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   <news:title>スパースロジスティック回帰による離散対向グラフモデルの学習（Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models）</news:title>
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   <news:title>離散テンソル分解のスムーズ解析（Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons）</news:title>
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   <news:title>非並列テキスト転換の教師なし評価指標と学習基準（Unsupervised Evaluation Metrics and Learning Criteria for Non-Parallel Textual Transfer）</news:title>
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   <news:title>相関の強いGPポスターの効率的サンプリングを可能にするRMHMCの実装（An Efficient Implementation of Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>材料シミュレーションのための均一に高精度な原子間ポテンシャルの能動学習（Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation）</news:title>
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    <news:language>ja</news:language>
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   <news:title>変化面──多次元的変化点と反事実予測（Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>胎児心エコー動画における局所時空間解剖学的位置特定（SEQUENTIAL ANATOMY LOCALIZATION IN FETAL ECHOCARDIOGRAPHY VIDEO）</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>コスト意識的因果グラフ学習の実験デザイン（Experimental Design for Cost-Aware Learning of Causal Graphs）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>汚れた訓練データから学ぶ反復トリム損失最小化（Learning with Bad Training Data via Iterative Trimmed Loss Minimization）</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>上位ρ分位からk本の腕を選ぶ探索手法の考察（Exploring k out of Top ρ Fraction of Arms in Stochastic Bandits）</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>宇宙の夜明けにおける21cm信号の解析的定式化（Analytic Formulation of 21 cm Signal from Cosmic Dawn: Lyα Fluctuations）</news:title>
   <news:publication_date>2026-06-28T18:27:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-28T18:27:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LPCNetによる低コスト音声合成（LPCNet: IMPROVING NEURAL SPEECH SYNTHESIS THROUGH LINEAR PREDICTION）</news:title>
   <news:publication_date>2026-06-28T18:27:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705918</loc>
  <lastmod>2026-06-28T18:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>資源制約下で「最大値」を狙うオンライン学習フレームワーク（MaxHedge: Maximising a Maximum Online）</news:title>
   <news:publication_date>2026-06-28T18:26:22Z</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>大規模視覚データを機械学習向けに高速に扱う仕組み（VDMS: Efficient Big-Visual-Data Access for Machine Learning Workloads）</news:title>
   <news:publication_date>2026-06-28T18:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705914</loc>
  <lastmod>2026-06-28T18:25:54Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>画像ノイズ除去のための強化畳み込みニューラルネットワーク（Enhanced CNN for image denoising）</news:title>
   <news:publication_date>2026-06-28T18:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-28T18:25:46Z</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>雲を「ノイズ」と見なす衛星画像の頑健なセグメンテーション（Convolutional LSTMs for Cloud-Robust Segmentation of Remote Sensing Imagery）</news:title>
   <news:publication_date>2026-06-28T18:25:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705910</loc>
  <lastmod>2026-06-28T17:34:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>専門家助言の統合による差別保持の問題（On preserving non-discrimination when combining expert advice）</news:title>
   <news:publication_date>2026-06-28T17:34:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705908</loc>
  <lastmod>2026-06-28T17:34:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ハイパースペクトル動画における物体追跡の新手法（Object Tracking in Hyperspectral Videos with Convolutional Features and Kernelized Correlation Filter）</news:title>
   <news:publication_date>2026-06-28T17:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705906</loc>
  <lastmod>2026-06-28T17:34:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ハイパーグラフに基づく半教師あり学習アルゴリズムの音声認識への適用（Hypergraph Based Semi-Supervised Learning Algorithms Applied to Speech Recognition Problem）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705904</loc>
  <lastmod>2026-06-28T17:33:27Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>識別力を重視したチャネル削減（Discrimination-aware Channel Pruning for Deep Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705902</loc>
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  <news:news>
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    <news:language>ja</news:language>
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   <news:title>TV事前情報を用いた画像超解像の実用的意味（Image Super-Resolution Using TV Priori Guided Convolutional Network）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705900</loc>
  <lastmod>2026-06-28T17:33:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ロボットが「ノー」を学ぶ――否定語獲得における禁止と拒否のメカニズム（Robots Learning to Say ‘No’: Prohibition and Rejective Mechanisms in Acquisition of Linguistic Negation）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705898</loc>
  <lastmod>2026-06-28T17:32:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>四次元におけるボソン—フェルミオン双対性（Boson-fermion duality in four dimensions）</news:title>
   <news:publication_date>2026-06-28T17:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705896</loc>
  <lastmod>2026-06-28T16:41:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>陽子スピンの深い混合（Proton Spin in Deep Inelastic Scattering）</news:title>
   <news:publication_date>2026-06-28T16:41:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705894</loc>
  <lastmod>2026-06-28T16:41:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>深層ニューラルネットワークの分散学習ガイド（A Hitchhiker’s Guide On Distributed Training of Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T16:41:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705892</loc>
  <lastmod>2026-06-28T16:41:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理世界で機能する音声の敵対的事例の生成（Robust Audio Adversarial Example for a Physical Attack）</news:title>
   <news:publication_date>2026-06-28T16:41:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705890</loc>
  <lastmod>2026-06-28T16:41:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的ヤコビアン境界アルゴリズム RecurJac（RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications）</news:title>
   <news:publication_date>2026-06-28T16:41:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705888</loc>
  <lastmod>2026-06-28T16:40:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Affinity Network による複数物体追跡の再設計（Deep Affinity Network for Multiple Object Tracking）</news:title>
   <news:publication_date>2026-06-28T16:40:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705886</loc>
  <lastmod>2026-06-28T16:40:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パリティ奇数のニュートリノトルク検出（Parity-odd neutrino torque detection）</news:title>
   <news:publication_date>2026-06-28T16:40:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/705884</loc>
  <lastmod>2026-06-28T16:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的系における安定で予測可能な構造の学習（Learning stable and predictive structures in kinetic systems: Benefits of a causal approach）</news:title>
   <news:publication_date>2026-06-28T16:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/705882</loc>
  <lastmod>2026-06-28T15:49:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>解析モデルと機械学習の融合による性能予測（Learning with Analytical Models）</news:title>
