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   <news:title>目的志向の分子グラフ生成のためのグラフ畳み込み方策ネットワーク（Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation）</news:title>
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   <news:title>ネットワークの深さと幅が仮説空間に与える影響（The effect of the choice of neural network depth and breadth on the size of its hypothesis space）</news:title>
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   <news:title>無限状態ジャンプ過程におけるベイズ推論の効率的データ増補（On Bayesian inferential tasks with infinite-state jump processes: efficient data augmentation）</news:title>
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   <news:title>人の修正から学ぶ際に不確実性を取り込む意義（Including Uncertainty when Learning from Human Corrections）</news:title>
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   <news:title>進化的モジュールネットワークによる視覚的推論（Visual Reasoning by Progressive Module Networks）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>MEBN-RM：リレーショナルデータから確率論的知識を組み立てる方法論（MEBN-RM: A Mapping between Multi-Entity Bayesian Network and Relational Model）</news:title>
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    <news:language>ja</news:language>
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   <news:title>有限時間解析が示すTD学習の実用的意味（A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>干渉制約ネットワークにおける共同電力配分の分散協調学習（Joint Power Allocation in Interference-Limited Networks via Distributed Coordinated Learning）</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>単眼画像から深さを「順序」で学ぶ新手法（Deep Ordinal Regression Network for Monocular Depth Estimation）</news:title>
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    <news:language>ja</news:language>
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   <news:title>難読化耐性を持つ実行可能ファイル検索（Obfuscation Resilient Search through Executable Classification）</news:title>
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   <news:title>放射線画像再考：BraTSに対する様々な手法の比較（Rethinking Radiology: An Analysis of Different Approaches to BraTS）</news:title>
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    <news:language>ja</news:language>
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   <news:title>オンラインベイズ実験設計によるハミルトニアン学習の実践（Hamiltonian Learning with Online Bayesian Experiment Design in Practice）</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>部分観測問題に対する深い変分強化学習（Deep Variational Reinforcement Learning for POMDPs）</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>群衆と雑多な背景でのリアルタイム行動認識（Action4D: Real-time Action Recognition in the Crowd and Clutter）</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>説得力のある議論を見つけるための大規模ベイズ的選好学習（Finding Convincing Arguments Using Scalable Bayesian Preference Learning）</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>電力網の確率的挙動と連鎖故障のシミュレーション（Simulating the stochastic dynamics and cascade failure of power networks）</news:title>
   <news:publication_date>2026-05-13T23:07:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:language>ja</news:language>
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   <news:title>局所構造を利用した構造化予測（Localized Structured Prediction）</news:title>
   <news:publication_date>2026-05-13T23:06:35Z</news:publication_date>
   <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>任意条件付き変分オートエンコーダ（Variational Autoencoder with Arbitrary Conditioning）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-13T23:06:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>属性ごとの差を扱うプライバシー機構の設計（Not All Attributes are Created Equal: dX-Private Mechanisms for Linear Queries）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-13T23:06:04Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>暗黙的確率過程と変分推論が切り開く関数空間のベイズ化（Variational Implicit Processes）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-13T22:14:25Z</lastmod>
  <news:news>
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    <news:language>ja</news:language>
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   <news:title>因果介入による公正性設計（Causal Interventions for Fairness）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-13T22:14:04Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>グラフ構造データに対する敵対的攻撃（Adversarial Attack on Graph Structured Data）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-13T22:13:34Z</lastmod>
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    <news:language>ja</news:language>
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   <news:title>機械から新たな物理を学ぶ（Learning New Physics from a Machine）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-13T22:11:51Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ワイヤレス給電センサネットワークにおける最適化と強化学習の比較（Optimization vs. Reinforcement Learning for Wirelessly Powered Sensor Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-13T22:11:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>適応的データ収集におけるバイアス低減と差分プライバシーの接点（Mitigating Bias in Adaptive Data Gathering via Differential Privacy）</news:title>
   <news:publication_date>2026-05-13T22:11:42Z</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>条件付き線形回帰（Conditional Linear Regression）</news:title>
   <news:publication_date>2026-05-13T22:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-13T22:11:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値確率変数のコルモゴロフモデル学習（Learning Kolmogorov Models for Binary Random Variables）</news:title>
   <news:publication_date>2026-05-13T22:11:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-13T21:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化された価値関数と乗法的正規化フロー（Randomized Value Functions via Multiplicative Normalizing Flows）</news:title>
   <news:publication_date>2026-05-13T21:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/689846</loc>
  <lastmod>2026-05-13T21:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの信頼性指標の方向性（Towards Dependability Metrics for Neural Networks）</news:title>
   <news:publication_date>2026-05-13T21:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/689844</loc>
  <lastmod>2026-05-13T21:16:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GianCarlo Ghirardiとの出会いと教育の本質（My life with GianCarlo Ghirardi）</news:title>
   <news:publication_date>2026-05-13T21:16:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/689842</loc>
  <lastmod>2026-05-13T21:16:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>血管セグメンテーションにおけるグラフ結合学習（Deep Vessel Segmentation By Learning Graphical Connectivity）</news:title>
   <news:publication_date>2026-05-13T21:16:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/689840</loc>
  <lastmod>2026-05-13T21:15:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索分野における深層ランキングモデルの実運用化（Deploying Deep Ranking Models for Search Verticals）</news:title>
   <news:publication_date>2026-05-13T21:15:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>グラフ上の探索における逐次的探索と停止の最適化（Finding the bandit in a graph: Sequential search-and-stop）</news:title>
   <news:publication_date>2026-05-13T21:15:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-05-13T21:15:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データ駆動で個別化された確率的脳アトラスを作る手法（Data-driven Probabilistic Atlases Capture Whole-brain Individual Variation）</news:title>
   <news:publication_date>2026-05-13T21:15:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/689834</loc>
  <lastmod>2026-05-13T20:23:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果バンディットにおける伝播推論の扱い（Causal Bandits with Propagating Inference）</news:title>
   <news:publication_date>2026-05-13T20:23:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689832</loc>
  <lastmod>2026-05-13T20:23:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数学習者による敵対的回帰（Adversarial Regression with Multiple Learners）</news:title>
   <news:publication_date>2026-05-13T20:23:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689830</loc>
  <lastmod>2026-05-13T20:23:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常ストリーミングデータに対する二重ロバストなベイズ推論（Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences）</news:title>
   <news:publication_date>2026-05-13T20:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689828</loc>
  <lastmod>2026-05-13T20:22:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TopRank: オンライン確率的ランキングの実践アルゴリズム（TopRank: A Practical Algorithm for Online Stochastic Ranking）</news:title>
   <news:publication_date>2026-05-13T20:22:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689826</loc>
  <lastmod>2026-05-13T20:22:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ADMMを用いた分散アルゴリズムの精度とプライバシーの同時改善（Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms）</news:title>
   <news:publication_date>2026-05-13T20:22:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689824</loc>
  <lastmod>2026-05-13T20:22:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>腹部多臓器セグメンテーションのための3D全畳み込みネットワークのマルチスケールピラミッド（A multi-scale pyramid of 3D fully convolutional networks for abdominal multi-organ segmentation）</news:title>
   <news:publication_date>2026-05-13T20:22:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689822</loc>
  <lastmod>2026-05-13T20:21:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シリコン中の鉄—水素相互作用の第一原理解析（First-principles calculations of iron-hydrogen reactions in silicon）</news:title>
   <news:publication_date>2026-05-13T20:21:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689820</loc>
  <lastmod>2026-05-13T19:30:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチブランチ構造を備えた深層ニューラルネットワークは非凸性が低い（Deep Neural Networks with Multi-Branch Architectures Are Less Non-Convex）</news:title>
   <news:publication_date>2026-05-13T19:30:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689818</loc>
  <lastmod>2026-05-13T19:29:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル推論ネットワークが変える表現学習の地平（Spectral Inference Networks: Unifying Deep and Spectral Learning）</news:title>
   <news:publication_date>2026-05-13T19:29:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689816</loc>
  <lastmod>2026-05-13T19:29:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データの解釈可能な離散表現学習（SOM-VAE: Interpretable Discrete Representation Learning on Time Series）</news:title>
   <news:publication_date>2026-05-13T19:29:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689814</loc>
  <lastmod>2026-05-13T19:29:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックス変分推論のブースティング（Boosting Black Box Variational Inference）</news:title>
   <news:publication_date>2026-05-13T19:29:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689812</loc>
  <lastmod>2026-05-13T19:29:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GraKeL: グラフカーネルライブラリの実務的理解（GraKeL: A Graph Kernel Library in Python）</news:title>
   <news:publication_date>2026-05-13T19:29:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689810</loc>
  <lastmod>2026-05-13T19:28:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層知識トレースの一貫性問題とその解決（Addressing Two Problems in Deep Knowledge Tracing via Prediction-Consistent Regularization）</news:title>
   <news:publication_date>2026-05-13T19:28:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689808</loc>
  <lastmod>2026-05-13T19:28:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習履歴から進路を予測する知識状態の活用（Incorporating Features Learned by an Enhanced Deep Knowledge Tracing Model for STEM/Non-STEM Job Prediction）</news:title>
   <news:publication_date>2026-05-13T19:28:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689806</loc>
  <lastmod>2026-05-13T18:37:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群からの剛体運動推定のための表現学習（PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds）</news:title>
   <news:publication_date>2026-05-13T18:37:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689804</loc>
  <lastmod>2026-05-13T18:36:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SBAF――恒星外惑星の居住可能性分類に向けた新しい活性化関数（SBAF: A New Activation Function for Artificial Neural Net based Habitability Classification）</news:title>
   <news:publication_date>2026-05-13T18:36:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689802</loc>
  <lastmod>2026-05-13T18:36:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非並列多対多音声変換を可能にするStarGAN-VC（STARGAN-VC: NON-PARALLEL MANY-TO-MANY VOICE CONVERSION WITH STAR GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-05-13T18:36:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689800</loc>
  <lastmod>2026-05-13T18:35:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチチャートによる3D形状生成の革新（Multi-chart Generative Surface Modeling）</news:title>
   <news:publication_date>2026-05-13T18:35:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689798</loc>
  <lastmod>2026-05-13T18:35:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ベイズ回帰モデルの要点と経営者の視点（Deep Bayesian regression models）</news:title>
   <news:publication_date>2026-05-13T18:35:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689796</loc>
  <lastmod>2026-05-13T18:35:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声に基づく感情認識のための敵対的オートエンコーダ（Adversarial Auto-encoders for Speech Based Emotion Recognition）</news:title>
   <news:publication_date>2026-05-13T18:35:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689794</loc>
  <lastmod>2026-05-13T18:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路網の位相的特徴による都市比較（Topological street-network characterization through feature-vector and cluster analysis）</news:title>
   <news:publication_date>2026-05-13T18:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689792</loc>
  <lastmod>2026-05-13T17:43:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜血管の分岐点検出のためのマルチタスクネットワーク（A Multi-task Network to Detect Junctions in Retinal Vasculature）</news:title>
   <news:publication_date>2026-05-13T17:43:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689790</loc>
  <lastmod>2026-05-13T17:33:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低温MOSトランジスタの物理モデル（Cryogenic MOS Transistor Model）</news:title>
   <news:publication_date>2026-05-13T17:33:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689788</loc>
  <lastmod>2026-05-13T17:33:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データに強いグラフベースの二標本検定の改良（On High-dimensional Modifications of Some Graph-based Two-sample Tests）</news:title>
   <news:publication_date>2026-05-13T17:33:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689786</loc>
  <lastmod>2026-05-13T17:32:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ユニタリ変換のためのロバスト学習制御設計（Robust Learning Control Design for Quantum Unitary Transformations）</news:title>
   <news:publication_date>2026-05-13T17:32:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689784</loc>
  <lastmod>2026-05-13T17:32:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高効率な微分可能プログラミングの実現（Efficient Differentiable Programming in a Functional Array-Processing Language）</news:title>
   <news:publication_date>2026-05-13T17:32:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689782</loc>
  <lastmod>2026-05-13T17:32:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜血管セグメンテーションにおける追加ラベル付き深層監視（Deep supervision with additional labels for retinal vessel segmentation task）</news:title>
   <news:publication_date>2026-05-13T17:32:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689780</loc>
