:23:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>天文学における転移学習の新しいパラダイム（Transfer Learning in Astronomy: A New Machine-Learning Paradigm）</news:title>
   <news:publication_date>2026-07-20T07:23:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713858</loc>
  <lastmod>2026-07-20T07:23:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形式概念体系における関連属性の定義（Relevant Attributes in Formal Contexts）</news:title>
   <news:publication_date>2026-07-20T07:23:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713856</loc>
  <lastmod>2026-07-20T06:31:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意の物体を動かす深層モーション転送（Animating Arbitrary Objects via Deep Motion Transfer）</news:title>
   <news:publication_date>2026-07-20T06:31:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713854</loc>
  <lastmod>2026-07-20T06:30:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型意思決定とマルチタスクネットワーク（Decentralized Decision-Making Over Multi-Task Networks）</news:title>
   <news:publication_date>2026-07-20T06:30:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713852</loc>
  <lastmod>2026-07-20T06:30:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン適応の一般的アプローチ（A General Approach to Domain Adaptation with Applications in Astronomy）</news:title>
   <news:publication_date>2026-07-20T06:30:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713850</loc>
  <lastmod>2026-07-20T06:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河団コアにおける（未）覆い隠された星形成の抑制の定量化 (Quantifying the suppression of the (un)-obscured star formation in galaxy cluster cores at 0.2≲z≲0.9)</news:title>
   <news:publication_date>2026-07-20T06:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713848</loc>
  <lastmod>2026-07-20T06:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転不変な指数族主成分分析：Steerable ePCA（Steerable ePCA: Rotationally Invariant Exponential Family PCA）</news:title>
   <news:publication_date>2026-07-20T06:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713846</loc>
  <lastmod>2026-07-20T06:29:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ホール系における準正準モードとホーキング・アンルン効果（Quasinormal Modes and Hawking-Unruh effect in Quantum Hall Systems）</news:title>
   <news:publication_date>2026-07-20T06:29:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713844</loc>
  <lastmod>2026-07-20T06:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプリング比を下げて推定数を増やすことでバギングがまばら回帰で改善する（Reducing Sampling Ratios and Increasing Number of Estimates Improve Bagging in Sparse Regression）</news:title>
   <news:publication_date>2026-07-20T06:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713842</loc>
  <lastmod>2026-07-20T05:38:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られた注釈データでのラベル伝播のための深層距離学習転移（Deep Metric Transfer for Label Propagation with Limited Annotated Data）</news:title>
   <news:publication_date>2026-07-20T05:38:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713840</loc>
  <lastmod>2026-07-20T05:37:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>論文のゲシュタルトで採否を判定する手法（Deep Paper Gestalt）</news:title>
   <news:publication_date>2026-07-20T05:37:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713838</loc>
  <lastmod>2026-07-20T05:37:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小情報完全測定の多様性（The Varieties of Minimal Tomographically Complete Measurements）</news:title>
   <news:publication_date>2026-07-20T05:37:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713836</loc>
  <lastmod>2026-07-20T05:36:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特別イベント時の公共交通利用を分解するベイズ加法モデル（A Bayesian additive model for understanding public transport usage in special events）</news:title>
   <news:publication_date>2026-07-20T05:36:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713834</loc>
  <lastmod>2026-07-20T05:36:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ジェットベトーを用いた重いニュートリノ探索（Heavy Neutrinos with Dynamic Jet Vetoes: Multilepton Searches at √s = 14, 27, and 100 TeV）</news:title>
   <news:publication_date>2026-07-20T05:36:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713832</loc>
  <lastmod>2026-07-20T05:36:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地下構造解析を視覚信号処理の視点で再定義する（Subsurface Structure Analysis Using Computational Interpretation and Learning: A Visual Signal Processing Perspective）</news:title>
   <news:publication_date>2026-07-20T05:36:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713830</loc>
  <lastmod>2026-07-20T05:36:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドソース交通データの欠損補完に対する多出力ガウス過程の提案（Multi-output Gaussian processes for crowdsourced traffic data imputation）</news:title>
