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   <news:title>Neural Rejuvenationによる深層ネットワーク訓練の効率化（Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization）</news:title>
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   <news:title>心電図データによるリスク層別化の新流儀（Multiple Instance Learning for ECG Risk Stratification）</news:title>
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   <news:title>アンチドートデータで推薦の偏向と不公平を是正する（Fighting Fire with Fire: Using Antidote Data to Improve Polarization and Fairness of Recommender Systems）</news:title>
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   <news:title>頭上カメラと外部固定視点による人物位置同定（Ego-Downward and Ambient Video based Person Location Association）</news:title>
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    <news:language>ja</news:language>
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   <news:title>アンカーボックス最適化による物体検出の精度向上（Anchor Box Optimization for Object Detection）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>画像分解で多様な視覚課題を単一枠組みで解く（Double-DIP: Unsupervised Image Decomposition via Coupled Deep-Image-Priors）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>プーリングによる介入確率の個人化（Personalizing Intervention Probabilities By Pooling）</news:title>
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  <lastmod>2026-07-12T13:20:43Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Autodockにおける自動ハイパーパラメータ選択（Automatic hyperparameter selection in Autodock）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T12:29:08Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ソフトマックス版ベルマン演算子の再考（Revisiting the Softmax Bellman Operator: New Benefits and New Perspective）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>公平性の確率的検証と集中不等式の応用（Probabilistic Verification of Fairness Properties via Concentration）</news:title>
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    <news:language>ja</news:language>
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   <news:title>伝播と生成を分離した映像予測（Disentangling Propagation and Generation for Video Prediction）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T12:17:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ソーシャルメディア利用者の表現学習（Learning Representations of Social Media Users）</news:title>
   <news:publication_date>2026-07-12T12:17:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710989</loc>
  <lastmod>2026-07-12T12:17:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>オミクスとMRIを統合してアルツハイマー病の希少遺伝マーカーを特定する（Integrating omics and MRI data with kernel-based tests and CNNs to identify rare genetic markers for Alzheimer’s disease）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T12:17:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>磁気共鳴弾性写真法へのCNNによる二重目的アプローチ（Dual Objective Approach Using A Convolutional Neural Network for Magnetic Resonance Elastography）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T12:17:06Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Cosine Metric Learning for Person Re-Identification（Deep Cosine Metric Learning for Person Re-Identification）</news:title>
   <news:publication_date>2026-07-12T12:17:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710983</loc>
  <lastmod>2026-07-12T11:25:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>健康データ向けユニーク関連情報に基づく特徴選択（Feature Selection Based on Unique Relevant Information for Health Data）</news:title>
   <news:publication_date>2026-07-12T11:25:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T11:17:08Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>効率的な生涯学習とA-GEMの実用性（EFFICIENT LIFELONG LEARNING WITH A-GEM）</news:title>
   <news:publication_date>2026-07-12T11:17:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T11:16:59Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>加齢黄斑変性の多目的ディープラーニングによる画像分類（A multi-task deep learning model for the classification of Age-related Macular Degeneration）</news:title>
   <news:publication_date>2026-07-12T11:16:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T11:16:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>時系列データにおける臨床共変量の補完（Imputation of Clinical Covariates in Time Series）</news:title>
   <news:publication_date>2026-07-12T11:16:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710975</loc>
  <lastmod>2026-07-12T11:15:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Snorkel DryBellによる弱い教師あり学習の実運用（Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710973</loc>
  <lastmod>2026-07-12T11:15:38Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>個別化医療における計算EEG：パーキンソン病を対象とした検討（Computational EEG in Personalized Medicine: A study in Parkinson’s Disease）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T11:15:23Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>深層表現が知覚品質特徴になる理由（Why Are Deep Representations Good Perceptual Quality Features?）</news:title>
   <news:publication_date>2026-07-12T11:15:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T10:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイバー犯罪のサプライチェーン自動検出への接近（Towards Automatic Discovery of Cybercrime Supply Chains）</news:title>
   <news:publication_date>2026-07-12T10:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T10:15:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>交通最適化におけるメタモデルの性能検証（Investigating performance of neural networks and gradient boosting models approximating microscopic traffic simulations in traffic optimization tasks）</news:title>
   <news:publication_date>2026-07-12T10:15:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T10:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>動的スペックルを利用した超解像アコースト光学トモグラフィー（Acousto-optic tomography beyond the acoustic diffraction-limit using speckle decorrelation）</news:title>
   <news:publication_date>2026-07-12T10:15:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710963</loc>
  <lastmod>2026-07-12T10:14:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Kikiチャレンジの危険動画検出（Kiki Kills: Identifying Dangerous Challenge Videos from Social Media）</news:title>
   <news:publication_date>2026-07-12T10:14:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/710961</loc>
  <lastmod>2026-07-12T10:13:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形バンディットにおける最良行動の迅速同定（Quick Best Action Identification in Linear Bandit Problems）</news:title>
   <news:publication_date>2026-07-12T10:13:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/710959</loc>
  <lastmod>2026-07-12T10:13:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入院患者の24時間以内退院予測（Predicting Inpatient Discharge Prioritization With Electronic Health Records）</news:title>
   <news:publication_date>2026-07-12T10:13:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710957</loc>
  <lastmod>2026-07-12T10:13:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不安定なCNNアクセラレータのための訓練法 — FPGAを事例とした実践的アプローチ (Training for ‘Unstable’ CNN Accelerator: A Case Study on FPGA)</news:title>
   <news:publication_date>2026-07-12T10:13:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/710955</loc>
  <lastmod>2026-07-12T09:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的ベイズ剪定によるCNN高速化（Accelerate CNN via Recursive Bayesian Pruning）</news:title>
   <news:publication_date>2026-07-12T09:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710953</loc>
  <lastmod>2026-07-12T09:21:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MDU‑Net：多段階で密に接続されたU‑Netによる医用画像セグメンテーション（MDU‑Net: multi‑scale densely connected U‑Net for biomedical image segmentation）</news:title>
   <news:publication_date>2026-07-12T09:21:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-12T09:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>それは私のものです！ロボットが所有関係とルールを学ぶ方法（That&amp;#039;s Mine! Learning Ownership Relations and Norms for Robots）</news:title>
   <news:publication_date>2026-07-12T09:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/710949</loc>
  <lastmod>2026-07-12T09:20:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布データの整合を変える一手（Regularized Wasserstein Means for Aligning Distributional Data）</news:title>
   <news:publication_date>2026-07-12T09:20:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/710947</loc>
  <lastmod>2026-07-12T09:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッドアナログ-デジタル大規模MIMOにおける機械学習を用いた高分解能到来方向測定とロバストなDM（Machine-Learning-based High-resolution DOA Measurement and Robust DM for Hybrid Analog-Digital Massive MIMO Transceiver）</news:title>
   <news:publication_date>2026-07-12T09:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710945</loc>
  <lastmod>2026-07-12T09:20:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化された残差ネットワークにおける勾配伝播の解析（Analysis on Gradient Propagation in Batch Normalized Residual Networks）</news:title>
   <news:publication_date>2026-07-12T09:20:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710943</loc>
  <lastmod>2026-07-12T09:20:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェブ教育動画の推論学習（Learning to Reason towards Understanding Web Instructional Videos）</news:title>
   <news:publication_date>2026-07-12T09:20:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710941</loc>
  <lastmod>2026-07-12T08:27:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN-EMによる生成モデルを用いたEM学習フレームワーク（GAN-EM: GAN based EM Learning Framework）</news:title>
   <news:publication_date>2026-07-12T08:27:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710939</loc>
  <lastmod>2026-07-12T08:27:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イメージスコア：有用なサンプルの選択方法（Image Score: How to Select Useful Samples）</news:title>
   <news:publication_date>2026-07-12T08:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710937</loc>
  <lastmod>2026-07-12T08:27:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群とビューの関係を学習するPVRNet（PVRNet: Point-View Relation Neural Network for 3D Shape Recognition）</news:title>
   <news:publication_date>2026-07-12T08:27:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710935</loc>
  <lastmod>2026-07-12T08:27:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模タスクとハードウェアに直接適合するニューラルアーキテクチャ探索（ProxylessNAS）</news:title>
   <news:publication_date>2026-07-12T08:27:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710933</loc>
  <lastmod>2026-07-12T08:26:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットと動的計画法のエンドツーエンド学習（End-to-end learning of convolutional neural net and dynamic programming for left ventricle segmentation）</news:title>
   <news:publication_date>2026-07-12T08:26:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710931</loc>
  <lastmod>2026-07-12T08:26:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復的再構成による弱い空間制約（Iterative Reorganization with Weak Spatial Constraints: Solving Arbitrary Jigsaw Puzzles for Unsupervised Representation Learning）</news:title>
   <news:publication_date>2026-07-12T08:26:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710929</loc>
  <lastmod>2026-07-12T08:26:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点移動で自分の居場所を作る仕組み：ECO（Egocentric Cognitive Map）</news:title>
   <news:publication_date>2026-07-12T08:26:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710927</loc>
  <lastmod>2026-07-12T07:35:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの勾配変動について（On variation of gradients of deep neural networks）</news:title>
   <news:publication_date>2026-07-12T07:35:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710925</loc>
  <lastmod>2026-07-12T07:35:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プラン認識駆動注意による視覚認識の改善（Plan-Recognition-Driven Attention Modeling for Visual Recognition）</news:title>
   <news:publication_date>2026-07-12T07:35:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710923</loc>
  <lastmod>2026-07-12T07:34:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化人工膵臓コントローラのインシリコ危険度解析（In-silico Risk Analysis of Personalized Artificial Pancreas Controllers via Rare-event Simulation）</news:title>
   <news:publication_date>2026-07-12T07:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710921</loc>
  <lastmod>2026-07-12T07:33:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高齢者歩行の安定性予測のためのLSTMネットワーク（LSTM-based Network for Human Gait Stability Prediction in an Intelligent Robotic Rollator）</news:title>
   <news:publication_date>2026-07-12T07:33:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710919</loc>
  <lastmod>2026-07-12T07:33:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>子どもの関与（エンゲージメント）を深層学習で推定する多視点アプローチ（A Deep Learning Approach for Multi-View Engagement Estimation of Children in a Child-Robot Joint Attention task）</news:title>
   <news:publication_date>2026-07-12T07:33:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710917</loc>
  <lastmod>2026-07-12T07:33:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SentiNetによる局所的普遍攻撃の検出（SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems）</news:title>
   <news:publication_date>2026-07-12T07:33:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710915</loc>
  <lastmod>2026-07-12T07:32:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AnyThreat：インサイダ脅威検出への機会主義的知識発見アプローチ（AnyThreat: An Opportunistic Knowledge Discovery Approach to Insider Threat Detection）</news:title>
   <news:publication_date>2026-07-12T07:32:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710913</loc>
  <lastmod>2026-07-12T06:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自信のある分布外例を生成して堅牢な分類器を作る（Building robust classifiers through generation of confident out of distribution examples）</news:title>
   <news:publication_date>2026-07-12T06:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710911</loc>
  <lastmod>2026-07-12T06:41:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U-net圧縮と知識蒸留の実務的示唆（On Compressing U-net Using Knowledge Distillation）</news:title>
   <news:publication_date>2026-07-12T06:41:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710909</loc>
  <lastmod>2026-07-12T06:41:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライブトラフィックを使った分類器の堅牢化（Improving robustness of classifiers by training against live traffic）</news:title>
   <news:publication_date>2026-07-12T06:41:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710907</loc>
  <lastmod>2026-07-12T06:41:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問を通じて生涯学習で画像にキャプションを付ける（Learning to Caption Images through a Lifetime by Asking Questions）</news:title>
   <news:publication_date>2026-07-12T06:41:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710905</loc>
  <lastmod>2026-07-12T06:41:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InGANによる自然画像の“DNA”の獲得とリマッピング (InGAN: Capturing and Remapping the “DNA” of a Natural Image)</news:title>
   <news:publication_date>2026-07-12T06:41:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710903</loc>
  <lastmod>2026-07-12T06:40:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的な目的関数で学習する遺伝的アルゴリズム（Hierarchical Genetic Algorithms with evolving objective functions）</news:title>
   <news:publication_date>2026-07-12T06:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710901</loc>
  <lastmod>2026-07-12T06:40:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層を模倣学習で発見する（DISCOVERING HIERARCHIES USING IMITATION LEARNING FROM HIERARCHY AWARE POLICIES）</news:title>
   <news:publication_date>2026-07-12T06:40:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710899</loc>
  <lastmod>2026-07-12T05:49:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EHRとEKGに基づく予測モデルの安定性評価（Measuring the Stability of EHR- and EKG-based Predictive Models）</news:title>
   <news:publication_date>2026-07-12T05:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710897</loc>
  <lastmod>2026-07-12T05:49:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図と心臓生理の確率モデル（A Probabilistic Model of Cardiac Physiology and Electrocardiograms）</news:title>
   <news:publication_date>2026-07-12T05:49:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710895</loc>
  <lastmod>2026-07-12T05:49:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動物ナビゲーションのための脳電気刺激（Brain Electrical Stimulation for Animal Navigation）</news:title>
   <news:publication_date>2026-07-12T05:49:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710893</loc>
  <lastmod>2026-07-12T05:48:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市環境のデータ駆動型大気質評価（Data-driven Air Quality Characterisation for Urban Environments: a Case Study）</news:title>
   <news:publication_date>2026-07-12T05:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710891</loc>
  <lastmod>2026-07-12T05:48:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeCoILFNetが変えるFPGA上のConvNet実装戦略（DeCoILFNet: Depth Concatenation and Inter-Layer Fusion based ConvNet Accelerator）</news:title>
   <news:publication_date>2026-07-12T05:48:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710889</loc>
  <lastmod>2026-07-12T05:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FineFool：注目（アテンション）で捉える微細物体輪郭攻撃（FineFool: Fine Object Contour Attack via Attention）</news:title>
   <news:publication_date>2026-07-12T05:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710887</loc>
  <lastmod>2026-07-12T05:47:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続的な画像検索スペクトルを横断する深層動的モデル（Traversing the Continuous Spectrum of Image Retrieval with Deep Dynamic Models）</news:title>
   <news:publication_date>2026-07-12T05:47:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710885</loc>
  <lastmod>2026-07-12T04:56:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチでは足りない状況 — HardFails: ソフトウェアから悪用されうるハードウェア不具合（When a Patch is Not Enough — HardFails: Software-Exploitable Hardware Bugs）</news:title>
   <news:publication_date>2026-07-12T04:56:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710883</loc>
  <lastmod>2026-07-12T04:56:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンティティとイベントの共同ニューラルモデリング（One for All: Neural Joint Modeling of Entities and Events）</news:title>
   <news:publication_date>2026-07-12T04:56:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710881</loc>
  <lastmod>2026-07-12T04:56:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Racial Faces in-the-Wild と IMAN が示したフェアネス改善の道筋（Racial Faces in-the-Wild: Reducing Racial Bias by Information Maximization Adaptation Network）</news:title>
   <news:publication_date>2026-07-12T04:56:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710879</loc>
  <lastmod>2026-07-12T04:55:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NTX：浮動小数点の汎用リダクション向け省電力ストリーミングアクセラレータ（NTX: An Energy-efficient Streaming Accelerator for Floating-point Generalized Reduction Workloads in 22 nm FD-SOI）</news:title>
   <news:publication_date>2026-07-12T04:55:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710877</loc>
  <lastmod>2026-07-12T04:55:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチパーティ対話における談話構造解析の順序的深層モデル（A Deep Sequential Model for Discourse Parsing on Multi-Party Dialogues）</news:title>
   <news:publication_date>2026-07-12T04:55:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710875</loc>
  <lastmod>2026-07-12T04:55:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差ネットワークの確率的訓練：微分方程式の視点（Stochastic Training of Residual Networks: a Differential Equation Viewpoint）</news:title>
   <news:publication_date>2026-07-12T04:55:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710873</loc>
  <lastmod>2026-07-12T04:55:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>損失関数とターゲット表現が敵対的ロバスト性に与える影響（Effects of Loss Functions And Target Representations on Adversarial Robustness）</news:title>
   <news:publication_date>2026-07-12T04:55:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710871</loc>