  <lastmod>2026-05-13T17:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TextRayによる胸部X線の全体理解（TextRay: Mining Clinical Reports to Gain a Broad Understanding of Chest X-rays）</news:title>
   <news:publication_date>2026-05-13T17:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689778</loc>
  <lastmod>2026-05-13T16:40:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PSD制約による一意復元と暗黙の正則化（Implicit regularization and solution uniqueness in over-parameterized matrix sensing）</news:title>
   <news:publication_date>2026-05-13T16:40:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689776</loc>
  <lastmod>2026-05-13T16:31:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込み型シーケンス・トゥ・シーケンスによる非侵襲型負荷監視（Convolutional Sequence to Sequence Non-intrusive Load Monitoring）</news:title>
   <news:publication_date>2026-05-13T16:31:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689774</loc>
  <lastmod>2026-05-13T16:31:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PieAPP: ペア比較で学ぶ視覚的画像誤差評価（PieAPP: Perceptual Image-Error Assessment through Pairwise Preference）</news:title>
   <news:publication_date>2026-05-13T16:31:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689772</loc>
  <lastmod>2026-05-13T16:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ化流体シミュレーションの生成モデル（Deep Fluids: A Generative Network for Parameterized Fluid Simulations）</news:title>
   <news:publication_date>2026-05-13T16:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689770</loc>
  <lastmod>2026-05-13T16:30:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みオートエンコーダの学習のための空間周波数損失（Spatial Frequency Loss for Learning Convolutional Autoencoders）</news:title>
   <news:publication_date>2026-05-13T16:30:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689768</loc>
  <lastmod>2026-05-13T16:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボールドウィン効果によるメタ学習（Meta-Learning by the Baldwin Effect）</news:title>
   <news:publication_date>2026-05-13T16:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689766</loc>
  <lastmod>2026-05-13T16:29:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的フィードバックから学ぶ階層化商品カテゴリー（Learning Hierarchical Item Categories from Implicit Feedback Data for Efficient Recommendations and Browsing）</news:title>
   <news:publication_date>2026-05-13T16:29:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689764</loc>
  <lastmod>2026-05-13T15:37:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークの隠れ層を因子分解の観点から覗く（A Peek Into the Hidden Layers of a Convolutional Neural Network Through a Factorization Lens）</news:title>
   <news:publication_date>2026-05-13T15:37:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689762</loc>
  <lastmod>2026-05-13T15:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間依存注意機構による医療概念の埋め込み（Medical Concept Embedding with Time-Aware Attention）</news:title>
   <news:publication_date>2026-05-13T15:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689760</loc>
  <lastmod>2026-05-13T15:30:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-meansの自由度とモデル選択（Degrees of Freedom and Model Selection for k-means Clustering）</news:title>
   <news:publication_date>2026-05-13T15:30:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689758</loc>
  <lastmod>2026-05-13T15:29:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gaussian Processを用いた複数の試験時攻撃の関係性の解析（Killing four birds with one Gaussian process）</news:title>
   <news:publication_date>2026-05-13T15:29:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689756</loc>
  <lastmod>2026-05-13T15:28:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Set-based Obfuscationによる強いPUFの機械学習耐性強化（Set-based Obfuscation for Strong PUFs against Machine Learning Attacks）</news:title>
   <news:publication_date>2026-05-13T15:28:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689754</loc>
  <lastmod>2026-05-13T15:28:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工膝関節置換術におけるリアルタイム手術器具認識（Real-time Surgical Tools Recognition in Total Knee Arthroplasty Using Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-13T15:28:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689752</loc>
  <lastmod>2026-05-13T15:27:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルゴリズム指向のニューラルネット設計（Deep Algorithms: designs for networks）</news:title>
   <news:publication_date>2026-05-13T15:27:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689750</loc>
  <lastmod>2026-05-13T14:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運動計画のための暗黙的サンプリング分布学習 (Learning Implicit Sampling Distributions for Motion Planning)</news:title>
   <news:publication_date>2026-05-13T14:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689748</loc>
  <lastmod>2026-05-13T14:27:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造を超えた分類手法（Beyond Trees: Classification with Sparse Pairwise Dependencies）</news:title>
   <news:publication_date>2026-05-13T14:27:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689746</loc>
  <lastmod>2026-05-13T14:27:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検閲された生存データのランキング学習（Learning to rank for censored survival data）</news:title>
   <news:publication_date>2026-05-13T14:27:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689744</loc>
  <lastmod>2026-05-13T14:26:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込み辞書学習によるスパイクソーティング（Spike Sorting by Convolutional Dictionary Learning）</news:title>
   <news:publication_date>2026-05-13T14:26:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689742</loc>
  <lastmod>2026-05-13T14:26:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列の疑似逆を小さなサブセットで推定する逆反復ボリュームサンプリング（Reverse Iterative Volume Sampling for Linear Regression）</news:title>
   <news:publication_date>2026-05-13T14:26:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689740</loc>
  <lastmod>2026-05-13T14:26:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Web規模レコメンデーションにおけるグラフ畳み込みの実用化（Graph Convolutional Neural Networks for Web-Scale Recommender Systems）</news:title>
   <news:publication_date>2026-05-13T14:26:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689738</loc>
  <lastmod>2026-05-13T14:25:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シリコン中の深い二重ドナーであるマグネシウムのさらなる研究（Further investigations of the deep double donor magnesium in silicon）</news:title>
   <news:publication_date>2026-05-13T14:25:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689736</loc>
  <lastmod>2026-05-13T13:33:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点異常と集合的異常の線形時間検出法（A linear time method for the detection of point and collective anomalies）</news:title>
   <news:publication_date>2026-05-13T13:33:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689734</loc>
  <lastmod>2026-05-13T13:25:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MILD-Netによる腺組織のインスタンス分割の意義（MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images）</news:title>
   <news:publication_date>2026-05-13T13:25:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689732</loc>
  <lastmod>2026-05-13T13:25:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚から言語への翻訳を複数モデルの合意で高精度化する手法（Mining for meaning: from vision to language through multiple networks consensus）</news:title>
   <news:publication_date>2026-05-13T13:25:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689730</loc>
  <lastmod>2026-05-13T13:24:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による脆性破壊の簡易化モデル化（Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications）</news:title>
   <news:publication_date>2026-05-13T13:24:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689728</loc>
  <lastmod>2026-05-13T13:24:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>命令文から目的を学ぶ仕組みの解説（LEARNING TO UNDERSTAND GOAL SPECIFICATIONS BY MODELLING REWARD）</news:title>
   <news:publication_date>2026-05-13T13:24:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689726</loc>
  <lastmod>2026-05-13T13:23:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生態学に着想を得た遺伝的アプローチによるニューラルネット構造探索（EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching from Scratch）</news:title>
   <news:publication_date>2026-05-13T13:23:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689724</loc>
  <lastmod>2026-05-13T13:23:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能なニューラルネットワークと加法指標モデル（Explainable Neural Networks based on Additive Index Models）</news:title>
   <news:publication_date>2026-05-13T13:23:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689722</loc>
  <lastmod>2026-05-13T12:31:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単調関数の非母数推定の統一的研究（A unified study of nonparametric inference for monotone functions）</news:title>
   <news:publication_date>2026-05-13T12:31:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689720</loc>
  <lastmod>2026-05-13T12:31:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLU活性化ニューラルネットワークの線形領域数に関する上界構成フレームワーク（A Framework for the construction of upper bounds on the number of affine linear regions of ReLU feed-forward neural networks）</news:title>
   <news:publication_date>2026-05-13T12:31:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689718</loc>
  <lastmod>2026-05-13T12:30:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WIYNのOne Degree Imagerの拡張と広視野撮像能力の向上（The WIYN One Degree Imager in 2018: An Extended 30-Detector Focal Plane）</news:title>
   <news:publication_date>2026-05-13T12:30:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689716</loc>
  <lastmod>2026-05-13T12:30:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い教師付きから学ぶ自動オブジェクト除去（Adversarial Scene Editing: Automatic Object Removal from Weak Supervision）</news:title>
   <news:publication_date>2026-05-13T12:30:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689714</loc>
  <lastmod>2026-05-13T12:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRPC: 因果グラフ推定を実用に近づけるRパッケージ（MRPC: An R package for accurate inference of causal graphs）</news:title>
   <news:publication_date>2026-05-13T12:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689712</loc>
  <lastmod>2026-05-13T12:29:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的深層学習とランダム化された和積ネットワーク（Probabilistic Deep Learning using Random Sum-Product Networks）</news:title>
   <news:publication_date>2026-05-13T12:29:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689710</loc>
  <lastmod>2026-05-13T12:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Y-Netによる大腸ポリープ検出の実務的意義（Y-Net: A deep Convolutional Neural Network for Polyp Detection）</news:title>
   <news:publication_date>2026-05-13T12:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689708</loc>
  <lastmod>2026-05-13T11:38:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体の状態分類における転移学習の実践（State Classification with CNN）</news:title>
   <news:publication_date>2026-05-13T11:38:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689706</loc>
  <lastmod>2026-05-13T11:37:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交通用ステレオ画像のセマンティックセグメンテーション性能評価（Performance Evaluation of Deep Learning Networks for Semantic Segmentation of Traffic Stereo-Pair Images）</news:title>
   <news:publication_date>2026-05-13T11:37:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689704</loc>
  <lastmod>2026-05-13T11:37:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形計画法におけるエントロピー罰則の明示的解析（An explicit analysis of the entropic penalty in linear programming）</news:title>
   <news:publication_date>2026-05-13T11:37:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689702</loc>
  <lastmod>2026-05-13T11:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>F理論のTASI講義 (TASI Lectures on F-theory)</news:title>
   <news:publication_date>2026-05-13T11:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689700</loc>
  <lastmod>2026-05-13T11:36:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mg II放射と吸収から読み解く星形成銀河の物理（Mg II emission and absorption in star-forming galaxies）</news:title>
   <news:publication_date>2026-05-13T11:36:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689698</loc>
  <lastmod>2026-05-13T11:36:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量分布のパスワイズ導関数（Pathwise Derivatives for Multivariate Distributions）</news:title>
   <news:publication_date>2026-05-13T11:36:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689696</loc>
  <lastmod>2026-05-13T11:36:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGを生成するGANの枠組みと実用性（EEG-GAN: Generative adversarial networks for electroencephalographic (EEG) brain signals）</news:title>
   <news:publication_date>2026-05-13T11:36:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689694</loc>
  <lastmod>2026-05-13T10:44:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異値変換による量子行列演算の飛躍的改善（Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics）</news:title>
   <news:publication_date>2026-05-13T10:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689692</loc>
  <lastmod>2026-05-13T10:43:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hubble Deep UV Legacy Surveyの意義と実務への示唆（The Hubble Deep UV Legacy Survey）</news:title>
   <news:publication_date>2026-05-13T10:43:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689690</loc>
  <lastmod>2026-05-13T10:43:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再パラメータ化トリックを超えるパスワイズ導関数（Pathwise Derivatives Beyond the Reparameterization Trick）</news:title>
   <news:publication_date>2026-05-13T10:43:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689688</loc>
  <lastmod>2026-05-13T10:42:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dynaにおける計画の“形”が高次元状態空間で与える影響（The Effect of Planning Shape on Dyna-style Planning in High-dimensional State Spaces）</news:title>
   <news:publication_date>2026-05-13T10:42:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689686</loc>
  <lastmod>2026-05-13T10:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中位表現に柔軟正規化を統合する（Integrating Flexible Normalization into Mid-Level Representations of Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-13T10:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689684</loc>
  <lastmod>2026-05-13T10:41:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペア比較から性能指標を引き出す仕組み（Performance Metric Elicitation from Pairwise Classifier Comparisons）</news:title>
   <news:publication_date>2026-05-13T10:41:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689682</loc>
  <lastmod>2026-05-13T10:41:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リレーショナルな視点で強化学習を変える（Relational Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-13T10:41:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689680</loc>
  <lastmod>2026-05-13T09:49:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係的再帰ニューラルネットワーク（Relational recurrent neural networks）</news:title>
   <news:publication_date>2026-05-13T09:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689678</loc>
  <lastmod>2026-05-13T09:49:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTM 実装のベンチマークが示したもの（LSTM Benchmarks for Deep Learning Frameworks）</news:title>
   <news:publication_date>2026-05-13T09:49:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689676</loc>