   <news:publication_date>2026-07-20T05:36:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713828</loc>
  <lastmod>2026-07-20T04:45:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純なフーリエ構造を持つ信号の普遍的サンプリング法（A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms）</news:title>
   <news:publication_date>2026-07-20T04:45:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713826</loc>
  <lastmod>2026-07-20T04:44:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNが暗黙のテンソル積表現を実装している（RNNs Implicitly Implement Tensor-Product Representations）</news:title>
   <news:publication_date>2026-07-20T04:44:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713824</loc>
  <lastmod>2026-07-20T04:44:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模クラウドソース交通データにおける時間変動する不確実性モデル（Heteroscedastic Gaussian processes for uncertainty modeling in large-scale crowdsourced traffic data）</news:title>
   <news:publication_date>2026-07-20T04:44:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713822</loc>
  <lastmod>2026-07-20T04:44:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NASAと技術的痕跡（NASA AND THE SEARCH FOR TECHNOSIGNATURES）</news:title>
   <news:publication_date>2026-07-20T04:44:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713820</loc>
  <lastmod>2026-07-20T04:43:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>切削工程の力測定を用いたリアルタイム異常検知手法の評価（An Evaluation of Methods for Real-Time Anomaly Detection using Force Measurements from the Turning Process）</news:title>
   <news:publication_date>2026-07-20T04:43:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713818</loc>
  <lastmod>2026-07-20T04:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元共変量バランス化傾向スコアによる因果効果の頑健推定 (Robust Estimation of Causal Effects via High-Dimensional Covariate Balancing Propensity Score)</news:title>
   <news:publication_date>2026-07-20T04:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713816</loc>
  <lastmod>2026-07-20T04:43:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>野生のバグ修正パッチを学習する実証研究（An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation）</news:title>
   <news:publication_date>2026-07-20T04:43:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713814</loc>
  <lastmod>2026-07-20T03:52:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトコンダクティブヒーターによる大規模シリコンフォトニックリング共振器制御（Photoconductive heaters enable control of large-scale silicon photonic ring resonator circuits）</news:title>
   <news:publication_date>2026-07-20T03:52:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713812</loc>
  <lastmod>2026-07-20T03:52:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現データからの癌検出とタイプ分類を促進する手法（A Method to Facilitate Cancer Detection and Type Classification from Gene Expression Data using a Deep Autoencoder and Neural Network）</news:title>
   <news:publication_date>2026-07-20T03:52:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713810</loc>
  <lastmod>2026-07-20T03:51:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の物体を説明する大規模ベンチマーク：nocaps（nocaps: novel object captioning at scale）</news:title>
   <news:publication_date>2026-07-20T03:51:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713808</loc>
  <lastmod>2026-07-20T03:51:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーティリティ規模太陽光発電所の自動検査（Automatic Inspection of Utility Scale Solar Power Plants using Deep Learning）</news:title>
   <news:publication_date>2026-07-20T03:51:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713806</loc>
  <lastmod>2026-07-20T03:51:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レーザー励起シリコンの自己学習型解析間原子ポテンシャル（Self-learning analytical interatomic potential describing laser-excited silicon）</news:title>
   <news:publication_date>2026-07-20T03:51:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713804</loc>
  <lastmod>2026-07-20T03:51:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数結合論に基づく深層手法による偏微分方程式解推定（Deep Theory of Functional Connections: A New Method for Estimating the Solutions of PDEs）</news:title>
   <news:publication_date>2026-07-20T03:51:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713802</loc>
  <lastmod>2026-07-20T03:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠赤外/サブミリ波検出器向けフォノニックフィルタ構造の作製（Fabrication of phononic filter structures for far-IR/sub-mm detector applications）</news:title>
   <news:publication_date>2026-07-20T03:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713800</loc>
  <lastmod>2026-07-20T02:59:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAPS中性子飛行時間チャッパースペクトロメータのアップグレード（Upgrade to the MAPS neutron time-of-flight chopper spectrometer）</news:title>
   <news:publication_date>2026-07-20T02:59:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713798</loc>