  <lastmod>2026-07-12T04:04:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランクプロジェクションツリーによる多層ニューラルネットワーク解釈（Rank Projection Trees for Multilevel Neural Network Interpretation）</news:title>
   <news:publication_date>2026-07-12T04:04:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710869</loc>
  <lastmod>2026-07-12T04:03:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>在宅高齢者の歩容可視化による見守り革新（Vision-Based Gait Analysis for Senior Care）</news:title>
   <news:publication_date>2026-07-12T04:03:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710867</loc>
  <lastmod>2026-07-12T04:03:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリと広告のカテゴリー類似度を近似する新手法（Approximating Categorical Similarity in Sponsored Search Relevance）</news:title>
   <news:publication_date>2026-07-12T04:03:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710865</loc>
  <lastmod>2026-07-12T04:03:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SwishNet：高速で軽量な1次元畳み込みネットワークによる音声・音楽・雑音の分類と分割（SwishNet: A Fast Convolutional Neural Network for Speech, Music and Noise Classification and Segmentation）</news:title>
   <news:publication_date>2026-07-12T04:03:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710863</loc>
  <lastmod>2026-07-12T04:02:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空画像における回転物体検出のためのRoIトランスフォーマ（Learning RoI Transformer for Detecting Oriented Objects in Aerial Images）</news:title>
   <news:publication_date>2026-07-12T04:02:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710861</loc>
  <lastmod>2026-07-12T04:02:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散的敵対的攻撃とサブモジュラ最適化（Discrete Adversarial Attacks and Submodular Optimization）</news:title>
   <news:publication_date>2026-07-12T04:02:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710859</loc>
  <lastmod>2026-07-12T04:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星夜間光データから経済成長を定量化する動的ネットワークと表現学習アプローチ（A Dynamic Network and Representation Learning Approach for Quantifying Economic Growth from Satellite Imagery）</news:title>
   <news:publication_date>2026-07-12T04:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710857</loc>
  <lastmod>2026-07-12T03:10:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜血管の動脈・静脈自動識別とセグメンテーション（AUTOMATED SEGMENTATION AND CLASSIFICATION OF ARTERIOLES AND VENULES USING CASCADING DILATED CONVOLUTIONAL NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-07-12T03:10:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710855</loc>
  <lastmod>2026-07-12T03:10:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知的画像インペインティングのための深層インセプション生成ネットワーク (Deep Inception Generative Network for Cognitive Image Inpainting)</news:title>
   <news:publication_date>2026-07-12T03:10:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710853</loc>
  <lastmod>2026-07-12T03:10:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブグラフ観測から連結成分数を推定するスペクトル手法（Number of Connected Components in a Graph: Estimation via Counting Patterns）</news:title>
   <news:publication_date>2026-07-12T03:10:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710851</loc>
  <lastmod>2026-07-12T03:09:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次離散のCFDデータ欠損を復元する深層学習と動力学学習（Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning）</news:title>
   <news:publication_date>2026-07-12T03:09:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710849</loc>
  <lastmod>2026-07-12T03:09:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー志向ユーザーのプロファイル取得法（How to Profile Privacy-Conscious Users in Recommender Systems）</news:title>
   <news:publication_date>2026-07-12T03:09:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710847</loc>
  <lastmod>2026-07-12T03:09:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スナップショット蒸留：1世代での教師―生徒最適化（Snapshot Distillation: Teacher-Student Optimization in One Generation）</news:title>
   <news:publication_date>2026-07-12T03:09:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710845</loc>
  <lastmod>2026-07-12T03:09:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AlGaN/AlGaN深紫外発光ダイオードの量子井戸数最適化（Optimization of quantum well number of AlGaN/AlGaN deep-ultraviolet light-emitting diodes）</news:title>
   <news:publication_date>2026-07-12T03:09:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710843</loc>
  <lastmod>2026-07-12T02:17:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セントーラス銀河団コアにおける金属の塵への取り込みの可能性（Possible depletion of metals into dust grains in the core of the Centaurus cluster of galaxies）</news:title>
   <news:publication_date>2026-07-12T02:17:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710841</loc>
  <lastmod>2026-07-12T02:17:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像で道路品質を等級付けする（Assigning a Grade: Accurate Measurement of Road Quality Using Satellite Imagery）</news:title>
   <news:publication_date>2026-07-12T02:17:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710839</loc>
  <lastmod>2026-07-12T02:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SKA1-Lowによる再電離期（EoR）深宇宙観測の候補野事前選定（Pre-selection of the Candidate Fields for Deep Imaging of the Epoch of Reionization with SKA1-Low）</news:title>
   <news:publication_date>2026-07-12T02:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710837</loc>
  <lastmod>2026-07-12T02:16:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データベース接続ログにおける異常検知のためのビッグデータアーキテクチャ（A Big Data Architecture for the Detection of Anomalies within Database Connection Logs）</news:title>
   <news:publication_date>2026-07-12T02:16:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710835</loc>
  <lastmod>2026-07-12T02:16:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的マルチストリーム映像要約（Multi-stream dynamic video Summarization）</news:title>
   <news:publication_date>2026-07-12T02:16:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710833</loc>
  <lastmod>2026-07-12T02:15:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Explore-Exploitによる対話的オンライン学習の実装と意義（Explore-Exploit: A Framework for Interactive and Online Learning）</news:title>
   <news:publication_date>2026-07-12T02:15:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710831</loc>
  <lastmod>2026-07-12T02:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク接続ログの異常検知（Anomaly Detection for Network Connection Logs）</news:title>
   <news:publication_date>2026-07-12T02:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710829</loc>
  <lastmod>2026-07-12T01:24:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RpropニューラルネットワークによるPV最大電力点追従と短絡電流制限（A Rprop-Neural-Network-Based PV Maximum Power Point Tracking Algorithm with Short-Circuit Current Limitation）</news:title>
   <news:publication_date>2026-07-12T01:24:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710827</loc>
  <lastmod>2026-07-12T01:23:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>出力層付近に限定したベイズ化で不確実性を捉える（The Relevance of Bayesian Layer Positioning to Model Uncertainty in Deep Bayesian Active Learning）</news:title>
   <news:publication_date>2026-07-12T01:23:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710825</loc>
  <lastmod>2026-07-12T01:23:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超キャパシタ（ウルトラキャパシタ）向けニューラルネットワーク最適制御の実装可能性（A Neural-Network-Based Optimal Control of Ultra-Capacitors with System Uncertainties）</news:title>
   <news:publication_date>2026-07-12T01:23:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710823</loc>
  <lastmod>2026-07-12T01:22:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床時系列データを用いた予測の落とし穴（Leveraging Clinical Time-Series Data for Prediction: A Cautionary Tale）</news:title>
   <news:publication_date>2026-07-12T01:22:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710821</loc>
  <lastmod>2026-07-12T01:22:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゾーン・クリギングによる回帰と分類（Regression and Classification by Zonal Kriging）</news:title>
   <news:publication_date>2026-07-12T01:22:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710819</loc>
  <lastmod>2026-07-12T01:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EvoMSA: 感情分析のための多言語進化的アプローチ (EvoMSA: A Multilingual Evolutionary Approach for Sentiment Analysis)</news:title>
   <news:publication_date>2026-07-12T01:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710817</loc>
  <lastmod>2026-07-12T01:22:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNN方策の有限状態表現の学習（Learning Finite State Representations of Recurrent Policy Networks）</news:title>
   <news:publication_date>2026-07-12T01:22:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710814</loc>
  <lastmod>2026-07-12T00:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークにおける暗黙のフィルタ単位スパース化（On Implicit Filter Level Sparsity in Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-12T00:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710812</loc>
  <lastmod>2026-07-12T00:31:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D半教師あり学習の不確実性配慮マルチビュー共同学習（3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training）</news:title>
   <news:publication_date>2026-07-12T00:31:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710810</loc>
  <lastmod>2026-07-12T00:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次埋め込みによるテキストクラスタリング（Sequential Embedding Induced Text Clustering）</news:title>
   <news:publication_date>2026-07-12T00:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710808</loc>
  <lastmod>2026-07-12T00:30:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮想現実学習環境におけるセキュリティ・プライバシー・安全性のリスク評価 (Security, Privacy and Safety Risk Assessment for Virtual Reality Learning Environment Applications)</news:title>
   <news:publication_date>2026-07-12T00:30:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710806</loc>
  <lastmod>2026-07-12T00:29:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Steinの無偏リスク推定器を活用した教師なしX線画像のデノイズ（Leveraging Deep Stein’s Unbiased Risk Estimator for Unsupervised X-ray Denoising）</news:title>
   <news:publication_date>2026-07-12T00:29:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710804</loc>
  <lastmod>2026-07-12T00:29:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像から複数照明を分離する学習法（Learning to Separate Multiple Illuminants in a Single Image）</news:title>
   <news:publication_date>2026-07-12T00:29:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710802</loc>
  <lastmod>2026-07-12T00:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VC次元を超えるラベルなし圧縮スキーム（Unlabeled Compression Schemes Exceeding the VC-dimension）</news:title>
   <news:publication_date>2026-07-12T00:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710800</loc>
  <lastmod>2026-07-11T23:38:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的視点から見るフェデレーテッドラーニング（Analyzing Federated Learning through an Adversarial Lens）</news:title>
   <news:publication_date>2026-07-11T23:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710798</loc>
  <lastmod>2026-07-11T23:36:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FU Ori天体の円盤風モデル（Disc wind models for FU Ori objects）</news:title>
   <news:publication_date>2026-07-11T23:36:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710796</loc>
  <lastmod>2026-07-11T23:27:33Z</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におけるスパース符号化の不確実性伝播（Uncertainty propagation in neural networks for sparse coding）</news:title>
   <news:publication_date>2026-07-11T23:27:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710794</loc>
  <lastmod>2026-07-11T23:27:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シャッフリングによるプライバシー増幅（Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity）</news:title>
   <news:publication_date>2026-07-11T23:27:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710792</loc>
  <lastmod>2026-07-11T23:26:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速かつ柔軟な屋内シーン合成（Fast and Flexible Indoor Scene Synthesis via Deep Convolutional Generative Models）</news:title>
   <news:publication_date>2026-07-11T23:26:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710790</loc>
  <lastmod>2026-07-11T23:26:27Z</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によるサーフェスコード用デコーダ比較（Comparing neural network based decoders for the surface code）</news:title>
   <news:publication_date>2026-07-11T23:26:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710788</loc>
  <lastmod>2026-07-11T23:26:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コミュニティ変化の検出手法（Testing Changes in Communities for the Stochastic Block Model）</news:title>
   <news:publication_date>2026-07-11T23:26:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710786</loc>
  <lastmod>2026-07-11T22:34:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロ流体デバイスの流れ形状設計に深層強化学習を用いる（Flow Shape Design for Microfluidic Devices Using Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-11T22:34:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710784</loc>
  <lastmod>2026-07-11T22:34:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多峰性分布の効率的サンプリング手法と理論的裏付け（Simulated Tempering Langevin Monte Carlo II: An Improved Proof using Soft Markov Chain Decomposition）</news:title>
   <news:publication_date>2026-07-11T22:34:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710782</loc>
  <lastmod>2026-07-11T22:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>政府支出パターンの対応分析（Correspondence Analysis of Government Expenditure Patterns）</news:title>
   <news:publication_date>2026-07-11T22:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710780</loc>
  <lastmod>2026-07-11T22:32:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スーパー神岡観測器における二核子・核子崩壊の探索（Dinucleon and Nucleon Decay to Two-Body Final States with no Hadrons in Super-Kamiokande）</news:title>
   <news:publication_date>2026-07-11T22:32:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710778</loc>
  <lastmod>2026-07-11T22:32:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>天の川平面とバルジをWFDで覆うべき理由（The Plane’s The Thing: The Case for Wide-Fast-Deep Coverage of the Galactic Plane and Bulge）</news:title>
   <news:publication_date>2026-07-11T22:32:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710776</loc>
  <lastmod>2026-07-11T22:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルでメタグレーティング設計を加速する（Freeform Diffractive Metagrating Design Based on Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-11T22:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710774</loc>
  <lastmod>2026-07-11T22:32:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画認識の高速化を実現する適応的フレーム選択（AdaFrame: Adaptive Frame Selection for Fast Video Recognition）</news:title>
   <news:publication_date>2026-07-11T22:32:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710772</loc>
  <lastmod>2026-07-11T21:41:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANの暗黙の仮定を読み解く（On the Implicit Assumptions of GANs）</news:title>
   <news:publication_date>2026-07-11T21:41:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710770</loc>
  <lastmod>2026-07-11T21:41:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Komondor: 次世代高密度WLAN向け無線ネットワークシミュレータ（Komondor: a Wireless Network Simulator for Next-Generation High-Density WLANs）</news:title>
   <news:publication_date>2026-07-11T21:41:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710768</loc>
  <lastmod>2026-07-11T21:40:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドープされたハバード模型のスナップショット分類に機械学習を用いる研究（Classifying Snapshots of the Doped Hubbard Model with Machine Learning）</news:title>
   <news:publication_date>2026-07-11T21:40:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710766</loc>
  <lastmod>2026-07-11T21:40:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケールで非線形力学を階層的に捉える手法（Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling）</news:title>
   <news:publication_date>2026-07-11T21:40:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710764</loc>
  <lastmod>2026-07-11T21:39:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sym-parameterを用いた混合ドメイン画像変換（Sym-parameterized Dynamic Inference for Mixed-Domain Image Translation）</news:title>
   <news:publication_date>2026-07-11T21:39:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710762</loc>
  <lastmod>2026-07-11T21:39:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティックレイアウトからの多様な画像生成（Diverse Image Synthesis from Semantic Layouts via Conditional IMLE）</news:title>
   <news:publication_date>2026-07-11T21:39:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710760</loc>
  <lastmod>2026-07-11T21:39:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNN-Cert: 畳み込みニューラルネットワークの堅牢性を証明する効率的フレームワーク（CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-11T21:39:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710758</loc>
  <lastmod>2026-07-11T20:47:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スムーズド解析による教師なし学習の安定化（Smoothed Analysis in Unsupervised Learning via Decoupling）</news:title>
   <news:publication_date>2026-07-11T20:47:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710756</loc>
  <lastmod>2026-07-11T20:47:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習でゲノムの構造カバレッジを広げる方法（Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints）</news:title>
   <news:publication_date>2026-07-11T20:47:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710754</loc>
  <lastmod>2026-07-11T20:46:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし分離表現学習に対する一般的な仮定への挑戦（Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations）</news:title>
   <news:publication_date>2026-07-11T20:46:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710752</loc>
  <lastmod>2026-07-11T20:46:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TOUCHDOWN: 実世界ストリートビューでの自然言語ナビゲーションと空間推論（TOUCHDOWN: Natural Language Navigation and Spatial Reasoning in Visual Street Environments）</news:title>
   <news:publication_date>2026-07-11T20:46:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710750</loc>
  <lastmod>2026-07-11T20:45:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素数ニューラルネットワークの実用性評価（Evaluation of Complex-Valued Neural Networks on Real-Valued Classification Tasks）</news:title>
   <news:publication_date>2026-07-11T20:45:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710748</loc>
  <lastmod>2026-07-11T20:45:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>薄膜気体の収縮に伴うマイクロバブル発生の高忠実度シミュレーション（High Fidelity Simulations of Micro-Bubble Shedding from Retracting Thin Gas Films in the Context of Liquid-Liquid Impact）</news:title>
   <news:publication_date>2026-07-11T20:45:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710746</loc>
  <lastmod>2026-07-11T20:45:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低温での対数的抵抗上昇が示すd波秩序の兆候（Logarithmic Upturn in Low-Temperature Electronic Transport as a Signature of d-Wave Order in Cuprate Superconductors）</news:title>
   <news:publication_date>2026-07-11T20:45:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710744</loc>
  <lastmod>2026-07-11T19:54:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス・マルチインスタンス学習の確率的最尤解法（A Multiclass Multiple Instance Learning Method with Exact Likelihood）</news:title>
   <news:publication_date>2026-07-11T19:54:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710742</loc>
  <lastmod>2026-07-11T19:54:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフを使った多視点正準相関分析の実践（Graph Multiview Canonical Correlation Analysis）</news:title>
   <news:publication_date>2026-07-11T19:54:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710740</loc>
  <lastmod>2026-07-11T19:53:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習を用いたトーリック符号の量子誤り訂正（Quantum error correction for the toric code using deep reinforcement learning）</news:title>