  <lastmod>2026-05-13T09:48:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>擾乱ニューラルネットワーク（Perturbative Neural Networks）</news:title>
   <news:publication_date>2026-05-13T09:48:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689674</loc>
  <lastmod>2026-05-13T09:48:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体検出器に対する敵対的パッチ攻撃（DPATCH: An Adversarial Patch Attack on Object Detectors）</news:title>
   <news:publication_date>2026-05-13T09:48:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689672</loc>
  <lastmod>2026-05-13T09:47:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次的Attend, Infer, Repeatによる移動物体の生成モデリング (Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects)</news:title>
   <news:publication_date>2026-05-13T09:47:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689670</loc>
  <lastmod>2026-05-13T09:47:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AdaGrad のステップサイズ：非凸問題での鋭い収束（AdaGrad stepsizes: Sharp convergence over nonconvex landscapes）</news:title>
   <news:publication_date>2026-05-13T09:47:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689668</loc>
  <lastmod>2026-05-13T09:47:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離可能データ上の確率的勾配降下法：固定学習率でも収束するという発見（Stochastic Gradient Descent on Separable Data: Exact Convergence with a Fixed Learning Rate）</news:title>
   <news:publication_date>2026-05-13T09:47:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689666</loc>
  <lastmod>2026-05-13T08:55:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mix &amp;amp; Match によるエージェント・カリキュラム（Mix &amp;amp; Match – Agent Curricula for Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-13T08:55:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689664</loc>
  <lastmod>2026-05-13T08:55:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイクル一貫性をベイズ的に解釈する（Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference）</news:title>
   <news:publication_date>2026-05-13T08:55:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689662</loc>
  <lastmod>2026-05-13T08:54:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>証拠に基づく深層学習による分類不確実性の定量化（Evidential Deep Learning to Quantify Classification Uncertainty）</news:title>
   <news:publication_date>2026-05-13T08:54:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689660</loc>
  <lastmod>2026-05-13T08:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル＋カーネルで解く条件付き確率密度推定（Neural-Kernelized Conditional Density Estimation）</news:title>
   <news:publication_date>2026-05-13T08:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689658</loc>
  <lastmod>2026-05-13T08:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非一様サンプリング点群に対するモンテカルロ畳み込み（Monte Carlo Convolution for Learning on Non-Uniformly Sampled Point Clouds）</news:title>
   <news:publication_date>2026-05-13T08:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689656</loc>
  <lastmod>2026-05-13T08:54:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銘柄選択のための機械学習フレームワーク (A Machine Learning Framework for Stock Selection)</news:title>
   <news:publication_date>2026-05-13T08:54:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689654</loc>
  <lastmod>2026-05-13T08:53:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>概念志向深層学習の本質（Concept-Oriented Deep Learning）</news:title>
   <news:publication_date>2026-05-13T08:53:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689652</loc>
  <lastmod>2026-05-13T08:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライマン連続体放射の逃亡調査：z=3.1における[O III]強出源からの電離放射（THE LYMAN CONTINUUM ESCAPE SURVEY: IONIZING RADIATION FROM [O III]-STRONG SOURCES AT A REDSHIFT OF 3.1）</news:title>
   <news:publication_date>2026-05-13T08:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689650</loc>
  <lastmod>2026-05-13T08:01:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イールドカーブの特徴抽出における機械学習の応用（Machine Learning for Yield Curve Feature Extraction: Application to Illiquid Corporate Bonds）</news:title>
   <news:publication_date>2026-05-13T08:01:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689648</loc>
  <lastmod>2026-05-13T08:00:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みネットワークを用いた疾病予測（Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer’s Disease）</news:title>
   <news:publication_date>2026-05-13T08:00:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689646</loc>
  <lastmod>2026-05-13T08:00:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競合する予測アルゴリズムのゲーム理論的分析（Competing Prediction Algorithms）</news:title>
   <news:publication_date>2026-05-13T08:00:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689644</loc>
  <lastmod>2026-05-13T07:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のような一般化を機械が行う方法（Human-like generalization in a machine through predicate learning）</news:title>
   <news:publication_date>2026-05-13T07:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689642</loc>
  <lastmod>2026-05-13T07:59:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PBILのレベル別解析（Level-Based Analysis of the Population-Based Incremental Learning Algorithm）</news:title>
   <news:publication_date>2026-05-13T07:59:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689640</loc>
  <lastmod>2026-05-13T07:59:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ構造推定に基づくスパーシファイング変換学習（Graph topology inference based on sparsifying transform learning）</news:title>
   <news:publication_date>2026-05-13T07:59:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689638</loc>
  <lastmod>2026-05-13T07:07:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>距離制約最適化の射影法（A Projection Method for Metric-Constrained Optimization）</news:title>
   <news:publication_date>2026-05-13T07:07:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689636</loc>
  <lastmod>2026-05-13T06:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原始惑星系円盤中の大気リサイクル抑制と浮力障壁（Suppression of atmospheric recycling of planets embedded in a protoplanetary disc by buoyancy barrier）</news:title>
   <news:publication_date>2026-05-13T06:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689634</loc>
  <lastmod>2026-05-13T06:57:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実用的なディープステレオ（Practical Deep Stereo）</news:title>
   <news:publication_date>2026-05-13T06:57:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689632</loc>
  <lastmod>2026-05-13T06:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル付き文字列から複数言語を学ぶ手法（Learning Several Languages from Labeled Strings: State Merging and Evolutionary Approaches）</news:title>
   <news:publication_date>2026-05-13T06:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689630</loc>
  <lastmod>2026-05-13T06:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基底空間の双曲性に関する進展（ON THE HYPERBOLICITY OF BASE SPACES FOR MAXIMALLY VARIATIONAL FAMILIES OF SMOOTH PROJECTIVE VARIETIES）</news:title>
   <news:publication_date>2026-05-13T06:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689628</loc>
  <lastmod>2026-05-13T06:56:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均が有限でない潜在分布を持つ生成モデルに関する考察（On Latent Distributions Without Finite Mean in Generative Models）</news:title>
   <news:publication_date>2026-05-13T06:56:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689626</loc>
  <lastmod>2026-05-13T06:56:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みカーネルを用いた深いガウス過程（Deep Gaussian Processes with Convolutional Kernels）</news:title>
   <news:publication_date>2026-05-13T06:56:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689624</loc>
  <lastmod>2026-05-13T06:04:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成可能な可逆ネットワークの訓練戦略（Training Generative Reversible Networks）</news:title>
   <news:publication_date>2026-05-13T06:04:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689622</loc>
  <lastmod>2026-05-13T05:55:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語順を説明して意味表現から統語構造を取り除く（Explaining Away Syntactic Structure in Semantic Document Representations）</news:title>
   <news:publication_date>2026-05-13T05:55:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689620</loc>
  <lastmod>2026-05-13T05:54:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索空間の縁問題を回避するベイズ最適化手法（BOCK : Bayesian Optimization with Cylindrical Kernels）</news:title>
   <news:publication_date>2026-05-13T05:54:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689618</loc>
  <lastmod>2026-05-13T05:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>加速ランダム座標降下法による確率的最適化とオンライン学習（Accelerated Randomized Coordinate Descent Algorithms for Stochastic Optimization and Online Learning）</news:title>
   <news:publication_date>2026-05-13T05:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689616</loc>
  <lastmod>2026-05-13T05:53:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外生的状態変数と報酬を見つけて除去する手法（Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-13T05:53:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689614</loc>
  <lastmod>2026-05-13T05:53:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層の重み回転が示す汎化性能の強力な指標（Layer rotation: a surprisingly powerful indicator of generalization in deep networks?）</news:title>
   <news:publication_date>2026-05-13T05:53:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689612</loc>
  <lastmod>2026-05-13T05:53:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパボリックタンジェント減衰による学習率スケジューリング（Stochastic Gradient Descent with Hyperbolic-Tangent Decay on Classification）</news:title>
   <news:publication_date>2026-05-13T05:53:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689610</loc>
  <lastmod>2026-05-13T05:01:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量画像超解像ネットワークの適応的重要度学習（Adaptive Importance Learning for Improving Lightweight Image Super-resolution Network）</news:title>
   <news:publication_date>2026-05-13T05:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689608</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>GuideR: ユーザー主導のルール学習がもたらす現場導入の革新（GuideR: a guided separate-and-conquer rule learning in classification, regression, and survival settings）</news:title>
   <news:publication_date>2026-05-13T04:52:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689606</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>ファジィC-平均法の視覚的品質指標（A Visual Quality Index for Fuzzy C-Means）</news:title>
   <news:publication_date>2026-05-13T04:51:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689604</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>幼鳥ハトの局所生存とユーメラニン色彩（Eumelanin-based colouration reflects local survival of juvenile feral pigeons in an urban pigeon house）</news:title>
   <news:publication_date>2026-05-13T04:50:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689602</loc>
  <lastmod>2026-05-13T04:50:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化と信頼性を両立する医療時系列予測：Deep Mixed Effect Model using Gaussian Processes（Deep Mixed Effect Model using Gaussian Processes）</news:title>
   <news:publication_date>2026-05-13T04:50:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689600</loc>
  <lastmod>2026-05-13T04:50:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数アルゴリズムを組み合わせる新しいアンサンブル結合法（Combining Multiple Algorithms in Classifier Ensembles using Generalized Mixture Functions）</news:title>
   <news:publication_date>2026-05-13T04:50:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689598</loc>
  <lastmod>2026-05-13T04:49:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ラベルと大量未ラベルを活かす半教師ありクラスタリング（Semi-Supervised Clustering with Neural Networks）</news:title>
   <news:publication_date>2026-05-13T04:49:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689596</loc>
  <lastmod>2026-05-13T03:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>浅い埋め込みによる深いMixture of Experts（Deep Mixture of Experts via Shallow Embedding）</news:title>
   <news:publication_date>2026-05-13T03:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689594</loc>
  <lastmod>2026-05-13T03:58:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Leolani：社会的コミュニケーションのための心の理論を持つ参照マシン（Leolani: a reference machine with a theory of mind for social communication）</news:title>
   <news:publication_date>2026-05-13T03:58:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689592</loc>
  <lastmod>2026-05-13T03:57:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限幅の深層ReLUネットワークの普遍近似力（The Universal Approximation Power of Finite-Width Deep ReLU Networks）</news:title>
   <news:publication_date>2026-05-13T03:57:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689590</loc>
  <lastmod>2026-05-13T03:56:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ℓpハイパーパラメータ学習のバイレベル非滑らか最適化（On ℓp-hyperparameter Learning via Bilevel Nonsmooth Optimization）</news:title>
   <news:publication_date>2026-05-13T03:56:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689588</loc>
  <lastmod>2026-05-13T03:56:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース会話コーパスに対するニューラル意味役割ラベリングのマルチタスク能動学習（Multi-Task Active Learning for Neural Semantic Role Labeling on Low Resource Conversational Corpus）</news:title>
   <news:publication_date>2026-05-13T03:56:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689586</loc>
  <lastmod>2026-05-13T03:56:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビジネスアーキテクチャのデータ駆動解析：グラフ理論の活用提案 (Data-driven Analytics for Business Architectures: Proposed Use of Graph Theory)</news:title>
   <news:publication_date>2026-05-13T03:56:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689584</loc>
  <lastmod>2026-05-13T03:56:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AIDA言語による科学的主張の形式化（Using the AIDA Language to Formally Organize Scientific Claims）</news:title>
   <news:publication_date>2026-05-13T03:56:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689582</loc>
  <lastmod>2026-05-13T03:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構付き全畳み込みネットワークによる音声感情認識（Attention Based Fully Convolutional Network for Speech Emotion Recognition）</news:title>
   <news:publication_date>2026-05-13T03:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689580</loc>
  <lastmod>2026-05-13T03:03:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>退屈が好奇心を駆動する仕組み：Homeo-Heterostatic Value Gradients（Boredom-driven curious learning by Homeo-Heterostatic Value Gradients）</news:title>
   <news:publication_date>2026-05-13T03:03:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689578</loc>
  <lastmod>2026-05-13T03:03:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド深層画像圧縮（Deep Image Compression via End-to-End Learning）</news:title>
   <news:publication_date>2026-05-13T03:03:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689576</loc>
  <lastmod>2026-05-13T03:02:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>μSR用FPGA実装32チャンネルTDCの設計と評価（32-channel TDC Implemented in FPGA for μSR Spectrometer）</news:title>
   <news:publication_date>2026-05-13T03:02:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689574</loc>
  <lastmod>2026-05-13T03:02:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2D周辺ヒートマップによる3D人体姿勢推定（3D Human Pose Estimation with 2D Marginal Heatmaps）</news:title>
