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   <news:title>フェンスを消す深層学習（My camera can see through fences: A deep learning approach for image de-fencing）</news:title>
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   <news:title>DeepLogicに学ぶ：ニューラルネットワークで論理推論を学習させる意義（DeepLogic: Towards End-to-End Differentiable Logical Reasoning）</news:title>
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   <news:title>効率的なオンラインポートフォリオと対数的後悔（Efficient Online Portfolio with Logarithmic Regret）</news:title>
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   <news:title>機械学習は数学の「面白さ」を見つけられるか（Can machine learning identify interesting mathematics? An exploration using empirically observed laws）</news:title>
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   <news:title>逐次学習による主曲線の自動要約（Sequential Learning of Principal Curves: Summarizing Data Streams on the Fly）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Wasserstein測度に基づくメジャー・コアセット（Wasserstein Measure Coresets）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>利用者主導のプライバシーのための協調学習（Learning to Collaborate for User-Controlled Privacy）</news:title>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>d次元ヒストグラム上のKantorovich–Wasserstein距離計算を(d+1)-部グラフで効率化（Computing Kantorovich-Wasserstein Distances on d-dimensional histograms using (d + 1)-partite graphs）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>地球温度変動のボラティリティ推定アルゴリズム（Algorithms for Estimating Trends in Global Temperature Volatility）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>Twitter上の政治議論と有権者の傾向（Political Discussion and Leanings on Twitter: the 2016 Italian Constitutional Referendum）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>欠損データを確率的に扱うニューラルネットワーク（Processing of missing data by neural networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Type I超新星PS16aqvの光度曲線の複雑性と放射性物質に関する深い限界（THE TYPE I SUPERLUMINOUS SUPERNOVA PS16AQV: LIGHTCURVE COMPLEXITY AND DEEP LIMITS ON RADIOACTIVE EJECTA IN A FAST EVENT）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-05T23:41:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>重力波イベントに対する強いレンズ銀河団の迅速光学追観測（Rapid optical follow-up of strong-lensing galaxy clusters in LIGO–Virgo GW sky localizations）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686937</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>GumBoltが切り開く離散潜在空間の新展開（GumBolt: Extending Gumbel trick to Boltzmann priors）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>線形ガウス・マルコフ過程の効率的カーネル学習（Accurate Kernel Learning for Linear Gaussian Markov Processes using a Scalable Likelihood Computation）</news:title>
   <news:publication_date>2026-05-05T23:31:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686933</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>がん医薬品探索のプロセスマイニング（Cancer Research UK Drug Discovery Process Mining）</news:title>
   <news:publication_date>2026-05-05T23:29:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686931</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>接尾辞両方向LSTMによる文表現改善（Improved Sentence Modeling using Suffix Bidirectional LSTM）</news:title>
   <news:publication_date>2026-05-05T23:29:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-05T23:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>損失関数から学習データを復元する理論（Reconstruction of training samples from loss functions）</news:title>
   <news:publication_date>2026-05-05T23:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-05T23:29:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ポジティブと非ラベルデータから学ぶ手法の実務的意義（Positive and Unlabeled Learning through Negative Selection and Imbalance-aware Classification）</news:title>
   <news:publication_date>2026-05-05T23:29:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686925</loc>
  <lastmod>2026-05-05T22:37:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配空間の効率的探索によるオンライン学習ランキングの高速化（Efficient Exploration of Gradient Space for Online Learning to Rank）</news:title>
   <news:publication_date>2026-05-05T22:37:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686923</loc>
  <lastmod>2026-05-05T22:37:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>力場に着想を得た記述子による材料機械学習（Machine learning with force-field inspired descriptors for materials: fast screening and mapping energy landscape）</news:title>
   <news:publication_date>2026-05-05T22:37:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686921</loc>
  <lastmod>2026-05-05T22:37:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>GANE: 生成的敵対ネットワークを用いたネットワーク埋め込み（GANE: A Generative Adversarial Network Embedding）</news:title>
   <news:publication_date>2026-05-05T22:37:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686919</loc>
  <lastmod>2026-05-05T22:36:20Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチテーパーとHDP-HMMによる睡眠EEGのスペクトル推定（Multitaper Spectral Estimation HDP-HMMs for EEG Sleep Inference）</news:title>
   <news:publication_date>2026-05-05T22:36:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686917</loc>
  <lastmod>2026-05-05T22:36:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ依存の正則化で「覚え込み」を止める――GRSVNetによる本質パターン学習の提案 (Stop memorizing: A data-dependent regularization framework for intrinsic pattern learning)</news:title>
   <news:publication_date>2026-05-05T22:36:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686915</loc>
  <lastmod>2026-05-05T22:36:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>弱い教師ありで学ぶ3D形状補完（Learning 3D Shape Completion under Weak Supervision）</news:title>
   <news:publication_date>2026-05-05T22:36:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686913</loc>
  <lastmod>2026-05-05T22:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブレンデッド条件付き勾配法の本質と応用可能性（Blended Conditional Gradients: the unconditioning of conditional gradients）</news:title>
   <news:publication_date>2026-05-05T22:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686911</loc>
  <lastmod>2026-05-05T21:43:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルで逆問題を教師なしに解く（An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-05T21:43:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686909</loc>
  <lastmod>2026-05-05T21:43:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間環境における近似ベイズ推論（Approximate Bayesian inference in spatial environments）</news:title>
   <news:publication_date>2026-05-05T21:43:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686907</loc>
  <lastmod>2026-05-05T21:43:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテキストを考慮した動作学習と推論（Learning and Inferring Movement with Deep Generative Model）</news:title>
   <news:publication_date>2026-05-05T21:43:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/686905</loc>
  <lastmod>2026-05-05T21:43:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XOGANによる一対多の教師なし画像翻訳（XOGAN: One-to-Many Unsupervised Image-to-Image Translation）</news:title>
   <news:publication_date>2026-05-05T21:43:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/686903</loc>
  <lastmod>2026-05-05T21:41:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互情報量に基づく動的学習率（Dynamic learning rate using Mutual Information）</news:title>
   <news:publication_date>2026-05-05T21:41:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/686901</loc>
  <lastmod>2026-05-05T21:40:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次ニューラル尤度（Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows）</news:title>
   <news:publication_date>2026-05-05T21:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/686899</loc>
  <lastmod>2026-05-05T21:40:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Siamese Capsule Networksによる少量学習の探求（Siamese Capsule Networks）</news:title>
   <news:publication_date>2026-05-05T21:40:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686897</loc>
  <lastmod>2026-05-05T20:49:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布的ロバスト逆共分散推定：ワッサースタイン・シュリンク推定器 (Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator)</news:title>
   <news:publication_date>2026-05-05T20:49:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686895</loc>
  <lastmod>2026-05-05T20:48:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-05T20:48:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686893</loc>
  <lastmod>2026-05-05T20:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的知識蒸留によるモデル圧縮（RECURRENT KNOWLEDGE DISTILLATION）</news:title>
   <news:publication_date>2026-05-05T20:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686891</loc>
  <lastmod>2026-05-05T20:48:06Z</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>2026-05-05T20:48:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686889</loc>
  <lastmod>2026-05-05T20:47:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>尤度を用いないコスモロジー推論のためのベイズ最適化（Bayesian optimisation for likelihood-free cosmological inference）</news:title>
   <news:publication_date>2026-05-05T20:47:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686887</loc>
  <lastmod>2026-05-05T20:47:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハッブル・タランチュラ計画が示した機械学習による前主系列星同定の刷新（Hubble Tarantula Treasury Project – VI. Identification of Pre–Main-Sequence Stars using Machine Learning techniques）</news:title>
   <news:publication_date>2026-05-05T20:47:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686885</loc>
  <lastmod>2026-05-05T20:46:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低コストなRNN性能予測手法の実務的意義（Low-Cost Recurrent Neural Network Expected Performance Evaluation）</news:title>
   <news:publication_date>2026-05-05T20:46:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686883</loc>
  <lastmod>2026-05-05T19:55:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層状ニューラルネットワークからの知識発見：非負タスク分解による可視化（Knowledge Discovery from Layered Neural Networks based on Non-negative Task Decomposition）</news:title>
   <news:publication_date>2026-05-05T19:55:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686881</loc>
  <lastmod>2026-05-05T19:55:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木編集距離の埋め込み学習が拓く計量学習の実用化（Tree Edit Distance Learning via Adaptive Symbol Embeddings）</news:title>
   <news:publication_date>2026-05-05T19:55:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686879</loc>
  <lastmod>2026-05-05T19:55:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ列に対する変化点検出手法（Change Point Methods on a Sequence of Graphs）</news:title>
   <news:publication_date>2026-05-05T19:55:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686877</loc>
  <lastmod>2026-05-05T19:54:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き生成対抗ネットワークを用いた画像キャプショニングの改善（Improving Image Captioning with Conditional Generative Adversarial Nets）</news:title>
   <news:publication_date>2026-05-05T19:54:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686875</loc>
  <lastmod>2026-05-05T19:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化模倣学習で学習時間を5倍短縮する地図不要ナビ（Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations）</news:title>
   <news:publication_date>2026-05-05T19:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686873</loc>
  <lastmod>2026-05-05T19:53:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズモデル削減が変えるモデル選択の速度と実務応用（Bayesian Model Reduction）</news:title>
   <news:publication_date>2026-05-05T19:53:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686871</loc>
  <lastmod>2026-05-05T19:53:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑なログに対する異常検知のための拡張 Dynamic Bayesian Networks（Extending Dynamic Bayesian Networks for Anomaly Detection in Complex Logs）</news:title>
   <news:publication_date>2026-05-05T19:53:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686869</loc>
  <lastmod>2026-05-05T19:01:37Z</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トロピカル幾何学（Tropical Geometry of Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-05T19:01:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686867</loc>
  <lastmod>2026-05-05T19:01:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地上望遠鏡データの自動選別が変える発見効率（Automatic vetting of planet candidates from ground based surveys: Machine learning with NGTS）</news:title>
   <news:publication_date>2026-05-05T19:01:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686865</loc>
  <lastmod>2026-05-05T18:59:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安全制約を組み込むTrusted Neural Networks（Trusted Neural Networks for Safety-Constrained Autonomous Control）</news:title>
   <news:publication_date>2026-05-05T18:59:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686863</loc>
  <lastmod>2026-05-05T18:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い食を発見した変光星IPHAS J051814.33+294113.0（Discovery of deep eclipses in the cataclysmic variable IPHAS J051814.33+294113.0）</news:title>
   <news:publication_date>2026-05-05T18:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686861</loc>
  <lastmod>2026-05-05T18:59:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多機能認知レーダのタスクスケジューリングにおけるMCTSと政策ネットワークの統合（Multifunction Cognitive Radar Task Scheduling Using Monte Carlo Tree Search and Policy Networks）</news:title>
   <news:publication_date>2026-05-05T18:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686859</loc>
  <lastmod>2026-05-05T18:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスバリデーショングラディエントによる汎化最適化（Optimizing for Generalization in Machine Learning with Cross-Validation Gradients）</news:title>
   <news:publication_date>2026-05-05T18:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686857</loc>
  <lastmod>2026-05-05T18:58:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザーに寄り添うAndroidアプリの個人化セキュリティ説明（Catering to Your Concerns: Automatic Generation of Personalised Security-Centric Descriptions for Android Apps）</news:title>
   <news:publication_date>2026-05-05T18:58:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686855</loc>
  <lastmod>2026-05-05T18:07:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文のエンコーダと文脈化ベクトルによる議論推論理解（SNU IDS at SemEval-2018 Task 12: Sentence Encoder with Contextualized Vectors for Argument Reasoning Comprehension）</news:title>
   <news:publication_date>2026-05-05T18:07:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686853</loc>
  <lastmod>2026-05-05T18:06:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界デモから人間可読な計画を学ぶ合成データ学習（Synthetically Trained Neural Networks for Learning Human-Readable Plans from Real-World Demonstrations）</news:title>
   <news:publication_date>2026-05-05T18:06:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686851</loc>
  <lastmod>2026-05-05T18:05:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Around View Monitoringに基づく自動運転のシーン理解ネットワーク（Scene Understanding Networks for Autonomous Driving based on Around View Monitoring System）</news:title>
   <news:publication_date>2026-05-05T18:05:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686849</loc>