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   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>シナプスから空間記憶地図へ（Through synapses to spatial memory maps: a topological model）</news:title>
   <news:publication_date>2026-06-28T15:49:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-28T15:48:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感度駆動型正則化によるスパースニューラルネット学習（Learning Sparse Neural Networks via Sensitivity-Driven Regularization）</news:title>
   <news:publication_date>2026-06-28T15:48:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/705876</loc>
  <lastmod>2026-06-28T15:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ネットワークの中心性を学習で高速化する研究（Computing Vertex Centrality Measures in Massive Real Networks with a Neural Learning Model）</news:title>
   <news:publication_date>2026-06-28T15:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705874</loc>
  <lastmod>2026-06-28T15:48:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習とリザバーコンピューティングによる分散型動的スペクトラムアクセス（Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach）</news:title>
   <news:publication_date>2026-06-28T15:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705872</loc>
  <lastmod>2026-06-28T15:47:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察されていないものを見る：並列化されたモンテカルロ木探索の単純なアプローチ（WATCH THE UNOBSERVED: A SIMPLE APPROACH TO PARALLELIZING MONTE CARLO TREE SEARCH）</news:title>
   <news:publication_date>2026-06-28T15:47:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705870</loc>
  <lastmod>2026-06-28T15:47:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク中心性指標における機械学習による近似手法（Machine Learning in Network Centrality Measures: Tutorial and Outlook）</news:title>
   <news:publication_date>2026-06-28T15:47:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705868</loc>
  <lastmod>2026-06-28T14:56:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルコフ連鎖の学習（On Learning Markov Chains）</news:title>
   <news:publication_date>2026-06-28T14:56:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705866</loc>
  <lastmod>2026-06-28T14:56:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習表現の理解に向けて：異なるニューラルネットワークはどの程度同じ表現を学ぶか (Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation)</news:title>
   <news:publication_date>2026-06-28T14:56:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705864</loc>
  <lastmod>2026-06-28T14:56:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DQN-TAMERによる人間-in-the-loop強化学習（DQN-TAMER: Human-in-the-Loop Reinforcement Learning with Intractable Feedback）</news:title>
   <news:publication_date>2026-06-28T14:56:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705862</loc>
  <lastmod>2026-06-28T14:55:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>残差ニューラルネットワークの深層極限（Deep Limits of Residual Neural Networks）</news:title>
   <news:publication_date>2026-06-28T14:55:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705860</loc>
  <lastmod>2026-06-28T14:54:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程事前分布付き変分オートエンコーダ（Gaussian Process Prior Variational Autoencoders）</news:title>
   <news:publication_date>2026-06-28T14:54:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705858</loc>
  <lastmod>2026-06-28T14:54:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形動力学のサンプル複雑度（Sample Complexity for Nonlinear Dynamics）</news:title>
   <news:publication_date>2026-06-28T14:54:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705856</loc>
  <lastmod>2026-06-28T14:54:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANに対する凸双対性フレームワークの示唆（A Convex Duality Framework for GANs）</news:title>
   <news:publication_date>2026-06-28T14:54:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705854</loc>
  <lastmod>2026-06-28T14:03:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専用モジュールネットワークの類似性基準による訓練によるリアルタイム行動認識 (Real-time Action Recognition with Dissimilarity-based Training of Specialized Module Networks)</news:title>
   <news:publication_date>2026-06-28T14:03:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705852</loc>
  <lastmod>2026-06-28T14:02:58Z</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におけるクリティカルパスの蒸留（Distilling Critical Paths in Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-28T14:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705850</loc>
  <lastmod>2026-06-28T14:02:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共分散保存型敵対的拡張ネットワーク（Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks）</news:title>
   <news:publication_date>2026-06-28T14:02:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705848</loc>
  <lastmod>2026-06-28T14:01:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CoSTARによるブロック積みデータセットとワークスペース制約（The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints）</news:title>
   <news:publication_date>2026-06-28T14:01:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705846</loc>
  <lastmod>2026-06-28T14:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FGSMの正則化効果とその一般化（Regularization Effect of Fast Gradient Sign Method and its Generalization）</news:title>
   <news:publication_date>2026-06-28T14:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705844</loc>
  <lastmod>2026-06-28T14:01:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢な深層ニューラルネットワークの探索（Towards Robust Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T14:01:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705842</loc>
  <lastmod>2026-06-28T14:01:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数グループNB‑IoTネットワークの協調深層強化学習による最適化（Cooperative Deep Reinforcement Learning for Multiple-Group NB-IoT Networks Optimization）</news:title>
   <news:publication_date>2026-06-28T14:01:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705840</loc>
  <lastmod>2026-06-28T13:10:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報欠損に基づく表現学習の新潮流：Variational Deficiency Bottleneck（The Variational Deficiency Bottleneck）</news:title>
   <news:publication_date>2026-06-28T13:10:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705838</loc>
  <lastmod>2026-06-28T13:01:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インテリジェント・ナノフォトニクス：ナノスケールで光学と人工知能を融合する研究（Intelligent Nanophotonics: Merging Photonics and Artificial Intelligence at the Nanoscale）</news:title>
   <news:publication_date>2026-06-28T13:01:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705836</loc>
  <lastmod>2026-06-28T13:00:50Z</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共通知識強化学習（Multi-Agent Common Knowledge）</news:title>
   <news:publication_date>2026-06-28T13:00:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705834</loc>
  <lastmod>2026-06-28T13:00:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイヤレスバックスキャッタで繰り返し動作を認識・計測する（From Communication to Sensing: Recognizing and Counting Repetitive Motions with Wireless Backscattering）</news:title>
   <news:publication_date>2026-06-28T13:00:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705832</loc>
  <lastmod>2026-06-28T13:00:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stein Variational Gradient Descentのモーメント一致性（Stein Variational Gradient Descent as Moment Matching）</news:title>
   <news:publication_date>2026-06-28T13:00:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705830</loc>
  <lastmod>2026-06-28T13:00:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実な入力を扱う回帰木（Uncertain Trees: Dealing with Uncertain Inputs in Regression Trees）</news:title>