   <news:publication_date>2026-07-11T19:53:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710738</loc>
  <lastmod>2026-07-11T19:52:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InverseRenderNetによる単一画像からの逆レンダリング（InverseRenderNet: Learning single image inverse rendering）</news:title>
   <news:publication_date>2026-07-11T19:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710736</loc>
  <lastmod>2026-07-11T19:52:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ的敵対的球面とノイズのない設定における推論（Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting）</news:title>
   <news:publication_date>2026-07-11T19:52:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710734</loc>
  <lastmod>2026-07-11T19:52:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重尾分布に基づくロバストなベイズ型クラスタ数推定（Robust Bayesian Cluster Enumeration Based on the t Distribution）</news:title>
   <news:publication_date>2026-07-11T19:52:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710732</loc>
  <lastmod>2026-07-11T19:52:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代表サンプル選定を高速化する手法の要点（Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer Vision）</news:title>
   <news:publication_date>2026-07-11T19:52:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710730</loc>
  <lastmod>2026-07-11T19:01:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手術室での顔検出の改善（Face Detection in the Operating Room: Comparison of State-of-the-art Methods and a Self-supervised Approach）</news:title>
   <news:publication_date>2026-07-11T19:01:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710728</loc>
  <lastmod>2026-07-11T19:00:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分的シーン合成（Incremental Scene Synthesis）</news:title>
   <news:publication_date>2026-07-11T19:00:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710726</loc>
  <lastmod>2026-07-11T19:00:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生存時間解析における治療強度選択への深い潜在変数モデルの応用 (A Deep Latent-Variable Model Application to Select Treatment Intensity in Survival Analysis)</news:title>
   <news:publication_date>2026-07-11T19:00:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710724</loc>
  <lastmod>2026-07-11T18:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タプルマックス損失による言語識別の最適化（Tuplemax Loss for Language Identification）</news:title>
   <news:publication_date>2026-07-11T18:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710722</loc>
  <lastmod>2026-07-11T18:59:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-11T18:59:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710720</loc>
  <lastmod>2026-07-11T18:59:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア工学における知識管理の体系的レビュー（Knowledge Management in Software Engineering: A Systematic Review）</news:title>
   <news:publication_date>2026-07-11T18:59:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710718</loc>
  <lastmod>2026-07-11T18:59:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタリングによる回帰とメトロポリス–ヘイスティングス（Regression by clustering using Metropolis-Hastings）</news:title>
   <news:publication_date>2026-07-11T18:59:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710716</loc>
  <lastmod>2026-07-11T18:07:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療文書とマルチモーダル学習による院内死亡率予測の精度改善（Improving Hospital Mortality Prediction with Medical Named Entities and Multimodal Learning）</news:title>
   <news:publication_date>2026-07-11T18:07:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710714</loc>
  <lastmod>2026-07-11T18:07:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセットやタスク間での表現の転移性（On the Transferability of Representations in Neural Networks Between Datasets and Tasks）</news:title>
   <news:publication_date>2026-07-11T18:07:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710712</loc>
  <lastmod>2026-07-11T18:07:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BCCNetによるラベル合成とニューラルネットワーク同時学習（BCCNet: Bayesian classifier combination neural network）</news:title>
   <news:publication_date>2026-07-11T18:07:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710710</loc>
  <lastmod>2026-07-11T18:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテを使った機械学習：薬剤不遵守の予測モデルと特徴利用（Machine Learning on Electronic Health Records: Models and Features Usages to predict Medication Non-Adherence）</news:title>
   <news:publication_date>2026-07-11T18:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710708</loc>
  <lastmod>2026-07-11T18:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間校正フィードバックによる反事実学習（Counterfactual Learning from Human Proofreading Feedback for Semantic Parsing）</news:title>
   <news:publication_date>2026-07-11T18:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710706</loc>
  <lastmod>2026-07-11T18:05:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種データがもたらす認知症検出の汎化力（The Effect of Heterogeneous Data for Alzheimer’s Disease Detection from Speech）</news:title>
   <news:publication_date>2026-07-11T18:05:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710704</loc>
  <lastmod>2026-07-11T18:05:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所差分プライバシー下での離散分布学習におけるランダマイズド・レスポンスの最適性（Locally Differentially-Private Randomized Response for Discrete Distribution Learning）</news:title>
   <news:publication_date>2026-07-11T18:05:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710702</loc>
  <lastmod>2026-07-11T17:14:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河群におけるMONDの優位なサンプル（MOND in galaxy groups: A superior sample）</news:title>
   <news:publication_date>2026-07-11T17:14:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710700</loc>
  <lastmod>2026-07-11T17:13:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ImageNet訓練済みCNNはテクスチャに偏る──形状バイアスを高める意義（IMAGENET-TRAINED CNNS ARE BIASED TOWARDS TEXTURE; INCREASING SHAPE BIAS IMPROVES ACCURACY AND ROBUSTNESS）</news:title>
   <news:publication_date>2026-07-11T17:13:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710698</loc>
  <lastmod>2026-07-11T17:13:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動列車連結のための機械学習による障害物検知（Machine Learning Based Obstacle Detection for Automatic Train Pairing）</news:title>
   <news:publication_date>2026-07-11T17:13:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710696</loc>
  <lastmod>2026-07-11T17:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>21 cm信号のパラメータ空間を最適にサンプリングする方法（Working towards an optimal sampling of the 21 cm signal parameter space）</news:title>
   <news:publication_date>2026-07-11T17:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710694</loc>
  <lastmod>2026-07-11T17:12:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ApolloCar3Dによる自動運転向け3D車両理解の大転換（ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving）</news:title>
   <news:publication_date>2026-07-11T17:12:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710692</loc>
  <lastmod>2026-07-11T17:12:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非一様フーリエデータからのエッジ検出とスパースベイズ学習（Detecting edges from non-uniform Fourier data via sparse Bayesian learning）</news:title>
   <news:publication_date>2026-07-11T17:12:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710690</loc>
  <lastmod>2026-07-11T17:11:55Z</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>2026-07-11T17:11:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710688</loc>
  <lastmod>2026-07-11T16:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復残差CNNによるバースト撮影の画質復元（Iterative Residual CNNs for Burst Photography Applications）</news:title>
   <news:publication_date>2026-07-11T16:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710686</loc>
  <lastmod>2026-07-11T16:20:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽における意味関係を掘る：Word2Vecを使った音楽表現の探索（From Context to Concept: Exploring Semantic Relationships in Music with Word2Vec）</news:title>
   <news:publication_date>2026-07-11T16:20:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710684</loc>
  <lastmod>2026-07-11T16:20:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPU容量を超える大規模モデルのデータ並列分散学習（Data-parallel distributed training of very large models beyond GPU capacity）</news:title>
   <news:publication_date>2026-07-11T16:20:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710682</loc>
  <lastmod>2026-07-11T16:18:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三次テンソル積による推論学習（Learning to Reason with Third-Order Tensor Products）</news:title>
   <news:publication_date>2026-07-11T16:18:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710680</loc>
  <lastmod>2026-07-11T16:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FLIPERでTESSの振動星を自動分類する（FLIPER: Classifying TESS Pulsating Stars）</news:title>
   <news:publication_date>2026-07-11T16:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710678</loc>
  <lastmod>2026-07-11T16:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔表情認識における二層注意と二段階マルチタスク学習（Two-level Attention with Two-stage Multi-task Learning for Facial Emotion Recognition）</news:title>
   <news:publication_date>2026-07-11T16:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710676</loc>
  <lastmod>2026-07-11T16:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高コストなブラックボックス最適化の新戦略（Global optimization of expensive black-box models based on asynchronous hybrid-criterion with interval reduction）</news:title>
   <news:publication_date>2026-07-11T16:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710674</loc>
  <lastmod>2026-07-11T15:26:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強相互作用領域へクエンチされたボース気体の初期ダイナミクス（Early-time dynamics of Bose gases quenched into the strongly interacting regime）</news:title>
   <news:publication_date>2026-07-11T15:26:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710672</loc>
  <lastmod>2026-07-11T15:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期性信号の異常検出における位相分類手法（A Machine-Learning Phase Classification Scheme for Anomaly Detection in Signals with Periodic Characteristics）</news:title>
   <news:publication_date>2026-07-11T15:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710670</loc>
  <lastmod>2026-07-11T15:26:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非包含部分列が突きつける自然言語推論の弱点（Non-entailed subsequences as a challenge for natural language inference）</news:title>
   <news:publication_date>2026-07-11T15:26:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710668</loc>
  <lastmod>2026-07-11T15:24:53Z</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/710666</loc>
  <lastmod>2026-07-11T15:24:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QUIC実装の相互運用性を導くテスト（Interoperability-Guided Testing of QUIC Implementations using Symbolic Execution）</news:title>
   <news:publication_date>2026-07-11T15:24:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710664</loc>
  <lastmod>2026-07-11T15:24:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似画像処理パイプラインからのディープニューラルネットワークのブートストラップ（Bootstrapping Deep Neural Networks from Approximate Image Processing Pipelines）</news:title>
   <news:publication_date>2026-07-11T15:24:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710662</loc>
  <lastmod>2026-07-11T15:24:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の非線形拡散問題のためのネットワーク（Networks for Nonlinear Diffusion Problems in Imaging）</news:title>
   <news:publication_date>2026-07-11T15:24:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-07-11T14:32:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多尺度分散表現による深層学習とbジェット識別への応用（Multi-Scale Distributed Representation for Deep Learning and its Application to b-Jet Tagging）</news:title>
   <news:publication_date>2026-07-11T14:32:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710658</loc>
  <lastmod>2026-07-11T14:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Haar Scattering Networksの実務的評価（Deep Haar Scattering Networks in Pattern Recognition: A Promising Approach）</news:title>
   <news:publication_date>2026-07-11T14:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710656</loc>
  <lastmod>2026-07-11T14:31:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TEA-DNN: 時間・エネルギー・精度を同時最適化するニューラルネット探索（TEA-DNN: the Quest for Time-Energy-Accuracy）</news:title>
   <news:publication_date>2026-07-11T14:31:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710654</loc>
  <lastmod>2026-07-11T14:31:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適座標上昇による特徴選択（Feature Selection with Optimal Coordinate Ascent (OCA))</news:title>
   <news:publication_date>2026-07-11T14:31:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710652</loc>
  <lastmod>2026-07-11T14:31:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化された粗→細の視覚認識と進行的学習（Generalized Coarse-to-Fine Visual Recognition with Progressive Training）</news:title>
   <news:publication_date>2026-07-11T14:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710650</loc>
  <lastmod>2026-07-11T14:31:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変長時系列データの同時表現学習とクラスタリング（Recurrent Deep Divergence-based Clustering for simultaneous feature learning and clustering of variable length time series）</news:title>
   <news:publication_date>2026-07-11T14:31:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710648</loc>
  <lastmod>2026-07-11T14:30:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャネル符号化におけるRNNベース深層学習の性能解析（Performance Analysis of Deep Learning based on Recurrent Neural Networks for Channel Coding）</news:title>
   <news:publication_date>2026-07-11T14:30:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710646</loc>
  <lastmod>2026-07-11T13:39:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を持つ敵対的生成ネットワークによる顔認識攻撃（Attacks on State-of-the-Art Face Recognition using Attentional Adversarial Attack Generative Network）</news:title>
   <news:publication_date>2026-07-11T13:39:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710644</loc>
  <lastmod>2026-07-11T13:31:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAMNetによる画像超解像の効率化（MAMNet: Multi-path Adaptive Modulation Network for Image Super-Resolution）</news:title>
   <news:publication_date>2026-07-11T13:31:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710642</loc>
  <lastmod>2026-07-11T13:31:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッドモデルによる平均推定の力（The Power of the Hybrid Model for Mean Estimation）</news:title>
   <news:publication_date>2026-07-11T13:31:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710640</loc>
  <lastmod>2026-07-11T13:31:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非標準的な監督学習問題の現状と応用展望（A snapshot on nonstandard supervised learning problems）</news:title>
   <news:publication_date>2026-07-11T13:31:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710638</loc>
  <lastmod>2026-07-11T13:30:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベントカメラを用いたセマンティックセグメンテーション入門（EV-SegNet: Semantic Segmentation for Event-based Cameras）</news:title>
   <news:publication_date>2026-07-11T13:30:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710636</loc>
  <lastmod>2026-07-11T13:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素数値ネットワークを用いた画像パッチ比較学習（Utilizing Complex-valued Network for Learning to Compare Image Patches）</news:title>
   <news:publication_date>2026-07-11T13:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710634</loc>
  <lastmod>2026-07-11T13:29:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOBIUSによるモデル非公開バイナリ化ニューラルネットワーク（MOBIUS: Model-Oblivious Binarized Neural Networks）</news:title>
   <news:publication_date>2026-07-11T13:29:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710632</loc>
  <lastmod>2026-07-11T12:37:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間層に導入する「2次統計」―GSoPが畳み込みネットワークを変える（Global Second-order Pooling Convolutional Networks）</news:title>
   <news:publication_date>2026-07-11T12:37:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710630</loc>
  <lastmod>2026-07-11T12:20:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生体信号における少数クラス拡張で実用的な異常検知を目指す手法（Class Augmented Semi-Supervised Learning for Practical Clinical Analytics on Physiological Signals）</news:title>
   <news:publication_date>2026-07-11T12:20:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710628</loc>
  <lastmod>2026-07-11T12:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模分散二次最適化の実用化（Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-11T12:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710626</loc>
  <lastmod>2026-07-11T12:19:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子生成モデルの比較基盤 MOSES（Molecular Sets: A Benchmarking Platform for Molecular Generation Models）</news:title>
   <news:publication_date>2026-07-11T12:19:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710624</loc>
  <lastmod>2026-07-11T12:18:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース化グラフ回帰による骨格ベース行動認識の最適化（Optimized Skeleton-based Action Recognition via Sparsified Graph Regression）</news:title>
   <news:publication_date>2026-07-11T12:18:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710622</loc>
  <lastmod>2026-07-11T12:18:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの3D形状再構築と2D-3D自己整合性（3D Shape Reconstruction from a Single 2D Image via 2D-3D Self-Consistency）</news:title>
   <news:publication_date>2026-07-11T12:18:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710620</loc>
  <lastmod>2026-07-11T12:18:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル学習ゲームのオーサリングツール：評価、総括と提案 (Mobile Learning Game Authoring Tools: Assessment, Synthesis and Proposals)</news:title>
   <news:publication_date>2026-07-11T12:18:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710618</loc>
  <lastmod>2026-07-11T11:26:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>透明誘電体へのサブナノ秒レーザーパルスによる単独微細構造の形成とアブレーション（Formation of solitary microstructure and ablation into transparent dielectric by a subnanosecond laser pulse）</news:title>
   <news:publication_date>2026-07-11T11:26:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710616</loc>
  <lastmod>2026-07-11T11:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮型マルチファンクションCNNによる医用画像分類の効率化（Effective, Fast, and Memory-Efﬁcient Compressed Multi-function Convolutional Neural Networks for More Accurate Medical Image Classification）</news:title>
   <news:publication_date>2026-07-11T11:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710614</loc>
  <lastmod>2026-07-11T11:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形状条件付き画像生成（Shape-conditioned Image Generation by Learning Latent Appearance Representation from Unpaired Data）</news:title>
   <news:publication_date>2026-07-11T11:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710612</loc>
  <lastmod>2026-07-11T11:20:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプル効率の高い確率的分散削減立方正則化法（Sample Efficient Stochastic Variance-Reduced Cubic Regularization Method）</news:title>
   <news:publication_date>2026-07-11T11:20:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710610</loc>
  <lastmod>2026-07-11T11:20:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン固有変分情報下界を用いた教師なし画像間翻訳（Unsupervised Image-to-Image Translation Using Domain-Specific Variational Information Bound）</news:title>
   <news:publication_date>2026-07-11T11:20:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710608</loc>
  <lastmod>2026-07-11T11:19:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep learning for pedestrians: backpropagation in CNNs（Deep learning for pedestrians: backpropagation in CNNs）</news:title>
   <news:publication_date>2026-07-11T11:19:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710606</loc>