  <lastmod>2026-05-05T18:04:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンパ節転移予測のための多目的ラジオミクスと3D畳み込みニューラルネットワークの統合（Predicting Lymph Node Metastasis in Head and Neck Cancer by Combining Many-objective Radiomics and 3-dimensional Convolutional Neural Network through Evidential Reasoning）</news:title>
   <news:publication_date>2026-05-05T18:04:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686847</loc>
  <lastmod>2026-05-05T18:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スタイライズされた画像キャプション生成の分離学習（SemStyle: Learning to Generate Stylised Image Captions using Unaligned Text）</news:title>
   <news:publication_date>2026-05-05T18:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686845</loc>
  <lastmod>2026-05-05T18:04:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MARS—メモリ注意機構による適応的推薦（MARS: Memory Attention-Aware Recommender System）</news:title>
   <news:publication_date>2026-05-05T18:04:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686843</loc>
  <lastmod>2026-05-05T17:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順列学習のためのSinkhorn方策勾配（Learning Permutations with Sinkhorn Policy Gradient）</news:title>
   <news:publication_date>2026-05-05T17:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686841</loc>
  <lastmod>2026-05-05T17:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-05T17:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686839</loc>
  <lastmod>2026-05-05T17:09:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Nested Agent による階層強化学習の効率化（Hierarchical Reinforcement Learning with Deep Nested Agents）</news:title>
   <news:publication_date>2026-05-05T17:09:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686837</loc>
  <lastmod>2026-05-05T17:08:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コーパスベースの対話ポリシー最適化のためのニューラルユーザシミュレータ（Neural User Simulation for Corpus-based Policy Optimisation for Spoken Dialogue Systems）</news:title>
   <news:publication_date>2026-05-05T17:08:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686835</loc>
  <lastmod>2026-05-05T17:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反例に導かれるデータ拡張（Counterexample-Guided Data Augmentation）</news:title>
   <news:publication_date>2026-05-05T17:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686833</loc>
  <lastmod>2026-05-05T17:08:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル特徴スケーリング法による教師あり次元削減 (Spectral Feature Scaling Method for Supervised Dimensionality Reduction)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686831</loc>
  <lastmod>2026-05-05T17:06:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病理画像でのテラバイト規模深層Multiple Instance Learning（Terabyte-scale Deep Multiple Instance Learning for Classification and Localization in Pathology）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686829</loc>
  <lastmod>2026-05-05T16:15:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>料理画像における物体の状態識別（Identifying Object States in Cooking-Related Images）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686827</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>フォレスト混合下界によるブロック不要の並列推論（A Forest Mixture Bound for Block-Free Parallel Inference）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686825</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多染色免疫組織化学組織セグメンテーションの一般化（Generalizing multistain immunohistochemistry tissue segmentation using one-shot color deconvolution deep neural networks）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/686823</loc>
  <lastmod>2026-05-05T16:11:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EU域内越境インターネット購入の供給側データ駆動測定法（A Data-Driven Supply-Side Approach for Measuring Cross-Border Internet Purchases）</news:title>
   <news:publication_date>2026-05-05T16:11:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686821</loc>
  <lastmod>2026-05-05T16:11:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型MAC最適化のための高速強化学習（Fast reinforcement learning for decentralized MAC optimization）</news:title>
   <news:publication_date>2026-05-05T16:11:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686819</loc>
  <lastmod>2026-05-05T16:10:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>思考の言語を柔軟にする：概念露出ごとのベイジアン文法更新 (Towards a more flexible Language of Thought: Bayesian grammar updates after each concept exposure)</news:title>
   <news:publication_date>2026-05-05T16:10:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686817</loc>
  <lastmod>2026-05-05T16:09:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテゴリ変数の符号化と標準化に関する一考察 (A Note on Coding and Standardization of Categorical Variables in (Sparse) Group Lasso Regression)</news:title>
   <news:publication_date>2026-05-05T16:09:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686815</loc>
  <lastmod>2026-05-05T15:17:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳房X線画像の高密度可変ビット長圧縮を可能にする全畳み込みモデル（Fully Convolutional Model for Variable Bit Length and Lossy High Density Compression of Mammograms）</news:title>
   <news:publication_date>2026-05-05T15:17:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686813</loc>
  <lastmod>2026-05-05T15:16:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像から弱教師あり学習で得る3次元人体姿勢推定（It’s all Relative: Monocular 3D Human Pose Estimation from Weakly Supervised Data）</news:title>
   <news:publication_date>2026-05-05T15:16:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686811</loc>
  <lastmod>2026-05-05T15:15:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語表現が科学研究の結果を予測する（Neural language representations predict outcomes of scientific research）</news:title>
   <news:publication_date>2026-05-05T15:15:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686809</loc>
  <lastmod>2026-05-05T15:13:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非滑らかモデルの学習：IV分位回帰と関連問題（Learning non-smooth models: instrumental variable quantile regressions and related problems）</news:title>
   <news:publication_date>2026-05-05T15:13:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686807</loc>
  <lastmod>2026-05-05T15:13:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師付き動画学習のためのNeuralNetwork-Viterbi（NeuralNetwork-Viterbi: A Framework for Weakly Supervised Video Learning）</news:title>
   <news:publication_date>2026-05-05T15:13:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686805</loc>
  <lastmod>2026-05-05T15:11:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ツリー編集距離の入門と実装ガイド（Revisiting the tree edit distance and its backtracing: A tutorial）</news:title>
   <news:publication_date>2026-05-05T15:11:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686803</loc>
  <lastmod>2026-05-05T15:11:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>曲線文様の設計同定（Design Identification of Curve Patterns on Cultural Heritage Objects: Combining Template Matching and CNN-based Re-Ranking）</news:title>
   <news:publication_date>2026-05-05T15:11:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686801</loc>
  <lastmod>2026-05-05T14:18:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ScaffoldNetによる生体工学用ポリマースキャフォールドの検出と分類（ScaffoldNet: Detecting and Classifying Biomedical Polymer-Based Scaffolds via a Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-05T14:18:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686799</loc>
  <lastmod>2026-05-05T14:17:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転に強い畳み込みフィルタ分解による表現の安定化（RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks）</news:title>
   <news:publication_date>2026-05-05T14:17:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686797</loc>
  <lastmod>2026-05-05T14:15:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知のトピック数に対する最小最大（ミニマックス）保証を持つ高速アルゴリズム（A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topics）</news:title>
   <news:publication_date>2026-05-05T14:15:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686795</loc>
  <lastmod>2026-05-05T14:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全観測からのサブスペース推定（Subspace Estimation from Incomplete Observations: A High-Dimensional Analysis）</news:title>
   <news:publication_date>2026-05-05T14:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686793</loc>
  <lastmod>2026-05-05T14:14:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態数に依存しない決定論的MDPの厳密解法（Memoryless Exact Solutions for Deterministic MDPs with Sparse Rewards）</news:title>
   <news:publication_date>2026-05-05T14:14:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686791</loc>
  <lastmod>2026-05-05T14:13:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の原因がもたらす恩恵 — Deconfounderによる観察データの因果推論の刷新 (The Blessings of Multiple Causes)</news:title>
   <news:publication_date>2026-05-05T14:13:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686789</loc>
  <lastmod>2026-05-05T14:13:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度を活かしたスライディングウィンドウによる物体候補生成（Disparity Sliding Window: Object Proposals From Disparity Images）</news:title>
   <news:publication_date>2026-05-05T14:13:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686787</loc>
  <lastmod>2026-05-05T13:19:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNNとk-NN：記憶と汎化の共存を解く（DNN or k-NN: That is the Generalize vs. Memorize Question）</news:title>
   <news:publication_date>2026-05-05T13:19:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686785</loc>
  <lastmod>2026-05-05T13:19:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチテナント・マルチフレームワーク環境におけるDLaaSの信頼性（Dependability in a Multi-tenant Multi-framework Deep Learning as-a-Service Platform）</news:title>
   <news:publication_date>2026-05-05T13:19:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686783</loc>
  <lastmod>2026-05-05T13:18:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸凹ゲームにおける加速収束の技術と意味（Faster Rates for Convex-Concave Games）</news:title>
   <news:publication_date>2026-05-05T13:18:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686781</loc>
  <lastmod>2026-05-05T13:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテを問答で注釈する手法（Annotating Electronic Medical Records for Question Answering）</news:title>
   <news:publication_date>2026-05-05T13:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686779</loc>
  <lastmod>2026-05-05T13:18:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメイン属性表現のCNNによる枠組み（Cross-domain attribute representation based on convolutional neural network）</news:title>
   <news:publication_date>2026-05-05T13:18:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686777</loc>
  <lastmod>2026-05-05T13:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レーンチェンジの状況評価：再帰モデルと予測の結合（Situation Assessment for Planning Lane Changes: Combining Recurrent Models and Prediction）</news:title>
   <news:publication_date>2026-05-05T13:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686775</loc>
  <lastmod>2026-05-05T13:16:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間不均一な個体群動態の数値解析手法（Spatially inhomogeneous population dynamics: beyond the mean field approximation）</news:title>
   <news:publication_date>2026-05-05T13:16:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686764</loc>
  <lastmod>2026-05-05T12:23:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実数階の等方性全変動による画像再構成（REAL ORDER (AN)-ISOTROPIC TOTAL VARIATION IN IMAGE PROCESSING - PART I: ANALYTICAL ANALYSIS AND FUNCTIONAL PROPERTIES）</news:title>
   <news:publication_date>2026-05-05T12:23:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686762</loc>
  <lastmod>2026-05-05T12:23:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Interpolatron：深層ニューラルネットワークの最適化を加速する補間・外挿手法 (Interpolatron: Interpolation or Extrapolation Schemes to Accelerate Optimization for Deep Neural Networks)</news:title>
   <news:publication_date>2026-05-05T12:23:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686760</loc>
  <lastmod>2026-05-05T12:22:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小マージン損失による顔認識の識別力強化（Minimum Margin Loss for Deep Face Recognition）</news:title>
   <news:publication_date>2026-05-05T12:22:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686758</loc>
  <lastmod>2026-05-05T12:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語拡張によるテキストベースゲーム学習の単一エージェント化（Language Expansion In Text-Based Games）</news:title>
   <news:publication_date>2026-05-05T12:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686756</loc>
  <lastmod>2026-05-05T12:20:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANomalyによる半教師あり異常検知（GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training）</news:title>
   <news:publication_date>2026-05-05T12:20:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686754</loc>
  <lastmod>2026-05-05T12:20:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床文書における医療概念間の関係分類を改善するCNNとマルチプーリング手法（Classifying medical relations in clinical text via convolutional neural networks）</news:title>
   <news:publication_date>2026-05-05T12:20:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686752</loc>
  <lastmod>2026-05-05T12:20:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カスカディア沈黙を破る（Breaking Cascadia’s Silence: Machine Learning Reveals the Constant Chatter of the Megathrust）</news:title>
   <news:publication_date>2026-05-05T12:20:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686750</loc>
  <lastmod>2026-05-05T11:27:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテナ積み込みのための進化的強化学習（Evolutionary RL for Container Loading）</news:title>
   <news:publication_date>2026-05-05T11:27:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686748</loc>
  <lastmod>2026-05-05T11:24:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大電網の高速判定を可能にした図（グラフ）畳み込み深層学習の適用（Fast Transient Stability Assessment of Large Power Grids Based on Massive Online Historical Data and Graph Convolutional Deep Learning）</news:title>
   <news:publication_date>2026-05-05T11:24:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686746</loc>
  <lastmod>2026-05-05T11:23:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疑似アノテータを用いたシングルショット能動学習（Single Shot Active Learning using Pseudo Annotators）</news:title>
   <news:publication_date>2026-05-05T11:23:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686744</loc>
  <lastmod>2026-05-05T11:23:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAVを使ったセルラー通信の対ジャミング強化（UAV-Aided Cellular Communications with Deep Reinforcement Learning Against Jamming）</news:title>
   <news:publication_date>2026-05-05T11:23:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686742</loc>
  <lastmod>2026-05-05T11:22:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元構造を用いた翌日電力価格予測：単変量対多変量フレームワーク (Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks)</news:title>
   <news:publication_date>2026-05-05T11:22:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686740</loc>
  <lastmod>2026-05-05T11:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>独立成分分析を相互依存指標で拡張する手法（Independent Component Analysis via Energy-based and Kernel-based Mutual Dependence Measures）</news:title>
   <news:publication_date>2026-05-05T11:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686738</loc>