   <news:publication_date>2026-06-28T13:00:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705828</loc>
  <lastmod>2026-06-28T12:59:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主成分分析と深層ニューラルネットワークによる船体最適化（Hull Form Optimization with Principal Component Analysis and Deep Neural Network）</news:title>
   <news:publication_date>2026-06-28T12:59:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705826</loc>
  <lastmod>2026-06-28T12:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロブログを用いた疑わしいニュース検出（Suspicious News Detection Using Micro Blog Text）</news:title>
   <news:publication_date>2026-06-28T12:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705824</loc>
  <lastmod>2026-06-28T11:59:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートシティにおけるSDN・AI・ビッグデータの統合的活用（Towards Smart City Innovation Under the Perspective of Software-Defined Networking, Artificial Intelligence and Big Data）</news:title>
   <news:publication_date>2026-06-28T11:59:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705822</loc>
  <lastmod>2026-06-28T11:59:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒエラルキー型ソフトマックスのXMLCへの無後悔一般化（A no-regret generalization of hierarchical softmax to extreme multi-label classification）</news:title>
   <news:publication_date>2026-06-28T11:59:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705820</loc>
  <lastmod>2026-06-28T11:58:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハーディのパラドックスを用いた実用的なノーシグナリング証明ランダムネス増幅と実験実装 (Practical No-Signalling proof Randomness Amplification using Hardy paradoxes and its experimental implementation)</news:title>
   <news:publication_date>2026-06-28T11:58:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705818</loc>
  <lastmod>2026-06-28T11:58:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みネットワークとアダマールネットワークの等価性（On the Equivalence of Convolutional and Hadamard Networks using DFT）</news:title>
   <news:publication_date>2026-06-28T11:58:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705816</loc>
  <lastmod>2026-06-28T11:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラウザで協働設計するニューラルネットワーク編集ツール（Fabrik: An online collaborative neural network editor）</news:title>
   <news:publication_date>2026-06-28T11:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705814</loc>
  <lastmod>2026-06-28T11:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>活性化関数の自動選択手法によるハイブリッド深層ニューラルネットワーク設計（A Methodology for Automatic Selection of Activation Functions to Design Hybrid Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T11:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705812</loc>
  <lastmod>2026-06-28T11:06:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>区間タイプの特徴化に基づく時系列クラスタリング（Time series clustering based on the characterisation of segment typologies）</news:title>
   <news:publication_date>2026-06-28T11:06:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705810</loc>
  <lastmod>2026-06-28T10:58:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆方向（後方角度）でのω光生成過程における核子Reggeonとパートン寄与の役割（Features of ω photoproduction off proton target at backward angles : Role of nucleon Reggeon in u-channel with parton contributions）</news:title>
   <news:publication_date>2026-06-28T10:58:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705808</loc>
  <lastmod>2026-06-28T10:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実験データで観察データの隠れ交絡を是正する方法（Removing Hidden Confounding by Experimental Grounding）</news:title>
   <news:publication_date>2026-06-28T10:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705806</loc>
  <lastmod>2026-06-28T10:57:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGBとDepthを横断する人物再識別のためのクロスモーダル蒸留（Cross-Modal Distillation for Person Re-Identification）</news:title>
   <news:publication_date>2026-06-28T10:57:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705804</loc>
  <lastmod>2026-06-28T10:57:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による雑音除去の実践と意義（Deep learning for denoising）</news:title>
   <news:publication_date>2026-06-28T10:57:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705802</loc>
  <lastmod>2026-06-28T10:56:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル比較のための判別的特徴抽出（Informative Features for Model Comparison）</news:title>
   <news:publication_date>2026-06-28T10:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705800</loc>
  <lastmod>2026-06-28T10:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集団知能のエージェントベースモデル入門（Agent-based models of collective intelligence）</news:title>
   <news:publication_date>2026-06-28T10:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705798</loc>
  <lastmod>2026-06-28T10:05:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データを扱うマルチラベル分類の改善（Handling Imbalanced Dataset in Multi-label Text Categorization using Bagging and Adaptive Boosting）</news:title>
   <news:publication_date>2026-06-28T10:05:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705796</loc>
  <lastmod>2026-06-28T10:05:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTのための学習と管理：適応性とスケーラビリティへの挑戦（Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability）</news:title>
   <news:publication_date>2026-06-28T10:05:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705794</loc>
  <lastmod>2026-06-28T10:05:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトゲート型Warping-GANによる姿勢誘導人物画像生成（Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis）</news:title>
   <news:publication_date>2026-06-28T10:05:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705792</loc>
  <lastmod>2026-06-28T10:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非局所フロッキング動力学：粒子シミュレーションからPDEの分数次数を学習する（Nonlocal flocking dynamics: Learning the fractional order of PDEs from particle simulations）</news:title>
   <news:publication_date>2026-06-28T10:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705790</loc>
  <lastmod>2026-06-28T10:04:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できる予測確率の調整法の実務的進化（Attended Temperature Scaling: A Practical Approach for Calibrating Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-28T10:04:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705788</loc>
  <lastmod>2026-06-28T10:04:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>忘却に対抗する自己教師ありGAN（Self-Supervised GAN to Counter Forgetting）</news:title>
   <news:publication_date>2026-06-28T10:04:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705786</loc>
  <lastmod>2026-06-28T10:04:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>余クラス受容野を持つ畳み込みニューラルネットワーク（Convolutional neural networks with extra-classical receptive fields）</news:title>
   <news:publication_date>2026-06-28T10:04:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705784</loc>
  <lastmod>2026-06-28T09:13:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈性に基づく敵対サンプル検出（Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples）</news:title>
   <news:publication_date>2026-06-28T09:13:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705782</loc>
  <lastmod>2026-06-28T09:12:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルとレンジ空間に基づく勾配不要学習（Gradient-Free Learning Based on the Kernel and the Range Space）</news:title>
   <news:publication_date>2026-06-28T09:12:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705780</loc>