  <lastmod>2026-07-11T11:19:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DuLa-Net：単一RGBパノラマから3D室内レイアウトを推定する二重投影ネットワーク (DuLa-Net: A Dual-Projection Network for Estimating Room Layouts from a Single RGB Panorama)</news:title>
   <news:publication_date>2026-07-11T11:19:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710604</loc>
  <lastmod>2026-07-11T10:28:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散拡張現実システムによる医療トレーニングとシミュレーション（A Distributed Augmented Reality System for Medical Training and Simulation）</news:title>
   <news:publication_date>2026-07-11T10:28:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710602</loc>
  <lastmod>2026-07-11T10:27:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論に基づく特徴選択の簡潔な停止基準（Simple stopping criteria for information theoretic feature selection）</news:title>
   <news:publication_date>2026-07-11T10:27:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710600</loc>
  <lastmod>2026-07-11T10:27:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測ファクトリー：予測モデルの自動開発と共同評価（Prediction Factory: automated development and collaborative evaluation of predictive models）</news:title>
   <news:publication_date>2026-07-11T10:27:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710598</loc>
  <lastmod>2026-07-11T10:26:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HYPE: 電子カルテから低血糖イベントを自動検出する高性能NLPシステム（HYPE: A High Performing NLP System for Automatically Detecting Hypoglycemia Events from Electronic Health Record Notes）</news:title>
   <news:publication_date>2026-07-11T10:26:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710596</loc>
  <lastmod>2026-07-11T10:26:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Autoconjによる共役性の自動認識と活用（Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language）</news:title>
   <news:publication_date>2026-07-11T10:26:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710594</loc>
  <lastmod>2026-07-11T10:26:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>触覚フィードバックが学びを変える――ハプティック教育の可能性と課題（The Haptic Paradigm in Education: Challenges and Case Studies）</news:title>
   <news:publication_date>2026-07-11T10:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710592</loc>
  <lastmod>2026-07-11T10:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化獣医疾患コーディングの改善のための大規模生成モデリング（Large-scale Generative Modeling to Improve Automated Veterinary Disease Coding）</news:title>
   <news:publication_date>2026-07-11T10:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710590</loc>
  <lastmod>2026-07-11T09:35:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Top-K部分集合の確率的バンディットと線形空間での非線形フィードバック（Stochastic Top-K Subset Bandits with Linear Space and Non-Linear Feedback）</news:title>
   <news:publication_date>2026-07-11T09:35:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/710588</loc>
  <lastmod>2026-07-11T09:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散推論のための線形サポートベクターマシン（Distributed Inference for Linear Support Vector Machine）</news:title>
   <news:publication_date>2026-07-11T09:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710586</loc>
  <lastmod>2026-07-11T09:34:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽コーパスを言語化する発想（Naive Dictionary On Musical Corpora: From Knowledge Representation To Pattern Recognition）</news:title>
   <news:publication_date>2026-07-11T09:34:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710584</loc>
  <lastmod>2026-07-11T09:34:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの物体形状復元の新しい流儀（Single-view Object Shape Reconstruction Using Deep Shape Prior and Silhouette）</news:title>
   <news:publication_date>2026-07-11T09:34:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710582</loc>
  <lastmod>2026-07-11T09:34:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再電離期クエーサー探索 IV：DES, VHS, unWISE 光度測定による六つの新規 z ≳6.5 クエーサーの発見 (Exploring Reionization-Era Quasars IV: Discovery of Six New z ≳6.5 Quasars with DES, VHS and unWISE Photometry)</news:title>
   <news:publication_date>2026-07-11T09:34:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710580</loc>
  <lastmod>2026-07-11T09:33:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習における交絡を評価する置換法（Using permutations to assess confounding in machine learning applications for digital health）</news:title>
   <news:publication_date>2026-07-11T09:33:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710578</loc>
  <lastmod>2026-07-11T09:33:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>燃焼系における粒子のラグランジュ軌跡を学習するVAE（Variational Autoencoding the Lagrangian Trajectories of Particles in a Combustion System）</news:title>
   <news:publication_date>2026-07-11T09:33:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710576</loc>
  <lastmod>2026-07-11T08:42:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味ある多様体座標の自動解釈（Manifold Coordinates with Physical Meaning）</news:title>
   <news:publication_date>2026-07-11T08:42:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710574</loc>
  <lastmod>2026-07-11T08:42:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナップサック制約下の敵対的バンディット（Adversarial Bandits with Knapsacks）</news:title>
   <news:publication_date>2026-07-11T08:42:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710572</loc>
  <lastmod>2026-07-11T08:42:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習モデルの計算コスト予測（Predicting the Computational Cost of Deep Learning Models）</news:title>
   <news:publication_date>2026-07-11T08:42:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710570</loc>
  <lastmod>2026-07-11T08:41:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学フローに基づく行動認識分類器への敵対的攻撃（Adversarial Attacks for Optical Flow-Based Action Recognition Classifiers）</news:title>
   <news:publication_date>2026-07-11T08:41:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710568</loc>
  <lastmod>2026-07-11T08:41:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>巨大惑星の大気金属量と内部構造をつなぐ制約（CONNECTING GIANT PLANET ATMOSPHERE AND INTERIOR MODELING: CONSTRAINTS ON ATMOSPHERIC METAL ENRICHMENT）</news:title>
   <news:publication_date>2026-07-11T08:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710566</loc>
  <lastmod>2026-07-11T08:41:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PET画像における減衰と散乱の同時補正を画像空間で実現する深層畳み込みニューラルネットワーク（Joint Correction of Attenuation and Scatter Using Deep Convolutional Neural Networks (DCNN) for Time-of-Flight PET）</news:title>
   <news:publication_date>2026-07-11T08:41:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710564</loc>
  <lastmod>2026-07-11T08:40:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳用ニューラル・コプロセッサの可能性（Towards Neural Co-Processors for the Brain: Combining Decoding and Encoding in Brain-Computer Interfaces）</news:title>
   <news:publication_date>2026-07-11T08:40:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710562</loc>
  <lastmod>2026-07-11T07:49:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆動画のグループレベル感情認識における非体積保存ベースの融合（Non-Volume Preserving-based Fusion to Group-Level Emotion Recognition on Crowd Videos）</news:title>
   <news:publication_date>2026-07-11T07:49:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710560</loc>
  <lastmod>2026-07-11T07:49:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的最適化によるDC関数と非滑らかな非凸正則化の収束理論（Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence）</news:title>
   <news:publication_date>2026-07-11T07:49:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710558</loc>
  <lastmod>2026-07-11T07:48:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非造影CTによる腰仙部神経の自動セグメンテーションが変える臨床計画（Deep learning based automatic segmentation of lumbosacral nerves on non-contrast CT for radiographic evaluation: a pilot study）</news:title>
   <news:publication_date>2026-07-11T07:48:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710556</loc>
  <lastmod>2026-07-11T07:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られた学習データから新視点へ一般化する意味的部位検出（Semantic Part Detection via Matching: Learning to Generalize to Novel Viewpoints from Limited Training Data）</news:title>
   <news:publication_date>2026-07-11T07:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710554</loc>
  <lastmod>2026-07-11T07:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イメージング大気チェレンコフ望遠鏡におけるガンマ／ハドロン分離の深層学習比較（Gamma/Hadron Separation in Imaging Air Cherenkov Telescopes Using Deep Learning Libraries TensorFlow and PyTorch）</news:title>
   <news:publication_date>2026-07-11T07:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710552</loc>
  <lastmod>2026-07-11T07:47:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による疾病フェノタイピング：糖尿病事例研究（Disease phenotyping using deep learning: A diabetes case study）</news:title>
   <news:publication_date>2026-07-11T07:47:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710550</loc>
  <lastmod>2026-07-11T07:47:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルなしデータで学ぶ少数ショット分類の新手法（Unsupervised Meta-Learning for Few-Shot Image Classification）</news:title>
   <news:publication_date>2026-07-11T07:47:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710548</loc>
  <lastmod>2026-07-11T06:56:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CHILESによる銀河のH I形態と環境の観測（CHILES: H I morphology and galaxy environment at z=0.12 and z=0.17）</news:title>
   <news:publication_date>2026-07-11T06:56:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710546</loc>
  <lastmod>2026-07-11T06:56:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非代表的なビデオデータの問題と自動評価の提案（Unrepresentative video data: A review and evaluation）</news:title>
   <news:publication_date>2026-07-11T06:56:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710544</loc>
  <lastmod>2026-07-11T06:56:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SWAGアルゴリズムがもたらす学習の再設計（The SWAG Algorithm; a Mathematical Approach that Outperforms Traditional Deep Learning. Theory and Implementation）</news:title>
   <news:publication_date>2026-07-11T06:56:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710542</loc>
  <lastmod>2026-07-11T06:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一細胞RNA-seqからの確率的細胞分化ツリー再構築（Reconstructing probabilistic trees of cellular differentiation）</news:title>
   <news:publication_date>2026-07-11T06:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710540</loc>
  <lastmod>2026-07-11T06:55:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スラッグLyα星雲が明かす宇宙間ガスの姿（The large and small scale properties of the intergalactic gas in the Slug Lyα nebula revealed by MUSE He ii emission observations）</news:title>
   <news:publication_date>2026-07-11T06:55:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710538</loc>
  <lastmod>2026-07-11T06:55:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散二重警戒ファジー適応共鳴理論（Distributed dual vigilance fuzzy adaptive resonance theory）</news:title>
   <news:publication_date>2026-07-11T06:55:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710536</loc>
  <lastmod>2026-07-11T06:55:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラ適応型の色補正を少数ショットのメタ学習として定式化する（Formulating Camera-Adaptive Color Constancy as a Few-shot Meta-Learning Problem）</news:title>
   <news:publication_date>2026-07-11T06:55:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710534</loc>
  <lastmod>2026-07-11T06:03:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOSDEF調査が示す高赤方偏移銀河の光学輝線等価幅の進化（THE MOSDEF SURVEY: SIGNIFICANT EVOLUTION IN THE REST-FRAME OPTICAL EMISSION LINE EQUIVALENT WIDTHS OF STAR-FORMING GALAXIES AT z = 1.4–3.8）</news:title>
   <news:publication_date>2026-07-11T06:03:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710532</loc>
  <lastmod>2026-07-11T06:03:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BPT図の「見逃し」を解く：星形成領域に現れるX線AGNの実態（Crossing the Line: Active Galactic Nuclei in the Star-forming region of the BPT Diagram）</news:title>
   <news:publication_date>2026-07-11T06:03:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710530</loc>
  <lastmod>2026-07-11T06:02:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音色強化型マルチモーダル音楽スタイル転送（Play as You Like: Timbre-enhanced Multi-modal Music Style Transfer）</news:title>
   <news:publication_date>2026-07-11T06:02:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710528</loc>
  <lastmod>2026-07-11T06:01:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CAPNetによる2D監視下の単一画像からの3D点群再構成（CAPNet: Continuous Approximation Projection For 3D Point Cloud Reconstruction Using 2D Supervision）</news:title>
   <news:publication_date>2026-07-11T06:01:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710526</loc>
  <lastmod>2026-07-11T06:01:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分畳み込みに基づくパディングの実践的解説（Partial Convolution based Padding）</news:title>
   <news:publication_date>2026-07-11T06:01:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710524</loc>
  <lastmod>2026-07-11T06:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全な属性付きネットワークの埋め込み（Attributed Network Embedding for Incomplete Attributed Networks）</news:title>
   <news:publication_date>2026-07-11T06:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710522</loc>
  <lastmod>2026-07-11T06:01:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SegETによる電子断層法画像の細胞構造セグメンテーション（SegET: Deep Neural Network with Rich Contextual Features for Cellular Structures Segmentation in Electron Tomography Image）</news:title>
   <news:publication_date>2026-07-11T06:01:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710520</loc>
  <lastmod>2026-07-11T05:10:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子動力学における特徴選択の変革（Variational Selection of Features for Molecular Kinetics）</news:title>
   <news:publication_date>2026-07-11T05:10:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710518</loc>
  <lastmod>2026-07-11T05:09:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話タスク横断の少数例一般化（Few-Shot Generalization Across Dialogue Tasks）</news:title>
   <news:publication_date>2026-07-11T05:09:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710516</loc>
  <lastmod>2026-07-11T05:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル確率的モータープリミティブによるヒューマノイド制御（NEURAL PROBABILISTIC MOTOR PRIMITIVES FOR HUMANOID CONTROL）</news:title>
   <news:publication_date>2026-07-11T05:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710514</loc>
  <lastmod>2026-07-11T05:09:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習における経験再生の力（Experience Replay for Continual Learning）</news:title>
   <news:publication_date>2026-07-11T05:09:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710512</loc>
  <lastmod>2026-07-11T05:08:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表面構造探索のためのSAMPLE法（SAMPLE: Surface Structure Search Enabled by Coarse Graining and Statistical Learning）</news:title>
   <news:publication_date>2026-07-11T05:08:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710510</loc>
  <lastmod>2026-07-11T05:08:25Z</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間に共通する表現ジオメトリ（Shared Representational Geometry Across Neural Networks）</news:title>
   <news:publication_date>2026-07-11T05:08:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710508</loc>
  <lastmod>2026-07-11T05:08:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像と文の多層共通意味空間によるフレーズ位置推定（Multi-level Multimodal Common Semantic Space for Image-Phrase Grounding）</news:title>
   <news:publication_date>2026-07-11T05:08:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710506</loc>
  <lastmod>2026-07-11T04:17:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D点群分類のためのグラフ畳み込みネットワーク（A GRAPH-CNN FOR 3D POINT CLOUD CLASSIFICATION）</news:title>
   <news:publication_date>2026-07-11T04:17:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710504</loc>
  <lastmod>2026-07-11T04:16:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習における人種カテゴリの取り扱い（Racial categories in machine learning）</news:title>
   <news:publication_date>2026-07-11T04:16:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710502</loc>
  <lastmod>2026-07-11T04:16:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さな顔に学習を集中させる頑健な顔検出（Robust Face Detection via Learning Small Faces on Hard Images）</news:title>
   <news:publication_date>2026-07-11T04:16:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710500</loc>
  <lastmod>2026-07-11T04:15:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WaveletNet：エッジ向けに計算量を対数スケールで削減する畳み込みネットワーク（WaveletNet: Logarithmic Scale Efficient Convolutional Neural Networks for Edge Devices）</news:title>
   <news:publication_date>2026-07-11T04:15:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710498</loc>
  <lastmod>2026-07-11T04:15:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有向グラフにおける調和解析と応用（Harmonic analysis on directed graphs and applications: From Fourier analysis to Wavelets）</news:title>
   <news:publication_date>2026-07-11T04:15:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710496</loc>
  <lastmod>2026-07-11T04:15:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>閾値構造を利用したオンライン学習アルゴリズム（A Structure-aware Online Learning Algorithm for Markov Decision Processes）</news:title>
   <news:publication_date>2026-07-11T04:15:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710494</loc>
  <lastmod>2026-07-11T04:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非平滑制約を伴うBasis Pursuit Denoise（Basis Pursuit Denoise with Nonsmooth Constraints）</news:title>
   <news:publication_date>2026-07-11T04:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710492</loc>
  <lastmod>2026-07-11T03:24:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差出力フィードバックを備えたリッジ多項式ニューラルネットワーク（Multi-step Time Series Forecasting Using Ridge Polynomial Neural Network with Error–Output Feed-backs）</news:title>
   <news:publication_date>2026-07-11T03:24:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710490</loc>
  <lastmod>2026-07-11T03:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河まわりの低表面光度潮汐特徴をCNNで同定する（Identification of Low Surface Brightness Tidal Features in Galaxies Using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-11T03:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710488</loc>
  <lastmod>2026-07-11T03:23:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カルマンフィルタの正体解明（Kalman filter demystified: from intuition to probabilistic graphical model to real case in financial markets）</news:title>
   <news:publication_date>2026-07-11T03:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710486</loc>
  <lastmod>2026-07-11T03:23:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間最適速度制御のための深層強化学習（Deep Reinforcement Learning for Time Optimal Velocity Control using Prior Knowledge）</news:title>
   <news:publication_date>2026-07-11T03:23:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710484</loc>
  <lastmod>2026-07-11T03:22:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>洞窟を出るための手法：2D画像から学ぶ3D形状復元（Escaping Plato’s Cave: 3D Shape From Adversarial Rendering）</news:title>
   <news:publication_date>2026-07-11T03:22:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710482</loc>
  <lastmod>2026-07-11T03:22:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド動画物体セグメンテーションの生成的外観モデル（A Generative Appearance Model for End-to-end Video Object Segmentation）</news:title>
   <news:publication_date>2026-07-11T03:22:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710480</loc>
  <lastmod>2026-07-11T03:22:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱ラベル付きバイグからのクラスタ学習によるデジタル病理解析（Cluster-Based Learning from Weakly Labeled Bags in Digital Pathology）</news:title>
   <news:publication_date>2026-07-11T03:22:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710478</loc>