  <lastmod>2026-05-05T11:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変量を考慮した条件付き平均独立の検定（Testing for Conditional Mean Independence with Covariates through Martingale Difference Divergence）</news:title>
   <news:publication_date>2026-05-05T11:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686736</loc>
  <lastmod>2026-05-05T10:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スキャッタリング変換を用いた生成ネットワークの逆問題としての定式化（Generative Networks as Inverse Problems with Scattering Transforms）</news:title>
   <news:publication_date>2026-05-05T10:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686734</loc>
  <lastmod>2026-05-05T10:22:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜画像の構造を守るデクラウド処理（Structure-preserving Guided Retinal Image Filtering and Its Application for Optic Disc Analysis）</news:title>
   <news:publication_date>2026-05-05T10:22:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686732</loc>
  <lastmod>2026-05-05T10:20:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボックス格子による確率的知識グラフ埋め込み（Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures）</news:title>
   <news:publication_date>2026-05-05T10:20:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686730</loc>
  <lastmod>2026-05-05T10:19:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Androidマルウェア検出ツールDroidMark（DroidMark – A Tool for Android Malware Detection using Taint Analysis and Bayesian Network）</news:title>
   <news:publication_date>2026-05-05T10:19:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686728</loc>
  <lastmod>2026-05-05T10:18:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Defense-GANによる敵対的攻撃からの保護（DEFENSE-GAN: PROTECTING CLASSIFIERS AGAINST ADVERSARIAL ATTACKS USING GENERATIVE MODELS）</news:title>
   <news:publication_date>2026-05-05T10:18:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686726</loc>
  <lastmod>2026-05-05T10:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向け転移学習による手話認識の最適化（Optimization of Transfer Learning for Sign Language Recognition Targeting Mobile Platform）</news:title>
   <news:publication_date>2026-05-05T10:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686724</loc>
  <lastmod>2026-05-05T10:18:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タクシー需要予測におけるHEDGEベースの空間分割戦略（Taxi demand forecasting: A HEDGE based tessellation strategy for improved accuracy）</news:title>
   <news:publication_date>2026-05-05T10:18:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686722</loc>
  <lastmod>2026-05-05T09:25:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外挿を用いた非負値行列因子分解アルゴリズムの高速化（Accelerating Nonnegative Matrix Factorization Algorithms using Extrapolation）</news:title>
   <news:publication_date>2026-05-05T09:25:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686720</loc>
  <lastmod>2026-05-05T09:24:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層接続マップを用いた車載センサのコンテキスト予測型クラウド通信（Machine Learning based Context-predictive Car-to-cloud Communication Using Multi-layer Connectivity Maps for Upcoming 5G Networks）</news:title>
   <news:publication_date>2026-05-05T09:24:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686718</loc>
  <lastmod>2026-05-05T09:23:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共分散を活用する特徴選択の新手法——Covariance-Insured Screening（Covariance-Insured Screening）</news:title>
   <news:publication_date>2026-05-05T09:23:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686716</loc>
  <lastmod>2026-05-05T09:22:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークスライシングにおける資源管理のための深層強化学習（Deep Reinforcement Learning for Resource Management in Network Slicing）</news:title>
   <news:publication_date>2026-05-05T09:22:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686714</loc>
  <lastmod>2026-05-05T09:21:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な並列リカレントニューラルネットワークと畳み込み注意によるマルチモーダル活動モデリング (Interpretable Parallel Recurrent Neural Networks with Convolutional Attentions for Multi-Modality Activity Modeling)</news:title>
   <news:publication_date>2026-05-05T09:21:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686712</loc>
  <lastmod>2026-05-05T09:21:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分割構造の不連続を一般化ひずみとして扱う手法と離散・連続系のフーリエ変換（Structural discontinuity as generalized strain and Fourier transform for discrete-continuous systems）</news:title>
   <news:publication_date>2026-05-05T09:21:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686710</loc>
  <lastmod>2026-05-05T09:20:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスターゲット・スタンス分類と自己注意ネットワーク（Cross-Target Stance Classification with Self-Attention Networks）</news:title>
   <news:publication_date>2026-05-05T09:20:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686708</loc>
  <lastmod>2026-05-05T08:28:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ADMMと加速ADMMを連続力学系として見る（ADMM and Accelerated ADMM as Continuous Dynamical Systems）</news:title>
   <news:publication_date>2026-05-05T08:28:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686706</loc>
  <lastmod>2026-05-05T08:28:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の純粋量子状態の学習手法（Learning unknown pure quantum states）</news:title>
   <news:publication_date>2026-05-05T08:28:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686704</loc>
  <lastmod>2026-05-05T08:27:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アフィンスプラインで解き明かす深層学習の仕組み（Mad Max: Affine Spline Insights into Deep Learning）</news:title>
   <news:publication_date>2026-05-05T08:27:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686702</loc>
  <lastmod>2026-05-05T08:27:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調フィルタリングのためのニューラル・パーソナライズド・エンベディング（Neural Personalized Embedding for Collaborative Filtering）</news:title>
   <news:publication_date>2026-05-05T08:27:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686700</loc>
  <lastmod>2026-05-05T08:26:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン請願の内容に基づく人気度予測（Content-based Popularity Prediction of Online Petitions Using a Deep Regression Model）</news:title>
   <news:publication_date>2026-05-05T08:26:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686698</loc>
  <lastmod>2026-05-05T08:26:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間変動する人気プロファイルを扱うキャッシングの学習理論的視点（Caching With Time-Varying Popularity Profiles: A Learning-Theoretic Perspective）</news:title>
   <news:publication_date>2026-05-05T08:26:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686696</loc>
  <lastmod>2026-05-05T08:26:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>浸透性を持つ帯水層の潮汐応答とその応用（Tidal Response of Groundwater in a Leaky Aquifer – Application to Oklahoma）</news:title>
   <news:publication_date>2026-05-05T08:26:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686694</loc>
  <lastmod>2026-05-05T07:34:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スロット整列を組み込んだ深層アンサンブルによる逐次自然言語生成（A Deep Ensemble Model with Slot Alignment for Sequence-to-Sequence Natural Language Generation）</news:title>
   <news:publication_date>2026-05-05T07:34:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686692</loc>
  <lastmod>2026-05-05T07:34:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画からの高密度深度と自己運動を学習するリカレントニューラルネットワーク（Recurrent Neural Network for Learning Dense Depth and Ego-Motion from Video）</news:title>
   <news:publication_date>2026-05-05T07:34:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686690</loc>
  <lastmod>2026-05-05T07:33:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠ステージ分類における同時分類・予測のCNNフレームワーク（Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification）</news:title>
   <news:publication_date>2026-05-05T07:33:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686688</loc>
  <lastmod>2026-05-05T07:33:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平衡状態の因果を捕らえる新枠組み―Causal Constraints Modelsの紹介 (Beyond Structural Causal Models: Causal Constraints Models)</news:title>
   <news:publication_date>2026-05-05T07:33:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686686</loc>
  <lastmod>2026-05-05T07:32:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層テンソル分解による畳み込みニューラルネットワークの終端学習（End-to-end Learning of a Convolutional Neural Network via Deep Tensor Decomposition）</news:title>
   <news:publication_date>2026-05-05T07:32:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686684</loc>
  <lastmod>2026-05-05T07:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BLEUスコアと意味表現は対立するか（Are BLEU and Meaning Representation in Opposition?）</news:title>
   <news:publication_date>2026-05-05T07:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686682</loc>
  <lastmod>2026-05-05T07:31:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス型ノイズを最適化して差分プライバシーを強化する（Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising）</news:title>
   <news:publication_date>2026-05-05T07:31:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686680</loc>
  <lastmod>2026-05-05T06:40:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表形式データ向け正則化学習ネットワーク（Regularization Learning Networks: Deep Learning for Tabular Datasets）</news:title>
   <news:publication_date>2026-05-05T06:40:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686678</loc>
  <lastmod>2026-05-05T06:32:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合意味関係分類（Composite Semantic Relation Classification）</news:title>
   <news:publication_date>2026-05-05T06:32:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686676</loc>
  <lastmod>2026-05-05T06:32:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>V2V通信における深層強化学習による資源割当の分散化（Deep Reinforcement Learning based Resource Allocation for V2V Communications）</news:title>
   <news:publication_date>2026-05-05T06:32:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686674</loc>
  <lastmod>2026-05-05T06:32:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QuaterNet: 四元数ベースの反復モデルによる人間の動作予測（QuaterNet: A Quaternion-based Recurrent Model for Human Motion）</news:title>
   <news:publication_date>2026-05-05T06:32:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686672</loc>
  <lastmod>2026-05-05T06:30:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化された有限次元カーネルSobolev差異（Regularized Finite Dimensional Kernel Sobolev Discrepancy）</news:title>
   <news:publication_date>2026-05-05T06:30:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686670</loc>
  <lastmod>2026-05-05T06:29:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きなデータ変動への耐性を高める自己内変換ネットワーク（Resisting Large Data Variations via Introspective Transformation Network）</news:title>
   <news:publication_date>2026-05-05T06:29:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686668</loc>
  <lastmod>2026-05-05T06:29:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測ルールの再形成（Prediction Rule Reshaping）</news:title>
   <news:publication_date>2026-05-05T06:29:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686666</loc>
  <lastmod>2026-05-05T05:37:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>X線血管造影ビデオにおける深層セグメンテーションと登録（Deep Segmentation and Registration in X-Ray Angiography Video）</news:title>
   <news:publication_date>2026-05-05T05:37:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686664</loc>
  <lastmod>2026-05-05T05:37:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汚れた出力上でのタスク不可知な頑健学習（Task Agnostic Robust Learning on Corrupt Outputs）</news:title>
   <news:publication_date>2026-05-05T05:37:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686662</loc>
  <lastmod>2026-05-05T05:36:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOABB: 信頼できるBCIアルゴリズムベンチマーク（MOABB: Trustworthy algorithm benchmarking for BCIs）</news:title>
   <news:publication_date>2026-05-05T05:36:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686660</loc>
  <lastmod>2026-05-05T05:35:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル多重スケール画像圧縮（Neural Multi-scale Image Compression）</news:title>
   <news:publication_date>2026-05-05T05:35:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686658</loc>
  <lastmod>2026-05-05T05:35:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回帰と多様体学習の統合による物体認識と姿勢推定（When Regression Meets Manifold Learning for Object Recognition and Pose Estimation）</news:title>
   <news:publication_date>2026-05-05T05:35:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686656</loc>
  <lastmod>2026-05-05T05:35:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠中の脳波から推定する「脳年齢」とその示唆（Brain Age from the Electroencephalogram of Sleep）</news:title>
   <news:publication_date>2026-05-05T05:35:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686654</loc>
  <lastmod>2026-05-05T05:35:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>薬物服用発言の検出に向けたディープラーニング研究（phramacovigilance - Exploring Deep Learning Techniques for Identifying Mentions of Medication Intake from Twitter）</news:title>
   <news:publication_date>2026-05-05T05:35:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686652</loc>
  <lastmod>2026-05-05T04:43:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリ節約を重視した厳格Very Fast Decision Tree（Strict Very Fast Decision Tree）</news:title>
   <news:publication_date>2026-05-05T04:43:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686650</loc>
  <lastmod>2026-05-05T04:43:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速レチノモルフィックイベント駆動表現による映像認識と強化学習（Fast Retinomorphic Event-Driven Representations for Video Recognition and Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-05T04:43:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686648</loc>
  <lastmod>2026-05-05T04:33:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習のためのProgress &amp;amp; Compress（Progress &amp;amp; Compress: A scalable framework for continual learning）</news:title>
   <news:publication_date>2026-05-05T04:33:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686646</loc>
  <lastmod>2026-05-05T04:32:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測から確率的チャネルモデルを学習する（Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-05T04:32:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686644</loc>
  <lastmod>2026-05-05T04:31:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河の星形成率を機械学習で推定する手法（Stellar formation rates in galaxies using Machine Learning models）</news:title>
   <news:publication_date>2026-05-05T04:31:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686642</loc>
  <lastmod>2026-05-05T04:31:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助タスクを用いたマルチタスク学習の強化（Auxiliary Tasks in Multi-task Learning）</news:title>
   <news:publication_date>2026-05-05T04:31:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686640</loc>
  <lastmod>2026-05-05T04:31:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク学習による細胞内巨視分子の分類・セグメンテーション・粗構造復元（Multi-task Learning for Macromolecule Classification, Segmentation and Coarse Structural Recovery in Cryo-Tomography）</news:title>