   <news:publication_date>2026-05-13T03:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689572</loc>
  <lastmod>2026-05-13T03:02:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>犯罪予測に関する深層学習の試み（Forecasting Crime with Deep Learning）</news:title>
   <news:publication_date>2026-05-13T03:02:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689570</loc>
  <lastmod>2026-05-13T03:01:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果分析入門（A Primer on Causal Analysis）</news:title>
   <news:publication_date>2026-05-13T03:01:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689568</loc>
  <lastmod>2026-05-13T02:10:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SoPhie: 社会的・物理的制約に従う軌跡を予測する注意型GAN（SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints）</news:title>
   <news:publication_date>2026-05-13T02:10:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689566</loc>
  <lastmod>2026-05-13T02:10:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダルでソーシャルメディアを理解するJTAV（JTAV: Jointly Learning Social Media Content Representation by Fusing Textual, Acoustic, and Visual Features）</news:title>
   <news:publication_date>2026-05-13T02:10:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689564</loc>
  <lastmod>2026-05-13T02:10:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能な敵対的頑健性指標（An Explainable Adversarial Robustness Metric for Deep Learning Neural Networks）</news:title>
   <news:publication_date>2026-05-13T02:10:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689562</loc>
  <lastmod>2026-05-13T02:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>(24) Themis における塵放出の探索とその示唆（Search for Dust Emission from (24) Themis Using the Gemini-North Telescope）</news:title>
   <news:publication_date>2026-05-13T02:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689560</loc>
  <lastmod>2026-05-13T02:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化スペクトラルクラスタリングとグラフ導電率の再解釈（Understanding Regularized Spectral Clustering via Graph Conductance）</news:title>
   <news:publication_date>2026-05-13T02:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689558</loc>
  <lastmod>2026-05-13T02:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き相互情報量を用いた適応エラスティックネットによるマイクロアレイ遺伝子選択（Informative Gene Selection for Microarray Classification via Adaptive Elastic Net with Conditional Mutual Information）</news:title>
   <news:publication_date>2026-05-13T02:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689556</loc>
  <lastmod>2026-05-13T02:07:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回避型敵対者下でのPAC学習の限界（PAC-learning in the presence of evasion adversaries）</news:title>
   <news:publication_date>2026-05-13T02:07:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689554</loc>
  <lastmod>2026-05-13T01:15:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星の対流層における磁場がもたらすTaylor–Proudman平衡の破れ（Breaking Taylor-Proudman balance by magnetic field in stellar convection zone）</news:title>
   <news:publication_date>2026-05-13T01:15:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689552</loc>
  <lastmod>2026-05-13T01:14:56Z</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>2026-05-13T01:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689550</loc>
  <lastmod>2026-05-13T01:14:24Z</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>2026-05-13T01:14:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689548</loc>
  <lastmod>2026-05-13T01:13:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合周辺尤度によるランダム効用モデルの推定（Composite Marginal Likelihood Methods for Random Utility Models）</news:title>
   <news:publication_date>2026-05-13T01:13:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-13T01:13:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-13T01:13:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ空間ノイズで深層Q学習の方策改ざん攻撃を緩和する（Mitigation of Policy Manipulation Attacks on Deep Q-Networks with Parameter-Space Noise）</news:title>
   <news:publication_date>2026-05-13T01:13:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689542</loc>
  <lastmod>2026-05-13T01:13:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DAWNBENCHのTTA評価が示す現場での示唆（Analysis of DAWNBench: Time-to-Accuracy）</news:title>
   <news:publication_date>2026-05-13T01:13:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689540</loc>
  <lastmod>2026-05-13T00:22:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CFCM: Coarse-to-Fine Context Memoryを用いた医用画像セグメンテーション（CFCM: Segmentation via Coarse to Fine Context Memory）</news:title>
   <news:publication_date>2026-05-13T00:22:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689538</loc>
  <lastmod>2026-05-13T00:21:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FlowNet3Dによる3次元点群のシーンフロー学習（FlowNet3D: Learning Scene Flow in 3D Point Clouds）</news:title>
   <news:publication_date>2026-05-13T00:21:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689536</loc>
  <lastmod>2026-05-13T00:21:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在構造ランダムグラフの推定と推論（On estimation and inference in latent structure random graphs）</news:title>
   <news:publication_date>2026-05-13T00:21:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689534</loc>
  <lastmod>2026-05-13T00:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンザフライ追跡のための粒子フィルタと焼きなまし重み付けQPSO（Learning to track on-the-fly using a particle filter with annealed-weighted QPSO modeled after a singular Dirac delta potential）</news:title>
   <news:publication_date>2026-05-13T00:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689532</loc>
  <lastmod>2026-05-13T00:20:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>累積報酬を超えるバンディット枠組みの一般化（A General Framework for Bandit Problems Beyond Cumulative Objectives）</news:title>
   <news:publication_date>2026-05-13T00:20:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689530</loc>
  <lastmod>2026-05-13T00:19:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な人間の移動データを用いた長期犯罪予測（Mining large-scale human mobility data for long-term crime prediction）</news:title>
   <news:publication_date>2026-05-13T00:19:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689528</loc>
  <lastmod>2026-05-13T00:19:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因子分解型敵対的ネットワークによる教師なしドメイン適応（Factorized Adversarial Networks for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-05-13T00:19:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689526</loc>
  <lastmod>2026-05-12T23:27:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>6つのニューロンでアタリを攻略する方法（Playing Atari with Six Neurons）</news:title>
   <news:publication_date>2026-05-12T23:27:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689524</loc>
  <lastmod>2026-05-12T23:27:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的強化学習による自律走行車の衝突回避ベンチマーク化（Adversarial Reinforcement Learning Framework for Benchmarking Collision Avoidance Mechanisms in Autonomous Vehicles）</news:title>
   <news:publication_date>2026-05-12T23:27:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689522</loc>
  <lastmod>2026-05-12T23:26:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前処理の違いを超えて学ぶ―前立腺組織スライド分類のための敵対的ドメイン適応（Adversarial Domain Adaptation for Classification of Prostate Histopathology Whole-Slide Images）</news:title>
   <news:publication_date>2026-05-12T23:26:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689520</loc>
  <lastmod>2026-05-12T23:26:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InでドープしたZnO表面におけるCOおよびOH吸着の第一原理研究（First-principles study of CO and OH adsorption on In-doped ZnO surfaces）</news:title>
   <news:publication_date>2026-05-12T23:26:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689518</loc>
  <lastmod>2026-05-12T23:25:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バックドロップ：確率的逆伝播の直感と実務的意義（Backdrop: Stochastic Backpropagation）</news:title>
   <news:publication_date>2026-05-12T23:25:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689516</loc>
  <lastmod>2026-05-12T23:25:43Z</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>2026-05-12T23:25:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689514</loc>
  <lastmod>2026-05-12T23:25:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プラトー関数の精密ランタイム解析（Precise Runtime Analysis for Plateau Functions）</news:title>
   <news:publication_date>2026-05-12T23:25:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689512</loc>
  <lastmod>2026-05-12T22:33:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純で強力な単語埋め込みの整列手法（Closed Form Word Embedding Alignment）</news:title>
   <news:publication_date>2026-05-12T22:33:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689510</loc>
  <lastmod>2026-05-12T22:32:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Next-Door解析によるポストモデル検討（Post model-fitting exploration via a “Next-Door” analysis）</news:title>
   <news:publication_date>2026-05-12T22:32:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689508</loc>
  <lastmod>2026-05-12T22:32:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動による電力系の撹乱位置推定と大きさの推定（Data-driven Localization and Estimation of Disturbance in the Interconnected Power System）</news:title>
   <news:publication_date>2026-05-12T22:32:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689506</loc>
  <lastmod>2026-05-12T22:31:21Z</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>2026-05-12T22:31:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689504</loc>
  <lastmod>2026-05-12T22:31:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Y-Net: 乳房生検画像のための同時セグメンテーションと分類（Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images）</news:title>
   <news:publication_date>2026-05-12T22:31:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689502</loc>
  <lastmod>2026-05-12T22:30:30Z</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>2026-05-12T22:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689500</loc>
  <lastmod>2026-05-12T22:30:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳線維配向のエンドツーエンド推定（End to End Brain Fiber Orientation Estimation Using Deep Learning）</news:title>
   <news:publication_date>2026-05-12T22:30:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689498</loc>
  <lastmod>2026-05-12T21:39:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼自己教師あり深度推定の深掘り（Digging Into Self-Supervised Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-05-12T21:39:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689496</loc>
  <lastmod>2026-05-12T21:38:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習で設計する非線形向け符号化（Learning a Code: Machine Learning for Approximate Non-Linear Coded Computation）</news:title>
   <news:publication_date>2026-05-12T21:38:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689494</loc>
  <lastmod>2026-05-12T21:38:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合意ベース学習（Agreement-based Learning）</news:title>
   <news:publication_date>2026-05-12T21:38:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689492</loc>
  <lastmod>2026-05-12T21:38:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T21:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689490</loc>
  <lastmod>2026-05-12T21:37:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理法則は反事実的通信を禁止しない（The laws of physics do not prohibit counterfactual communication）</news:title>
   <news:publication_date>2026-05-12T21:37:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689488</loc>
  <lastmod>2026-05-12T21:37:36Z</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RNN圧縮の動的階層革新：DirNet（Dynamically Hierarchy Revolution: DirNet for Compressing Recurrent Neural Network on Mobile Devices）</news:title>
   <news:publication_date>2026-05-12T21:37:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689486</loc>
  <lastmod>2026-05-12T21:37:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ML-Leaksによる学習データ漏洩の実態（ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models）</news:title>
   <news:publication_date>2026-05-12T21:37:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689484</loc>
  <lastmod>2026-05-12T20:45:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Graphsの提案と意義（Deep Graphs）</news:title>
   <news:publication_date>2026-05-12T20:45:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689482</loc>
  <lastmod>2026-05-12T20:45:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディフェオモルフィック学習の要点と経営への示唆（Diffeomorphic Learning）</news:title>
   <news:publication_date>2026-05-12T20:45:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689480</loc>
  <lastmod>2026-05-12T20:45:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークによる学習可能な物理エンジン（Graph Networks as Learnable Physics Engines for Inference and Control）</news:title>
   <news:publication_date>2026-05-12T20:45:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689478</loc>
  <lastmod>2026-05-12T20:44:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元強化学習における進化戦略の課題（Challenges in High-dimensional Reinforcement Learning with Evolution Strategies）</news:title>
   <news:publication_date>2026-05-12T20:44:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689476</loc>
  <lastmod>2026-05-12T20:44:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>眼鏡耐性を持つ顔認識のための顔合成（Face Synthesis for Eyeglass-Robust Face Recognition）</news:title>
   <news:publication_date>2026-05-12T20:44:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689474</loc>
  <lastmod>2026-05-12T20:44:28Z</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>2026-05-12T20:44:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689472</loc>
  <lastmod>2026-05-12T20:43:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と機械における物理的構築のための関係性誘導バイアス（Relational inductive bias for physical construction in humans and machines）</news:title>
   <news:publication_date>2026-05-12T20:43:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689470</loc>
  <lastmod>2026-05-12T19:53:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>副作用の罰則に関するステップワイズ相対到達可能性（Penalizing side effects using stepwise relative reachability）</news:title>
   <news:publication_date>2026-05-12T19:53:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689468</loc>
  <lastmod>2026-05-12T19:52:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称相互制約を持つ深層連続条件付き確率場によるオンライン多物体追跡（Deep Continuous Conditional Random Fields with Asymmetric Inter-object Constraints for Online Multi-object Tracking）</news:title>
   <news:publication_date>2026-05-12T19:52:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689466</loc>
  <lastmod>2026-05-12T19:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dual-tree複素ウェーブレット変換のための勾配ベースフィルタ設計（Gradient-based Filter Design for the Dual-tree Wavelet Transform）</news:title>
   <news:publication_date>2026-05-12T19:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689464</loc>
  <lastmod>2026-05-12T19:50:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏極された深部散乱における電弱パラメータの決定（Determination of electroweak parameters in polarised deep-inelastic scattering at HERA）</news:title>
   <news:publication_date>2026-05-12T19:50:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689462</loc>