  <lastmod>2026-06-28T09:12:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による抽象オプションの階層化（Learning Abstract Options）</news:title>
   <news:publication_date>2026-06-28T09:12:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705778</loc>
  <lastmod>2026-06-28T09:12:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長距離特徴伝播を効率化する二重注意機構（A2-Nets: Double Attention Networks）</news:title>
   <news:publication_date>2026-06-28T09:12:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705776</loc>
  <lastmod>2026-06-28T09:11:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短セグメント心音分類のための深層畳み込みニューラルネットワークアンサンブル（Short-segment heart sound classification using an ensemble of deep convolutional neural networks）</news:title>
   <news:publication_date>2026-06-28T09:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705774</loc>
  <lastmod>2026-06-28T09:11:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>滑らかな分布に対するkNN情報推定量の解析（Analysis of KNN Information Estimators for Smooth Distributions）</news:title>
   <news:publication_date>2026-06-28T09:11:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705772</loc>
  <lastmod>2026-06-28T09:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳腫瘍セグメンテーションの体積畳み込みニューラルネットワーク（A Volumetric Convolutional Neural Network for Brain Tumor Segmentation）</news:title>
   <news:publication_date>2026-06-28T09:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705770</loc>
  <lastmod>2026-06-28T08:20:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルセンサデータの匿名化（Mobile Sensor Data Anonymization）</news:title>
   <news:publication_date>2026-06-28T08:20:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705768</loc>
  <lastmod>2026-06-28T08:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的・暗黙的コミュニケーションによる効率的で信頼できる社会的ナビゲーション（Efficient and Trustworthy Social Navigation Via Explicit and Implicit Robot-Human Communication）</news:title>
   <news:publication_date>2026-06-28T08:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705766</loc>
  <lastmod>2026-06-28T08:11:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床精神医学で解釈可能な推論を実現するMCAルールマイニング (MCA-based Rule Mining Enables Interpretable Inference in Clinical Psychiatry)</news:title>
   <news:publication_date>2026-06-28T08:11:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705764</loc>
  <lastmod>2026-06-28T08:10:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>気象とサウンドスケープの形状を監視する新しい統計手法（Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large data sets）</news:title>
   <news:publication_date>2026-06-28T08:10:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705762</loc>
  <lastmod>2026-06-28T08:10:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般確率空間における多変量情報量の推定器（Estimators for Multivariate Information Measures in General Probability Spaces）</news:title>
   <news:publication_date>2026-06-28T08:10:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705760</loc>
  <lastmod>2026-06-28T08:10:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のデモと介入を効率的に組み合わせた安全なリアルタイム学習（Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time）</news:title>
   <news:publication_date>2026-06-28T08:10:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705758</loc>
  <lastmod>2026-06-28T08:10:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>監視映像の品質を自動判定する深層畳み込みネットワーク（DEEP CONVOLUTIONAL NEURAL NETWORK APPLIED TO QUALITY ASSESSMENT FOR VIDEO TRACKING）</news:title>
   <news:publication_date>2026-06-28T08:10:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705756</loc>
  <lastmod>2026-06-28T07:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトログラム・チャンネルU-Net：音源分離を直観的に解く（SPECTROGRAM-CHANNELS U-NET: A SOURCE SEPARATION MODEL）</news:title>
   <news:publication_date>2026-06-28T07:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705754</loc>
  <lastmod>2026-06-28T07:11:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸であっても不整合な代替損失関数の学習保証の定量化（Quantifying Learning Guarantees for Convex but Inconsistent Surrogates）</news:title>
   <news:publication_date>2026-06-28T07:11:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705752</loc>
  <lastmod>2026-06-28T07:11:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震カタログに基づく機械学習による実験室断層状態の識別と完全度閾値の影響（Earthquake catalog-based machine learning identification of laboratory fault states and the effects of magnitude of completeness）</news:title>
   <news:publication_date>2026-06-28T07:11:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705750</loc>
  <lastmod>2026-06-28T07:10:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Attentionベース階層デコーダによるGUIからの自動コード生成（Automatic Graphics Program Generation using Attention-Based Hierarchical Decoder）</news:title>
   <news:publication_date>2026-06-28T07:10:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705748</loc>
  <lastmod>2026-06-28T07:10:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重袋（bags-of-bags）で学ぶネットワーク設計の革新 — LEARNING AND INTERPRETING MULTI-MULTI-INSTANCE LEARNING NETWORKS (LEARNING AND INTERPRETING MULTI-MULTI-INSTANCE LEARNING NETWORKS)</news:title>
   <news:publication_date>2026-06-28T07:10:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705746</loc>
  <lastmod>2026-06-28T07:09:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Whetstoneによる二値通信ニューラルネットワーク訓練法（Whetstone: A Method for Training Deep Artificial Neural Networks for Binary Communication）</news:title>
   <news:publication_date>2026-06-28T07:09:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705744</loc>
  <lastmod>2026-06-28T07:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動微分の現在地と進むべき方向（Automatic differentiation in ML: Where we are and where we should be going）</news:title>
   <news:publication_date>2026-06-28T07:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705742</loc>
  <lastmod>2026-06-28T06:18:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相空間積分に対するニューラルネットワークアプローチ (Neural Network-Based Approach to Phase Space Integration)</news:title>
   <news:publication_date>2026-06-28T06:18:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705740</loc>
  <lastmod>2026-06-28T06:18:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NMBS-IIフィールドにおけるIRAC深層モザイク化の意義（IRAC mapping of the NMBS-II fields）</news:title>
   <news:publication_date>2026-06-28T06:18:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705738</loc>
  <lastmod>2026-06-28T06:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模経験的リスク最小化のための効率的分散ヘッセ非依存アルゴリズム（Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy）</news:title>
   <news:publication_date>2026-06-28T06:17:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705736</loc>
  <lastmod>2026-06-28T06:17:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定性保証付き強化学習：制御理論的視点での検証（STABILITY-CERTIFIED REINFORCEMENT LEARNING: A CONTROL-THEORETIC PERSPECTIVE）</news:title>
   <news:publication_date>2026-06-28T06:17:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705734</loc>
  <lastmod>2026-06-28T06:17:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディアから救援ニーズを自動抽出・順位付けする手法（Automatic Identification and Ranking of Emergency Aids in Social Media Macro Community）</news:title>
   <news:publication_date>2026-06-28T06:17:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/705732</loc>
  <lastmod>2026-06-28T06:17:07Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T06:17:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705730</loc>