  <lastmod>2026-07-20T02:59:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子軌道エネルギー予測における化学的多様性とKRRの実務的示唆（Chemical diversity in molecular orbital energy predictions with kernel ridge regression）</news:title>
   <news:publication_date>2026-07-20T02:59:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713796</loc>
  <lastmod>2026-07-20T02:59:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像における多臓器解析の計算解剖学（Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Review）</news:title>
   <news:publication_date>2026-07-20T02:59:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713794</loc>
  <lastmod>2026-07-20T02:59:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンコーダ・デコーダによる敵対的信号デノイジング（Adversarial Signal Denoising with Encoder-Decoder Networks）</news:title>
   <news:publication_date>2026-07-20T02:59:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713792</loc>
  <lastmod>2026-07-20T02:59:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUで学ぶ因果構造学習の大幅高速化（cuPC: CUDA-based Parallel PC Algorithm for Causal Structure Learning on GPU）</news:title>
   <news:publication_date>2026-07-20T02:59:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713790</loc>
  <lastmod>2026-07-20T02:58:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一次アルゴリズムは O(1/k) より速く収束する（First-Order Algorithms Converge Faster than O(1/k) on Convex Problems）</news:title>
   <news:publication_date>2026-07-20T02:58:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713788</loc>
  <lastmod>2026-07-20T02:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河の星形成分布が示す「内部での強化と抑制」──Main Sequence 上下で変わる星生成の局所性（Spatial distribution of stellar mass and star formation activity at 0.2</news:title>
   <news:publication_date>2026-07-20T02:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713786</loc>
  <lastmod>2026-07-20T02:07:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼性に基づく凝集型階層クラスタリング（Reliable Agglomerative Clustering）</news:title>
   <news:publication_date>2026-07-20T02:07:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713784</loc>
  <lastmod>2026-07-20T02:07:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス内分割によるワンクラス特徴学習（One-Class Feature Learning Using Intra-Class Splitting）</news:title>
   <news:publication_date>2026-07-20T02:07:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713782</loc>
  <lastmod>2026-07-20T02:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による量子誤り訂正コードの最適化（Optimizing Quantum Error Correction Codes with Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-20T02:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713780</loc>
  <lastmod>2026-07-20T02:06:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリ内連想処理によるDNN推論加速 AIDA（AIDA: Associative DNN Inference Accelerator）</news:title>
   <news:publication_date>2026-07-20T02:06:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713778</loc>
  <lastmod>2026-07-20T02:06:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中性子照射後の深掘り型APDの時間計測性能（Deep Diffused APDs for Charged Particle Timing Applications: Performance after Neutron Irradiation）</news:title>
   <news:publication_date>2026-07-20T02:06:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713776</loc>
  <lastmod>2026-07-20T02:06:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さな顔に注目する顔検出の設計（SFA: Small Faces Attention Face Detector）</news:title>
   <news:publication_date>2026-07-20T02:06:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713774</loc>
  <lastmod>2026-07-20T02:06:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚効果を真似て学ぶ教師なしメタ学習による図-地分割（Unsupervised Meta-learning of Figure-Ground Segmentation via Imitating Visual Effects）</news:title>
   <news:publication_date>2026-07-20T02:06:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713772</loc>
  <lastmod>2026-07-20T01:15:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模混合データフレームのための低ランク＋スパース加法モデル（Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames）</news:title>
   <news:publication_date>2026-07-20T01:15:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713770</loc>
  <lastmod>2026-07-20T01:14:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習を考慮した問題類似度の新指標（Kappa Learning: A New Method for Measuring Similarity Between Educational Items Using Performance Data）</news:title>
   <news:publication_date>2026-07-20T01:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713768</loc>
  <lastmod>2026-07-20T01:14:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列異常検知における深層フィードフォワードネットワークの実用性（Feedforward Neural Network for Time Series Anomaly Detection）</news:title>