  <lastmod>2026-05-12T19:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互推薦のオンライン学習と理論的保証（Online Reciprocal Recommendation with Theoretical Performance Guarantees）</news:title>
   <news:publication_date>2026-05-12T19:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689460</loc>
  <lastmod>2026-05-12T19:50:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TDか否か：深層強化学習における時間差分の役割（TD OR NOT TD: ANALYZING THE ROLE OF TEMPORAL DIFFERENCING IN DEEP REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-05-12T19:50:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689458</loc>
  <lastmod>2026-05-12T19:50:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>K-meansによる効率的かつ拡張性の高いバッチベイズ最適化（Efficient and Scalable Batch Bayesian Optimization Using K-Means）</news:title>
   <news:publication_date>2026-05-12T19:50:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689456</loc>
  <lastmod>2026-05-12T18:57:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>天王星におけるメタン分布と極域の明るさ変化（THE METHANE DISTRIBUTION AND POLAR BRIGHTENING ON URANUS）</news:title>
   <news:publication_date>2026-05-12T18:57:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689454</loc>
  <lastmod>2026-05-12T18:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事例とプロトタイプから学ぶ分類の考え方（Learning from Exemplars and Prototypes in Machine Learning and Psychology）</news:title>
   <news:publication_date>2026-05-12T18:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689452</loc>
  <lastmod>2026-05-12T18:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストを脳地図に翻訳する手法（Text to brain: predicting the spatial distribution of neuroimaging observations from text reports）</news:title>
   <news:publication_date>2026-05-12T18:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689450</loc>
  <lastmod>2026-05-12T18:56:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形時系列とニューラルネットによるRed Hatのボラティリティ解析（Non-linear Time Series and Artificial Neural Network of Red Hat Volatility）</news:title>
   <news:publication_date>2026-05-12T18:56:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689448</loc>
  <lastmod>2026-05-12T18:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間依存交絡因子の最適バランシングによる周辺構造モデルの改善（Optimal balancing of time-dependent confounders for marginal structural models）</news:title>
   <news:publication_date>2026-05-12T18:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689446</loc>
  <lastmod>2026-05-12T18:55:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群ごとの定常ノイズを調整してICAを堅牢化する（Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise）</news:title>
   <news:publication_date>2026-05-12T18:55:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689444</loc>
  <lastmod>2026-05-12T18:55:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層多構造形状解析：神経解剖学への応用（Deep Multi-Structural Shape Analysis: Application to Neuroanatomy）</news:title>
   <news:publication_date>2026-05-12T18:55:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689442</loc>
  <lastmod>2026-05-12T18:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個体間公平性に基づくデータ表現学習の意義（iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making）</news:title>
   <news:publication_date>2026-05-12T18:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689440</loc>
  <lastmod>2026-05-12T18:03:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキサス・オクラホマ・カンザス州におけるPGA・PGV予測のためのニューラルネットワーク方程式（Neural Network-Based Equations for Predicting PGA and PGV in Texas, Oklahoma, and Kansas）</news:title>
   <news:publication_date>2026-05-12T18:03:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689438</loc>
  <lastmod>2026-05-12T18:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RedNet：残差エンコーダ・デコーダによる屋内RGB-Dセマンティックセグメンテーション（RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-12T18:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689436</loc>
  <lastmod>2026-05-12T18:01:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペロブスカイト酸化物の熱力学的安定性予測（Predicting the thermodynamic stability of perovskite oxides using machine learning models）</news:title>
   <news:publication_date>2026-05-12T18:01:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689434</loc>
  <lastmod>2026-05-12T18:01:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自閉スペクトラム症支援を目的としたモバイルアプリの実務的レビュー（Applications for mobile devices focused on support for autism spectrum disorder population and / or people in their immediate environment in their daily lives: a systematic and practical review from a Spanish-speaking perspective）</news:title>
   <news:publication_date>2026-05-12T18:01:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689432</loc>
  <lastmod>2026-05-12T18:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳画像データの規範的モデリングとスケーラブルなマルチタスクガウス過程（Normative Modeling of Neuroimaging Data using Scalable Multi-Task Gaussian Processes）</news:title>
   <news:publication_date>2026-05-12T18:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689430</loc>
  <lastmod>2026-05-12T18:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多ユーザ向け多アンテナマルチキャストの遅延性能（Delay Performance of Multi-Antenna Multicasting in Wireless Networks）</news:title>
   <news:publication_date>2026-05-12T18:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689428</loc>
  <lastmod>2026-05-12T17:09:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膵嚢胞の画像診断を変える一歩（Differential Diagnosis for Pancreatic Cysts in CT Scans Using Densely-Connected Convolutional Networks）</news:title>
   <news:publication_date>2026-05-12T17:09:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689426</loc>
  <lastmod>2026-05-12T17:08:23Z</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ポテンシャルと古典力場の適応結合（Adaptive coupling of a deep neural network potential to a classical force field）</news:title>
   <news:publication_date>2026-05-12T17:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689424</loc>
  <lastmod>2026-05-12T17:07:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形ヌーリングによるメタラーニングの考え方と実務的含意（Meta-Learner with Linear Nulling）</news:title>
   <news:publication_date>2026-05-12T17:07:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689422</loc>
  <lastmod>2026-05-12T17:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的二重レベル多目的進化による単層・多層エコーステートネットワーク自己符号化器の進化（Hierarchical Bi-level Multi-Objective Evolution of Single- and Multi-layer Echo State Network Autoencoders for Data Representations）</news:title>
   <news:publication_date>2026-05-12T17:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689420</loc>
  <lastmod>2026-05-12T17:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度マルチモードファイバー内視鏡による深部脳イメージングの進展（High-fidelity multimode fibre-based endoscopy for deep‑brain in vivo imaging）</news:title>
   <news:publication_date>2026-05-12T17:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689418</loc>
  <lastmod>2026-05-12T17:05:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造グラフ上の全変動正則化推定量の理論と実務的示唆（On the total variation regularized estimator over a class of tree graphs）</news:title>
   <news:publication_date>2026-05-12T17:05:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689416</loc>
  <lastmod>2026-05-12T17:05:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データで熱赤外（TIR）トラッキングを変える（Synthetic data generation for end-to-end thermal infrared tracking）</news:title>
   <news:publication_date>2026-05-12T17:05:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689414</loc>
  <lastmod>2026-05-12T16:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互評価から学ぶ分散学習（Distributed Learning from Interactions in Social Networks）</news:title>
   <news:publication_date>2026-05-12T16:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689412</loc>
  <lastmod>2026-05-12T16:13:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>提案したエポックとMFCC特徴を用いたDNN-HMMベースの話者適応感情認識（DNN-HMM based Speaker Adaptive Emotion Recognition using Proposed Epoch and MFCC Features）</news:title>
   <news:publication_date>2026-05-12T16:13:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689410</loc>
  <lastmod>2026-05-12T16:12:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所適応大マージンを導入する深層埋め込み学習（ALMN: Deep Embedding Learning with Geometrical Virtual Point Generating）</news:title>
   <news:publication_date>2026-05-12T16:12:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689408</loc>
  <lastmod>2026-05-12T16:12:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汚れたカテゴリ変数の学習のための類似度エンコーディング (Similarity encoding for learning with dirty categorical variables)</news:title>
   <news:publication_date>2026-05-12T16:12:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689406</loc>
  <lastmod>2026-05-12T16:12:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークプロトコルの自動抽象化と弱教師ありクラスタリング（Automatic clustering of a network protocol with weakly-supervised clustering）</news:title>
   <news:publication_date>2026-05-12T16:12:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689404</loc>
  <lastmod>2026-05-12T16:11:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小平均の逐次検定：ThompsonからMurphyサンプリングへ（Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling）</news:title>
   <news:publication_date>2026-05-12T16:11:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689402</loc>
  <lastmod>2026-05-12T16:10:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師データなしで学習する画像デノイザ（Training deep learning based image denoisers from undersampled measurements without ground truth and without image prior）</news:title>
   <news:publication_date>2026-05-12T16:10:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689400</loc>
  <lastmod>2026-05-12T15:19:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライベートPAC学習は有限のLittlestone次元を示唆する（Private PAC learning implies finite Littlestone dimension）</news:title>
   <news:publication_date>2026-05-12T15:19:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689398</loc>
  <lastmod>2026-05-12T15:19:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配／ミラー降下法：ミニマックス最適性と暗黙の正則化（STOCHASTIC GRADIENT/MIRROR DESCENT: MINI-MAX OPTIMALITY AND IMPLICIT REGULARIZATION）</news:title>
   <news:publication_date>2026-05-12T15:19:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689396</loc>
  <lastmod>2026-05-12T15:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定化された自由空間光周波数伝送（Stabilized free-space optical frequency transfer）</news:title>
   <news:publication_date>2026-05-12T15:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689394</loc>
  <lastmod>2026-05-12T15:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小児X線画像におけるカテーテル自動検出（Automatic catheter detection in pediatric X-ray images using a scale-recurrent network and synthetic data）</news:title>
   <news:publication_date>2026-05-12T15:17:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689392</loc>
  <lastmod>2026-05-12T15:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホログラフィックニューラルアーキテクチャ（Holographic Neural Architectures）</news:title>
   <news:publication_date>2026-05-12T15:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689390</loc>
  <lastmod>2026-05-12T15:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚仕様からのプログラム合成（Program Synthesis from Visual Specification）</news:title>
   <news:publication_date>2026-05-12T15:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689388</loc>
  <lastmod>2026-05-12T15:16:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散計算の安全性と可用性を同時に高める設計 — Lagrange Coded Computing（Lagrange Coded Computing: Optimal Design for Resiliency, Security, and Privacy）</news:title>
   <news:publication_date>2026-05-12T15:16:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689386</loc>
  <lastmod>2026-05-12T14:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>伝統中国語向け読解データセットDRCDの構築と評価（DRCD: A Chinese Machine Reading Comprehension Dataset）</news:title>
   <news:publication_date>2026-05-12T14:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689384</loc>
  <lastmod>2026-05-12T14:23:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事実に自信を持ち滑らかさを保つ学習（Adversarial confidence and smoothness regularizations for scalable unsupervised discriminative learning）</news:title>
   <news:publication_date>2026-05-12T14:23:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689382</loc>
  <lastmod>2026-05-12T14:23:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>どれだけ共有するか？ポーカー風の選択的プライバシー保護フレームワーク（How Much Are You Willing to Share? A “Poker-Styled” Selective Privacy Preserving Framework for Recommender Systems）</news:title>
   <news:publication_date>2026-05-12T14:23:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689380</loc>
  <lastmod>2026-05-12T14:23:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ホモジニアスモデル学習におけるアルゴリズム的正則化（Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced）</news:title>
   <news:publication_date>2026-05-12T14:23:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689378</loc>
  <lastmod>2026-05-12T14:22:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>価格が品質を示す場合の競争的価格形成（Competitive pricing despite search costs if lower price signals quality）</news:title>
   <news:publication_date>2026-05-12T14:22:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689376</loc>
  <lastmod>2026-05-12T14:22:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空画像のシーン分類における最近の進展と機会（RECENT ADVANCES AND OPPORTUNITIES IN SCENE CLASSIFICATION OF AERIAL IMAGES WITH DEEP MODELS）</news:title>
   <news:publication_date>2026-05-12T14:22:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689374</loc>
  <lastmod>2026-05-12T14:22:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ多発の医療テキストから誤綴りを掘る自動生成器（An unsupervised and customizable misspelling generator for mining noisy health-related text sources）</news:title>
   <news:publication_date>2026-05-12T14:22:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689372</loc>
  <lastmod>2026-05-12T13:31:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像と深層学習によるアフリカのインフラ品質評価（Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning）</news:title>
   <news:publication_date>2026-05-12T13:31:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689370</loc>
  <lastmod>2026-05-12T13:21:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SparkとMPIをつなぐ「Alchemist」の意義（Alchemist: An Apache Spark ⇔MPI Interface）</news:title>
   <news:publication_date>2026-05-12T13:21:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689368</loc>
  <lastmod>2026-05-12T13:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>慎重な探索とインターリービングによる保守的探索（Conservative Exploration using Interleaving）</news:title>
   <news:publication_date>2026-05-12T13:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689366</loc>
  <lastmod>2026-05-12T13:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カスタマイズされたデータ表現と近似計算の機械学習応用への展開 (Deploying Customized Data Representation and Approximate Computing in Machine Learning Applications)</news:title>
   <news:publication_date>2026-05-12T13:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689364</loc>
  <lastmod>2026-05-12T13:18:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成敵対ネットワークにおける分断された多様体学習（Disconnected Manifold Learning for Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-12T13:18:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689362</loc>