   <news:publication_date>2026-05-05T04:31:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686638</loc>
  <lastmod>2026-05-05T03:39:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を取り込むことで対話理解が一段進化する（A Context-based Approach for Dialogue Act Recognition using Simple Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-05T03:39:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686636</loc>
  <lastmod>2026-05-05T03:31:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全教師なしでの単語埋め込みクロスリンガル写像に対する頑健な自己学習法（A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings）</news:title>
   <news:publication_date>2026-05-05T03:31:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686634</loc>
  <lastmod>2026-05-05T03:31:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定曲率多様体上のグラフ埋め込みによるグラフストリームの変化検出 (Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds)</news:title>
   <news:publication_date>2026-05-05T03:31:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686632</loc>
  <lastmod>2026-05-05T03:29:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化非線形変数選択（Structured nonlinear variable selection）</news:title>
   <news:publication_date>2026-05-05T03:29:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686630</loc>
  <lastmod>2026-05-05T03:29:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発話単位注意を用いた双方向RNNによる会話分析（Conversational Analysis using Utterance-level Attention-based Bidirectional Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-05T03:29:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686628</loc>
  <lastmod>2026-05-05T03:29:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動の表現学習（Learning Representations of Spatial Displacement through Sensorimotor Prediction）</news:title>
   <news:publication_date>2026-05-05T03:29:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686626</loc>
  <lastmod>2026-05-05T03:28:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子K近傍法に基づく画像分類（Image Classification Based on Quantum KNN Algorithm）</news:title>
   <news:publication_date>2026-05-05T03:28:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686624</loc>
  <lastmod>2026-05-05T02:36:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常検知の説明に向けて（Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models）</news:title>
   <news:publication_date>2026-05-05T02:36:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686622</loc>
  <lastmod>2026-05-05T02:36:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元時系列データ解析におけるカーネル転移作用素の固有関数利用法（Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions）</news:title>
   <news:publication_date>2026-05-05T02:36:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686620</loc>
  <lastmod>2026-05-05T02:35:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>患者依存性を排した特徴学習のための敵対的訓練（Adversarial Training for Patient-Independent Feature Learning with IVOCT Data for Plaque Classification）</news:title>
   <news:publication_date>2026-05-05T02:35:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686618</loc>
  <lastmod>2026-05-05T02:34:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成非類似度測度とフィンガープリント測位への応用（CDM: Compound dissimilarity measure and an application to fingerprinting-based positioning）</news:title>
   <news:publication_date>2026-05-05T02:34:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686616</loc>
  <lastmod>2026-05-05T02:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量ピラミッドネットワークによる単一画像の雨除去（Lightweight Pyramid Networks for Image Deraining）</news:title>
   <news:publication_date>2026-05-05T02:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686614</loc>
  <lastmod>2026-05-05T02:33:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈的拡張によるテキストデータ増強（Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations）</news:title>
   <news:publication_date>2026-05-05T02:33:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686612</loc>
  <lastmod>2026-05-05T02:32:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多関係ネットワークの構造表現学習（A Structural Representation Learning for Multi-relational Networks）</news:title>
   <news:publication_date>2026-05-05T02:32:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686610</loc>
  <lastmod>2026-05-05T01:41:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNSグラフマイニングにおけるアジリティバイアスの検証（Investigating the Agility Bias in DNS Graph Mining）</news:title>
   <news:publication_date>2026-05-05T01:41:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686608</loc>
  <lastmod>2026-05-05T01:41:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼カメラとコンパクトセマンティックマップによる車両自己位置推定（Monocular Vehicle Self-localization method based on Compact Semantic Map）</news:title>
   <news:publication_date>2026-05-05T01:41:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686606</loc>
  <lastmod>2026-05-05T01:40:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FollowNet：自然言語指示に従うロボット航行（FollowNet: Robot Navigation by Following Natural Language Directions with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-05T01:40:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686604</loc>
  <lastmod>2026-05-05T01:40:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>候補抽出と解答選択の共同学習による読解強化（Joint Training of Candidate Extraction and Answer Selection for Reading Comprehension）</news:title>
   <news:publication_date>2026-05-05T01:40:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686602</loc>
  <lastmod>2026-05-05T01:40:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仮想エッジコンピューティングにおける最適化された計算オフロード性能（Optimized Computation Offloading Performance in Virtual Edge Computing Systems via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-05T01:40:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686600</loc>
  <lastmod>2026-05-05T01:40:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市場の自己学習とインビジブルハンド推論（Market Self-Learning of Signals, Impact and Optimal Trading: Invisible Hand Inference with Free Energy）</news:title>
   <news:publication_date>2026-05-05T01:40:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686598</loc>
  <lastmod>2026-05-05T01:40:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変計量過緩和ハイブリッド近接外勾配法のアルゴリズム枠組み（An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method）</news:title>
   <news:publication_date>2026-05-05T01:40:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686596</loc>
  <lastmod>2026-05-05T00:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴アフィニティに基づく疑似ラベリングによる半教師あり人物再識別（Feature Affinity based Pseudo-Labeling for Semi-supervised Person Re-identification）</news:title>
   <news:publication_date>2026-05-05T00:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686594</loc>
  <lastmod>2026-05-05T00:37:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像ピラミッドでスケールを適応的に融合する群衆カウント法（Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid）</news:title>
   <news:publication_date>2026-05-05T00:37:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686592</loc>
  <lastmod>2026-05-05T00:37:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負テンソル分解に基づく教師なし機械学習による反応性混合解析（Unsupervised Machine Learning Based on Non-Negative Tensor Factorization for Analyzing Reactive-Mixing）</news:title>
   <news:publication_date>2026-05-05T00:37:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686590</loc>
  <lastmod>2026-05-05T00:37:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢でプライバシー保護されたテキスト表現の学習（Towards Robust and Privacy-preserving Text Representations）</news:title>
   <news:publication_date>2026-05-05T00:37:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686588</loc>
  <lastmod>2026-05-05T00:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメインに含まれる要素とは（What’s in a Domain? Learning Domain-Robust Text Representations using Adversarial Training）</news:title>
   <news:publication_date>2026-05-05T00:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686586</loc>
  <lastmod>2026-05-04T23:44:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調的判別器による長文生成の改善（Learning to Write with Cooperative Discriminators）</news:title>
   <news:publication_date>2026-05-04T23:44:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686584</loc>
  <lastmod>2026-05-04T23:44:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ化クリッピング活性化による量子化ニューラルネットワーク（PACT: PARAMETERIZED CLIPPING ACTIVATION FOR QUANTIZED NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-05-04T23:44:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686582</loc>
  <lastmod>2026-05-04T23:44:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーン非依存な人物再識別の評価（An Evaluation of Deep CNN Baselines for Scene-Independent Person Re-Identiﬁcation）</news:title>
   <news:publication_date>2026-05-04T23:44:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686580</loc>
  <lastmod>2026-05-04T23:42:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SoPaによるCNN・RNN・WFSAの橋渡し（SoPa: Bridging CNNs, RNNs, and Weighted Finite-State Machines）</news:title>
   <news:publication_date>2026-05-04T23:42:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686578</loc>
  <lastmod>2026-05-04T23:42:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ケック・ライマン連続スペクトル調査（KLCS）が示す高赤方偏移銀河のイオン化放射（THE KECK LYMAN CONTINUUM SPECTROSCOPIC SURVEY (KLCS): THE EMERGENT IONIZING SPECTRUM OF GALAXIES AT Z ∼3）</news:title>
   <news:publication_date>2026-05-04T23:42:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686576</loc>
  <lastmod>2026-05-04T23:42:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味ターゲット駆動ナビゲーションのための視覚表現（Visual Representations for Semantic Target Driven Navigation）</news:title>
   <news:publication_date>2026-05-04T23:42:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686574</loc>
  <lastmod>2026-05-04T23:41:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Spark-MPIが拓く第5のパラダイム（Spark-MPI: Approaching the Fifth Paradigm of Cognitive Applications）</news:title>
   <news:publication_date>2026-05-04T23:41:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686572</loc>
  <lastmod>2026-05-04T22:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交絡因子の因果効果共変（Causal-effect Covariability of Confounders）</news:title>
   <news:publication_date>2026-05-04T22:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686570</loc>
  <lastmod>2026-05-04T22:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習エージェントは意図をモデル化するか（Do deep reinforcement learning agents model intentions?）</news:title>
   <news:publication_date>2026-05-04T22:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686568</loc>
  <lastmod>2026-05-04T22:48:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移銀河のフィードバックを探る：拡張された紫外線光度関数による検証（Probing feedback in high-z galaxies using extended UV luminosity functions）</news:title>
   <news:publication_date>2026-05-04T22:48:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686566</loc>
  <lastmod>2026-05-04T22:47:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙初期の透明度を測る新しい指標――CHORUSによるz=7でのLyα輝線宇宙論的解析（CHORUS II. SUBARU/HSC DETERMINATION OF THE LYα LUMINOSITY FUNCTION AT Z = 7.0: CONSTRAINTS ON COSMIC REIONIZATION MODEL PARAMETER）</news:title>
   <news:publication_date>2026-05-04T22:47:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686564</loc>
  <lastmod>2026-05-04T22:46:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイグナス領域に対する超高エネルギーγ線サーベイ（A VERY HIGH ENERGY γ-RAY SURVEY TOWARDS THE CYGNUS REGION OF THE GALAXY）</news:title>
   <news:publication_date>2026-05-04T22:46:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686562</loc>
  <lastmod>2026-05-04T22:46:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相秩序を教師なしで識別する方法（Identifying topological order through unsupervised machine learning）</news:title>
   <news:publication_date>2026-05-04T22:46:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686560</loc>
  <lastmod>2026-05-04T22:46:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二足歩行ロボットにおける動的歩行の単純化と制御分解（Dynamic Walking of Legged Machines）</news:title>
   <news:publication_date>2026-05-04T22:46:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686558</loc>
  <lastmod>2026-05-04T21:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深宇宙航法におけるX線パルサを用いた自律ナビゲーションの実現可能性（Feasibility and performance assessment of a practical autonomous deep space navigation system based on X-ray pulsar timing）</news:title>
   <news:publication_date>2026-05-04T21:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686556</loc>
  <lastmod>2026-05-04T21:53:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限状態・有限時間の平均場ゲームと学習収束の橋渡し（Finite mean field games: fictitious play and convergence to a first order continuous mean field game）</news:title>
   <news:publication_date>2026-05-04T21:53:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686554</loc>
  <lastmod>2026-05-04T21:52:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純な堆積モデルから学ぶ普遍性とスケーリング（Learning universality and scaling from simple deposition models）</news:title>
   <news:publication_date>2026-05-04T21:52:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686552</loc>
  <lastmod>2026-05-04T21:51:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Federated Learningにおける匿名性の崩壊とその制御（Understanding and Controlling Deanonymization in Federated Learning）</news:title>
   <news:publication_date>2026-05-04T21:51:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686550</loc>
  <lastmod>2026-05-04T21:51:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推論問題における「ハードフェーズ」のガラス性の解明（On the glassy nature of the hard phase in inference problems）</news:title>
   <news:publication_date>2026-05-04T21:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686548</loc>
  <lastmod>2026-05-04T21:51:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信念の濃淡を扱う社会的学習モデル（Naive Bayesian Learning in Social Networks）</news:title>
   <news:publication_date>2026-05-04T21:51:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686546</loc>
  <lastmod>2026-05-04T20:58:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球を「系外惑星」として観測する実証実験（Using Deep Space Climate Observatory Measurements to Study the Earth as An Exoplanet）</news:title>
   <news:publication_date>2026-05-04T20:58:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686544</loc>
  <lastmod>2026-05-04T20:58:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ信号のサンプリングを強化学習として解く（Graph Signal Sampling via Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-04T20:58:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686542</loc>
  <lastmod>2026-05-04T20:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合音声から直接読み取る 完全エンドツーエンド多人数音声認識（A Purely End-to-end System for Multi-speaker Speech Recognition）</news:title>
   <news:publication_date>2026-05-04T20:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686540</loc>
  <lastmod>2026-05-04T20:56:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子化可能な埋め込み表現の効率的なエンドツーエンド学習（Efficient end-to-end learning for quantizable representations）</news:title>