  <lastmod>2026-06-28T06:16:42Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的パラメータの機械学習による推定（Machine learning determination of dynamical parameters: The Ising model case）</news:title>
   <news:publication_date>2026-06-28T06:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705728</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T05:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705726</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>話し言葉の協調構造解析（Parsing Coordination for Spoken Language Understanding）</news:title>
   <news:publication_date>2026-06-28T05:25:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705724</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-28T05:25:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705722</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-28T05:24:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-28T05:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705718</loc>
  <lastmod>2026-06-28T05:24:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生涯オンライン学習のための知識蓄積（Accumulating Knowledge for Lifelong Online Learning）</news:title>
   <news:publication_date>2026-06-28T05:24:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705716</loc>
  <lastmod>2026-06-28T05:23:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前処理不要の計算的組織染色と脱染の実現（Computational Histological Staining and Destaining of Prostate Core Biopsy RGB Images with Generative Adversarial Neural Networks）</news:title>
   <news:publication_date>2026-06-28T05:23:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705714</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TanDEM-XとCartosat-1の標高データ融合による都市域DEM精度向上（Fusion of TanDEM-X and Cartosat-1 Elevation Data Supported by Neural Network-Predicted Weight Maps）</news:title>
   <news:publication_date>2026-06-28T04:33:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705712</loc>
  <lastmod>2026-06-28T04:32:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VAEの事前分布を再サンプリングする手法（Resampled Priors for Variational Autoencoders）</news:title>
   <news:publication_date>2026-06-28T04:32:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705710</loc>
  <lastmod>2026-06-28T04:32:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテの退院サマリーの抽出的要約（Extractive Summarization of Electronic Health Record Discharge Notes）</news:title>
   <news:publication_date>2026-06-28T04:32:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705708</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>樹状突起を用いた皮質マイクロ回路は逆伝播を近似する (Dendritic cortical microcircuits approximate the backpropagation algorithm)</news:title>
   <news:publication_date>2026-06-28T04:32:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚情報からの連続動作学習を効率化する深層内発的動機づけアクター・クリティック（Deep intrinsically motivated continuous actor-critic for efficient robotic visuomotor skill learning）</news:title>
   <news:publication_date>2026-06-28T04:32:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-28T04:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型IoTシステムのための新興エッジコンピューティング技術（Emerging Edge Computing Technologies for Distributed Internet of Things (IoT) Systems）</news:title>
   <news:publication_date>2026-06-28T04:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705702</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>モバイル向け随時ステレオ画像深度推定（Anytime Stereo Image Depth Estimation on Mobile Devices）</news:title>
   <news:publication_date>2026-06-28T04:31:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705700</loc>
  <lastmod>2026-06-28T03:40:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノックオフ手法の安定化（Stabilizing Knockoffs: Multiple Simultaneous Knockoffs and Entropy Maximization）</news:title>
   <news:publication_date>2026-06-28T03:40:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705698</loc>
  <lastmod>2026-06-28T03:40:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>システムピークへの寄与に基づくデータ駆動型顧客セグメンテーション（A Data-Driven Customer Segmentation Strategy Based on Contribution to System Peak Demand）</news:title>
   <news:publication_date>2026-06-28T03:40:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705696</loc>
  <lastmod>2026-06-28T03:40:02Z</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>2026-06-28T03:40:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705694</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>生成モデルを用いた外れ値検出の理論と実装（Outlier Detection using Generative Models with Theoretical Performance Guarantees）</news:title>
   <news:publication_date>2026-06-28T03:39:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705692</loc>
  <lastmod>2026-06-28T03:39:24Z</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>2026-06-28T03:39:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705690</loc>
  <lastmod>2026-06-28T03:39:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過剰パラメータ化がEMにもたらす利点（Benefits of over-parameterization with EM）</news:title>
   <news:publication_date>2026-06-28T03:39:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705688</loc>
  <lastmod>2026-06-28T03:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピラミダルFSMNとラティスフリーMMIによる音声認識精度向上（A NOVEL PYRAMIDAL-FSMN ARCHITECTURE WITH LATTICE-FREE MMI FOR SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-06-28T03:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705686</loc>
  <lastmod>2026-06-28T02:47:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見えない環境での音声強調を拡張するノイズ埋め込みと大規模環境学習（Scaling Speech Enhancement in Unseen Environments with Noise Embeddings）</news:title>
   <news:publication_date>2026-06-28T02:47:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705684</loc>
  <lastmod>2026-06-28T02:47:31Z</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>2026-06-28T02:47:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705682</loc>
  <lastmod>2026-06-28T02:47:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル端末で動くリアルタイム文脈学習とIoT制御（Real-time Context-aware Learning System for IoT Applications）</news:title>
   <news:publication_date>2026-06-28T02:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705680</loc>
  <lastmod>2026-06-28T02:46:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模銀河画像データベースのハイブリッド注釈手法（A hybrid approach to machine learning annotation of large galaxy image databases）</news:title>
   <news:publication_date>2026-06-28T02:46:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705678</loc>
  <lastmod>2026-06-28T02:46:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習における単一事例の複数回重み更新（Online learning using multiple times weight updating）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705676</loc>
  <lastmod>2026-06-28T02:46:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>聖書文脈でのドメイン適応：小規模データでの質問応答性能を高める手法（Finding Answers from the Word of God: Domain Adaptation for Neural Networks in Biblical Question Answering）</news:title>
   <news:publication_date>2026-06-28T02:46:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705674</loc>
  <lastmod>2026-06-28T01:55:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像における人物再識別を加速する空間・時間注意ネットワーク（Video-based Person Re-identification Using Spatial-Temporal Attention Networks）</news:title>
   <news:publication_date>2026-06-28T01:55:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705672</loc>