   <news:publication_date>2026-07-20T01:14:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713766</loc>
  <lastmod>2026-07-20T01:13:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形多様体上の動的系のモデル縮約と深層畳み込みオートエンコーダ（Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders）</news:title>
   <news:publication_date>2026-07-20T01:13:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713764</loc>
  <lastmod>2026-07-20T01:13:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みネットワークのデータ不要型自動加速（Data-free Automatic Acceleration of Convolutional Networks）</news:title>
   <news:publication_date>2026-07-20T01:13:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713762</loc>
  <lastmod>2026-07-20T01:12:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化動的価格設定の原始双対学習アルゴリズム（A Primal-dual Learning Algorithm for Personalized Dynamic Pricing with an Inventory Constraint）</news:title>
   <news:publication_date>2026-07-20T01:12:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713760</loc>
  <lastmod>2026-07-20T01:12:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SfMLearner++: Monocular DepthとEgo-Motionを幾何学的制約で学ぶ（SfMLearner++: Learning Monocular Depth &amp;amp; Ego-Motion using Meaningful Geometric Constraints）</news:title>
   <news:publication_date>2026-07-20T01:12:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713758</loc>
  <lastmod>2026-07-20T00:20:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多項式NARXモデルの構造選択における2次元粒子群最適化（Structure Selection of Polynomial NARX Models using Two Dimensional (2D) Particle Swarms）</news:title>
   <news:publication_date>2026-07-20T00:20:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713756</loc>
  <lastmod>2026-07-20T00:20:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2.5Dを用いた多GPU実装によるCT画像再構成の深層学習（2.5D DEEP LEARNING FOR CT IMAGE RECONSTRUCTION USING A MULTI-GPU IMPLEMENTATION）</news:title>
   <news:publication_date>2026-07-20T00:20:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713754</loc>
  <lastmod>2026-07-20T00:19:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期価格予測のための板情報特徴量調査（Investigating Limit Order Book Characteristics for Short Term Price Prediction: a Machine Learning Approach）</news:title>
   <news:publication_date>2026-07-20T00:19:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713752</loc>
  <lastmod>2026-07-20T00:19:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>4つの低赤shift銀河団のダークマター分布（Dark Matter Distribution of Four Low-z Clusters of Galaxies）</news:title>
   <news:publication_date>2026-07-20T00:19:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713750</loc>
  <lastmod>2026-07-20T00:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深在塩水帯における二酸化炭素の対流溶解の実験的洞察（Convective dissolution of carbon dioxide in deep saline aquifers）</news:title>
   <news:publication_date>2026-07-20T00:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713748</loc>
  <lastmod>2026-07-20T00:19:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタラクティブ画像編集のための逐次注意GAN（Sequential Attention GAN for Interactive Image Editing）</news:title>
   <news:publication_date>2026-07-20T00:19:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713746</loc>
  <lastmod>2026-07-20T00:18:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバスト性が深層学習と出会う：自己教師ありエゴモーションのエンドツーエンドハイブリッドパイプライン（Robustness Meets Deep Learning: An End-to-End Hybrid Pipeline for Unsupervised Learning of Egomotion）</news:title>
   <news:publication_date>2026-07-20T00:18:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713744</loc>
  <lastmod>2026-07-19T23:27:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>価値敏感な学習分析設計の方向性（Towards Value-Sensitive Learning Analytics Design）</news:title>
   <news:publication_date>2026-07-19T23:27:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713742</loc>
  <lastmod>2026-07-19T23:26:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代数的グラフ学習によるタンパク質—リガンド結合自由エネルギー予測（Algebraic graph learning of protein-ligand binding affinity）</news:title>
   <news:publication_date>2026-07-19T23:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713740</loc>
  <lastmod>2026-07-19T23:24:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分オートエンコーダとマルチモーダルアーティスト埋め込みによる歌詞生成（Generating lyrics with variational autoencoder and multi-modal artist embeddings）</news:title>
   <news:publication_date>2026-07-19T23:24:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713738</loc>
  <lastmod>2026-07-19T23:24:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復的信念改訂と資源制約：論理を幾何学として捉える（Iterated Belief Revision Under Resource Constraints: Logic as Geometry）</news:title>
   <news:publication_date>2026-07-19T23:24:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713736</loc>