   <news:publication_date>2026-05-04T20:56:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686538</loc>
  <lastmod>2026-05-04T20:56:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的マルチスケールニューラルネットワークにおける継続学習（Continuous Learning in a Hierarchical Multiscale Neural Network）</news:title>
   <news:publication_date>2026-05-04T20:56:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686536</loc>
  <lastmod>2026-05-04T20:55:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表形式強化学習における人間知の活用（Leveraging human knowledge in tabular reinforcement learning）</news:title>
   <news:publication_date>2026-05-04T20:55:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686534</loc>
  <lastmod>2026-05-04T20:54:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頑健で効率的なグラフ対応転送による人物再識別（Robust and Efficient Graph Correspondence Transfer for Person Re-identification）</news:title>
   <news:publication_date>2026-05-04T20:54:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686532</loc>
  <lastmod>2026-05-04T20:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所鞍点最適化：曲率を利用した脱出手法（Local Saddle Point Optimization: A Curvature Exploitation Approach）</news:title>
   <news:publication_date>2026-05-04T20:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686530</loc>
  <lastmod>2026-05-04T20:00:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内在次元と連関ルールへの応用（Intrinsic dimension and its application to association rules）</news:title>
   <news:publication_date>2026-05-04T20:00:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686528</loc>
  <lastmod>2026-05-04T20:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的に使われる投票規則のプライバシーはどれほどか（How Private Are Commonly-Used Voting Rules?）</news:title>
   <news:publication_date>2026-05-04T20:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686526</loc>
  <lastmod>2026-05-04T20:00:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療文書の連続表現を生成する手法（Generating Continuous Representations of Medical Texts）</news:title>
   <news:publication_date>2026-05-04T20:00:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686524</loc>
  <lastmod>2026-05-04T19:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的適応忘却変分フィルタ（The Hierarchical Adaptive Forgetting Variational Filter）</news:title>
   <news:publication_date>2026-05-04T19:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686522</loc>
  <lastmod>2026-05-04T19:59:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布に基づくラベル空間変換によるマルチラベル学習（Distribution-based Label Space Transformation for Multi-label Learning）</news:title>
   <news:publication_date>2026-05-04T19:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686520</loc>
  <lastmod>2026-05-04T19:06:57Z</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散乱光制御の実用化可能性（Light scattering control with neural networks in transmission and reflection）</news:title>
   <news:publication_date>2026-05-04T19:06:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686518</loc>
  <lastmod>2026-05-04T19:06:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的深層ハッシングのためのセマンティッククラスタ単一損失（Semantic Cluster Unary Loss for Efficient Deep Hashing）</news:title>
   <news:publication_date>2026-05-04T19:06:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686516</loc>
  <lastmod>2026-05-04T19:06:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NEURON: 自然言語で学ぶクエリ最適化（NEURON: Query Optimization Meets Natural Language Processing For Augmenting Database Education）</news:title>
   <news:publication_date>2026-05-04T19:06:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686514</loc>
  <lastmod>2026-05-04T19:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歪みに強い注目領域分割を実現するメトリック表現ネットワーク（Ro-SOS: Metric Expression Network for Robust Salient Object Segmentation）</news:title>
   <news:publication_date>2026-05-04T19:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686512</loc>
  <lastmod>2026-05-04T19:04:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロストラクチャ雑音下における非パラメトリックベイズ的ボラティリティ学習（Nonparametric Bayesian volatility learning under microstructure noise）</news:title>
   <news:publication_date>2026-05-04T19:04:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686510</loc>
  <lastmod>2026-05-04T19:04:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>悪意あるスクリプトのニューラル分類（Neural Classification of Malicious Scripts）</news:title>
   <news:publication_date>2026-05-04T19:04:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686508</loc>
  <lastmod>2026-05-04T19:04:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多モードファイバーを透かして見る学習（Learning to see through multimode fibers）</news:title>
   <news:publication_date>2026-05-04T19:04:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686506</loc>
  <lastmod>2026-05-04T18:13:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文体に敏感な単語ベクトルの教師なし学習（Unsupervised Learning of Style-sensitive Word Vectors）</news:title>
   <news:publication_date>2026-05-04T18:13:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686504</loc>
  <lastmod>2026-05-04T18:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正規表現とニューラルネットワークの結婚（Marrying Up Regular Expressions with Neural Networks）</news:title>
   <news:publication_date>2026-05-04T18:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686502</loc>
  <lastmod>2026-05-04T18:00:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Facebook投稿の影響度予測（Prediction of Facebook Post Metrics using Machine Learning）</news:title>
   <news:publication_date>2026-05-04T18:00:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686500</loc>
  <lastmod>2026-05-04T18:00:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセットが別でも学べる“つなぐ”設計――クロス接続ネットワークの可能性（Cross-connected Networks for Multi-task Learning of Detection and Segmentation）</news:title>
   <news:publication_date>2026-05-04T18:00:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686498</loc>
  <lastmod>2026-05-04T18:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔のランドマーク検出の体系的レビュー（Facial Landmark Detection: a Literature Survey）</news:title>
   <news:publication_date>2026-05-04T18:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686496</loc>
  <lastmod>2026-05-04T18:00:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響ランドマークを用いた多目的学習による資源乏しい言語のASR改善（Improved ASR for Under-Resourced Languages Through Multi-Task Learning with Acoustic Landmarks）</news:title>
   <news:publication_date>2026-05-04T18:00:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686494</loc>
  <lastmod>2026-05-04T17:08:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>世代学習で育てる深層ニューラルネットワーク（Training Deep Neural Networks in Generations: A More Tolerant Teacher Educates Better Students）</news:title>
   <news:publication_date>2026-05-04T17:08:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686492</loc>
  <lastmod>2026-05-04T17:00:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軌道フェッシュバッハ共鳴を用いた希土類フェルミ気体の単粒子励起と強結合効果（Single-particle Excitations and Strong Coupling Effects in the BCS-BEC Crossover Regime of a Rare-Earth Fermi Gas with an Orbital Feshbach Resonance）</news:title>
   <news:publication_date>2026-05-04T17:00:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686490</loc>
  <lastmod>2026-05-04T17:00:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文章の簡素化を行うSeq2Seqモデル（Simplifying Sentences with Sequence to Sequence Models）</news:title>
   <news:publication_date>2026-05-04T17:00:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686488</loc>
  <lastmod>2026-05-04T16:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核内EMC効果をΛ/¯Λ生成で探る—半包含型深部非弾性散乱による差別化の提案 (Nuclear EMC effect through ¯Λ/Λ production in semi-inclusive deep-inelastic scattering processes)</news:title>
   <news:publication_date>2026-05-04T16:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686486</loc>
  <lastmod>2026-05-04T16:58:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔と声の対応を学習する方法（On Learning Associations of Faces and Voices）</news:title>
   <news:publication_date>2026-05-04T16:58:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686484</loc>
  <lastmod>2026-05-04T16:58:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ニューラルネットワークによるロボットの新奇動作生成（A Dynamic Neural Network Approach to Generating Robot’s Novel Actions: A Simulation Experiment）</news:title>
   <news:publication_date>2026-05-04T16:58:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686482</loc>
  <lastmod>2026-05-04T16:57:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Radio Galaxy Zoo におけるラジオ源の銀河ホスト同定と機械学習による自動化（Radio Galaxy Zoo: Machine learning for radio source host galaxy cross-identification）</news:title>
   <news:publication_date>2026-05-04T16:57:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686480</loc>
  <lastmod>2026-05-04T16:06:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定境界を支持する敵対的サンプルを用いた知識蒸留（Knowledge Distillation with Adversarial Samples Supporting Decision Boundary）</news:title>
   <news:publication_date>2026-05-04T16:06:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686478</loc>
  <lastmod>2026-05-04T16:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験再生の進歩（Advances in Experience Replay）</news:title>
   <news:publication_date>2026-05-04T16:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686476</loc>
  <lastmod>2026-05-04T16:06:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識におけるパッチ間相関を学習する完全結合型1対Nマッチング手法（Fully Associative Patch-based 1-to-N Matcher for Face Recognition）</news:title>
   <news:publication_date>2026-05-04T16:06:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686474</loc>
  <lastmod>2026-05-04T16:05:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車両軌跡予測における畳み込みソーシャルプーリングの意義（Convolutional Social Pooling for Vehicle Trajectory Prediction）</news:title>
   <news:publication_date>2026-05-04T16:05:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686472</loc>
  <lastmod>2026-05-04T16:04:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形次元削減による複数データセットの判別分析（Nonlinear Dimensionality Reduction for Discriminative Analytics of Multiple Datasets）</news:title>
   <news:publication_date>2026-05-04T16:04:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686470</loc>
  <lastmod>2026-05-04T16:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインメトリック学習の多層フレームワーク（A Multilayer Framework for Online Metric Learning）</news:title>
   <news:publication_date>2026-05-04T16:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686468</loc>
  <lastmod>2026-05-04T16:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔画像のブレ除去を学ぶ（Learning to Deblur Images with Exemplars）</news:title>
   <news:publication_date>2026-05-04T16:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686466</loc>
  <lastmod>2026-05-04T15:12:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的多様性が情報カスケードを抑える仕組み（Social diversity for reducing the impact of information cascades on social learning）</news:title>
   <news:publication_date>2026-05-04T15:12:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686464</loc>
  <lastmod>2026-05-04T15:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルは本当に「質問」を理解しているか（Did the Model Understand the Question?）</news:title>
   <news:publication_date>2026-05-04T15:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686462</loc>
  <lastmod>2026-05-04T15:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Crowdbreaksによる公衆衛生トレンド追跡（Crowdbreaks: Tracking Health Trends using Public Social Media Data and Crowdsourcing）</news:title>
   <news:publication_date>2026-05-04T15:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686460</loc>
  <lastmod>2026-05-04T15:09:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑高次元データと限られたシミュレーション下の近似ベイズ計算に向けて（ABC-CDE: Towards Approximate Bayesian Computation with Complex High-Dimensional Data and Limited Simulations）</news:title>
   <news:publication_date>2026-05-04T15:09:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686458</loc>
  <lastmod>2026-05-04T15:09:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同質的リーマン多様体上のCNNとその神経画像への応用（A CNN for homogeneous Riemannian manifolds with applications to Neuroimaging）</news:title>
   <news:publication_date>2026-05-04T15:09:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686456</loc>
  <lastmod>2026-05-04T15:07:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SkyLensによる重力レンズ像シミュレーションの実務的意義（Image simulations for gravitational lensing with SkyLens）</news:title>
   <news:publication_date>2026-05-04T15:07:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686454</loc>
  <lastmod>2026-05-04T15:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Schema.org Actionsによる機械可読Web API（Machine Readable Web APIs with Schema.org Action Annotations）</news:title>
   <news:publication_date>2026-05-04T15:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686452</loc>
  <lastmod>2026-05-04T14:15:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウェアラブルの音声とIMUを融合したショット検出（WEARABLE AUDIO AND IMU BASED SHOT DETECTION IN RACQUET SPORTS）</news:title>
   <news:publication_date>2026-05-04T14:15:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686450</loc>
  <lastmod>2026-05-04T14:12:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランキング説明の忠実な手法（Faithfully Explaining Rankings in a News Recommender System）</news:title>
   <news:publication_date>2026-05-04T14:12:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686448</loc>
  <lastmod>2026-05-04T14:11:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー効率の高いハダマードニューラルネットワーク（Energy Efficient Hadamard Neural Networks）</news:title>
   <news:publication_date>2026-05-04T14:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686446</loc>
  <lastmod>2026-05-04T14:09:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意を取り入れた構造表現学習が変える視覚認識（Deep Attentional Structured Representation Learning for Visual Recognition）</news:title>
   <news:publication_date>2026-05-04T14:09:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686444</loc>
  <lastmod>2026-05-04T14:09:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼度スコアの白箱メタモデルと線形分類器プローブ（Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes）</news:title>
   <news:publication_date>2026-05-04T14:09:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686442</loc>
  <lastmod>2026-05-04T14:09:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>A La Carte Embeddingの実務的意義（A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors）</news:title>
   <news:publication_date>2026-05-04T14:09:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686440</loc>
  <lastmod>2026-05-04T14:08:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脊椎動物パラログにおける「親－子」関係の深い歴史の再構築（Reconstruction of the deep history of “Parent-Daughter” relationships among vertebrate paralogs）</news:title>
   <news:publication_date>2026-05-04T14:08:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686438</loc>