  <lastmod>2026-05-12T13:18:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチエージェント強化学習における二重平均化と双対最適化（Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization）</news:title>
   <news:publication_date>2026-05-12T13:18:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689360</loc>
  <lastmod>2026-05-12T13:18:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分解によるMVRチェーングラフの構造学習 (Structural Learning of MVR Chain Graphs via Decomposition)</news:title>
   <news:publication_date>2026-05-12T13:18:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689358</loc>
  <lastmod>2026-05-12T12:25:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構がメタラーニングにもたらす効果（On the Importance of Attention in Meta-Learning for Few-Shot Text Classification）</news:title>
   <news:publication_date>2026-05-12T12:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689356</loc>
  <lastmod>2026-05-12T12:25:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚質問応答における反例検出（On the Flip Side: Identifying Counterexamples in Visual Question Answering）</news:title>
   <news:publication_date>2026-05-12T12:25:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689354</loc>
  <lastmod>2026-05-12T12:25:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データからグラフを学習する：信号表現の視点（Learning graphs from data: A signal representation perspective）</news:title>
   <news:publication_date>2026-05-12T12:25:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689352</loc>
  <lastmod>2026-05-12T12:24:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TernausNetV2による衛星画像のインスタンス分割（TernausNetV2: Fully Convolutional Network for Instance Segmentation）</news:title>
   <news:publication_date>2026-05-12T12:24:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689350</loc>
  <lastmod>2026-05-12T12:24:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在木学習と微分可能パーサによる文表現（Latent Tree Learning with Differentiable Parsers: Shift-Reduce Parsing and Chart Parsing）</news:title>
   <news:publication_date>2026-05-12T12:24:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689348</loc>
  <lastmod>2026-05-12T12:24:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像をConvNetで分類するCADシステムの研究（Study and development of a Computer-Aided Diagnosis system for classification of chest x-ray images using convolutional neural networks pre-trained for ImageNet and data augmentation）</news:title>
   <news:publication_date>2026-05-12T12:24:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689346</loc>
  <lastmod>2026-05-12T12:23:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BPjsによる反応型システムのモデリングフレームワーク（BPjs — a framework for modeling reactive systems using a scripting language and BP）</news:title>
   <news:publication_date>2026-05-12T12:23:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689344</loc>
  <lastmod>2026-05-12T11:32:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子位相転移の機械学習解析（Machine learning of quantum phase transitions）</news:title>
   <news:publication_date>2026-05-12T11:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689342</loc>
  <lastmod>2026-05-12T11:32:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低滑らかさ回帰関数に対する正則化Nyström部分サンプリングの解析（ANALYSIS OF REGULARIZED NYSTRÖM SUBSAMPLING FOR REGRESSION FUNCTIONS OF LOW SMOOTHNESS）</news:title>
   <news:publication_date>2026-05-12T11:32:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689340</loc>
  <lastmod>2026-05-12T11:31:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測データの雑音と欠損を乗り越える行列因子分解による因果推論（Causal Inference with Noisy and Missing Covariates via Matrix Factorization）</news:title>
   <news:publication_date>2026-05-12T11:31:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689338</loc>
  <lastmod>2026-05-12T11:31:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AID++: 航空画像シーン分類のための大規模データセット更新（AID++: AN UPDATED VERSION OF AID ON SCENE CLASSIFICATION）</news:title>
   <news:publication_date>2026-05-12T11:31:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689336</loc>
  <lastmod>2026-05-12T11:31:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文の意味的埋め込みの学習（Learning Semantic Sentence Embeddings using Pair-wise Discriminator）</news:title>
   <news:publication_date>2026-05-12T11:31:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689334</loc>
  <lastmod>2026-05-12T11:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列MRIのk空間ディープラーニング（k-Space Deep Learning for Parallel MRI: Application to Time-Resolved MR Angiography）</news:title>
   <news:publication_date>2026-05-12T11:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689332</loc>
  <lastmod>2026-05-12T11:30:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非敵対的な教師なしドメイン写像（NAM: Non-Adversarial Unsupervised Domain Mapping）</news:title>
   <news:publication_date>2026-05-12T11:30:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689330</loc>
  <lastmod>2026-05-12T10:39:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フロープレディクションによる光学フロー推定の進化（ProFlow: Learning to Predict Optical Flow）</news:title>
   <news:publication_date>2026-05-12T10:39:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689328</loc>
  <lastmod>2026-05-12T10:39:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジャックナイフ経験的尤度によるギニ相関とその等価性検定（Jackknife Empirical Likelihood Methods for Gini Correlations and their Equality Testing）</news:title>
   <news:publication_date>2026-05-12T10:39:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689326</loc>
  <lastmod>2026-05-12T10:39:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標志向対話システムのための高度な対話マネージャ構築（Building Advanced Dialogue Managers for Goal-Oriented Dialogue Systems）</news:title>
   <news:publication_date>2026-05-12T10:39:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689324</loc>
  <lastmod>2026-05-12T10:38:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化された強化学習における探索最小化（Exploration in Structured Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-12T10:38:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689322</loc>
  <lastmod>2026-05-12T10:38:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチキャスト注意機構による検索型質問応答と応答予測の革新（Multi-Cast Attention Networks for Retrieval-based Question Answering and Response Prediction）</news:title>
   <news:publication_date>2026-05-12T10:38:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689320</loc>
  <lastmod>2026-05-12T10:38:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドローンによる実時間監視と暴力者検出（Eye in the Sky: Real-time Drone Surveillance System for Violent Individuals Identification）</news:title>
   <news:publication_date>2026-05-12T10:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689318</loc>
  <lastmod>2026-05-12T10:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双対‑原始グラフ畳み込みネットワーク（Dual-Primal Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-05-12T10:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689316</loc>
  <lastmod>2026-05-12T09:47:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像列から物語を紡ぐニューラル・ビジュアルストーリーテラー（Contextualize, Show and Tell: A Neural Visual Storyteller）</news:title>
   <news:publication_date>2026-05-12T09:47:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689314</loc>
  <lastmod>2026-05-12T09:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次近似で迫る統計的二値分類の限界（Second-Order Asymptotically Optimal Statistical Classification）</news:title>
   <news:publication_date>2026-05-12T09:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689312</loc>
  <lastmod>2026-05-12T09:46:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメトリック偏微分方程式のデータ駆動同定（Data-driven identification of parametric partial differential equations）</news:title>
   <news:publication_date>2026-05-12T09:46:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689310</loc>
  <lastmod>2026-05-12T09:46:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型アテンションによるソーシャル文脈画像推薦（A Hierarchical Attention Model for Social Contextual Image Recommendation）</news:title>
   <news:publication_date>2026-05-12T09:46:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689308</loc>
  <lastmod>2026-05-12T09:45:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ無しでソフトマックスを設計する発想（Data-Free/Data-Sparse Softmax Parameter Estimation with Structured Class Geometries）</news:title>
   <news:publication_date>2026-05-12T09:45:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689306</loc>
  <lastmod>2026-05-12T09:45:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小ノルム学習が示す過学習への解（Minnorm training: an algorithm for training over-parameterized deep neural networks）</news:title>
   <news:publication_date>2026-05-12T09:45:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689304</loc>
  <lastmod>2026-05-12T09:45:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル機械翻訳における密情報フロー（Dense Information Flow for Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-12T09:45:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689302</loc>
  <lastmod>2026-05-12T08:54:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>走行データから学習・一般化するモーションプリミティブ（Learning and Generalizing Motion Primitives from Driving Data for Path-Tracking Applications）</news:title>
   <news:publication_date>2026-05-12T08:54:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689300</loc>
  <lastmod>2026-05-12T08:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データに効く分散型ガウス過程の整合化手法（Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression）</news:title>
   <news:publication_date>2026-05-12T08:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689298</loc>
  <lastmod>2026-05-12T08:52:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可解釈な階層的意味畳み込みニューラルネットワークによる肺結節悪性度分類（An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification）</news:title>
   <news:publication_date>2026-05-12T08:52:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689296</loc>
  <lastmod>2026-05-12T08:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライマル・デュアル Frank‑Wolfe による確率制約最適化の実務的示唆（Primal‑Dual Frank‑Wolfe for Constrained Stochastic Programs with Convex and Non‑convex Objectives）</news:title>
   <news:publication_date>2026-05-12T08:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689294</loc>
  <lastmod>2026-05-12T08:51:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレイヤー基底探索と効率的アルゴリズム（On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-12T08:51:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689292</loc>
  <lastmod>2026-05-12T08:51:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的注意機構を備えたリカレントハイウェイネットワークによる時系列予測（Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction）</news:title>
   <news:publication_date>2026-05-12T08:51:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689290</loc>
  <lastmod>2026-05-12T08:51:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フロンティアフィールド銀河団 MACS J1149 の質量モデルの実務的示唆（MASS MODELING OF FRONTIER FIELDS CLUSTER MACS J1149.5+2223 USING STRONG AND WEAK LENSING）</news:title>
   <news:publication_date>2026-05-12T08:51:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689288</loc>
  <lastmod>2026-05-12T08:00:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Pepperに学ぶ棋譜と知識の融合――強化学習におけるExpert Iteration型チェスエージェントの要点（Deep Pepper: Expert Iteration based Chess agent in the Reinforcement Learning Setting）</news:title>
   <news:publication_date>2026-05-12T08:00:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689286</loc>
  <lastmod>2026-05-12T07:59:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非局所ニューラルネットワーク、非局所拡散と非局所モデリング (Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling)</news:title>
   <news:publication_date>2026-05-12T07:59:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689284</loc>
  <lastmod>2026-05-12T07:58:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的大規模グラフのリアルタイム監視の幾何学的手法（A Geometric Approach for Real-time Monitoring of Dynamic Large Scale Graphs）</news:title>
   <news:publication_date>2026-05-12T07:58:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689282</loc>
  <lastmod>2026-05-12T07:58:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>理想化モデルが敵対的事例を持たない十分条件（Sufficient Conditions for Idealised Models to Have No Adversarial Examples）</news:title>
   <news:publication_date>2026-05-12T07:58:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689280</loc>
  <lastmod>2026-05-12T07:58:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>厚さで制御されるスメクティック—ヘキサティック転移と三重点への近接（Evidence of a first-order smectic – hexatic transition and its proximity to tricritical point in smectic films）</news:title>
   <news:publication_date>2026-05-12T07:58:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689278</loc>
  <lastmod>2026-05-12T07:58:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生涯固定時間学習と最良一致検索の鍵（SPARSE DISTRIBUTED REPRESENTATION, HIERARCHY, CRITICAL PERIODS, METAPLASTICITY）</news:title>
   <news:publication_date>2026-05-12T07:58:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689276</loc>
  <lastmod>2026-05-12T07:57:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性下での最適クラスタリング（Optimal Clustering under Uncertainty）</news:title>
   <news:publication_date>2026-05-12T07:57:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689274</loc>
  <lastmod>2026-05-12T07:05:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所解釈可能モデルと監督付き分割による説明手法（Locally Interpretable Models and Effects based on Supervised Partitioning）</news:title>
   <news:publication_date>2026-05-12T07:05:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689272</loc>
  <lastmod>2026-05-12T07:05:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>商用オークションデータのスクレイピングと前処理による詐欺検出基盤の作り方（Scraping and Preprocessing Commercial Auction Data for Fraud Classification）</news:title>
   <news:publication_date>2026-05-12T07:05:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689270</loc>
  <lastmod>2026-05-12T07:04:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計情報に依存しない直交マッチング追跡（Signal and Noise Statistics Oblivious Orthogonal Matching Pursuit）</news:title>
   <news:publication_date>2026-05-12T07:04:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689268</loc>
  <lastmod>2026-05-12T07:04:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非分解型性能指標に対する二値分類の最適化手法（Binary Classification with Karmic, Threshold-Quasi-Concave Metrics）</news:title>
   <news:publication_date>2026-05-12T07:04:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689266</loc>
  <lastmod>2026-05-12T07:04:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記憶モデルに着想を得たRNNの新たな枠組み（A Novel Framework for Recurrent Neural Networks with Enhancing Information Processing and Transmission between Units）</news:title>
   <news:publication_date>2026-05-12T07:04:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689264</loc>
  <lastmod>2026-05-12T07:03:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間・時間の深層特徴空間におけるSqueeze-and-Excitationによる行動認識強化（Squeeze-and-Excitation on Spatial and Temporal Deep Feature Space for Action Recognition）</news:title>
   <news:publication_date>2026-05-12T07:03:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689262</loc>