  <lastmod>2026-07-19T23:24:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース化と低精度化の同時最適化（SQuantizer: Simultaneous Learning for Both Sparse and Low-precision Neural Networks）</news:title>
   <news:publication_date>2026-07-19T23:24:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713734</loc>
  <lastmod>2026-07-19T23:24:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NeuralWarp：時系列類似度を再定義するワーピングネットワーク（NeuralWarp: Time-Series Similarity with Warping Networks）</news:title>
   <news:publication_date>2026-07-19T23:24:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713732</loc>
  <lastmod>2026-07-19T23:23:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>導関数を使わない方策最適化の理論的保証（Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems）</news:title>
   <news:publication_date>2026-07-19T23:23:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713730</loc>
  <lastmod>2026-07-19T22:32:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TD正則化されたアクタークリティック法（TD-Regularized Actor-Critic Methods）</news:title>
   <news:publication_date>2026-07-19T22:32:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713728</loc>
  <lastmod>2026-07-19T22:31:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ予測子の有限時間最適性（Finite-time optimality of Bayesian predictors）</news:title>
   <news:publication_date>2026-07-19T22:31:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713726</loc>
  <lastmod>2026-07-19T22:31:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高性能・エッジ向けGBDT学習の論理アーキテクチャ（Efficient logic architecture in training gradient boosting decision tree for high-performance and edge computing）</news:title>
   <news:publication_date>2026-07-19T22:31:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713724</loc>
  <lastmod>2026-07-19T22:30:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リモートセンシングにおける多源・多時系列データ融合（Multisource and Multitemporal Data Fusion in Remote Sensing）</news:title>
   <news:publication_date>2026-07-19T22:30:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713722</loc>
  <lastmod>2026-07-19T22:30:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルにおける高速近似測地線（Fast Approximate Geodesics for Deep Generative Models）</news:title>
   <news:publication_date>2026-07-19T22:30:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713720</loc>
  <lastmod>2026-07-19T22:30:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的磁性体を用いたアナログ信号処理（Analog Signal Processing Using Stochastic Magnets）</news:title>
   <news:publication_date>2026-07-19T22:30:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713718</loc>
  <lastmod>2026-07-19T22:30:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>kテスト可能言語の合併学習（Learning Unions of k-Testable Languages）</news:title>
   <news:publication_date>2026-07-19T22:30:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713716</loc>
  <lastmod>2026-07-19T21:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線ネットワークの幾何学的特徴の統計学習（Statistical learning of geometric characteristics of wireless networks）</news:title>
   <news:publication_date>2026-07-19T21:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713714</loc>
  <lastmod>2026-07-19T21:38:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的フィードバックを扱うためのファクタリゼーションマシン改良（Factorization Machines for Datasets with Implicit Feedback）</news:title>
   <news:publication_date>2026-07-19T21:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713712</loc>
  <lastmod>2026-07-19T21:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動分類器を科学的計測器として扱う危険性（Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth）</news:title>
   <news:publication_date>2026-07-19T21:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713710</loc>
  <lastmod>2026-07-19T21:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>D3D: 動画の行動認識を軽くする蒸留済み3Dネットワーク（Distilled 3D Networks for Video Action Recognition）</news:title>
   <news:publication_date>2026-07-19T21:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713708</loc>
  <lastmod>2026-07-19T21:36:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不変性・因果性・頑健性が描く予測の新地平（Invariance, Causality and Robustness）</news:title>
   <news:publication_date>2026-07-19T21:36:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713706</loc>
  <lastmod>2026-07-19T21:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核子のパリティ双対性と中性子星構造の新しい見方（Chiral symmetry restoration by parity doubling and the structure of neutron stars）</news:title>
   <news:publication_date>2026-07-19T21:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713704</loc>
  <lastmod>2026-07-19T21:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模序数回帰の新手法（A Novel Large-Scale Ordinal Regression Model）</news:title>