  <lastmod>2026-06-28T01:55:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スズの孤立電子対が招くキャリア捕獲の問題（Lone-pair effect on carrier capture in Cu2ZnSnS4 solar cells）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705670</loc>
  <lastmod>2026-06-28T01:54:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リーダーボードを超えて：InsightとDeploymentチャレンジの役割（Beyond the Leaderboard: Insight and Deployment Challenges to Address Research Problems）</news:title>
   <news:publication_date>2026-06-28T01:54:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705668</loc>
  <lastmod>2026-06-28T01:54:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミリ波V2XにおけるDeepRLベースの分散車両位置制御によるカバレッジ拡張（Deep-Reinforcement-Learning-Based Distributed Vehicle Position Controls for Coverage Expansion in mmWave V2X）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705666</loc>
  <lastmod>2026-06-28T01:54:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直列結合同一DNNによる雑音型依存性の低減（CONCATENATED IDENTICAL DNN (CI-DNN) TO REDUCE NOISE-TYPE DEPENDENCE IN DNN-BASED SPEECH ENHANCEMENT）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-28T01:54:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CAPSULE-FORENSICSによる偽造画像・動画検出（CAPSULE-FORENSICS: USING CAPSULE NETWORKS TO DETECT FORGED IMAGES AND VIDEOS）</news:title>
   <news:publication_date>2026-06-28T01:54:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705662</loc>
  <lastmod>2026-06-28T01:54:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合モデルの大域収束をめざすCM-EMアルゴリズム（From the EM Algorithm to the CM-EM Algorithm for Global Convergence of Mixture Models）</news:title>
   <news:publication_date>2026-06-28T01:54:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705660</loc>
  <lastmod>2026-06-28T01:03:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HPC向けオンライン障害分類の実践（Online Fault Classification in HPC Systems through Machine Learning）</news:title>
   <news:publication_date>2026-06-28T01:03:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705658</loc>
  <lastmod>2026-06-28T01:03:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ポアソンガンマ動的システム（Deep Poisson gamma dynamical systems）</news:title>
   <news:publication_date>2026-06-28T01:03:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705656</loc>
  <lastmod>2026-06-28T01:03:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>4D OCTの最大強度投影に対する深層学習ベースの2.5Dフロー場推定（Deep learning based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography）</news:title>
   <news:publication_date>2026-06-28T01:03:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705654</loc>
  <lastmod>2026-06-28T01:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文章簡約のためのトランスフォーマとパラフレーズ規則の統合 (Integrating Transformer and Paraphrase Rules for Sentence Simplification)</news:title>
   <news:publication_date>2026-06-28T01:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705652</loc>
  <lastmod>2026-06-28T01:02:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CrystalGANで結晶構造を発見する（CrystalGAN: Learning to Discover Crystallographic Structures with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-28T01:02:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705650</loc>
  <lastmod>2026-06-28T01:02:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CubeSatにおける光通信の可能性（Optical Communication on CubeSats – Enabling the Next Era in Space Science –）</news:title>
   <news:publication_date>2026-06-28T01:02:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705648</loc>
  <lastmod>2026-06-28T01:01:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフォレストの可逆（と非可逆）圧縮（Lossless (and Lossy) Compression of Random Forests）</news:title>
   <news:publication_date>2026-06-28T01:01:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705646</loc>
  <lastmod>2026-06-28T00:11:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特定相手を狙うマルチエージェント通信の設計（TarMAC: Targeted Multi-Agent Communication）</news:title>
   <news:publication_date>2026-06-28T00:11:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705644</loc>
  <lastmod>2026-06-28T00:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度ビデオ分類における冗長性削減注意機構（Fine-grained Video Categorization with Redundancy Reduction Attention）</news:title>
   <news:publication_date>2026-06-28T00:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705642</loc>
  <lastmod>2026-06-28T00:10:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケールドデジタル学習環境におけるシーケンシャルなランダム化（Beyond A/B Testing: Sequential Randomization for Developing Interventions in Scaled Digital Learning Environments）</news:title>
   <news:publication_date>2026-06-28T00:10:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705640</loc>
  <lastmod>2026-06-28T00:10:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>住宅向けバッテリー最適運用における太陽光・負荷予測の活用（Using solar and load predictions in battery scheduling at the residential level）</news:title>
   <news:publication_date>2026-06-28T00:10:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705638</loc>
  <lastmod>2026-06-28T00:10:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身体的問答のためのニューラル・モジュラー制御（Neural Modular Control for Embodied Question Answering）</news:title>
   <news:publication_date>2026-06-28T00:10:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705636</loc>
  <lastmod>2026-06-28T00:10:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InversionNetによるフルウェーブフォーム反演の高速化と高精度化（InversionNet: A Real-Time and Accurate Full Waveform Inversion with CNNs and continuous CRFs）</news:title>
   <news:publication_date>2026-06-28T00:10:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705634</loc>
  <lastmod>2026-06-28T00:09:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース関係遷移モデルの学習（Learning Sparse Relational Transition Models）</news:title>
   <news:publication_date>2026-06-28T00:09:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705632</loc>
  <lastmod>2026-06-27T23:18:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型マルチプレイヤーバンディットにおける通信不要の最適化（Game of Thrones: Fully Distributed Learning for Multi-Player Bandits）</news:title>
   <news:publication_date>2026-06-27T23:18:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705630</loc>
  <lastmod>2026-06-27T23:18:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識のデータ特化適応閾値（Data-specific Adaptive Threshold for Face Recognition and Authentication）</news:title>
   <news:publication_date>2026-06-27T23:18:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705628</loc>
  <lastmod>2026-06-27T23:18:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍表現を効率的に学習する Differentiable Boundary Sets（Efficient learning of neighbor representations for boundary trees and forests）</news:title>
   <news:publication_date>2026-06-27T23:18:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705626</loc>
  <lastmod>2026-06-27T23:17:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Size-Noise Tradeoffs in Generative Networks（Size-Noise Tradeoffs in Generative Networks）</news:title>
   <news:publication_date>2026-06-27T23:17:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705624</loc>
  <lastmod>2026-06-27T23:17:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパスで学ぶ磁気共鳴の教育実験（Exploring magnetic resonance with a compass）</news:title>
   <news:publication_date>2026-06-27T23:17:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705622</loc>