  <lastmod>2026-07-11T02:31:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通信効率化された端末内学習：Federated DistillationとAugmentationの実際（Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data）</news:title>
   <news:publication_date>2026-07-11T02:31:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710476</loc>
  <lastmod>2026-07-11T02:31:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Predictive Filter Flowによる画像再構成（Image Reconstruction with Predictive Filter Flow）</news:title>
   <news:publication_date>2026-07-11T02:31:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710474</loc>
  <lastmod>2026-07-11T02:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語・文字レベルのマルチタスク学習が音声認識の帰納的バイアスに与える影響（On the Inductive Bias of Word-Character-Level Multi-Task Learning for Speech Recognition）</news:title>
   <news:publication_date>2026-07-11T02:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710472</loc>
  <lastmod>2026-07-11T02:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電波継続観測データからパルサー候補を見つける人工ニューラルネットワーク（Artificial neural networks for selection of pulsar candidates from the radio continuum surveys）</news:title>
   <news:publication_date>2026-07-11T02:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710470</loc>
  <lastmod>2026-07-11T02:29:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算負荷の小さい機械学習モデルを用いた海洋波予測のエンサンブル集約（Ensemble model aggregation using a computationally lightweight machine-learning model to forecast ocean waves）</news:title>
   <news:publication_date>2026-07-11T02:29:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710468</loc>
  <lastmod>2026-07-11T02:29:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>数値積分誤差の較正を改善する：シグマポイントフィルタにおけるBayes–Sard四分法の応用（Improved Calibration of Numerical Integration Error in Sigma-Point Filters）</news:title>
   <news:publication_date>2026-07-11T02:29:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710466</loc>
  <lastmod>2026-07-11T02:29:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>磁気共鳴フィンガープリンティングにおける次元の呪いの回避（Circumventing the Curse of Dimensionality in Magnetic Resonance Fingerprinting through a Deep Learning Approach）</news:title>
   <news:publication_date>2026-07-11T02:29:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710464</loc>
  <lastmod>2026-07-11T01:38:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>追跡システムを「もの化」する視点――Thinging Machineによる図式化の提案（Tracking Systems as Thinging Machine）</news:title>
   <news:publication_date>2026-07-11T01:38:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710462</loc>
  <lastmod>2026-07-11T01:37:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオゲームにおける顧客生涯価値の予測（Customer Lifetime Value in Video Games Using Deep Learning and Parametric Models）</news:title>
   <news:publication_date>2026-07-11T01:37:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710460</loc>
  <lastmod>2026-07-11T01:37:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>姿勢誘導による人物画像生成のための座標ベーステクスチャ補間（Coordinate-based Texture Inpainting for Pose-Guided Human Image Generation）</news:title>
   <news:publication_date>2026-07-11T01:37:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710458</loc>
  <lastmod>2026-07-11T01:37:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置ごとに最適な専門家をつなぐGIRNet（GIRNet: Interleaved Multi-Task Recurrent State Sequence Models）</news:title>
   <news:publication_date>2026-07-11T01:37:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710456</loc>
  <lastmod>2026-07-11T01:37:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>厚い生体組織での回折限界軸方向走査を可能にする収差補正アダプティブレンズ（Diffraction-limited axial scanning in thick biological tissue employing an aberration correcting adaptive lens）</news:title>
   <news:publication_date>2026-07-11T01:37:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710454</loc>
  <lastmod>2026-07-11T01:36:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軌道に基づく学習が示す効率化の実像（Trajectory-based Learning for Ball-in-Maze Games）</news:title>
   <news:publication_date>2026-07-11T01:36:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710452</loc>
  <lastmod>2026-07-11T01:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のキーポイント推定に基づくニューラル手話翻訳（Neural Sign Language Translation based on Human Keypoint Estimation）</news:title>
   <news:publication_date>2026-07-11T01:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710450</loc>
  <lastmod>2026-07-11T00:45:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共同対角化を高速化する準ニュートン法の提案（Beyond Pham’s algorithm for joint diagonalization）</news:title>
   <news:publication_date>2026-07-11T00:45:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710448</loc>
  <lastmod>2026-07-11T00:44:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Collective Matrix Factorizationの要点と実務応用（Deep Collective Matrix Factorization for Augmented Multi-View Learning）</news:title>
   <news:publication_date>2026-07-11T00:44:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710446</loc>
  <lastmod>2026-07-11T00:44:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ESPNetv2: 軽量で電力効率の高い汎用畳み込みニューラルネットワーク（ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network）</news:title>
   <news:publication_date>2026-07-11T00:44:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710444</loc>
  <lastmod>2026-07-11T00:43:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短時間12誘導心電図に対する深層畳み込みネットワークによる自動診断（Automatic Diagnosis of Short-Duration 12-Lead ECG using a Deep Convolutional Network）</news:title>
   <news:publication_date>2026-07-11T00:43:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710442</loc>
  <lastmod>2026-07-11T00:43:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MeshNetによるメッシュベースの3D形状表現（MeshNet: Mesh Neural Network for 3D Shape Representation）</news:title>
   <news:publication_date>2026-07-11T00:43:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710440</loc>
  <lastmod>2026-07-11T00:43:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MeSH概念で拡張した単語埋め込み（The MeSH-gram Neural Network Model: Extending Word Embedding Vectors with MeSH Concepts for UMLS Semantic Similarity and Relatedness in the Biomedical Domain）</news:title>
   <news:publication_date>2026-07-11T00:43:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710438</loc>
  <lastmod>2026-07-11T00:42:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり学習を拡点にしたBidirectional GANの改良（Semi-supervised learning with Bidirectional GANs）</news:title>
   <news:publication_date>2026-07-11T00:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710436</loc>
  <lastmod>2026-07-10T23:52:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンラベルデータから貧困層を特定するクラスタリング比較（A comparison of cluster algorithms as applied to unsupervised surveys）</news:title>
   <news:publication_date>2026-07-10T23:52:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710434</loc>
  <lastmod>2026-07-10T23:51:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトラル特徴変換による人物再識別（Spectral Feature Transformation for Person Re-identiﬁcation）</news:title>
   <news:publication_date>2026-07-10T23:51:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710432</loc>
  <lastmod>2026-07-10T23:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合マルチンゲールの再考（Mixture Martingales Revisited）</news:title>
   <news:publication_date>2026-07-10T23:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710430</loc>
  <lastmod>2026-07-10T23:51:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散電子カルテに対するFederated‑Autonomous Deep Learning（FADL: Federated‑Autonomous Deep Learning for Distributed Electronic Health Record）</news:title>
   <news:publication_date>2026-07-10T23:51:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710428</loc>
  <lastmod>2026-07-10T23:50:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepMappingによる無監督点群マッピングの要点解説（DeepMapping: Unsupervised Map Estimation From Multiple Point Clouds）</news:title>
   <news:publication_date>2026-07-10T23:50:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710426</loc>
  <lastmod>2026-07-10T23:50:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声感情認識に対する敵対的攻撃と防御—GANによる堅牢化の可能性（Adversarial Machine Learning And Speech Emotion Recognition: Utilizing Generative Adversarial Networks For Robustness）</news:title>
   <news:publication_date>2026-07-10T23:50:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710424</loc>
  <lastmod>2026-07-10T23:50:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>稀少クラスの医用画像を増やすGeneral-to-detailed GAN（General-to-Detailed GAN for Infrequent Class Medical Images）</news:title>
   <news:publication_date>2026-07-10T23:50:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710422</loc>
  <lastmod>2026-07-10T22:59:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNベースの知覚システムの形式的検証（Formal Verification of CNN-based Perception Systems）</news:title>
   <news:publication_date>2026-07-10T22:59:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710420</loc>
  <lastmod>2026-07-10T22:50:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRAMベースの確率的ニューロンで構成する確率推論ネットワーク（Composable Probabilistic Inference Networks Using MRAM-based Stochastic Neurons）</news:title>
   <news:publication_date>2026-07-10T22:50:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710418</loc>
  <lastmod>2026-07-10T22:50:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画回転予測による自己教師付き時空間特徴学習（Self-Supervised Spatiotemporal Feature Learning via Video Rotation Prediction）</news:title>
   <news:publication_date>2026-07-10T22:50:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710416</loc>
  <lastmod>2026-07-10T22:49:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチドキュメント読解の深層カスケードモデル（A Deep Cascade Model for Multi-Document Reading Comprehension）</news:title>
   <news:publication_date>2026-07-10T22:49:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710414</loc>
  <lastmod>2026-07-10T22:49:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散推定と推論のための一次ニュートン型推定器（First-order Newton-type Estimator for Distributed Estimation and Inference）</news:title>
   <news:publication_date>2026-07-10T22:49:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710412</loc>
  <lastmod>2026-07-10T22:48:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリック識別報酬による教師なし制御（Unsupervised Control through Non-Parametric Discriminative Rewards）</news:title>
   <news:publication_date>2026-07-10T22:48:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710410</loc>
  <lastmod>2026-07-10T22:48:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なしマルチモーダル機械翻訳（Unsupervised Multi-modal Neural Machine Translation）</news:title>
   <news:publication_date>2026-07-10T22:48:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710408</loc>
  <lastmod>2026-07-10T21:57:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続電子顕微鏡からの堅牢な神経回路再構築（Robust neural circuit reconstruction from serial electron microscopy with convolutional recurrent networks）</news:title>
   <news:publication_date>2026-07-10T21:57:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710406</loc>
  <lastmod>2026-07-10T21:57:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MH-GANによる生成サンプルの精度改善（Metropolis-Hastings Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-10T21:57:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710404</loc>
  <lastmod>2026-07-10T21:57:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチラベル分類の探索空間を系統的に定義する（STUDYING THE SEARCH SPACE OF MULTI-LABEL CLASSIFICATION ALGORITHMS）</news:title>
   <news:publication_date>2026-07-10T21:57:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710402</loc>
  <lastmod>2026-07-10T21:56:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別患者生存分布の構築と評価に関する有効な方法（Effective Ways to Build and Evaluate Individual Survival Distributions）</news:title>
   <news:publication_date>2026-07-10T21:56:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710400</loc>
  <lastmod>2026-07-10T21:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次元削減に基づくデータ探索のための視覚的インタラクションフレームワーク (A Visual Interaction Framework for Dimensionality Reduction Based Data Exploration)</news:title>
   <news:publication_date>2026-07-10T21:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710398</loc>
  <lastmod>2026-07-10T21:55:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的頑健な中国剰余定理による複数数値の復元（Statistical Robust Chinese Remainder Theorem for Multiple Numbers: Wrapped Gaussian Mixture Model）</news:title>
   <news:publication_date>2026-07-10T21:55:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710396</loc>
  <lastmod>2026-07-10T21:55:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次元粒子群最適化による非線形系の構造選択（Two-Dimensional (2D) Particle Swarms for Structure Selection of Nonlinear Systems）</news:title>
   <news:publication_date>2026-07-10T21:55:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710394</loc>
  <lastmod>2026-07-10T21:03:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転における深層強化学習（Deep Reinforcement Learning for Autonomous Driving）</news:title>
   <news:publication_date>2026-07-10T21:03:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710392</loc>
  <lastmod>2026-07-10T21:03:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CyLKs: ラベル無しでLucas–Kanadeを強化する手法（CyLKs: Unsupervised Cycle Lucas-Kanade Network for Landmark Tracking）</news:title>
   <news:publication_date>2026-07-10T21:03:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710390</loc>
  <lastmod>2026-07-10T21:03:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による乱流の超解像再構成（Super-resolution reconstruction of turbulent flows with machine learning）</news:title>
   <news:publication_date>2026-07-10T21:03:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710388</loc>
  <lastmod>2026-07-10T21:02:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Regionletsによる汎用物体検出の改良 (Deep Regionlets: Blended Representation and Deep Learning for Generic Object Detection)</news:title>
   <news:publication_date>2026-07-10T21:02:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710386</loc>
  <lastmod>2026-07-10T21:02:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標指向の視覚ナビゲーションにおけるHAUSRの提示（Target Driven Visual Navigation with Hybrid Asynchronous Universal Successor Representations）</news:title>
   <news:publication_date>2026-07-10T21:02:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710384</loc>
  <lastmod>2026-07-10T21:02:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モチーフを使って異種情報ネットワークの意図に沿ったクラスタを導く手法（User-Guided Clustering in Heterogeneous Information Networks via Motif-Based Comprehensive Transcription）</news:title>
   <news:publication_date>2026-07-10T21:02:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710382</loc>
  <lastmod>2026-07-10T21:01:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>帰結を可視化する化学モデルの盲点（Using Attribution to Decode Dataset Bias in Neural Network Models for Chemistry）</news:title>
   <news:publication_date>2026-07-10T21:01:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710380</loc>
  <lastmod>2026-07-10T20:10:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wave-U-Netによる音声強調の改善（Improved Speech Enhancement with the Wave-U-Net）</news:title>
   <news:publication_date>2026-07-10T20:10:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710378</loc>
  <lastmod>2026-07-10T20:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり学習で泡室検出器の粒子識別を作る（Developing a Bubble Chamber Particle Discriminator Using Semi-Supervised Learning）</news:title>
   <news:publication_date>2026-07-10T20:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710376</loc>
  <lastmod>2026-07-10T20:10:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユニバーサル敵対的摂動とその耐性訓練（Universal Adversarial Training）</news:title>
   <news:publication_date>2026-07-10T20:10:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710374</loc>
  <lastmod>2026-07-10T20:09:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索を速める「再起動分布」の活用（Exploring Restart Distributions）</news:title>
   <news:publication_date>2026-07-10T20:09:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710372</loc>
  <lastmod>2026-07-10T20:09:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平性ソリューションの前提を問い直す（Questioning the assumptions behind fairness solutions）</news:title>
   <news:publication_date>2026-07-10T20:09:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710370</loc>
  <lastmod>2026-07-10T20:08:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラグ相関に基づく深層学習による方向性トレンド変化予測（Lagged correlation-based deep learning for directional trend change prediction in financial time series）</news:title>
   <news:publication_date>2026-07-10T20:08:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710368</loc>
  <lastmod>2026-07-10T20:08:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きGANにおけるクラス内変動の弱教師あり制御（Taking Control of Intra-class Variation in Conditional GANs Under Weak Supervision）</news:title>
   <news:publication_date>2026-07-10T20:08:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710366</loc>
  <lastmod>2026-07-10T19:17:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表情類似性のためのコンパクト表現（A Compact Embedding for Facial Expression Similarity）</news:title>
   <news:publication_date>2026-07-10T19:17:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710364</loc>
  <lastmod>2026-07-10T19:16:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ぶれ（モーションブラー）を合成する学習手法（Learning to Synthesize Motion Blur）</news:title>
   <news:publication_date>2026-07-10T19:16:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710362</loc>
  <lastmod>2026-07-10T19:16:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチベースの段階的3D点群アップサンプリング (Patch-based Progressive 3D Point Set Upsampling)</news:title>
   <news:publication_date>2026-07-10T19:16:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710360</loc>
  <lastmod>2026-07-10T19:15:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>走行は安全か？ドライブアビリティ評価の概観（Is it Safe to Drive? An Overview of Factors, Challenges, and Datasets for Driveability Assessment in Autonomous Driving）</news:title>
   <news:publication_date>2026-07-10T19:15:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710358</loc>
  <lastmod>2026-07-10T19:15:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり敵対的生成ネットワークを回帰へ一般化する（Generalizing semi-supervised generative adversarial networks to regression using feature contrasting）</news:title>
   <news:publication_date>2026-07-10T19:15:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710356</loc>
  <lastmod>2026-07-10T19:15:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表形式データの合成に挑むTGAN（Synthesizing Tabular Data using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-10T19:15:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710354</loc>
  <lastmod>2026-07-10T19:15:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変長ゲームログからのプレイヤー戦略クラスタリング（Clustering Player Strategies from Variable-Length Game Logs in Dominion）</news:title>
   <news:publication_date>2026-07-10T19:15:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710352</loc>
  <lastmod>2026-07-10T18:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速セマンティックセグメンテーションのためのShelfNet（ShelfNet for Fast Semantic Segmentation）</news:title>
   <news:publication_date>2026-07-10T18:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710350</loc>
  <lastmod>2026-07-10T18:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習によるエネルギーハーベストセンサの設定拡張（Scaling Configuration of Energy Harvesting Sensors with Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-10T18:22:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710348</loc>