  <lastmod>2026-05-04T13:15:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間ベイズ・オンライン変化点検出とモデル選択（Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection）</news:title>
   <news:publication_date>2026-05-04T13:15:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686436</loc>
  <lastmod>2026-05-04T13:14:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AMORE-UPFのBiLSTMとエンティティライブラリ（AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library）</news:title>
   <news:publication_date>2026-05-04T13:14:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686434</loc>
  <lastmod>2026-05-04T13:14:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師ありデータで肺結節を検出するDeepEM（DeepEM: Deep 3D ConvNets With EM For Weakly Supervised Pulmonary Nodule Detection）</news:title>
   <news:publication_date>2026-05-04T13:14:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686432</loc>
  <lastmod>2026-05-04T13:12:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NASH: 生成的セマンティックハッシュのためのエンドツーエンドニューラルアーキテクチャ（NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing）</news:title>
   <news:publication_date>2026-05-04T13:12:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686430</loc>
  <lastmod>2026-05-04T13:12:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ALMAによるSCUBA-2サーベイのz∼4.5 [C II]候補検出（AN ALMA SURVEY OF THE SCUBA-2 COSMOLOGY LEGACY SURVEY UKIDSS/UDS FIELD: IDENTIFYING CANDIDATE z ∼4.5 [C II] EMITTERS）</news:title>
   <news:publication_date>2026-05-04T13:12:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686428</loc>
  <lastmod>2026-05-04T13:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ALMAによるSCUBA-2コスモロジーサーベイUDS領域のサブミリ波銀河数カウント（An ALMA survey of the SCUBA-2 Cosmology Legacy Survey UKIDSS/UDS field: Number counts of submillimeter galaxies）</news:title>
   <news:publication_date>2026-05-04T13:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686426</loc>
  <lastmod>2026-05-04T13:11:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SAR ATRのための検証支援付きCNN「SAVERS」の提案（SAR ATR with verification support (SAVERS))</news:title>
   <news:publication_date>2026-05-04T13:11:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686424</loc>
  <lastmod>2026-05-04T12:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データと人間の知見を活かした野生動物密猟予測（Exploiting Data and Human Knowledge for Predicting Wildlife Poaching）</news:title>
   <news:publication_date>2026-05-04T12:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686422</loc>
  <lastmod>2026-05-04T12:18:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化された材料特性計算の体系化（Automated computation of materials properties）</news:title>
   <news:publication_date>2026-05-04T12:18:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686420</loc>
  <lastmod>2026-05-04T12:17:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cycle-Dehazeによる単一画像のデヘイズ（Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing）</news:title>
   <news:publication_date>2026-05-04T12:17:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686418</loc>
  <lastmod>2026-05-04T12:16:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正規類似ネットワークによる生成モデリング（Normal Similarity Network for Generative Modelling）</news:title>
   <news:publication_date>2026-05-04T12:16:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686416</loc>
  <lastmod>2026-05-04T12:16:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子イオンコライダーで探るグルーオン・シベルス関数（Accessing the Gluon Sivers Function at a future Electron-Ion Collider）</news:title>
   <news:publication_date>2026-05-04T12:16:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686414</loc>
  <lastmod>2026-05-04T12:16:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>費用対効果の高い選好取得と集約の枠組み（A Cost-Effective Framework for Preference Elicitation and Aggregation）</news:title>
   <news:publication_date>2026-05-04T12:16:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686412</loc>
  <lastmod>2026-05-04T12:15:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電波宇宙の実践的シミュレーションが示したもの（The Tiered Radio Extragalactic Continuum Simulation (T-RECS)）</news:title>
   <news:publication_date>2026-05-04T12:15:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686410</loc>
  <lastmod>2026-05-04T11:24:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepMutation: 深層学習のためのミューテーションテスト（DeepMutation: Mutation Testing of Deep Learning Systems）</news:title>
   <news:publication_date>2026-05-04T11:24:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686408</loc>
  <lastmod>2026-05-04T11:23:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SHADE：情報ベースの正則化による深層学習の安定化（SHADE: INFORMATION-BASED REGULARIZATION FOR DEEP LEARNING）</news:title>
   <news:publication_date>2026-05-04T11:23:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686406</loc>
  <lastmod>2026-05-04T11:22:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変再構成可能な可視ナノフォトニクスによる深部脳神経刺激の新展開（A Reconfigurable Nanophotonics Platform for Sub-Millisecond, Deep Brain Neural Stimulation）</news:title>
   <news:publication_date>2026-05-04T11:22:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686404</loc>
  <lastmod>2026-05-04T11:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>決定木を組み込んだGANで学習を安定化する手法（Generative Adversarial Forests for Better Conditioned Adversarial Learning）</news:title>
   <news:publication_date>2026-05-04T11:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686402</loc>
  <lastmod>2026-05-04T11:20:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン適応における敵対的学習とグラフ埋め込みの統合（Domain Adaptation with Adversarial Training and Graph Embeddings）</news:title>
   <news:publication_date>2026-05-04T11:20:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686400</loc>
  <lastmod>2026-05-04T11:20:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情文の“翻訳”を非対向データで実現する方法（Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-05-04T11:20:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686398</loc>
  <lastmod>2026-05-04T11:20:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハリケーン災害時のTwitterデータ分析が示した実務的知見（A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria）</news:title>
   <news:publication_date>2026-05-04T11:20:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686396</loc>
  <lastmod>2026-05-04T10:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルネットワークにおける不正ドローン検知の機械学習的アプローチ（Rogue Drone Detection: A Machine Learning Approach）</news:title>
   <news:publication_date>2026-05-04T10:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686394</loc>
  <lastmod>2026-05-04T10:27:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な単一ショット3D細胞追跡を実現する深層学習法（Fast 3D cell tracking with wide-field fluorescence microscopy through deep learning）</news:title>
   <news:publication_date>2026-05-04T10:27:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686392</loc>
  <lastmod>2026-05-04T10:26:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモード光ファイバーを深層学習で制御する（Multimode Optical Fiber Transmission with a Deep Learning Network）</news:title>
   <news:publication_date>2026-05-04T10:26:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686390</loc>
  <lastmod>2026-05-04T10:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Functional Baby Talk: 初学者Haskellコードの誤り分析（Functional Baby Talk: Analysis of Code Fragments from Novice Haskell Programmers）</news:title>
   <news:publication_date>2026-05-04T10:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686388</loc>
  <lastmod>2026-05-04T10:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル処理を学ぶ構造的帰納法の入門（Vector Programming Using Structural Recursion）</news:title>
   <news:publication_date>2026-05-04T10:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686386</loc>
  <lastmod>2026-05-04T10:25:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Garrett近似を用いた非対称矩形井戸のエネルギー近似と応用（Garrett approximation for asymmetric rectangular potentials and its applications to quantum well infrared photodetectors）</news:title>
   <news:publication_date>2026-05-04T10:25:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686384</loc>
  <lastmod>2026-05-04T10:24:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lasso-Zeroによるモデル選択：過剰適合と閾値で針を見つける（Model selection with Lasso-Zero: adding straw to the haystack to better find needles）</news:title>
   <news:publication_date>2026-05-04T10:24:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686382</loc>
  <lastmod>2026-05-04T09:33:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェア・ソフトウェア協調によるニューラルネットワーク攻撃フレームワーク（Hu-Fu: Hardware and Software Collaborative Attack Framework against Neural Networks）</news:title>
   <news:publication_date>2026-05-04T09:33:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686380</loc>
  <lastmod>2026-05-04T09:31:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>σ Orionis星団の視差と固有運動の網羅的測定（Parallactic distances and proper motions of virtually all stars in the σ Orionis cluster）</news:title>
   <news:publication_date>2026-05-04T09:31:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686378</loc>
  <lastmod>2026-05-04T09:31:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rによるハイパースペクトルデータ解析を現場へ橋渡しするhsdarの意義（hsdar: Hyperspectral Data Analysis in R）</news:title>
   <news:publication_date>2026-05-04T09:31:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686376</loc>
  <lastmod>2026-05-04T09:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Atlas Location Autocontextによる3D CTランドマーク検出の到達点（Attaining human-level performance with atlas location autocontext for anatomical landmark detection in 3D CT data）</news:title>
   <news:publication_date>2026-05-04T09:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686374</loc>
  <lastmod>2026-05-04T09:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物語的イベント進化グラフによる脚本イベント予測（Constructing Narrative Event Evolutionary Graph for Script Event Prediction）</news:title>
   <news:publication_date>2026-05-04T09:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686372</loc>
  <lastmod>2026-05-04T09:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KL-UCB-Switchの二重最適性（KL-UCB-Switch: Optimal Regret Bounds for Stochastic Bandits from Both a Distribution-Dependent and a Distribution-Free Viewpoints）</news:title>
   <news:publication_date>2026-05-04T09:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686370</loc>
  <lastmod>2026-05-04T09:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生映像から学ぶ直感的物理学（Unsupervised Intuitive Physics from Visual Observations）</news:title>
   <news:publication_date>2026-05-04T09:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686368</loc>
  <lastmod>2026-05-04T08:38:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラッソを用いた処置効果推定の有限標本性能（The Finite Sample Performance of Treatment Effects Estimators based on the Lasso）</news:title>
   <news:publication_date>2026-05-04T08:38:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686366</loc>
  <lastmod>2026-05-04T08:38:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子QCDとハミルトン有効場理論による核子励起状態の解析（Nucleon Excited States from Lattice QCD and Hamiltonian Effective Field Theory）</news:title>
   <news:publication_date>2026-05-04T08:38:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686364</loc>
  <lastmod>2026-05-04T08:38:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河団強レンズ像が示す超大質量ブラックホールの直接測定（A LIKELY SUPER MASSIVE BLACK HOLE REVEALED BY ITS EINSTEIN RADIUS IN HUBBLE FRONTIER FIELDS IMAGES）</news:title>
   <news:publication_date>2026-05-04T08:38:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686362</loc>
  <lastmod>2026-05-04T08:38:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分ベイズによる混合モデルの推定とモデル選択の一貫性（Consistency of Variational Bayes Inference for Estimation and Model Selection in Mixtures）</news:title>
   <news:publication_date>2026-05-04T08:38:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686360</loc>
  <lastmod>2026-05-04T08:37:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密度推定に基づくワン・クラス決定木（A One-Class Classification Decision Tree Based on Kernel Density Estimation）</news:title>
   <news:publication_date>2026-05-04T08:37:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686358</loc>
  <lastmod>2026-05-04T08:36:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を備えた深層学習による自動睡眠段階分類（A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification）</news:title>
   <news:publication_date>2026-05-04T08:36:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686356</loc>
  <lastmod>2026-05-04T08:36:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習の基礎と実務的理解（Machine Learning: The Basics）</news:title>
   <news:publication_date>2026-05-04T08:36:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686354</loc>
  <lastmod>2026-05-04T07:44:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DualCNNによる低レベルビジョンの再定義（Learning Dual Convolutional Neural Networks for Low-Level Vision）</news:title>
   <news:publication_date>2026-05-04T07:44:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686352</loc>
  <lastmod>2026-05-04T07:44:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジェネレーターネットワークによるActive Appearance Model再現（Replicating Active Appearance Model by Generator Network）</news:title>
   <news:publication_date>2026-05-04T07:44:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686350</loc>
  <lastmod>2026-05-04T07:43:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変化に敏感な敵対的サンプルを見抜く――Mutation Testingによる検知法（Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing）</news:title>
   <news:publication_date>2026-05-04T07:43:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686348</loc>
  <lastmod>2026-05-04T07:43:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>避難訓練における没入型バーチャルリアリティを活用したシリアスゲームの体系的レビュー（Immersive Virtual Reality Serious Games for Evacuation Training and Research: A Systematic Literature Review）</news:title>
   <news:publication_date>2026-05-04T07:43:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686346</loc>
  <lastmod>2026-05-04T07:43:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的マルチエージェント軌跡からの識別的辞書学習のための深い決定木（Deep Decision Trees for Discriminative Dictionary Learning with Adversarial Multi-Agent Trajectories）</news:title>
   <news:publication_date>2026-05-04T07:43:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686344</loc>
  <lastmod>2026-05-04T07:43:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ショックとICMEの複合構造が地磁気嵐を増幅する仕組み（Why the Shock-ICME Complex Structure is Important: Learning From the Early 2007 September CMEs）</news:title>
   <news:publication_date>2026-05-04T07:43:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686342</loc>
  <lastmod>2026-05-04T06:51:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語と構文が紡ぐ仮説──子どもの語学習における統語–意味のオーバーハイポセシス（Word learning and the acquisition of syntactic–semantic overhypotheses）</news:title>
   <news:publication_date>2026-05-04T06:51:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686340</loc>