   <news:publication_date>2026-07-19T21:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713702</loc>
  <lastmod>2026-07-19T20:44:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベントカメラの教師なし学習で光学フロー・深度・自動運動を同時に学ぶ（Unsupervised Event-based Learning of Optical Flow, Depth, and Egomotion）</news:title>
   <news:publication_date>2026-07-19T20:44:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713700</loc>
  <lastmod>2026-07-19T20:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子核内でのハドロン形成を遅い中性子で探る手法（Slow neutron production as a probe of hadron formation in high-energy γ* A reactions）</news:title>
   <news:publication_date>2026-07-19T20:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713698</loc>
  <lastmod>2026-07-19T20:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低コストWiFiによる交通モニタリングシステム（DeepWiTraffic: Low Cost WiFi-Based Traffic Monitoring System Using Deep Learning）</news:title>
   <news:publication_date>2026-07-19T20:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713696</loc>
  <lastmod>2026-07-19T20:35:54Z</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自動学習フレームワークの提案（Toward Intelligent Network Optimization in Wireless Networking: An Auto-learning Framework）</news:title>
   <news:publication_date>2026-07-19T20:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713694</loc>
  <lastmod>2026-07-19T20:35:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RankGAN: 顔生成における最大マージンランキング型GANの段階的強化（RankGAN: A Maximum Margin Ranking GAN for Generating Faces）</news:title>
   <news:publication_date>2026-07-19T20:35:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713692</loc>
  <lastmod>2026-07-19T20:35:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤特定モデルのベイズ的パラメータ推定（Bayesian parameter estimation of miss-specified models）</news:title>
   <news:publication_date>2026-07-19T20:35:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713690</loc>
  <lastmod>2026-07-19T20:34:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙のガスで読み解く星の成長──PHIBSS2が示した分子ガス主導の銀河進化（PHIBSS2: Molecular Gas and Galaxy Evolution）</news:title>
   <news:publication_date>2026-07-19T20:34:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713688</loc>
  <lastmod>2026-07-19T19:43:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非教師あり深層学習の医用画像解析への旅路（A Tour of Unsupervised Deep Learning for Medical Image Analysis）</news:title>
   <news:publication_date>2026-07-19T19:43:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713686</loc>
  <lastmod>2026-07-19T19:43:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒッグス粒子のCP状態判別に向けた機械学習分類（Machine learning classification: case of Higgs boson CP state in H →ττ decay at LHC）</news:title>
   <news:publication_date>2026-07-19T19:43:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713684</loc>
  <lastmod>2026-07-19T19:42:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力散乱と放射の赤外特性を問う — エイコナル近似による整理（Infrared features of gravitational scattering and radiation in the eikonal approach）</news:title>
   <news:publication_date>2026-07-19T19:42:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713682</loc>
  <lastmod>2026-07-19T19:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム性低減による圧縮センシングの刷新（Derandomizing compressed sensing with combinatorial design）</news:title>
   <news:publication_date>2026-07-19T19:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713680</loc>
  <lastmod>2026-07-19T19:41:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様性と特異性を高める画像キャプショニング（Improving Image Captioning Diversity and Specificity with Specificity-Guided Training）</news:title>
   <news:publication_date>2026-07-19T19:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713678</loc>
  <lastmod>2026-07-19T19:41:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adamが生む暗黙の重みスパース化（Adam Induces Implicit Weight Sparsity in Rectifier Neural Networks）</news:title>
   <news:publication_date>2026-07-19T19:41:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713676</loc>
  <lastmod>2026-07-19T19:40:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非常に低消費電力なニューラルTime-of-Flight技術（Very Power Efficient Neural Time-of-Flight）</news:title>
   <news:publication_date>2026-07-19T19:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713674</loc>
  <lastmod>2026-07-19T18:49:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MoDL-MUSSELSによる多ショット回折MRIの位相誤差補正（MoDL-MUSSELS: Model-Based Deep Learning for Multishot Sensitivity-Encoded Diffusion MRI）</news:title>
   <news:publication_date>2026-07-19T18:49:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713672</loc>