  <lastmod>2026-07-10T18:22:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー監督による登録学習（Multiview Supervision By Registration）</news:title>
   <news:publication_date>2026-07-10T18:22:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710346</loc>
  <lastmod>2026-07-10T18:22:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>印刷文字画像の構成的モデルによる欠損語認識（A Compositional Textual Model for Recognition of Imperfect Word Images）</news:title>
   <news:publication_date>2026-07-10T18:22:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710344</loc>
  <lastmod>2026-07-10T18:22:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepPos: CSIを用いた屋内測位における深層教師付きオートエンコーダの提案 (DeepPos: Deep Supervised Autoencoder Network for CSI Based Indoor Localization)</news:title>
   <news:publication_date>2026-07-10T18:22:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710342</loc>
  <lastmod>2026-07-10T18:21:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現実のトポロジーを持つ非連結交差点における分散型信号制御（Distributed traffic light control at uncoupled intersections with real-world topology by deep reinforcement learning）</news:title>
   <news:publication_date>2026-07-10T18:21:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710340</loc>
  <lastmod>2026-07-10T18:21:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子最適化のための文法と強化学習 (Grammars and Reinforcement Learning for Molecule Optimization)</news:title>
   <news:publication_date>2026-07-10T18:21:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710338</loc>
  <lastmod>2026-07-10T17:30:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体局在化タスクにおける不確実性の較正（Calibrating Uncertainties in Object Localization Task）</news:title>
   <news:publication_date>2026-07-10T17:30:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710336</loc>
  <lastmod>2026-07-10T17:21:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DLHub: 科学向けモデルとデータの公開・配信基盤（DLHub: Model and Data Serving for Science）</news:title>
   <news:publication_date>2026-07-10T17:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710334</loc>
  <lastmod>2026-07-10T17:21:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エントロピーが政策最適化に与える影響（Understanding the Impact of Entropy on Policy Optimization）</news:title>
   <news:publication_date>2026-07-10T17:21:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710332</loc>
  <lastmod>2026-07-10T17:21:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助回転損失を用いた自己教師付きGAN（Self-Supervised GANs via Auxiliary Rotation Loss）</news:title>
   <news:publication_date>2026-07-10T17:21:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710330</loc>
  <lastmod>2026-07-10T17:20:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分割変分推論による統一フレームワーク（Partitioned Variational Inference: A unified framework encompassing federated and continual learning）</news:title>
   <news:publication_date>2026-07-10T17:20:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710328</loc>
  <lastmod>2026-07-10T17:19:50Z</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不確実性を実務で扱う——Bayesian Neural Network Ensembles（Bayesian Neural Network Ensembles）</news:title>
   <news:publication_date>2026-07-10T17:19:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710326</loc>
  <lastmod>2026-07-10T17:19:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的で傾いた3D点群を整える反復的変換学習（Iterative Transformer Network for 3D Point Cloud）</news:title>
   <news:publication_date>2026-07-10T17:19:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710324</loc>
  <lastmod>2026-07-10T16:28:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力依存の動的フィルタ選択を行うGaterNet（You Look Twice: GaterNet for Dynamic Filter Selection in CNNs）</news:title>
   <news:publication_date>2026-07-10T16:28:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710322</loc>
  <lastmod>2026-07-10T16:26:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限でない深さのアフィンDeligne–Lusztig多様体が拓く局所対応の幾何学（AFFINE DELIGNE–LUSZTIG VARIETIES AT INFINITE LEVEL）</news:title>
   <news:publication_date>2026-07-10T16:26:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710320</loc>
  <lastmod>2026-07-10T16:26:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重い電子系における相互情報量の示すもの（Mutual information in heavy-fermion systems）</news:title>
   <news:publication_date>2026-07-10T16:26:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710318</loc>
  <lastmod>2026-07-10T16:25:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deformable ConvNets v2 が変えた物体検出の実務的インパクト（Deformable ConvNets v2: More Deformable, Better Results）</news:title>
   <news:publication_date>2026-07-10T16:25:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710316</loc>
  <lastmod>2026-07-10T16:25:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Scan2CADによるCADモデルとRGB-Dスキャンの位置合わせ（Scan2CAD: Learning CAD Model Alignment in RGB-D Scans）</news:title>
   <news:publication_date>2026-07-10T16:25:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710314</loc>
  <lastmod>2026-07-10T16:25:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティクスを組み合わせた集団健康リスク解析（Semantically-aware population health risk analyses）</news:title>
   <news:publication_date>2026-07-10T16:25:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710312</loc>
  <lastmod>2026-07-10T16:25:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ハードウェア上で解析的勾配を評価する手法（Evaluating analytic gradients on quantum hardware）</news:title>
   <news:publication_date>2026-07-10T16:25:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710310</loc>
  <lastmod>2026-07-10T15:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルノイズに強い条件付き生成モデルの作り方（Label-Noise Robust Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-10T15:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710308</loc>
  <lastmod>2026-07-10T15:33:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス重複を扱う画像生成の新展開（Class-Distinct and Class-Mutual Image Generation with GANs）</news:title>
   <news:publication_date>2026-07-10T15:33:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710306</loc>
  <lastmod>2026-07-10T15:33:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度物体生成のための階層的非教師あり分解 FineGAN（FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery）</news:title>
   <news:publication_date>2026-07-10T15:33:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710304</loc>
  <lastmod>2026-07-10T15:32:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル局所記述子の理解と改善（Understanding and Improving Kernel Local Descriptors）</news:title>
   <news:publication_date>2026-07-10T15:32:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710302</loc>
  <lastmod>2026-07-10T15:31:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムニューラルネットにおける結び目の性質 (Knots in random neural networks)</news:title>
   <news:publication_date>2026-07-10T15:31:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710300</loc>
  <lastmod>2026-07-10T15:31:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適なプライベート検定の構造（The Structure of Optimal Private Tests for Simple Hypotheses）</news:title>
   <news:publication_date>2026-07-10T15:31:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710298</loc>
  <lastmod>2026-07-10T15:31:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不明な保護クラス下での公平性評価の盲点（Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved）</news:title>
   <news:publication_date>2026-07-10T15:31:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710296</loc>
  <lastmod>2026-07-10T14:39:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抗生物質耐性分類での信頼できる不確実性推定（Reliable uncertainty estimate for antibiotic resistance classification with Stochastic Gradient Langevin Dynamics）</news:title>
   <news:publication_date>2026-07-10T14:39:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710294</loc>
  <lastmod>2026-07-10T14:39:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散同期SGDアルゴリズムのための効率的なデータ通信（MG-WFBP: Efficient Data Communication for Distributed Synchronous SGD Algorithms）</news:title>
   <news:publication_date>2026-07-10T14:39:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710292</loc>
  <lastmod>2026-07-10T14:38:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ethereumコミュニティの感情解析による詐欺リスク検出（SOC: hunting the underground inside story of the ethereum Social-network Opinion and Comment）</news:title>
   <news:publication_date>2026-07-10T14:38:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710290</loc>
  <lastmod>2026-07-10T14:38:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>症例ベース検索のための概念中心ハイパーテキスト手法（A Concept-Centered Hypertext Approach to Case-Based Retrieval）</news:title>
   <news:publication_date>2026-07-10T14:38:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710288</loc>
  <lastmod>2026-07-10T14:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LEASGDによる分散学習の効率化と差分プライバシーの両立（LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning）</news:title>
   <news:publication_date>2026-07-10T14:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710286</loc>
  <lastmod>2026-07-10T14:37:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による生RAW向け画像の逆処理（Unprocessing Images for Learned Raw Denoising）</news:title>
   <news:publication_date>2026-07-10T14:37:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710284</loc>
  <lastmod>2026-07-10T14:36:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河系球状星団における外側領域のRR Lyrae星探索（Search for Extra-Tidal RR Lyrae Stars in Milky Way Globular Clusters From Gaia DR2）</news:title>
   <news:publication_date>2026-07-10T14:36:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710282</loc>
  <lastmod>2026-07-10T13:45:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ的グラフ畳み込みニューラルネットワークによる半教師付き分類（Bayesian graph convolutional neural networks for semi-supervised classification）</news:title>
   <news:publication_date>2026-07-10T13:45:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710280</loc>
  <lastmod>2026-07-10T13:45:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双線形パラメータ化による微分可能なランク正則化（Bilinear Parameterization For Differentiable Rank-Regularization）</news:title>
   <news:publication_date>2026-07-10T13:45:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710278</loc>
  <lastmod>2026-07-10T13:45:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生波形から学ぶ構音障害検出（LEARNING TO DETECT DYSARTHRIA FROM RAW SPEECH）</news:title>
   <news:publication_date>2026-07-10T13:45:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710276</loc>
  <lastmod>2026-07-10T13:44:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画における自動顔年齢推移（Automatic Face Aging in Videos via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-10T13:44:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710274</loc>
  <lastmod>2026-07-10T13:43:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モビフェイス：モバイル向け軽量顔認識モデル（MobiFace: A Lightweight Deep Learning Face Recognition on Mobile Devices）</news:title>
   <news:publication_date>2026-07-10T13:43:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710272</loc>
  <lastmod>2026-07-10T13:43:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GAN訓練は継続学習問題であるという視点の再定義（Generative Adversarial Network Training Is a Continual Learning Problem）</news:title>
   <news:publication_date>2026-07-10T13:43:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710270</loc>
  <lastmod>2026-07-10T13:43:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非結晶シリコンの原子構造と原子エネルギーの定量化（Quantifying Chemical Structure and Atomic Energies in Amorphous Silicon Networks）</news:title>
   <news:publication_date>2026-07-10T13:43:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710268</loc>
  <lastmod>2026-07-10T12:52:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮動画における高速物体検出（Fast Object Detection in Compressed Video）</news:title>
   <news:publication_date>2026-07-10T12:52:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710266</loc>
  <lastmod>2026-07-10T12:51:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現の代替性が示すニューラル表現の本質（Understanding the Importance of Single Directions via Representative Substitution）</news:title>
   <news:publication_date>2026-07-10T12:51:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710264</loc>
  <lastmod>2026-07-10T12:51:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合システムにおける状態表現学習とマルチモーダルデータ（Learning State Representations in Complex Systems with Multimodal Data）</news:title>
   <news:publication_date>2026-07-10T12:51:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710262</loc>
  <lastmod>2026-07-10T12:50:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dense xUnitネットワークの効率化（Dense xUnit Networks）</news:title>
   <news:publication_date>2026-07-10T12:50:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710260</loc>
  <lastmod>2026-07-10T12:50:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>姿勢依存の操作性能伝達（Geometry-aware Manipulability Transfer）</news:title>
   <news:publication_date>2026-07-10T12:50:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710258</loc>
  <lastmod>2026-07-10T12:50:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬が減衰するバンディット問題は確率的バンディットより難しくない（Rotting bandits are not harder than stochastic ones）</news:title>
   <news:publication_date>2026-07-10T12:50:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710256</loc>
  <lastmod>2026-07-10T12:50:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数物体追跡における露出バイアスと評価関数不整合の排除（Eliminating Exposure Bias and Loss-Evaluation Mismatch in Multiple Object Tracking）</news:title>
   <news:publication_date>2026-07-10T12:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710254</loc>
  <lastmod>2026-07-10T11:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Noise2Voidによる単一ノイズ画像からの学習が変えた点（Noise2Void - Learning Denoising from Single Noisy Images）</news:title>
   <news:publication_date>2026-07-10T11:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710252</loc>
  <lastmod>2026-07-10T11:48:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速かつ高精度な3D衣服ドレーピング手法の実務的意義（GarNet: A Two-Stream Network for Fast and Accurate 3D Cloth Draping）</news:title>
   <news:publication_date>2026-07-10T11:48:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710250</loc>
  <lastmod>2026-07-10T11:47:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル非定常スペクトルカーネル（Neural Non-Stationary Spectral Kernel）</news:title>
   <news:publication_date>2026-07-10T11:47:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710248</loc>
  <lastmod>2026-07-10T11:46:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>将来の地上観測でフェルミバブルの超高エネルギーガンマ線をどう制約するか（Constraints on very high energy gamma-ray emission from the Fermi Bubbles with future ground-based experiments）</news:title>
   <news:publication_date>2026-07-10T11:46:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710246</loc>
  <lastmod>2026-07-10T11:46:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラジル最高裁の文書分類にBi-LSTMを使う研究（Document classification using a Bi-LSTM to unclog Brazil’s supreme court）</news:title>
   <news:publication_date>2026-07-10T11:46:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710244</loc>
  <lastmod>2026-07-10T11:46:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンショット・マルチモーダル検索の実務解説（One-Shot Item Search with Multimodal Data）</news:title>
   <news:publication_date>2026-07-10T11:46:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710242</loc>
  <lastmod>2026-07-10T11:45:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視線を超えて：ハンドセグメンテーションのためのゲーテッド再帰アーキテクチャ（Beyond One Glance: Gated Recurrent Architecture for Hand Segmentation）</news:title>
   <news:publication_date>2026-07-10T11:45:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710240</loc>
  <lastmod>2026-07-10T10:54:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベータ分布に基づくドリフト検出法（Beta Distribution Drift Detection for Adaptive Classifiers）</news:title>
   <news:publication_date>2026-07-10T10:54:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710238</loc>
  <lastmod>2026-07-10T10:44:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数基地局を同時に学習して最適化する手法（Kernel-based Multi-Task Contextual Bandits in Cellular Network Configuration）</news:title>
   <news:publication_date>2026-07-10T10:44:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710236</loc>
  <lastmod>2026-07-10T10:43:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフライン手書き文字認識における2D-LSTMの存否（Are 2D-LSTM really dead for offline text recognition?）</news:title>
   <news:publication_date>2026-07-10T10:43:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710234</loc>
  <lastmod>2026-07-10T10:43:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UnDEMoN 2.0がもたらす単眼深度推定の実用性向上（UnDEMoN 2.0: Improved Depth and Ego Motion Estimation through Deep Image Sampling）</news:title>
   <news:publication_date>2026-07-10T10:43:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710232</loc>
  <lastmod>2026-07-10T10:43:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二面式点字画像データセットDSBIと点字点検出評価（Double-Sided Braille Image Dataset and Algorithm Evaluation for Braille Dots Detection）</news:title>
   <news:publication_date>2026-07-10T10:43:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710230</loc>
  <lastmod>2026-07-10T10:43:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>落下する細長い微小スイマーの泳法を強化学習で学ぶ（Swimming strategy of settling elongated microswimmers by reinforcement learning）</news:title>
   <news:publication_date>2026-07-10T10:43:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710228</loc>
  <lastmod>2026-07-10T10:42:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-10T09:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再構成可能ハードウェア向け非一様量子化器の実用化（Efficient Non-uniform Quantizer for Quantized Neural Network Targeting Re-configurable Hardware）</news:title>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-07-10T09:51:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>数値スパース性を利用した効率的学習：固有ベクトル計算と回帰の高速化（Exploiting Numerical Sparsity for Efficient Learning: Faster Eigenvector Computation and Regression）</news:title>
   <news:publication_date>2026-07-10T09:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Object Tracking by ReconstructionによるRGB-D長期追跡の刷新（Object Tracking by Reconstruction with View-Specific Discriminative Correlation Filters）</news:title>
   <news:publication_date>2026-07-10T09:49:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-10T09:49:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710214</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンピュータビジョンと深層学習による藻類検出（Algae Detection Using Computer Vision and Deep Learning）</news:title>
   <news:publication_date>2026-07-10T09:49:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710212</loc>
  <lastmod>2026-07-10T08:57:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>期限制約付きマルチチャネルネットワークにおける最適学習（Optimal Learning for Dynamic Coding in Deadline-Constrained Multi-Channel Networks）</news:title>
   <news:publication_date>2026-07-10T08:57:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710210</loc>
  <lastmod>2026-07-10T08:57:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的かつ効果的な敵対的攻撃のためのFrank-Wolfeフレームワーク（A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks）</news:title>
   <news:publication_date>2026-07-10T08:57:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710208</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>雑音耐性を持つ音声・映像の注意機構によるオンライン人物認証（NOISE-TOLERANT AUDIO-VISUAL ONLINE PERSON VERIFICATION USING AN ATTENTION-BASED NEURAL NETWORK FUSION）</news:title>
   <news:publication_date>2026-07-10T08:56:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710206</loc>