  <lastmod>2026-05-04T06:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノードの“中身”を埋め込む時代へ — 異種ネットワークのためのコンテント対応表現学習（CARL: Content-Aware Representation Learning for Heterogeneous Networks）</news:title>
   <news:publication_date>2026-05-04T06:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686338</loc>
  <lastmod>2026-05-04T06:51:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多次元周期カーネルを近似する指標集合フーリエ級数特徴（Index Set Fourier Series Features for Approximating Multi-dimensional Periodic Kernels）</news:title>
   <news:publication_date>2026-05-04T06:51:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686336</loc>
  <lastmod>2026-05-04T06:50:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存の学習済み深層ニューラルネットワークの統合とマージ（Unifying and Merging Well-trained Deep Neural Networks for Inference Stage）</news:title>
   <news:publication_date>2026-05-04T06:50:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686334</loc>
  <lastmod>2026-05-04T06:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非矩形スキャンにおける走査透過電子顕微鏡の圧縮センシング（Compressed Sensing of Scanning Transmission Electron Microscopy (STEM) on Non-Rectangular Scans）</news:title>
   <news:publication_date>2026-05-04T06:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686332</loc>
  <lastmod>2026-05-04T06:49:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAP推論におけるメッセージ伝播の高速化とBenders分解（Accelerating Message Passing for MAP with Benders Decomposition）</news:title>
   <news:publication_date>2026-05-04T06:49:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686330</loc>
  <lastmod>2026-05-04T06:49:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列戦略関係を学習する生成的敵対的模倣学習（Learning Temporal Strategic Relationships using Generative Adversarial Imitation Learning）</news:title>
   <news:publication_date>2026-05-04T06:49:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686328</loc>
  <lastmod>2026-05-04T05:58:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>浅い線形ニューラルネットワークの最適化幾何学（The Global Optimization Geometry of Shallow Linear Neural Networks）</news:title>
   <news:publication_date>2026-05-04T05:58:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686326</loc>
  <lastmod>2026-05-04T05:50:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低域通過リカレントニューラルネットワーク（Low-pass Recurrent Neural Networks – A memory architecture for longer-term correlation discovery）</news:title>
   <news:publication_date>2026-05-04T05:50:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686324</loc>
  <lastmod>2026-05-04T05:50:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dセマンティック地図を用いた同時自己位置推定とセグメンテーション（DeLS-3D: Deep Localization and Segmentation with a 3D Semantic Map）</news:title>
   <news:publication_date>2026-05-04T05:50:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686322</loc>
  <lastmod>2026-05-04T05:50:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像改ざん検出のためのリッチ特徴学習（Learning Rich Features for Image Manipulation Detection）</news:title>
   <news:publication_date>2026-05-04T05:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686320</loc>
  <lastmod>2026-05-04T05:48:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像キャプショニング（Image Captioning）</news:title>
   <news:publication_date>2026-05-04T05:48:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686318</loc>
  <lastmod>2026-05-04T05:48:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dyna：確率的最適化のための運動量法（Dyna: A Method of Momentum for Stochastic Optimization）</news:title>
   <news:publication_date>2026-05-04T05:48:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686316</loc>
  <lastmod>2026-05-04T05:47:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不可能を可能にする理由：ニューラルネットワークはなぜ学習できるのか（Doing the impossible: Why neural networks can be trained at all）</news:title>
   <news:publication_date>2026-05-04T05:47:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686314</loc>
  <lastmod>2026-05-04T04:55:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張可能なニューラル行列補完（EXTENDABLE NEURAL MATRIX COMPLETION）</news:title>
   <news:publication_date>2026-05-04T04:55:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-04T04:44:55Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-04T04:44:55Z</news:publication_date>
   <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>
   </news:publication>
   <news:title>異種走行データベースの統合を目指す研究──交通プリミティブによるデータ統一（A Tempt to Unify Heterogeneous Driving Databases using Traffic Primitives）</news:title>
   <news:publication_date>2026-05-04T04:44:47Z</news:publication_date>
   <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>
   </news:publication>
   <news:title>Lehmer変換とその理論的性質（Lehmer Transform and Its Theoretical Properties）</news:title>
   <news:publication_date>2026-05-04T04:44:33Z</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>氷嵐を計算で捉える枠組み（A Computational Framework for Modelling and Analyzing Ice Storms）</news:title>
   <news:publication_date>2026-05-04T04:43:00Z</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>深層強化学習による非線形微分方程式の一般解法（General solutions for nonlinear differential equations: a rule-based self-learning approach using deep reinforcement learning）</news:title>
   <news:publication_date>2026-05-04T03:52:02Z</news:publication_date>
   <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>
   </news:publication>
   <news:title>共同検出とクラスタリングによるニューラル共参照解決（Neural Coreference Resolution with Deep Biaffine Attention by Joint Mention Detection and Mention Clustering）</news:title>
   <news:publication_date>2026-05-04T03:51:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/686300</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>Spark-MPIによる準リアルタイム処理パイプラインの構築（Building Near-Real-Time Processing Pipelines with the Spark-MPI Platform）</news:title>
   <news:publication_date>2026-05-04T03:50:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686298</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>クエリ応答のためのオンザフライ表生成（On-the-fly Table Generation）</news:title>
   <news:publication_date>2026-05-04T03:50:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686296</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字列カーネルで方言を見抜く手法の勝因（UnibucKernel Reloaded）</news:title>
   <news:publication_date>2026-05-04T03:50:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686294</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>要約自己符号化器による表現監督 — Chinese Social Media Text Summarization（Autoencoder as Assistant Supervisor: Improving Text Representation for Chinese Social Media Text Summarization）</news:title>
   <news:publication_date>2026-05-04T02:58:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686292</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>顔表情認識のための共分散プーリング（Covariance Pooling for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-05-04T02:58:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686290</loc>
  <lastmod>2026-05-04T02:57:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門家は皆同じくらい優れているか？アナリスト業績予測の評価（Are All Experts Equally Good? A Study of Analyst Earnings Estimates）</news:title>
   <news:publication_date>2026-05-04T02:57:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/686288</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>ソフトウェア工学における深層学習の実務的意義（Deep Learning in Software Engineering）</news:title>
   <news:publication_date>2026-05-04T02:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンドメイン対話システムにおける質問生成の型付きデコーダ学習（Learning to Ask Questions in Open-domain Conversational Systems with Typed Decoders）</news:title>
   <news:publication_date>2026-05-04T02:56:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686284</loc>
  <lastmod>2026-05-04T02:04:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的品揃え最適化の最適方策（An Optimal Policy for Dynamic Assortment Planning Under Uncapacitated Multinomial Logit Models）</news:title>
   <news:publication_date>2026-05-04T02:04:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-04T01:58:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-04T01:57:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Zero-Shot Dialog Generation with Cross-Domain Latent Actions（Zero-Shot Dialog Generation with Cross-Domain Latent Actions）</news:title>
   <news:publication_date>2026-05-04T01:57:52Z</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>カリキュラム敵対的訓練（Curriculum Adversarial Training）</news:title>
   <news:publication_date>2026-05-04T01:57:12Z</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>述語と項を同時に予測するニューラル意味役割付与（Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling）</news:title>
   <news:publication_date>2026-05-04T01:55:36Z</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>機械学習のための引用データセットと参照文字列からの要素抽出（Citation Data-set for Machine Learning Citation Styles and Entity Extraction from Citation Strings）</news:title>
   <news:publication_date>2026-05-04T01:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学物理教育における学習の公平性を問う（Equity in College Physics Student Learning: a Critical Quantitative Intersectionality Investigation）</news:title>
   <news:publication_date>2026-05-04T01:55:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686270</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>セマンティックセグメンテーションにおける畳み込みCRFの実用化（Convolutional CRFs for Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-04T01:02:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686268</loc>
  <lastmod>2026-05-04T01:02:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形計量学習の滑らかな合成手法（Nonlinear Metric Learning through Geodesic Interpolation within Lie Groups）</news:title>
   <news:publication_date>2026-05-04T01:02:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686266</loc>
  <lastmod>2026-05-04T01:01:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リモート視線推定のための眼領域ランドマーク学習（Learning to Find Eye Region Landmarks for Remote Gaze Estimation in Unconstrained Settings）</news:title>
   <news:publication_date>2026-05-04T01:01:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686264</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>DropoutとHamiltonian Monte Carloによる予測不確実性の改善（Improving Predictive Uncertainty Estimation using Dropout – Hamiltonian Monte Carlo）</news:title>
   <news:publication_date>2026-05-04T00:59:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686262</loc>
  <lastmod>2026-05-04T00:59:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純で効果的なモデルベースの変数重要度指標（A Simple and Effective Model-Based Variable Importance Measure）</news:title>
   <news:publication_date>2026-05-04T00:59:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-04T00:59:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生まれ変わるニューラルネットワーク（Born-Again Neural Networks）</news:title>
   <news:publication_date>2026-05-04T00:59:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686258</loc>
  <lastmod>2026-05-04T00:58:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドを使った増分学習フレームワーク（Incremental Learning Framework Using Cloud Computing）</news:title>
   <news:publication_date>2026-05-04T00:58:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686256</loc>
  <lastmod>2026-05-04T00:07:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習と認知アーキテクチャによるリアルタイム再スケジューリング（Generating Rescheduling Knowledge using Reinforcement Learning in a Cognitive Architecture）</news:title>
   <news:publication_date>2026-05-04T00:07:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SOARを用いたリアルタイム再スケジューリングの認知的アプローチ（A Cognitive Approach to Real-time Rescheduling using SOAR-RL）</news:title>
   <news:publication_date>2026-05-04T00:06:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686252</loc>
  <lastmod>2026-05-04T00:05:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張されたコンテンツベースの特徴エンジニアリングパイプライン（EXTENDED PIPELINE FOR CONTENT-BASED FEATURE ENGINEERING IN MUSIC GENRE RECOGNITION）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-05-04T00:04:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同意率初期化最尤推定器による分類器アンサンブルの統合（Agreement Rate Initialized Maximum Likelihood Estimator for Ensemble Classifier Aggregation and Its Application in Brain-Computer Interface）</news:title>
   <news:publication_date>2026-05-04T00:04:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686248</loc>
  <lastmod>2026-05-04T00:04:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGを用いた運転者の眠気推定とEBMAL（Enhanced Batch-Mode Active Learning）</news:title>
   <news:publication_date>2026-05-04T00:04:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686246</loc>
  <lastmod>2026-05-04T00:04:03Z</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BCIキャリブレーションのための能動半教師付き転移学習（Active Semi-supervised Transfer Learning (ASTL) for Offline BCI Calibration）</news:title>
   <news:publication_date>2026-05-04T00:04:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習のハイパーパラメータ自動設定（Towards Autonomous Reinforcement Learning: Automatic Setting of Hyper-parameters using Bayesian Optimization）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>外れ値は協調学習を台無しにするか（Do Outliers Ruin Collaboration?）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/686240</loc>
  <lastmod>2026-05-03T23:03:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回帰問題のプール型逐次能動学習（Pool-Based Sequential Active Learning for Regression）</news:title>
   <news:publication_date>2026-05-03T23:03:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686238</loc>
  <lastmod>2026-05-03T23:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体中心とシーン中心のCNN特徴の相補性がもたらす変化（Exploring object-centric and scene-centric CNN features and their complementarity for human rights violations recognition in images）</news:title>
   <news:publication_date>2026-05-03T23:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686236</loc>
  <lastmod>2026-05-03T23:00:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様性を備えた自動運転データセット BDD100K（BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning）</news:title>
   <news:publication_date>2026-05-03T23:00:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686234</loc>
  <lastmod>2026-05-03T23:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウシアン混合ラテントベクトル文法（Gaussian Mixture Latent Vector Grammars）</news:title>
   <news:publication_date>2026-05-03T23:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686232</loc>
  <lastmod>2026-05-03T23:00:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門家の選好で学ぶタスク転移（Task Transfer by Preference-Based Cost Learning）</news:title>
   <news:publication_date>2026-05-03T23:00:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686230</loc>
  <lastmod>2026-05-03T22:08:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>方向認識型空間コンテキスト特徴による影検出と除去（Direction-aware Spatial Context Features for Shadow Detection and Removal）</news:title>
   <news:publication_date>2026-05-03T22:08:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686228</loc>
  <lastmod>2026-05-03T22:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AdvEntuRe: 知識誘導型生成を用いたテキスト含意の敵対的学習（AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples）</news:title>