  <lastmod>2026-06-27T23:17:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間を取り込むニューラルネットワーク—スティグメルジーを用いた時間表現（Using stigmergy to incorporate the time into artificial neural networks）</news:title>
   <news:publication_date>2026-06-27T23:17:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705620</loc>
  <lastmod>2026-06-27T23:17:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多人数並列化でマンフォールド最適化を効率化する手法（Communication Efficient Parallel Algorithms for Optimization on Manifolds）</news:title>
   <news:publication_date>2026-06-27T23:17:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705618</loc>
  <lastmod>2026-06-27T22:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トロイダルネマティクスにおけるユリ型ねじれ分布（Lily-like twist distribution in toroidal nematics）</news:title>
   <news:publication_date>2026-06-27T22:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705616</loc>
  <lastmod>2026-06-27T22:17:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散信頼を促進するブロックチェーン活用の試み（PROMOTING DISTRIBUTED TRUST IN MACHINE LEARNING AND COMPUTATIONAL SIMULATION VIA A BLOCKCHAIN NETWORK）</news:title>
   <news:publication_date>2026-06-27T22:17:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705614</loc>
  <lastmod>2026-06-27T22:16:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TensorFlowとCUDA対応MPIによる分散DNN学習のスケーラブル化（Scalable Distributed DNN Training using TensorFlow and CUDA-Aware MPI: Characterization, Designs, and Performance Evaluation）</news:title>
   <news:publication_date>2026-06-27T22:16:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705612</loc>
  <lastmod>2026-06-27T22:16:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>劣化文書の二値化を強化する敵対的ノイズ・テクスチャ増強（IMPROVING DOCUMENT BINARIZATION VIA ADVERSARIAL NOISE-TEXTURE AUGMENTATION）</news:title>
   <news:publication_date>2026-06-27T22:16:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705610</loc>
  <lastmod>2026-06-27T22:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回帰におけるアンサンブル損失関数による頑健化（RELF: Robust Regression Extended with Ensemble Loss Function）</news:title>
   <news:publication_date>2026-06-27T22:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705608</loc>
  <lastmod>2026-06-27T22:15:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一観測から学べるガウス埋め込み（Provable Gaussian Embedding with One Observation）</news:title>
   <news:publication_date>2026-06-27T22:15:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705606</loc>
  <lastmod>2026-06-27T22:15:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線画像のテクスチャを高速に合成する技術（RADIOMIC SYNTHESIS USING DEEP CONVOLUTIONAL NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-27T22:15:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705604</loc>
  <lastmod>2026-06-27T21:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低精度演算子の自動生成が切り開く現場適用の道（Automating Generation of Low Precision Deep Learning Operators）</news:title>
   <news:publication_date>2026-06-27T21:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705602</loc>
  <lastmod>2026-06-27T21:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配の一様収束と非凸学習の最適化（Uniform Convergence of Gradients for Non-Convex Learning and Optimization）</news:title>
   <news:publication_date>2026-06-27T21:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705600</loc>
  <lastmod>2026-06-27T21:23:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文法を教える敵対的分散（Teaching Syntax by Adversarial Distraction）</news:title>
   <news:publication_date>2026-06-27T21:23:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705598</loc>
  <lastmod>2026-06-27T21:22:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>退屈な宇宙論の「見えない差」を見分ける機械学習の力（On the dissection of degenerate cosmologies with machine learning）</news:title>
   <news:publication_date>2026-06-27T21:22:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705596</loc>
  <lastmod>2026-06-27T21:22:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合視覚運動タスクのワンショット階層模倣学習（One-Shot Hierarchical Imitation Learning of Compound Visuomotor Tasks）</news:title>
   <news:publication_date>2026-06-27T21:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705594</loc>
  <lastmod>2026-06-27T21:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による異質な処置効果推定（Heterogeneous Treatment Effect Estimation through Deep Learning）</news:title>
   <news:publication_date>2026-06-27T21:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705592</loc>
  <lastmod>2026-06-27T21:21:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で標準宇宙論と修正重力モデルを見分ける（Distinguishing standard and modified gravity cosmologies with machine learning）</news:title>
   <news:publication_date>2026-06-27T21:21:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705590</loc>
  <lastmod>2026-06-27T20:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可逆的再帰型ニューラルネットワーク（Reversible Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-27T20:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705588</loc>
  <lastmod>2026-06-27T20:29:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチ正規化の効率化とサンプリング手法（Batch Normalization Sampling）</news:title>
   <news:publication_date>2026-06-27T20:29:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705586</loc>
  <lastmod>2026-06-27T20:28:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>力の位置不確実性下における最悪ケース構造解析の効率的サンプリング（EFFICIENT LOAD SAMPLING FOR WORST-CASE STRUCTURAL ANALYSIS UNDER FORCE LOCATION UNCERTAINTY）</news:title>
   <news:publication_date>2026-06-27T20:28:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705584</loc>
  <lastmod>2026-06-27T20:28:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核ノルム正則化によるパネル回帰モデルの推定（Nuclear Norm Regularized Estimation of Panel Regression Models）</news:title>
   <news:publication_date>2026-06-27T20:28:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705582</loc>
  <lastmod>2026-06-27T20:28:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シグネチャモーメントによる確率過程の法則の特徴付け（Signature Moments to Characterize Laws of Stochastic Processes）</news:title>
   <news:publication_date>2026-06-27T20:28:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705580</loc>
  <lastmod>2026-06-27T20:27:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳表現のデコードとマルチモーダル学習（Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features）</news:title>
   <news:publication_date>2026-06-27T20:27:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705578</loc>
  <lastmod>2026-06-27T20:27:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的人口分布の高解像度生成（DeepDPM: Dynamic Population Mapping via Deep Neural Network）</news:title>
   <news:publication_date>2026-06-27T20:27:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705576</loc>
  <lastmod>2026-06-27T19:36:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルに対するクロネッカー構造部分空間の一致検出（Tensor Matched Kronecker-Structured Subspace Detection for Missing Information）</news:title>
   <news:publication_date>2026-06-27T19:36:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705574</loc>
  <lastmod>2026-06-27T19:36:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間行動認識のハイパーパラメータ最適化に関する予備研究（A Preliminary Study on Hyperparameter Configuration for Human Activity Recognition）</news:title>
   <news:publication_date>2026-06-27T19:36:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705572</loc>