  <lastmod>2026-07-10T08:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を考慮した音声映像活動認識（Uncertainty-aware Audiovisual Activity Recognition using Deep Bayesian Variational Inference）</news:title>
   <news:publication_date>2026-07-10T08:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クープマン理論と線形近似空間（Koopman Theory and Linear Approximation Spaces）</news:title>
   <news:publication_date>2026-07-10T08:55:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-10T08:55:24Z</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>エンドツーエンド画像色付けのための知覚条件付き生成対向ネットワーク（Perceptual Conditional Generative Adversarial Networks for End-to-End Image Colourization）</news:title>
   <news:publication_date>2026-07-10T08:54:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710198</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>構造と属性を同時に扱う柔軟なネットワーク埋め込み（Flexible Attributed Network Embedding）</news:title>
   <news:publication_date>2026-07-10T08:03:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710196</loc>
  <lastmod>2026-07-10T07:56:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次集約型畳み込みネットワークの要点（Sequentially Aggregated Convolutional Networks）</news:title>
   <news:publication_date>2026-07-10T07:56:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710194</loc>
  <lastmod>2026-07-10T07:56:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応類似度に基づくノード埋め込みによる大規模グラフ学習（Node Embedding with Adaptive Similarities for Scalable Learning over Graphs）</news:title>
   <news:publication_date>2026-07-10T07:56:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710192</loc>
  <lastmod>2026-07-10T07:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>何が解釈可能か？意思決定支援システムのための機械学習設計（What is Interpretable? Using Machine Learning to Design Interpretable Decision-Support Systems）</news:title>
   <news:publication_date>2026-07-10T07:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-07-10T07:54:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元インデックス分散モデルの新展開（High-dimensional Index Volatility Models via Stein’s Identity）</news:title>
   <news:publication_date>2026-07-10T07:54:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710188</loc>
  <lastmod>2026-07-10T07:54:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散深層学習のための確率的勾配プッシュ（Stochastic Gradient Push for Distributed Deep Learning）</news:title>
   <news:publication_date>2026-07-10T07:54:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710186</loc>
  <lastmod>2026-07-10T07:53:55Z</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>2026-07-10T07:53:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710184</loc>
  <lastmod>2026-07-10T07:01:36Z</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>2026-07-10T07:01:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710182</loc>
  <lastmod>2026-07-10T07:01:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習に導かれる誘導進化とタンパク質設計（Machine learning-guided directed evolution for protein engineering）</news:title>
   <news:publication_date>2026-07-10T07:01:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710180</loc>
  <lastmod>2026-07-10T07:01:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスリンガルな単語とエンティティの共同表現学習（Joint Representation Learning of Cross-lingual Words and Entities via Attentive Distant Supervision）</news:title>
   <news:publication_date>2026-07-10T07:01:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710178</loc>
  <lastmod>2026-07-10T07:00:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>品質認識型マルチモーダル顕著性検出（Quality-Aware Multimodal Saliency Detection via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-10T07:00:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710176</loc>
  <lastmod>2026-07-10T06:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層連続局所学習のためのシナプス可塑性ダイナミクス（Synaptic Plasticity Dynamics for Deep Continuous Local Learning (DECOLLE))</news:title>
   <news:publication_date>2026-07-10T06:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710174</loc>
  <lastmod>2026-07-10T06:59:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ガイダンスを用いたナビゲーション学習（Learning with Stochastic Guidance for Navigation）</news:title>
   <news:publication_date>2026-07-10T06:59:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710172</loc>
  <lastmod>2026-07-10T06:59:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画におけるフレーム重複検出の粗→細深層学習フレームワーク（A Coarse-to-fine Deep Convolutional Neural Network Framework for Frame Duplication Detection and Localization in Forged Videos）</news:title>
   <news:publication_date>2026-07-10T06:59:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710170</loc>
  <lastmod>2026-07-10T06:08:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Generalized PolyDot符号を用いた分散DNN学習の統一的戦略（A Unified Coded Deep Neural Network Training Strategy Based on Generalized PolyDot Codes for Matrix Multiplication）</news:title>
   <news:publication_date>2026-07-10T06:08:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710168</loc>
  <lastmod>2026-07-10T06:07:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MATCH-Netによる生存予測の動的化（MATCH-Net: Dynamic Prediction in Survival Analysis using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-07-10T06:07:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710166</loc>
  <lastmod>2026-07-10T06:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Feynman-Kacに基づくResNetアンサンブルで自然精度と頑強性を改善（ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies）</news:title>
   <news:publication_date>2026-07-10T06:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710164</loc>
  <lastmod>2026-07-10T06:06:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>fMRIエンコーディングにおける回帰専門家混合モデル（Mixture of Regression Experts in fMRI Encoding）</news:title>
   <news:publication_date>2026-07-10T06:06:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710162</loc>
  <lastmod>2026-07-10T06:06:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-10T06:06:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-07-10T06:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カスタムウェイクワード検出を手元で実現する低負荷手法（DONUT: CTC-based Query-by-Example Keyword Spotting）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-07-10T06:06:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANtruthによる合成画像から実写への変換（GANtruth – an unpaired image-to-image translation method for driving scenarios）</news:title>
   <news:publication_date>2026-07-10T06:06:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/710156</loc>
  <lastmod>2026-07-10T05:14:27Z</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による決定木の自動誘導（Automatic Induction of Neural Network Decision Tree Algorithms）</news:title>
   <news:publication_date>2026-07-10T05:14:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710154</loc>
  <lastmod>2026-07-10T05:13:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ネットワークのための埋め込み基盤 DynamicGEM の意義（DynamicGEM: A Library for Dynamic Graph Embedding Methods）</news:title>
   <news:publication_date>2026-07-10T05:13:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710152</loc>
  <lastmod>2026-07-10T05:13:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生涯学習型強化学習のための環境設計（Environments for Lifelong Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-10T05:13:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710150</loc>
  <lastmod>2026-07-10T05:12:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報探索対話戦略の最適化（Optimization of Information-Seeking Dialogue Strategy for Argumentation-Based Dialogue System）</news:title>
   <news:publication_date>2026-07-10T05:12:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710148</loc>
  <lastmod>2026-07-10T05:12:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DESによる外縁天体の位置精度と星食予測の改善（ASTROMETRY AND OCCULTATION PREDICTIONS TO TRANSNEPTUNIAN AND CENTAUR OBJECTS OBSERVED WITHIN THE DARK ENERGY SURVEY）</news:title>
   <news:publication_date>2026-07-10T05:12:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710146</loc>
  <lastmod>2026-07-10T05:12:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像誘導ニューラルオブジェクトレンダリング（Image-Guided Neural Object Rendering）</news:title>
   <news:publication_date>2026-07-10T05:12:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710144</loc>
  <lastmod>2026-07-10T05:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数インスタンスを扱う空間変換器（MIST: Multiple Instance Spatial Transformer）</news:title>
   <news:publication_date>2026-07-10T05:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710142</loc>
  <lastmod>2026-07-10T04:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一視点からの3D再構築における視点事前知識の学習 (Learning View Priors for Single-view 3D Reconstruction)</news:title>
   <news:publication_date>2026-07-10T04:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710140</loc>
  <lastmod>2026-07-10T04:20:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動標的認識の堅牢表現学習（Learning Robust Representations for Automatic Target Recognition）</news:title>
   <news:publication_date>2026-07-10T04:20:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710138</loc>
  <lastmod>2026-07-10T04:19:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生波形とメルスペクトログラムの高次特徴を組み合わせた音声タグ付け（COMBINING HIGH-LEVEL FEATURES OF RAW AUDIO WAVES AND MEL-SPECTROGRAMS FOR AUDIO TAGGING）</news:title>
   <news:publication_date>2026-07-10T04:19:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710136</loc>
  <lastmod>2026-07-10T04:19:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間・視点を意識した映像生成による教師なし表現学習（Time-Aware and View-Aware Video Rendering for Unsupervised Representation Learning）</news:title>
   <news:publication_date>2026-07-10T04:19:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710134</loc>
  <lastmod>2026-07-10T04:18:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子ゲーティングネットワークが強化学習にもたらす変化（Genetic-Gated Networks for Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-10T04:18:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710132</loc>
  <lastmod>2026-07-10T04:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像をシーングラフに変換する注意型関係ネットワーク（Attentive Relational Networks for Mapping Images to Scene Graphs）</news:title>
   <news:publication_date>2026-07-10T04:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710130</loc>
  <lastmod>2026-07-10T04:18:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディリクレ過程混合モデルによる時系列列の整列（Sequence Alignment with Dirichlet Process Mixtures）</news:title>
   <news:publication_date>2026-07-10T04:18:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710128</loc>
  <lastmod>2026-07-10T03:26:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顧客対応チャットにおける能動的応答支援（Beyond &amp;quot;How may I help you?&amp;quot;: Assisting Customer Service Agents with Proactive Responses）</news:title>
   <news:publication_date>2026-07-10T03:26:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710126</loc>
  <lastmod>2026-07-10T03:26:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトエッジ検出に導かれた敵対的動画圧縮（Adversarial Video Compression Guided by Soft Edge Detection）</news:title>
   <news:publication_date>2026-07-10T03:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710124</loc>
  <lastmod>2026-07-10T03:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANsfer Learningによるラベル付き・ラベル無しデータの統合的拡張（GANsfer Learning: Combining labelled and unlabelled data for GAN based data augmentation）</news:title>
   <news:publication_date>2026-07-10T03:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710122</loc>
  <lastmod>2026-07-10T03:25:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低レベル反復プログラムの帰納的合成への足がかり（Stepping Stones to Inductive Synthesis of Low-Level Looping Programs）</news:title>
   <news:publication_date>2026-07-10T03:25:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710120</loc>
  <lastmod>2026-07-10T03:25:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絵画を写真に変える技術—Art2Real（Art2Real: Unfolding the Reality of Artworks）</news:title>
   <news:publication_date>2026-07-10T03:25:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710118</loc>
  <lastmod>2026-07-10T03:25:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を埋め込む知識グラフの革新（Embedding Uncertain Knowledge Graphs）</news:title>
   <news:publication_date>2026-07-10T03:25:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710116</loc>
  <lastmod>2026-07-10T03:24:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Bayesian Self-Training入門（Deep Bayesian Self-Training）</news:title>
   <news:publication_date>2026-07-10T03:24:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710114</loc>
  <lastmod>2026-07-10T02:33:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画向け時空間ニューラルアーキテクチャの進化（Evolving Space-Time Neural Architectures for Videos）</news:title>
   <news:publication_date>2026-07-10T02:33:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710112</loc>
  <lastmod>2026-07-10T02:23:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明生成における仮説推論に基づく手法（Abduction-Based Explanations for Machine Learning Models）</news:title>
   <news:publication_date>2026-07-10T02:23:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710110</loc>
  <lastmod>2026-07-10T02:23:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推論時のノイズ計算は有害か有益か（Noisy Computations during Inference: Harmful or Helpful?）</news:title>
   <news:publication_date>2026-07-10T02:23:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710108</loc>
  <lastmod>2026-07-10T02:21:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エリプティカル銀河M86での一過性超高輝度X線源の発見（Discovery of a transient ultraluminous X-ray source in the elliptical galaxy M86）</news:title>
   <news:publication_date>2026-07-10T02:21:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710106</loc>
  <lastmod>2026-07-10T02:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANの内部解剖（GAN Dissection: Visualizing and Understanding Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-07-10T02:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710104</loc>
  <lastmod>2026-07-10T02:21:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライマンα放射銀河の二点相関とネットワークトポロジーの統計 (STATISTICS OF TWO-POINT CORRELATION AND NETWORK TOPOLOGY FOR LYMAN ALPHA EMITTERS AT Z ≈2.67)</news:title>
   <news:publication_date>2026-07-10T02:21:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710102</loc>
  <lastmod>2026-07-10T02:21:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的含意タスクと説明可能なEVEモデル（Visual Entailment Task for Visually-Grounded Language Learning）</news:title>
   <news:publication_date>2026-07-10T02:21:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710100</loc>
  <lastmod>2026-07-10T01:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HOGWILD!-Gibbsは全変数の期待値を正確に推定できるか（HOGWILD!-Gibbs Can Be PanAccurate）</news:title>
   <news:publication_date>2026-07-10T01:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710098</loc>
  <lastmod>2026-07-10T01:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響質問応答のための合成データセット CLEAR（CLEAR: A Dataset for Compositional Language and Elementary Acoustic Reasoning）</news:title>
   <news:publication_date>2026-07-10T01:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710096</loc>
  <lastmod>2026-07-10T01:29:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低線量CTに対する深層畳み込みニューラルネットワークによるノイズ低減（Low-Dose CT via Deep CNN with Skip Connection and Network in Network）</news:title>
   <news:publication_date>2026-07-10T01:29:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710094</loc>
  <lastmod>2026-07-10T01:28:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィルタ相関に基づく深層モデル圧縮（Leveraging Filter Correlations for Deep Model Compression）</news:title>
   <news:publication_date>2026-07-10T01:28:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710092</loc>
  <lastmod>2026-07-10T01:28:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物再識別のための類似性保持画像間ドメイン適応（Similarity-preserving Image-image Domain Adaptation for Person Re-identification）</news:title>
   <news:publication_date>2026-07-10T01:28:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710090</loc>
  <lastmod>2026-07-10T01:28:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Androidの解除パターン収集方法とデータセット横断比較（A Survey of Collection Methods and Cross-Data Set Comparison of Android Unlock Patterns）</news:title>
   <news:publication_date>2026-07-10T01:28:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710088</loc>
  <lastmod>2026-07-10T01:28:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓の超音波動画から1年死亡率を予測する深層ニューラルネットワーク（A deep neural network to enhance prediction of 1-year mortality using echocardiographic videos of the heart）</news:title>
   <news:publication_date>2026-07-10T01:28:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710086</loc>
  <lastmod>2026-07-10T00:36:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模なマルチマッチングのための高次射影パワー反復法（Higher-order Projected Power Iterations for Scalable Multi-Matching）</news:title>
   <news:publication_date>2026-07-10T00:36:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710084</loc>
  <lastmod>2026-07-10T00:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフベースの大規模個別固有表現同定（Scalable graph-based individual named entity identification）</news:title>
   <news:publication_date>2026-07-10T00:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710082</loc>
  <lastmod>2026-07-10T00:35:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GP-CNASによるCNNアーキテクチャ探索（GP-CNAS: Convolutional Neural Network Architecture Search with Genetic Programming）</news:title>
   <news:publication_date>2026-07-10T00:35:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710080</loc>
  <lastmod>2026-07-10T00:35:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2Dトレースで3D注釈負担を半減する手法（Tracing in 2D to Reduce the Annotation Effort for 3D Deep Delineation）</news:title>
   <news:publication_date>2026-07-10T00:35:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710078</loc>
  <lastmod>2026-07-10T00:35:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳卒中後の言語回復予測における2DスティッチMRIと畳み込みネットワークの有用性（Predicting Language Recovery after Stroke with Convolutional Networks on Stitched MRI）</news:title>
   <news:publication_date>2026-07-10T00:35:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710076</loc>
  <lastmod>2026-07-10T00:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像コレクションからの教師なし3D形状学習（Unsupervised 3D Shape Learning from Image Collections in the Wild）</news:title>
   <news:publication_date>2026-07-10T00:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710074</loc>
  <lastmod>2026-07-10T00:34:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Network Interpolation（Deep Network Interpolation for Continuous Imagery Effect Transition）</news:title>
   <news:publication_date>2026-07-10T00:34:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710072</loc>
  <lastmod>2026-07-09T23:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層アンサンブルテンソル分解による縦断的患者軌跡分類（Deep Ensemble Tensor Factorization for Longitudinal Patient Trajectories Classification）</news:title>
   <news:publication_date>2026-07-09T23:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710070</loc>
  <lastmod>2026-07-09T23:43:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクト畳み込みネットワークの訓練のための線形過剰パラメータ化（ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks）</news:title>
   <news:publication_date>2026-07-09T23:43:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710068</loc>
  <lastmod>2026-07-09T23:43:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>証拠を生成する視点横断歩容認識：Discriminant Gait GAN（DiGGAN）によるアプローチ（Robust Cross-view Gait Recognition with Evidence: A Discriminant Gait GAN (DiGGAN) Approach）</news:title>
   <news:publication_date>2026-07-09T23:43:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710066</loc>