  <lastmod>2026-07-19T18:49:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レプトン–ハドロン散乱に基づく基礎科学の戦略（The “DIS and Related Subjects” Strategy Document: Fundamental Science from Lepton-Hadron Scattering）</news:title>
   <news:publication_date>2026-07-19T18:49:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713670</loc>
  <lastmod>2026-07-19T18:49:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周辺分布に基づく新しい距離計量の提案（Chain Rule Optimal Transport）</news:title>
   <news:publication_date>2026-07-19T18:49:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713668</loc>
  <lastmod>2026-07-19T18:48:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WEKAのRandom Forestを不均衡データ向けに改良する試み（The Random Forest Classifier in WEKA: Discussion and New Developments for Imbalanced Data）</news:title>
   <news:publication_date>2026-07-19T18:48:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713666</loc>
  <lastmod>2026-07-19T18:48:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープニューラルネットワークのマルウェア耐性強化（Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples）</news:title>
   <news:publication_date>2026-07-19T18:48:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713664</loc>
  <lastmod>2026-07-19T18:47:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リスク回避型二段階モデルにおける強凸性の意義（Strong Convexity for Risk-Averse Two-Stage Models with Fixed Complete Linear Recourse）</news:title>
   <news:publication_date>2026-07-19T18:47:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713662</loc>
  <lastmod>2026-07-19T18:47:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数クラスにおけるサンプリング離散化誤差の論点整理（Sampling discretization error for function classes）</news:title>
   <news:publication_date>2026-07-19T18:47:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713660</loc>
  <lastmod>2026-07-19T17:56:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観光領域におけるソーシャルメディア分析が意思決定を変える（Enhancing Decision Making Capacity in Tourism Domain Using Social Media Analytics）</news:title>
   <news:publication_date>2026-07-19T17:56:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713658</loc>
  <lastmod>2026-07-19T17:56:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エアリアル画像の窓検出とファサード解析（Window detection in aerial texture images of the 3D CityGML Berlin Model）</news:title>
   <news:publication_date>2026-07-19T17:56:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713656</loc>
  <lastmod>2026-07-19T17:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>浅層の手がかりを導入した混合モデルによる深層視覚追跡（Shallow Cue Guided Deep Visual Tracking via Mixed Models）</news:title>
   <news:publication_date>2026-07-19T17:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713654</loc>
  <lastmod>2026-07-19T17:55:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルネット上のサイバーブルイング検出に関する再現性研究（Cyberbullying Detection in Social Networks Using Deep Learning Based Models; A Reproducibility Study）</news:title>
   <news:publication_date>2026-07-19T17:55:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713652</loc>
  <lastmod>2026-07-19T17:55:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超音波画像におけるビームフォーミングの学習化（Learning beamforming in ultrasound imaging）</news:title>
   <news:publication_date>2026-07-19T17:55:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713650</loc>
  <lastmod>2026-07-19T17:54:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絵画の作家・様式・ジャンルを同時に分類する深層マルチブランチネットワーク（Multitask Painting Categorization by Deep Multibranch Neural Network）</news:title>
   <news:publication_date>2026-07-19T17:54:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713648</loc>
  <lastmod>2026-07-19T17:54:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レプトン・ジェット相関を用いた核内トモグラフィーの新展開（Lepton-jet Correlations in Deep Inelastic Scattering at the Electron-Ion Collider）</news:title>
   <news:publication_date>2026-07-19T17:54:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713646</loc>
  <lastmod>2026-07-19T17:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>収入データの信頼性評価と階層相関再構築（Credibility evaluation of income data with hierarchical correlation reconstruction）</news:title>
   <news:publication_date>2026-07-19T17:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713644</loc>
  <lastmod>2026-07-19T17:02:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Switch-LSTMsによる多基準中国語形態素解析（Switch-LSTMs for Multi-Criteria Chinese Word Segmentation）</news:title>
   <news:publication_date>2026-07-19T17:02:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713642</loc>
  <lastmod>2026-07-19T17:02:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログレッシブデータサイエンスの可能性と課題 (Progressive Data Science: Potential and Challenges)</news:title>