  <lastmod>2026-05-12T07:03:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DAQN: 深層オートエンコーダによる事前学習で強化学習の試行回数を削減する手法（DAQN: Deep Auto-encoder and Q-Network）</news:title>
   <news:publication_date>2026-05-12T07:03:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689260</loc>
  <lastmod>2026-05-12T06:12:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689258</loc>
  <lastmod>2026-05-12T06:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察から学ぶ内部モデルによる報酬設計（Internal Model from Observations for Reward Shaping）</news:title>
   <news:publication_date>2026-05-12T06:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689256</loc>
  <lastmod>2026-05-12T06:11:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック認識型生成対抗ネットワークによる胸部X線画像の教師なしドメイン適応（Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation）</news:title>
   <news:publication_date>2026-05-12T06:11:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689254</loc>
  <lastmod>2026-05-12T06:10:40Z</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>2026-05-12T06:10:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689252</loc>
  <lastmod>2026-05-12T06:10:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T06:10:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689250</loc>
  <lastmod>2026-05-12T06:10:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非IIDデータを扱う連合学習（Federated Learning with Non-IID Data）</news:title>
   <news:publication_date>2026-05-12T06:10:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689248</loc>
  <lastmod>2026-05-12T06:09:25Z</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>2026-05-12T06:09:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689246</loc>
  <lastmod>2026-05-12T05:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダが生成線形モデルを学ぶ方法（Autoencoders Learn Generative Linear Models）</news:title>
   <news:publication_date>2026-05-12T05:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689244</loc>
  <lastmod>2026-05-12T05:18:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的例の検出を狙うKey-based Network（Detecting Adversarial Examples via Key-based Network）</news:title>
   <news:publication_date>2026-05-12T05:18:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689242</loc>
  <lastmod>2026-05-12T05:17:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタラクティブな位置情報付きマルチメディア検索の効率化（Efficient Interactive Search for Geo-tagged Multimedia Data）</news:title>
   <news:publication_date>2026-05-12T05:17:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689240</loc>
  <lastmod>2026-05-12T05:17:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内在等長多様体学習と屋内位置推定への応用（INTRINSIC ISOMETRIC MANIFOLD LEARNING WITH APPLICATION TO LOCALIZATION）</news:title>
   <news:publication_date>2026-05-12T05:17:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689238</loc>
  <lastmod>2026-05-12T05:16:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリック学習における変数選択とパワーシリーズカーネル（Variable Selection for Nonparametric Learning with Power Series Kernels）</news:title>
   <news:publication_date>2026-05-12T05:16:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689236</loc>
  <lastmod>2026-05-12T05:16:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核物理観測量のモデル基づく外挿に対するベイズ的アプローチ（Bayesian approach to model-based extrapolation of nuclear observables）</news:title>
   <news:publication_date>2026-05-12T05:16:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689234</loc>
  <lastmod>2026-05-12T05:16:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い好奇心探索によるエージェント内探索（Deep Curiosity Search: Intra-Life Exploration Can Improve Performance on Challenging Deep Reinforcement Learning Problems）</news:title>
   <news:publication_date>2026-05-12T05:16:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689232</loc>
  <lastmod>2026-05-12T04:24:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wassersteinと価値認識型モデル学習の等価性（Equivalence Between Wasserstein and Value-Aware Loss for Model-based Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-12T04:24:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689230</loc>
  <lastmod>2026-05-12T04:23:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超金属量極低銀河の光学的同定と分光学的確認（Photometric identification and MMT spectroscopy of new extremely metal-poor galaxies: towards a better understanding of young stellar populations at low metallicity）</news:title>
   <news:publication_date>2026-05-12T04:23:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689228</loc>
  <lastmod>2026-05-12T04:23:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スイスアーミー級の無限小ジャックナイフ（A Swiss Army Infinitesimal Jackknife）</news:title>
   <news:publication_date>2026-05-12T04:23:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689226</loc>
  <lastmod>2026-05-12T04:23:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索の外部性とデータ多様性がもたらす効果（The Externalities of Exploration and How Data Diversity Helps Exploitation）</news:title>
   <news:publication_date>2026-05-12T04:23:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689224</loc>
  <lastmod>2026-05-12T04:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル近接勾配降下法による圧縮イメージング（Neural Proximal Gradient Descent for Compressive Imaging）</news:title>
   <news:publication_date>2026-05-12T04:22:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689222</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T04:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689220</loc>
  <lastmod>2026-05-12T04:22:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T04:22:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689218</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>行列因子化における収束保証付き加速（Provably convergent acceleration in factored gradient descent with applications in matrix sensing）</news:title>
   <news:publication_date>2026-05-12T03:31:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689216</loc>
  <lastmod>2026-05-12T03:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的かつ証明可能に最適なクラスタリング（Efficient, Certifiably Optimal Clustering with Applications to Latent Variable Graphical Models）</news:title>
   <news:publication_date>2026-05-12T03:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689214</loc>
  <lastmod>2026-05-12T03:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>体験記憶を強化学習エージェントに組み込む—リザバーサンプリングによる外部記憶管理（INTEGRATING EPISODIC MEMORY INTO A REINFORCEMENT LEARNING AGENT USING RESERVOIR SAMPLING）</news:title>
   <news:publication_date>2026-05-12T03:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689212</loc>
  <lastmod>2026-05-12T03:30:30Z</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>2026-05-12T03:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689210</loc>
  <lastmod>2026-05-12T03:30:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTM学習の逆伝播を構造的に疎化して高速化する手法（Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training）</news:title>
   <news:publication_date>2026-05-12T03:30:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689208</loc>
  <lastmod>2026-05-12T03:30:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T03:30:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689206</loc>
  <lastmod>2026-05-12T03:29:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の雑音に強いDNN音声強調（DNN Based Speech Enhancement for Unseen Noises Using Monte Carlo Dropout）</news:title>
   <news:publication_date>2026-05-12T03:29:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689204</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689202</loc>
  <lastmod>2026-05-12T02:38:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の視線から学ぶ注意で視覚運動タスクを効率化する（AGIL: Learning Attention from Human for Visuomotor Tasks）</news:title>
   <news:publication_date>2026-05-12T02:38:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689200</loc>
  <lastmod>2026-05-12T02:37:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形畳み込みネットワークにおける勾配降下法の暗黙的バイアス（Implicit Bias of Gradient Descent on Linear Convolutional Networks）</news:title>
   <news:publication_date>2026-05-12T02:37:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689198</loc>
  <lastmod>2026-05-12T02:36:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による材料物理の代替的枠組み（Machine learning materials physics: Surrogate optimization and multi-fidelity algorithms predict precipitate morphology in an alternative to phase field dynamics）</news:title>
   <news:publication_date>2026-05-12T02:36:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689196</loc>
  <lastmod>2026-05-12T02:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボット支援前立腺切除術における手術行動認識（Surgical Activity Recognition in Robot-Assisted Radical Prostatectomy using Deep Learning）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689194</loc>
  <lastmod>2026-05-12T02:36:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689192</loc>
  <lastmod>2026-05-12T02:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的スペクトル密度に対する逆伝播（Backpropagation for Implicit Spectral Densities）</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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 </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>入門天文学におけるLecture-Tutorialsの教育効果と実装指針（Lecture-Tutorials in Introductory Astronomy）</news:title>
   <news:publication_date>2026-05-12T01:43:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689186</loc>
  <lastmod>2026-05-12T01:43:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>純粋状態近似のための敵対的量子回路学習（Adversarial quantum circuit learning for pure state approximation）</news:title>
   <news:publication_date>2026-05-12T01:43:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689184</loc>
  <lastmod>2026-05-12T01:43:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的敵対ネットワークを用いた分布の補正（Unfolding with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-12T01:43:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689182</loc>
  <lastmod>2026-05-12T01:42:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前景・背景分類による教師なし視覚表現学習（A Classification approach towards Unsupervised Learning of Visual Representations）</news:title>
   <news:publication_date>2026-05-12T01:42:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689180</loc>
  <lastmod>2026-05-12T01:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CIFAR-10分類器は本当に一般化しているのか（Do CIFAR-10 Classiﬁers Generalize to CIFAR-10?）</news:title>
   <news:publication_date>2026-05-12T01:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689178</loc>
  <lastmod>2026-05-12T01:41:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーボリック空間における大余白分類（Large-Margin Classification in Hyperbolic Space）</news:title>
   <news:publication_date>2026-05-12T01:41:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689168</loc>
  <lastmod>2026-05-12T00:50:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Kolmogorov方程式を深層学習で解く（Solving the Kolmogorov PDE by means of deep learning）</news:title>
   <news:publication_date>2026-05-12T00:50:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689166</loc>
  <lastmod>2026-05-12T00:49:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Whitening と Coloring によるバッチ正規化の拡張（WHITENING AND COLORING BATCH TRANSFORM FOR GANS）</news:title>
   <news:publication_date>2026-05-12T00:49:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689164</loc>
  <lastmod>2026-05-12T00:48:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械は耳を持つとよりよく聞こえる（Machines hear better when they have ears）</news:title>
   <news:publication_date>2026-05-12T00:48:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689162</loc>
  <lastmod>2026-05-12T00:48:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多体系局在における相転移の特徴抽出の自動化（Automated discovery of characteristic features of phase transitions in many-body localization）</news:title>
   <news:publication_date>2026-05-12T00:48:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689160</loc>
  <lastmod>2026-05-12T00:47:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定なヘッシアン下でのニュートン法の全域線形収束（Global linear convergence of Newton’s method without strong-convexity or Lipschitz gradients）</news:title>
   <news:publication_date>2026-05-12T00:47:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689158</loc>
  <lastmod>2026-05-12T00:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴に適応するグラフと過分割グラフ（Adapted and Oversegmenting Graphs: Application to Geometric Deep Learning）</news:title>
   <news:publication_date>2026-05-12T00:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689156</loc>
  <lastmod>2026-05-12T00:46:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パターン探索型多次元尺度法（Pattern Search Multidimensional Scaling）</news:title>
   <news:publication_date>2026-05-12T00:46:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689154</loc>
  <lastmod>2026-05-11T23:55:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表現の逆変換と自己回帰密度モデルによる解釈（Inverting Supervised Representations with Autoregressive Neural Density Models）</news:title>
   <news:publication_date>2026-05-11T23:55:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689152</loc>
  <lastmod>2026-05-11T23:55:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続学習で素子の信頼性問題を克服する（Overcoming device unreliability with continuous learning in a population coding based computing system）</news:title>
   <news:publication_date>2026-05-11T23:55:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689150</loc>
  <lastmod>2026-05-11T23:55:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電波銀河形態の生成と解析（Radio Galaxy Morphology Generation Using DNN Autoencoder and Gaussian Mixture Models）</news:title>
   <news:publication_date>2026-05-11T23:55:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689148</loc>
  <lastmod>2026-05-11T23:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙インフレーションは究極の顕微鏡である（Cosmic Inflation: The Most Powerful Microscope in the Universe）</news:title>
   <news:publication_date>2026-05-11T23:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689146</loc>
  <lastmod>2026-05-11T23:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療分野における機械学習の課題と機会の総覧（A Review of Challenges and Opportunities in Machine Learning for Health）</news:title>
   <news:publication_date>2026-05-11T23:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689144</loc>
  <lastmod>2026-05-11T23:54:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーシステンス・パスとシグネチャ特徴量による位相データ解析（Persistence paths and signature features in topological data analysis）</news:title>
   <news:publication_date>2026-05-11T23:54:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689142</loc>
  <lastmod>2026-05-11T23:53:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNN訓練の収束を加速する非線形手法の実践的意義（NONLINEAR ACCELERATION OF CNNS）</news:title>
   <news:publication_date>2026-05-11T23:53:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689140</loc>
  <lastmod>2026-05-11T23:02:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模顔認識のための高精度かつ高効率な類似検索（Accurate and Efficient Similarity Search for Large Scale Face Recognition）</news:title>
   <news:publication_date>2026-05-11T23:02:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689138</loc>