   <news:publication_date>2026-05-03T22:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686226</loc>
  <lastmod>2026-05-03T22:00:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般相対論的磁気流体力学シミュレーションによる相対論的ジェットの多波長観測（Multiwavelength Observations of Relativistic Jets from General Relativistic Magnetohydrodynamic Simulations）</news:title>
   <news:publication_date>2026-05-03T22:00:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686224</loc>
  <lastmod>2026-05-03T21:59:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間層にある構造的なargmaxを逆伝播する手法：SPIGOTの実用的意義（Backpropagating through Structured Argmax using a SPIGOT）</news:title>
   <news:publication_date>2026-05-03T21:59:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686222</loc>
  <lastmod>2026-05-03T21:58:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明瞭化質問のランク付けで対話の質を上げる（Learning to Ask Good Questions: Ranking Clarification Questions using Neural Expected Value of Perfect Information）</news:title>
   <news:publication_date>2026-05-03T21:58:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686220</loc>
  <lastmod>2026-05-03T21:57:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によって変わる「知覚」の神経基盤（Neural correlates of learned categorical perception）</news:title>
   <news:publication_date>2026-05-03T21:57:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686218</loc>
  <lastmod>2026-05-03T21:06:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム性で敵対的転送性を壊す（Breaking Transferability of Adversarial Samples with Randomness）</news:title>
   <news:publication_date>2026-05-03T21:06:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686216</loc>
  <lastmod>2026-05-03T21:06:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>硬い粒子の運動における初期境界値問題 II：非一意性に関する研究 (On the Initial Boundary-Value Problem in the Kinetic Theory of Hard Particles II: Non-uniqueness)</news:title>
   <news:publication_date>2026-05-03T21:06:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686214</loc>
  <lastmod>2026-05-03T21:06:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterユーザーの位置推定を深層マルチビュー学習で行う（Twitter User Geolocation using Deep Multiview Learning）</news:title>
   <news:publication_date>2026-05-03T21:06:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686212</loc>
  <lastmod>2026-05-03T21:05:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠測値を含むロジスティック回帰の統一的扱い（Logistic Regression with Missing Covariates – Parameter Estimation, Model Selection and Prediction within a Joint-Modeling Framework）</news:title>
   <news:publication_date>2026-05-03T21:05:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686210</loc>
  <lastmod>2026-05-03T21:05:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速で確率的なディフェオモルフィック画像登録の無監督学習（Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration）</news:title>
   <news:publication_date>2026-05-03T21:05:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686208</loc>
  <lastmod>2026-05-03T21:05:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重埋め込みとCNNによるアスペクト抽出（Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction）</news:title>
   <news:publication_date>2026-05-03T21:05:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686206</loc>
  <lastmod>2026-05-03T21:04:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト領域で「問い合わせ生成」を行う手法の要点（Textual Membership Queries）</news:title>
   <news:publication_date>2026-05-03T21:04:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686204</loc>
  <lastmod>2026-05-03T20:13:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列フローフィールドによる多人数姿勢追跡の実装的意義（JointFlow: Temporal Flow Fields for Multi-Person Pose Tracking）</news:title>
   <news:publication_date>2026-05-03T20:13:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686202</loc>
  <lastmod>2026-05-03T20:12:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブール代数に基づく確率的テンソル分解の実装と有用性（TensOrMachine: Probabilistic Boolean Tensor Decomposition）</news:title>
   <news:publication_date>2026-05-03T20:12:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686200</loc>
  <lastmod>2026-05-03T20:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>τ崩壊による二中間子生成の体系化（τ −→ντM1M2, with M1, M2 pseudoscalar or vector mesons）</news:title>
   <news:publication_date>2026-05-03T20:12:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686198</loc>
  <lastmod>2026-05-03T20:12:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張畳み込みを見直す：弱教師あり・半教師ありセマンティックセグメンテーションへの単純アプローチ（Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-03T20:12:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686196</loc>
  <lastmod>2026-05-03T20:12:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差境界条件に適応するERMと確率近似の高速収束（Fast Rates of ERM and Stochastic Approximation）</news:title>
   <news:publication_date>2026-05-03T20:12:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686194</loc>
  <lastmod>2026-05-03T20:11:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計モデルと意味モデルを組み合わせた多文書要約（Using Statistical and Semantic Models for Multi-Document Summarization）</news:title>
   <news:publication_date>2026-05-03T20:11:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686192</loc>
  <lastmod>2026-05-03T19:20:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によって生じるカテゴリ知覚（Learning-induced categorical perception in a neural network model）</news:title>
   <news:publication_date>2026-05-03T19:20:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686190</loc>
  <lastmod>2026-05-03T19:19:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質結晶化X線画像の分類にCNNを使う効能（Classification of Protein Crystallization X-Ray Images Using Major Convolutional Neural Network Architectures）</news:title>
   <news:publication_date>2026-05-03T19:19:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686188</loc>
  <lastmod>2026-05-03T19:19:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ContextNetによる文脈と詳細の両立で実用化するリアルタイム意味分割（ContextNet: Exploring Context and Detail for Semantic Segmentation in Real-time）</news:title>
   <news:publication_date>2026-05-03T19:19:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686186</loc>
  <lastmod>2026-05-03T19:18:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コホモロジー定式化における欠落したビアンキ恒等式（On Missing Bianchi Identities in Cohomology Formulation）</news:title>
   <news:publication_date>2026-05-03T19:18:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686184</loc>
  <lastmod>2026-05-03T19:18:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河団中心における最も明るい銀河の協調的組み立て（Coordinated Assembly of Brightest Cluster Galaxies）</news:title>
   <news:publication_date>2026-05-03T19:18:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686182</loc>
  <lastmod>2026-05-03T19:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボリューム型深層畳み込みニューラルネットワークによるダークマターハロー模擬カタログ生成（A volumetric deep Convolutional Neural Network for simulation of mock dark matter halo catalogues）</news:title>
   <news:publication_date>2026-05-03T19:18:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686180</loc>
  <lastmod>2026-05-03T19:17:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインバンディット線形最適化の基礎とSCRiBLe（ONLINE BANDIT LINEAR OPTIMIZATION: A STUDY）</news:title>
   <news:publication_date>2026-05-03T19:17:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686178</loc>
  <lastmod>2026-05-03T18:26:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタラクティブ強化学習における既存知識の動的再利用（Interactive Reinforcement Learning with Dynamic Reuse of Prior Knowledge）</news:title>
   <news:publication_date>2026-05-03T18:26:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686176</loc>
  <lastmod>2026-05-03T18:26:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地下フォーラムの私的やり取りを予測する方法（Under the Underground: Predicting Private Interactions in Underground Forums）</news:title>
   <news:publication_date>2026-05-03T18:26:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686174</loc>
  <lastmod>2026-05-03T18:25:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情解析システムに潜む性別・人種バイアスの実態（Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems）</news:title>
   <news:publication_date>2026-05-03T18:25:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686172</loc>
  <lastmod>2026-05-03T18:24:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー収穫型IoTにおけるアクセス制御とバッテリ予測の強化学習的統合（Reinforcement Learning based Multi-Access Control and Battery Prediction with Energy Harvesting in IoT Systems）</news:title>
   <news:publication_date>2026-05-03T18:24:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/686170</loc>
  <lastmod>2026-05-03T18:24:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続的インテグレーションの設定を静的に検証する（Statically Verifying Continuous Integration Configurations）</news:title>
   <news:publication_date>2026-05-03T18:24:43Z</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>学校におけるアプリ作成教育の実践と示唆（APP CREATION IN SCHOOLS FOR DIFFERENT CURRICULA SUBJECTS - LESSONS LEARNED）</news:title>
   <news:publication_date>2026-05-03T18:24:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-03T18:24:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pocket Game Jams：学校における構成主義的アプローチ（Pocket Game Jams: a Constructionist Approach at Schools）</news:title>
   <news:publication_date>2026-05-03T18:24:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-03T17:32:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ゲームジャムが育む計算思考と非公式学習の力（THE ROLE OF GAME JAMS IN DEVELOPING INFORMAL LEARNING OF COMPUTATIONAL THINKING: A CROSS-EUROPEAN CASE STUDY）</news:title>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ゲーム開発を通じた学習とジェンダー差（Game Development-Based Learning Experience: Gender Differences in Game Design）</news:title>
   <news:publication_date>2026-05-03T17:32:37Z</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>
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   <news:title>手術中データ埋め込み解析による急性腎障害予測の向上（Improved Predictive Models for Acute Kidney Injury with IDEAs: Intraoperative Data Embedded Analytics）</news:title>
   <news:publication_date>2026-05-03T17:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>小マゼラン雲の空間分解星形成履歴の再構築（The spatially resolved star formation history of the main body of the Small Magellanic Cloud）</news:title>
   <news:publication_date>2026-05-03T17:31:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686156</loc>
  <lastmod>2026-05-03T17:31:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自発性電位間隔の分布に関して（On the distribution of spontaneous potentials intervals in nervous transmission）</news:title>
   <news:publication_date>2026-05-03T17:31:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686154</loc>
  <lastmod>2026-05-03T17:31:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学校におけるプログラミング活動を支援するゲームテンプレートの評価（Evaluation of Game Templates to support Programming Activities in Schools）</news:title>
   <news:publication_date>2026-05-03T17:31:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686152</loc>
  <lastmod>2026-05-03T16:40:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-03T16:40:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-03T16:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>正規化ワッサースタイン距離による越境文書検索（Cross-lingual Document Retrieval using Regularized Wasserstein Distance）</news:title>
   <news:publication_date>2026-05-03T16:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-03T16:40:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公共行政研究における機械学習と組織評判の計測（Machine Learning for Public Administration Research, with Application to Organizational Reputation）</news:title>
   <news:publication_date>2026-05-03T16:40:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686146</loc>
  <lastmod>2026-05-03T16:39:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感覚運動的視点から見る視覚特徴の基底付け（A Sensorimotor Perspective on Grounding the Semantic of Simple Visual Features）</news:title>
   <news:publication_date>2026-05-03T16:39:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-03T16:39:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測マルコフ決定過程における深い階層型強化学習（Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes）</news:title>
   <news:publication_date>2026-05-03T16:39:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686142</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>反復学習で支援する対話型画像分割（Iteratively Trained Interactive Segmentation）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686140</loc>
  <lastmod>2026-05-03T16:38:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>PAD-Netによる同時深度推定とシーン解析の統合（PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing）</news:title>
   <news:publication_date>2026-05-03T16:38:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686138</loc>
  <lastmod>2026-05-03T15:47:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>力覚相互作用スキルの評価を学習する手法（Learning Movement Assessment Primitives for Force Interaction Skills）</news:title>
   <news:publication_date>2026-05-03T15:47:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686136</loc>
  <lastmod>2026-05-03T15:39:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構による弱教師ありドメイン特化色名推定（Weakly Supervised Domain-Specific Color Naming Based on Attention）</news:title>
   <news:publication_date>2026-05-03T15:39:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686134</loc>
  <lastmod>2026-05-03T15:39:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像を活用して動画認識を強化する階層型生成対抗ネットワーク（Exploiting Images for Video Recognition with Hierarchical Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-03T15:39:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686132</loc>
  <lastmod>2026-05-03T15:38:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>女性ティーンとコーディング：性差に配慮した創造的学習環境（Female Teenagers and Coding: Create Gender Sensitive and Creative Learning Environments）</news:title>
   <news:publication_date>2026-05-03T15:38:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686130</loc>
  <lastmod>2026-05-03T15:38:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Pocket Codeを用いたゲームデザインが学校の学びを変える（Game Design with Pocket Code: Providing a Constructionist Environment for Girls in the School Context）</news:title>
   <news:publication_date>2026-05-03T15:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686128</loc>
  <lastmod>2026-05-03T15:38:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超信頼・低遅延V2V通信におけるフェデレーテッド学習の実装と意義（Federated Learning for Ultra-Reliable Low-Latency V2V Communications）</news:title>
   <news:publication_date>2026-05-03T15:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/686126</loc>
  <lastmod>2026-05-03T15:37:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ML搭載自律システムのための定量的k投影カバレッジ（Quantitative Projection Coverage for Testing ML-enabled Autonomous Systems）</news:title>
   <news:publication_date>2026-05-03T15:37:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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