   <news:publication_date>2026-07-19T17:02:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713640</loc>
  <lastmod>2026-07-19T17:02:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>8ビット浮動小数点で深層学習を学習する意義（Training Deep Neural Networks with 8-bit Floating Point Numbers）</news:title>
   <news:publication_date>2026-07-19T17:02:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713638</loc>
  <lastmod>2026-07-19T17:02:03Z</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おける「レイジー（怠惰）学習」の実態（On Lazy Training in Differentiable Programming）</news:title>
   <news:publication_date>2026-07-19T17:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713636</loc>
  <lastmod>2026-07-19T17:01:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子の深いレーザー冷却と効率的磁気圧縮（Deep laser cooling and efficient magnetic compression of molecules）</news:title>
   <news:publication_date>2026-07-19T17:01:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713634</loc>
  <lastmod>2026-07-19T17:01:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterにおける自動アカウントの語彙解析（Lexical Analysis of Automated Accounts on Twitter）</news:title>
   <news:publication_date>2026-07-19T17:01:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713632</loc>
  <lastmod>2026-07-19T16:10:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンコーダを備えた生成モデルの実証研究（An Empirical Study of Generative Models with Encoders）</news:title>
   <news:publication_date>2026-07-19T16:10:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713630</loc>
  <lastmod>2026-07-19T16:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PnP-AdaNetによるクロスモダリティ医用画像適応（PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation）</news:title>
   <news:publication_date>2026-07-19T16:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713628</loc>
  <lastmod>2026-07-19T16:09:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケッチ版SVDとレバレッジスコア順序付けの実証的評価（An Empirical Evaluation of Sketched SVD and its Application to Leverage Score Ordering）</news:title>
   <news:publication_date>2026-07-19T16:09:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713626</loc>
  <lastmod>2026-07-19T16:09:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速適応しきい値による均一ニューラルネットワーク量子化（FAT: Fast Adjustable Threshold for Uniform Neural Network Quantization）</news:title>
   <news:publication_date>2026-07-19T16:09:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713624</loc>
  <lastmod>2026-07-19T16:09:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AnFlo: Androidアプリにおける機密情報の異常フロー検出（AnFlo: Detecting Anomalous Sensitive Information Flows in Android Apps）</news:title>
   <news:publication_date>2026-07-19T16:09:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713622</loc>
  <lastmod>2026-07-19T16:09:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な選好学習：大余白オンライン特徴・ルール学習のゲーム理論的枠組み（Interpretable preference learning: a game theoretic framework for large margin on-line feature and rule learning）</news:title>
   <news:publication_date>2026-07-19T16:09:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713620</loc>
  <lastmod>2026-07-19T16:08:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層雑音耐性顔復元のための逐次ゲーティングアンサンブルネットワーク（Sequential Gating Ensemble Network for Noise Robust Multi-Scale Face Restoration）</news:title>
   <news:publication_date>2026-07-19T16:08:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713618</loc>
  <lastmod>2026-07-19T15:18:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期走行に強い単眼視覚自己位置推定の統合手法（Deep Global-Relative Networks for End-to-End 6-DoF Visual Localization and Odometry）</news:title>
   <news:publication_date>2026-07-19T15:18:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713616</loc>
  <lastmod>2026-07-19T15:17:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイバーセキュリティにおける機械学習の課題とデータセット（Machine Learning in Cyber-Security - Problems, Challenges and Data Sets）</news:title>
   <news:publication_date>2026-07-19T15:17:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713614</loc>
  <lastmod>2026-07-19T15:17:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔画像から身長や体型を推定する研究の要点（Physical Attribute Prediction Using Deep Residual Neural Networks）</news:title>
   <news:publication_date>2026-07-19T15:17:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713612</loc>
  <lastmod>2026-07-19T15:17:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランク欠測メカニズム下の行列補完（Matrix Completion under Low-Rank Missing Mechanism）</news:title>
   <news:publication_date>2026-07-19T15:17:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/713610</loc>
  <lastmod>2026-07-19T15:17:01Z</lastmod>
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