  <lastmod>2026-05-11T23:02:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線診断レポート品質の自動生成による説明可能なAIの道（Producing radiologist-quality reports for interpretable artificial intelligence）</news:title>
   <news:publication_date>2026-05-11T23:02:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689136</loc>
  <lastmod>2026-05-11T23:02:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRI臓器セグメンテーションのドメイン適応と逆分類精度（Domain Adaptation for MRI Organ Segmentation using Reverse Classification Accuracy）</news:title>
   <news:publication_date>2026-05-11T23:02:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689134</loc>
  <lastmod>2026-05-11T23:02:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ケプラー観測データにおけるフレア検出の機械学習的手法（Finding flares in Kepler data using machine-learning tools）</news:title>
   <news:publication_date>2026-05-11T23:02:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689132</loc>
  <lastmod>2026-05-11T23:01:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習型圧縮アーティファクト除去の実践：深層残差ネットワークによるBPG後処理（Learned Compression Artifact Removal by Deep Residual Networks）</news:title>
   <news:publication_date>2026-05-11T23:01:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689130</loc>
  <lastmod>2026-05-11T23:01:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース盲復号における局所最適解の構造（Structured Local Optima in Sparse Blind Deconvolution）</news:title>
   <news:publication_date>2026-05-11T23:01:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689128</loc>
  <lastmod>2026-05-11T23:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチユーザーネットワークにおける情報鮮度最適化と強化学習の適用（A Reinforcement Learning Approach to Age of Information in Multi-User Networks）</news:title>
   <news:publication_date>2026-05-11T23:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689126</loc>
  <lastmod>2026-05-11T22:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分相関ハイパーサーフェスと有向ガウス型グラフィカルモデル（Partial Correlation Hypersurfaces in Gaussian Graphical Models）</news:title>
   <news:publication_date>2026-05-11T22:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689124</loc>
  <lastmod>2026-05-11T22:09:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存知識を活かして新しい解剖学と画像を学ぶ（Learn the new, keep the old: Extending pretrained models with new anatomy and images）</news:title>
   <news:publication_date>2026-05-11T22:09:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689122</loc>
  <lastmod>2026-05-11T22:09:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による凸境界を用いた線形二次制御方策合成（Learning convex bounds for linear quadratic control policy synthesis）</news:title>
   <news:publication_date>2026-05-11T22:09:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689120</loc>
  <lastmod>2026-05-11T22:08:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテの自然言語生成（Natural Language Generation for Electronic Health Records）</news:title>
   <news:publication_date>2026-05-11T22:08:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689118</loc>
  <lastmod>2026-05-11T22:08:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Oblivious DNSによるDNS問い合わせのプライバシー確保（Oblivious DNS: Practical Privacy for DNS Queries）</news:title>
   <news:publication_date>2026-05-11T22:08:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689116</loc>
  <lastmod>2026-05-11T22:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>包括的ニューラルランダムフィールドによる生成モデリング（Generative Modeling by Inclusive Neural Random Fields）</news:title>
   <news:publication_date>2026-05-11T22:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689114</loc>
  <lastmod>2026-05-11T22:07:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一チャンネル音源分離のためのスパース探索と辞書学習（Sparse Pursuit and Dictionary Learning for Blind Source Separation in Polyphonic Music Recordings）</news:title>
   <news:publication_date>2026-05-11T22:07:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689112</loc>
  <lastmod>2026-05-11T21:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推論を活用した強化学習によるクラウドソーシングのインセンティブ設計（Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing）</news:title>
   <news:publication_date>2026-05-11T21:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689110</loc>
  <lastmod>2026-05-11T21:08:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球状星団における中間質量ブラックホールの探査（THE MAVERIC SURVEY: STILL NO EVIDENCE FOR ACCRETING INTERMEDIATE-MASS BLACK HOLES IN GLOBULAR CLUSTERS）</news:title>
   <news:publication_date>2026-05-11T21:08:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689108</loc>
  <lastmod>2026-05-11T21:08:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二ブロック可分凸最適化問題に対する近接交互最小化アルゴリズム（The Proximal Alternating Minimization Algorithm for two-block separable convex optimization problems with linear constraints）</news:title>
   <news:publication_date>2026-05-11T21:08:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689106</loc>
  <lastmod>2026-05-11T21:07:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル機械翻訳におけるドメイン適応の総覧（A Survey of Domain Adaptation for Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-11T21:07:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689104</loc>
  <lastmod>2026-05-11T21:06:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TAPASによる学習不要の精度予測（TAPAS: Train-less Accuracy Predictor for Architecture Search）</news:title>
   <news:publication_date>2026-05-11T21:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689102</loc>
  <lastmod>2026-05-11T21:06:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANを使った教師なし物体共ローカライゼーション（Generative Adversarial Networks for Unsupervised Object Co-localization）</news:title>
   <news:publication_date>2026-05-11T21:06:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689100</loc>
  <lastmod>2026-05-11T21:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書の分割と学習目標自動生成がもたらす授業設計の効率化（Document Chunking and Learning Objective Generation for Instruction Design）</news:title>
   <news:publication_date>2026-05-11T21:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689098</loc>
  <lastmod>2026-05-11T20:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不正確な近接オンライン勾配法による動的最適化の追跡（Online Learning with Inexact Proximal Online Gradient Descent Algorithms）</news:title>
   <news:publication_date>2026-05-11T20:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689096</loc>
  <lastmod>2026-05-11T20:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>問いへの好奇心を育てる――学習した注意機構によるノベルティ探索（Being curious about the answers to questions: novelty search with learned attention）</news:title>
   <news:publication_date>2026-05-11T20:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689094</loc>
  <lastmod>2026-05-11T20:13:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多車両フロッキング制御におけるDDPGの適用（Multi-vehicle Flocking Control with Deep Deterministic Policy Gradient Method）</news:title>
   <news:publication_date>2026-05-11T20:13:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689092</loc>
  <lastmod>2026-05-11T20:12:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチトラック楽曲の潜在空間学習（LEARNING A LATENT SPACE OF MULTITRACK MEASURES）</news:title>
   <news:publication_date>2026-05-11T20:12:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689090</loc>
  <lastmod>2026-05-11T20:12:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル機械翻訳のスケーリング（Scaling Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-11T20:12:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689088</loc>
  <lastmod>2026-05-11T20:12:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データに強い顔認識表現学習（Deep Imbalanced Learning for Face Recognition and Attribute Prediction）</news:title>
   <news:publication_date>2026-05-11T20:12:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689086</loc>
  <lastmod>2026-05-11T20:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオ記述技術の全体像と評価指標の課題（Video Description: A Survey of Methods, Datasets and Evaluation Metrics）</news:title>
   <news:publication_date>2026-05-11T20:12:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689084</loc>
  <lastmod>2026-05-11T19:20:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間-スペクトル深層残差ネットワークによる高スペクトル画像のノイズ除去（Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-11T19:20:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689082</loc>
  <lastmod>2026-05-11T19:20:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形係数による深層ニューラルネットワークの一般化予測（The Nonlinearity Coefficient: Predicting Generalization in Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-11T19:20:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689080</loc>
  <lastmod>2026-05-11T19:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化の理解（Understanding Batch Normalization）</news:title>
   <news:publication_date>2026-05-11T19:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689078</loc>
  <lastmod>2026-05-11T19:19:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタリーブド低ランクグループ畳み込み（IGCV3: Interleaved Low-Rank Group Convolutions）</news:title>
   <news:publication_date>2026-05-11T19:19:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689076</loc>
  <lastmod>2026-05-11T19:19:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抵抗性クロスポイント素子によるLSTM学習の高速化（Training LSTM Networks with Resistive Cross-Point Devices）</news:title>
   <news:publication_date>2026-05-11T19:19:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689074</loc>
  <lastmod>2026-05-11T19:19:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>簡略モデルと概ね楽観的計画による高速探索（FAST EXPLORATION WITH SIMPLIFIED MODELS AND APPROXIMATELY OPTIMISTIC PLANNING IN MODEL-BASED REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-05-11T19:19:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689072</loc>
  <lastmod>2026-05-11T19:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非微分モデルの再パラメータ化勾配（Reparameterization Gradient for Non-differentiable Models）</news:title>
   <news:publication_date>2026-05-11T19:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689070</loc>
  <lastmod>2026-05-11T18:27:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル制御変量によるモンテカルロ分散削減（Neural Control Variates for Monte Carlo Variance Reduction）</news:title>
   <news:publication_date>2026-05-11T18:27:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689068</loc>
  <lastmod>2026-05-11T18:27:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スピーチ駆動で表現豊かなリップ同期を実現する条件付き逐次生成対抗ネットワーク（Speech-Driven Expressive Talking Lips with Conditional Sequential Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-11T18:27:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689066</loc>
  <lastmod>2026-05-11T18:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深くネストされた階層モデルの高速推定（Fitting a Deeply-Nested Hierarchical Model to a Large Book Review Dataset Using a Moment-Based Estimator）</news:title>
   <news:publication_date>2026-05-11T18:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689064</loc>
  <lastmod>2026-05-11T18:26:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンデムブロックによる畳み込みニューラルネットワークの再考（Tandem Blocks in Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-11T18:26:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689062</loc>
  <lastmod>2026-05-11T18:26:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照スキャン不要なEPIゴースト補正のk-空間ディープラーニング（k-Space Deep Learning for Reference-free EPI Ghost Correction）</news:title>
   <news:publication_date>2026-05-11T18:26:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689060</loc>
  <lastmod>2026-05-11T18:26:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ジャクソン微分に基づくq-ニューロン（q-Neurons: Neuron Activations based on Stochastic Jackson’s Derivative Operators）</news:title>
   <news:publication_date>2026-05-11T18:26:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689058</loc>
  <lastmod>2026-05-11T18:25:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の解釈は投影図である（Interpreting Deep Learning: The Machine Learning Rorschach Test?）</news:title>
   <news:publication_date>2026-05-11T18:25:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689056</loc>
  <lastmod>2026-05-11T17:33:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>まれな危険状況に対する予防行動の模倣学習（Modeling Preemptive Behaviors for Uncommon Hazardous Situations From Demonstrations）</news:title>
   <news:publication_date>2026-05-11T17:33:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689054</loc>
  <lastmod>2026-05-11T17:33:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海面水温の予測と再構築におけるパッチレベルニューラルネットワーク表現（SEA SURFACE TEMPERATURE PREDICTION AND RECONSTRUCTION USING PATCH-LEVEL NEURAL NETWORK REPRESENTATIONS）</news:title>
   <news:publication_date>2026-05-11T17:33:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689052</loc>
  <lastmod>2026-05-11T17:33:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチレベル3D CNNによるマルチスケール空間特徴学習（Multi-level 3D CNN for Learning Multi-scale Spatial Features）</news:title>
   <news:publication_date>2026-05-11T17:33:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689050</loc>
  <lastmod>2026-05-11T17:31:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチコア環境における並列多重配列アラインメントアルゴリズムの現状調査（A Survey of the State-of-the-Art Parallel Multiple Sequence Alignment Algorithms on Multicore Systems）</news:title>
   <news:publication_date>2026-05-11T17:31:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689048</loc>
  <lastmod>2026-05-11T17:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模シーンにおける光フローを用いた新規ビデオ予測（Novel Video Prediction for Large-scale Scene using Optical Flow）</news:title>
   <news:publication_date>2026-05-11T17:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689046</loc>
  <lastmod>2026-05-11T17:31:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロンの重要度はどのように測るか（How Important Is a Neuron?）</news:title>
   <news:publication_date>2026-05-11T17:31:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689044</loc>
  <lastmod>2026-05-11T17:31:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙モデルから“金鉱”を掘る――シミュレータを用いた尤度フリー推論の効率化 (Mining gold from implicit models to improve likelihood-free inference)</news:title>
   <news:publication_date>2026-05-11T17:31:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689042</loc>
  <lastmod>2026-05-11T16:39:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人のゲノムを大規模に分類・推定する畳み込み埋め込みネットワーク（Convolutional Embedded Networks for Population Scale Clustering and Bio-ancestry Inferencing）</news:title>
   <news:publication_date>2026-05-11T16:39:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689040</loc>
  <lastmod>2026-05-11T16:38:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>携帯通信記録からの居場所推定と在場パターン解析（Characterizing presence patterns and segmenting user locations from cell phone data）</news:title>
   <news:publication_date>2026-05-11T16:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/689038</loc>
  <lastmod>2026-05-11T16:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロン編集による外挿可能な変換学習（Out-of-Sample Extrapolation with Neuron Editing）</news:title>
   <news:publication_date>2026-05-11T16:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/689036</loc>
  <lastmod>2026-05-11T16:37:00Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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