  <lastmod>2026-07-09T23:42:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人配列と参照ゲノムのインターレースで変異検出を最適化する（Interlacing Personal and Reference Genomes for Machine Learning Disease-Variant Detection）</news:title>
   <news:publication_date>2026-07-09T23:42:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710064</loc>
  <lastmod>2026-07-09T23:42:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不足ペナルティを用いた再生可能エネルギー深度統合下の電力オークション（Auctioning Electricity under Deep Renewable Integration using a Penalty for Shortfall）</news:title>
   <news:publication_date>2026-07-09T23:42:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710062</loc>
  <lastmod>2026-07-09T23:42:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造制約付きリレーションネットワークによる文表現（Sentence Encoding with Tree-Constrained Relation Networks）</news:title>
   <news:publication_date>2026-07-09T23:42:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710060</loc>
  <lastmod>2026-07-09T23:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークによるCSIベース認証（Deep Neural Networks Meet CSI-Based Authentication）</news:title>
   <news:publication_date>2026-07-09T23:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710058</loc>
  <lastmod>2026-07-09T22:50:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オミクスデータに機械学習を適用するためのフレームワーク（A Framework for Implementing Machine Learning on Omics Data）</news:title>
   <news:publication_date>2026-07-09T22:50:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710056</loc>
  <lastmod>2026-07-09T22:50:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状況認識型群衆カウントの新展開（Context-Aware Crowd Counting）</news:title>
   <news:publication_date>2026-07-09T22:50:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710054</loc>
  <lastmod>2026-07-09T22:50:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼブラフィッシュの群れをニューラルネットで再現する（Modelling zebrafish collective behaviours with multilayer perceptrons optimised by evolutionary algorithms）</news:title>
   <news:publication_date>2026-07-09T22:50:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710052</loc>
  <lastmod>2026-07-09T22:49:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事実要素化された状態・行動空間における計画のためのコンパクトで効率的な符号化（Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models）</news:title>
   <news:publication_date>2026-07-09T22:49:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710050</loc>
  <lastmod>2026-07-09T22:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルと知識ベースの統合によるポーランド語固有表現認識（COMBINING NEURAL AND KNOWLEDGE-BASED APPROACHES TO NAMED ENTITY RECOGNITION IN POLISH）</news:title>
   <news:publication_date>2026-07-09T22:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710048</loc>
  <lastmod>2026-07-09T22:49:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト画像の超解像に特化したDeep Laplacian Pyramid Networks（DEEP LAPLACIAN PYRAMID NETWORK FOR TEXT IMAGES SUPER-RESOLUTION）</news:title>
   <news:publication_date>2026-07-09T22:49:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710046</loc>
  <lastmod>2026-07-09T22:48:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損・汚染観測下でのスパーススペクトル推定（Sparse spectral estimation with missing and corrupted measurements）</news:title>
   <news:publication_date>2026-07-09T22:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710044</loc>
  <lastmod>2026-07-09T21:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深部脳刺激（DBS）手術における術中効果予測を目指す機械学習（Towards Machine Learning Prediction of Deep Brain Stimulation (DBS) Intra-operative Efficacy Maps）</news:title>
   <news:publication_date>2026-07-09T21:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710042</loc>
  <lastmod>2026-07-09T21:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚障害者支援のためのCNNによるライブ物体認識システム（A Convolutional Neural Network based Live Object Recognition System as Blind Aid）</news:title>
   <news:publication_date>2026-07-09T21:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710040</loc>
  <lastmod>2026-07-09T21:57:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病的音声検出におけるチャネル効果への頑健性（Robustness against the channel effect in pathological voice detection）</news:title>
   <news:publication_date>2026-07-09T21:57:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710038</loc>
  <lastmod>2026-07-09T21:57:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照文字列から最適な解析器を推薦するメタラーニングの実装（ParsRec: A Novel Meta-Learning Approach to Recommending Bibliographic Reference Parsers）</news:title>
   <news:publication_date>2026-07-09T21:57:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710036</loc>
  <lastmod>2026-07-09T21:57:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意スタイル転送のための交換可能特徴整列ネットワーク（EFANet: Exchangeable Feature Alignment Network for Arbitrary Style Transfer）</news:title>
   <news:publication_date>2026-07-09T21:57:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710034</loc>
  <lastmod>2026-07-09T21:57:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学術用レコメンダーを手軽に提供する仕組み（The Architecture of Mr. DLib’s Scientific Recommender-System API）</news:title>
   <news:publication_date>2026-07-09T21:57:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710032</loc>
  <lastmod>2026-07-09T21:56:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間・時間にわたるスパース自己符号化器による教師なし学習（Unsupervised learning with sparse space-and-time autoencoders）</news:title>
   <news:publication_date>2026-07-09T21:56:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710030</loc>
  <lastmod>2026-07-09T21:05:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全な共変量から因果効果を推定する方法（Estimating Causal Effects With Partial Covariates）</news:title>
   <news:publication_date>2026-07-09T21:05:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710028</loc>
  <lastmod>2026-07-09T21:05:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>普遍的半教師付きセマンティックセグメンテーション（Universal Semi-Supervised Semantic Segmentation）</news:title>
   <news:publication_date>2026-07-09T21:05:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710026</loc>
  <lastmod>2026-07-09T21:05:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サーフェス再構成から学ぶマッチャブル画像検索（Matchable Image Retrieval by Learning from Surface Reconstruction）</news:title>
   <news:publication_date>2026-07-09T21:05:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710024</loc>
  <lastmod>2026-07-09T21:04:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冠動脈疾患の機械学習分類の実務的インパクト（Machine Learning Classifications of Coronary Artery Disease）</news:title>
   <news:publication_date>2026-07-09T21:04:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710022</loc>
  <lastmod>2026-07-09T21:04:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散かつ安全な機械学習と自己集計による多者集約（Distributed and Secure ML with Self-tallying Multi-party Aggregation）</news:title>
   <news:publication_date>2026-07-09T21:04:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710020</loc>
  <lastmod>2026-07-09T21:04:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微分位相から見るフィードフォワードニューラルネットの学習課題（A Differential Topological View of Challenges in Learning with Feedforward Neural Networks）</news:title>
   <news:publication_date>2026-07-09T21:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710018</loc>
  <lastmod>2026-07-09T21:04:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ階層独立相関フィルタによる映像トラッキングの実務的意義（Multi-hierarchical Independent Correlation Filters for Visual Tracking）</news:title>
   <news:publication_date>2026-07-09T21:04:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710016</loc>
  <lastmod>2026-07-09T20:12:42Z</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を用いたLHCでの新物理探索（Variational Autoencoders for New Physics Mining at the Large Hadron Collider）</news:title>
   <news:publication_date>2026-07-09T20:12:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710014</loc>
  <lastmod>2026-07-09T20:12:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然環境を用いた可変BCI刺激によるヒューマノイドロボットのリアルタイムナビゲーション（Using Variable Natural Environment Brain-Computer Interface Stimuli for Real-time Humanoid Robot Navigation）</news:title>
   <news:publication_date>2026-07-09T20:12:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710012</loc>
  <lastmod>2026-07-09T20:11:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的積分と統計計算の役割に関する再応答（Rejoinder for “Probabilistic Integration: A Role in Statistical Computation?”）</news:title>
   <news:publication_date>2026-07-09T20:11:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710010</loc>
  <lastmod>2026-07-09T20:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集団誘導型ノベルティサーチが変える探索戦略（Population-Guided Novelty Search for Reinforcement Learning in Hard Exploration Environments）</news:title>
   <news:publication_date>2026-07-09T20:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710008</loc>
  <lastmod>2026-07-09T20:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト文書処理のための一般化差分プライバシー（Generalised Differential Privacy for Text Document Processing）</news:title>
   <news:publication_date>2026-07-09T20:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710006</loc>
  <lastmod>2026-07-09T20:10:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮可能かつ学習可能な暗号化によるクラウド活用の安全設計（Compressible and Learnable Encryption for Untrusted Cloud Environments）</news:title>
   <news:publication_date>2026-07-09T20:10:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710004</loc>
  <lastmod>2026-07-09T20:10:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>製品市場予測におけるネットワークと機械学習の統合アプローチ（A combined network and machine learning approaches for product market forecasting）</news:title>
   <news:publication_date>2026-07-09T20:10:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710002</loc>
  <lastmod>2026-07-09T19:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在的信念の学習と認識的推論による効率的かつ有意義な対話管理（Learning Latent Beliefs and Performing Epistemic Reasoning for Efficient and Meaningful Dialog Management）</news:title>
   <news:publication_date>2026-07-09T19:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/710000</loc>
  <lastmod>2026-07-09T19:18:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形効果の堅牢な推定と検定（CVEK: Robust Estimation and Testing for Nonlinear Effects using Kernel Machine Ensemble）</news:title>
   <news:publication_date>2026-07-09T19:18:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709998</loc>
  <lastmod>2026-07-09T19:18:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像で物体を3D位置まで特定する技術の実用化可能性（MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization）</news:title>
   <news:publication_date>2026-07-09T19:18:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709996</loc>
  <lastmod>2026-07-09T19:17:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ構造を用いたマルチタスク学習（Multi-task Learning over Graph Structures）</news:title>
   <news:publication_date>2026-07-09T19:17:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709994</loc>
  <lastmod>2026-07-09T19:17:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像による物体検出と姿勢推定の総覧（A survey on joint object detection and pose estimation using monocular vision）</news:title>
   <news:publication_date>2026-07-09T19:17:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709992</loc>
  <lastmod>2026-07-09T19:17:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた都市規模道路監査システム（City-Scale Road Audit System using Deep Learning）</news:title>
   <news:publication_date>2026-07-09T19:17:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709990</loc>
  <lastmod>2026-07-09T19:16:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attentioned Convolutional LSTM Inpainting Networkによる映像異常検知の要点と実務インパクト（Attentioned Convolutional LSTM Inpainting Network for Anomaly Detection in Videos）</news:title>
   <news:publication_date>2026-07-09T19:16:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709988</loc>
  <lastmod>2026-07-09T18:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの3D車線検出の直截的手法（3D-LaneNet: End-to-End 3D Multiple Lane Detection）</news:title>
   <news:publication_date>2026-07-09T18:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709986</loc>
  <lastmod>2026-07-09T18:25:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インスタンス認識型ニューラルアーキテクチャ探索（InstaNAS: Instance-aware Neural Architecture Search）</news:title>
   <news:publication_date>2026-07-09T18:25:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709984</loc>
  <lastmod>2026-07-09T18:25:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非構造化環境における自律走行のためのデータセットIDD (IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained Environments)</news:title>
   <news:publication_date>2026-07-09T18:25:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709982</loc>
  <lastmod>2026-07-09T18:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TMA画像解析に深層特徴を取り入れる意義（Incorporating Deep Features in the Analysis of Tissue Microarray Images）</news:title>
   <news:publication_date>2026-07-09T18:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709980</loc>
  <lastmod>2026-07-09T18:24:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境シーン認識における単純クラスタリングの実用性（SERVANT: Scene Recognition Through Visual and Acoustic Cues）</news:title>
   <news:publication_date>2026-07-09T18:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709978</loc>
  <lastmod>2026-07-09T18:24:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非公式中国語の大規模コーパスLSICCの意義（LSICC: A LARGE SCALE INFORMAL CHINESE CORPUS）</news:title>
   <news:publication_date>2026-07-09T18:24:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709976</loc>
  <lastmod>2026-07-09T18:24:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像と音声を組み合わせた鳥種分類の新展開（Cross-domain Deep Feature Combination for Bird Species Classification with Audio-visual Data）</news:title>
   <news:publication_date>2026-07-09T18:24:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709974</loc>
  <lastmod>2026-07-09T17:32:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックスモデルの説明をやめて解釈可能なモデルを使うべきだ（Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead）</news:title>
   <news:publication_date>2026-07-09T17:32:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709972</loc>
  <lastmod>2026-07-09T17:24:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像時系列の分類における時間畳み込みニューラルネットワーク（Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series）</news:title>
   <news:publication_date>2026-07-09T17:24:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709970</loc>
  <lastmod>2026-07-09T17:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人化された商品検索のための注意付き長短期嗜好モデリング（Attentive Long Short-Term Preference Modeling for Personalized Product Search）</news:title>
   <news:publication_date>2026-07-09T17:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709968</loc>
  <lastmod>2026-07-09T17:24:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習によるアップリフトモデリングの再定式化（Reinforcement Learning for Uplift Modeling）</news:title>
   <news:publication_date>2026-07-09T17:24:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709966</loc>
  <lastmod>2026-07-09T17:23:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Self-similarity Groupingによる人物再識別の非教師ドメイン適応（Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification）</news:title>
   <news:publication_date>2026-07-09T17:23:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709964</loc>
  <lastmod>2026-07-09T17:22:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的損失関数を持つ深層学習における周波数原理とその応用可能性 (Frequency Principle in Deep Learning with General Loss Functions and Its Potential Application)</news:title>
   <news:publication_date>2026-07-09T17:22:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709962</loc>
  <lastmod>2026-07-09T17:22:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内部表現コラージュによる空間制御可能な画像合成（Spatially Controllable Image Synthesis with Internal Representation Collaging）</news:title>
   <news:publication_date>2026-07-09T17:22:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709960</loc>
  <lastmod>2026-07-09T16:31:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚障害者向けモバイルコンピューティングの概観（A Survey of Mobile Computing for the Visually Impaired）</news:title>
   <news:publication_date>2026-07-09T16:31:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709958</loc>
  <lastmod>2026-07-09T16:31:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hapi: 標準WiFiで実現する疑似3次元キャリブレーションフリー屋内測位（Hapi: A Robust Pseudo-3D Calibration-Free WiFi-based Indoor Localization System）</news:title>
   <news:publication_date>2026-07-09T16:31:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709956</loc>
  <lastmod>2026-07-09T16:31:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Foreground Clusteringによる画像・動画の同時セグメンテーションとローカリゼーション（Foreground Clustering for Joint Segmentation and Localization in Videos and Images）</news:title>
   <news:publication_date>2026-07-09T16:31:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709954</loc>
  <lastmod>2026-07-09T16:30:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>従属データと外れ値からの多項式近似の復元保証 (Recovery Guarantees for Polynomial Approximation from Dependent Data with Outliers)</news:title>
   <news:publication_date>2026-07-09T16:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709952</loc>
  <lastmod>2026-07-09T16:30:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希少疾患診断タスクに対するモデルベース強化学習アプローチ（A MODEL-BASED REINFORCEMENT LEARNING APPROACH FOR A RARE DISEASE DIAGNOSTIC TASK）</news:title>
   <news:publication_date>2026-07-09T16:30:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709950</loc>
  <lastmod>2026-07-09T16:30:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分によるエンドツーエンド航行と自己位置推定（Variational End-to-End Navigation and Localization）</news:title>
   <news:publication_date>2026-07-09T16:30:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709948</loc>
  <lastmod>2026-07-09T16:29:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォン上でリアルタイム睡眠段階判定を行う研究の要点（Real-Time Sleep Staging using Deep Learning on a Smartphone for a Wearable EEG）</news:title>
   <news:publication_date>2026-07-09T16:29:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709946</loc>
  <lastmod>2026-07-09T15:38:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率最適化のための不正確SARAHアルゴリズム（Inexact SARAH Algorithm for Stochastic Optimization）</news:title>
   <news:publication_date>2026-07-09T15:38:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/709944</loc>
  <lastmod>2026-07-09T15:38:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース主成分解析をスパース線形回帰から解く（Sparse PCA from Sparse Linear Regression）</news:title>
   <news:publication_date>2026-07-09T15:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </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>暗号通貨のポンプ・アンド・ダンプの構造解析（The Anatomy of a Cryptocurrency Pump-and-Dump Scheme）</news:title>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-07-09T15:37:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WarpGANによる自動カリカチュア生成（WarpGAN: Automatic Caricature Generation）</news:title>
   <news:publication_date>2026-07-09T15:37:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-07-09T15:37:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習による逆治療計画の知能化（Intelligent Inverse Treatment Planning via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-07-09T15:37:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/709934</loc>
  <lastmod>2026-07-09T15:37:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テストの（不）公平性から学ぶ教訓（50 Years of Test (Un)fairness: Lessons for Machine Learning）</news:title>
   <news:publication_date>2026-07-09T15:37:05Z</news:publication_date>
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