  <lastmod>2026-06-27T19:35:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分可変速度制限を深層強化学習で制御する研究（Differential Variable Speed Limits Control for Freeway Recurrent Bottlenecks via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-27T19:35:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705570</loc>
  <lastmod>2026-06-27T19:35:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルツハイマー病の認知評価に関するVRとチューリング試験の応用（Cognitive Evaluation for the Diagnosis of Alzheimer’s Disease based on Turing Test and Virtual Environments）</news:title>
   <news:publication_date>2026-06-27T19:35:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705568</loc>
  <lastmod>2026-06-27T19:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン消費者レビューにおける両面（ツーサイド）議論の役割（Understanding the Role of Two-Sided Argumentation in Online Consumer Reviews: A Language-Based Perspective）</news:title>
   <news:publication_date>2026-06-27T19:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705566</loc>
  <lastmod>2026-06-27T19:35:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないデータでも動く深層学習の現実（Learning Emotion from 100 Observations: Unexpected Robustness of Deep Learning under Strong Data Limitations）</news:title>
   <news:publication_date>2026-06-27T19:35:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705564</loc>
  <lastmod>2026-06-27T19:34:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>T-GANによる生成モデル訓練の新潮流（Training Generative Adversarial Networks Via Turing Test）</news:title>
   <news:publication_date>2026-06-27T19:34:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705562</loc>
  <lastmod>2026-06-27T18:43:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子チャネル学習と近似状態識別の効率的アルゴリズム（Sample Efficient Algorithms for Learning Quantum Channels in PAC Model and the Approximate State Discrimination Problem）</news:title>
   <news:publication_date>2026-06-27T18:43:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705560</loc>
  <lastmod>2026-06-27T18:43:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散領域における分類器回避の最小コスト保証（Evading Classifiers in Discrete Domains with Provable Optimality Guarantees）</news:title>
   <news:publication_date>2026-06-27T18:43:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705558</loc>
  <lastmod>2026-06-27T18:42:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HAR-Net: 深層表現と手作り特徴量を融合した人間行動認識（HAR-Net: Fusing Deep Representation and Hand-crafted Features for Human Activity Recognition）</news:title>
   <news:publication_date>2026-06-27T18:42:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705556</loc>
  <lastmod>2026-06-27T18:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理のためのベイズ圧縮（Bayesian Compression for Natural Language Processing）</news:title>
   <news:publication_date>2026-06-27T18:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705554</loc>
  <lastmod>2026-06-27T18:41:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い共分散轨道に基づく顔表情の自動解析（Automatic Analysis of Facial Expressions Based on Deep Covariance Trajectories）</news:title>
   <news:publication_date>2026-06-27T18:41:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705552</loc>
  <lastmod>2026-06-27T18:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡データに対するスーパーアンサンブル分類器（Superensemble Classifier for Improving Predictions in Imbalanced Datasets）</news:title>
   <news:publication_date>2026-06-27T18:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705550</loc>
  <lastmod>2026-06-27T18:41:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一の深度画像からの敵対的セマンティックシーン補完（Adversarial Semantic Scene Completion from a Single Depth Image）</news:title>
   <news:publication_date>2026-06-27T18:41:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705548</loc>
  <lastmod>2026-06-27T17:49:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>藻類の自動分類に関する研究（Investigating the Automatic Classification of Algae Using Fusion of Spectral and Morphological Characteristics of Algae via Deep Residual Learning）</news:title>
   <news:publication_date>2026-06-27T17:49:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705546</loc>
  <lastmod>2026-06-27T17:49:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重い裾の確率的線形バンディットに対するほぼ最適アルゴリズム（Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs）</news:title>
   <news:publication_date>2026-06-27T17:49:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705544</loc>
  <lastmod>2026-06-27T17:49:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形信号のエントロピーと圧縮に関する全館エネルギーデータの研究（Waveform Signal Entropy and Compression Study of Whole-Building Energy Datasets）</news:title>
   <news:publication_date>2026-06-27T17:49:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705542</loc>
  <lastmod>2026-06-27T17:48:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カウントデータの無向グラフィカルモデルの構造学習（Structure learning of undirected graphical models for count data）</news:title>
   <news:publication_date>2026-06-27T17:48:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705540</loc>
  <lastmod>2026-06-27T17:48:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短い発話に対する話者認証の補償（Short utterance compensation in speaker verification via cosine-based teacher-student learning of speaker embeddings）</news:title>
   <news:publication_date>2026-06-27T17:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705538</loc>
  <lastmod>2026-06-27T17:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロサービス、継続的アーキテクチャと技術的負債利息（Microservices, Continuous Architecture, and Technical Debt Interest: An Empirical Study）</news:title>
   <news:publication_date>2026-06-27T17:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705536</loc>
  <lastmod>2026-06-27T17:48:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANによるデータ拡張（GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-27T17:48:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705534</loc>
  <lastmod>2026-06-27T16:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異常から正常への翻訳による医用画像合成と病変検出（An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection）</news:title>
   <news:publication_date>2026-06-27T16:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705532</loc>
  <lastmod>2026-06-27T16:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株価のジャンプ到来予測と新しい注意機構付きネットワーク（Forecasting of Jump Arrivals in Stock Prices: New Attention-based Network Architecture using Limit Order Book Data）</news:title>
   <news:publication_date>2026-06-27T16:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705530</loc>
  <lastmod>2026-06-27T16:55:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子緩和が相転移へ与える影響：機械学習ポテンシャルによる高エントロピー合金の研究 (Impact of lattice relaxations on phase transitions in a high-entropy alloy studied by machine-learning potentials)</news:title>
   <news:publication_date>2026-06-27T16:55:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705528</loc>
  <lastmod>2026-06-27T16:54:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンパクトな語義セグメンテーションモデルの高速NAS（Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells）</news:title>
   <news:publication_date>2026-06-27T16:54:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705526</loc>
  <lastmod>2026-06-27T16:54:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキング神経回路で実現する適応的運動制御と学習（Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor）</news:title>
   <news:publication_date>2026-06-27T16:54:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705524</loc>
  <lastmod>2026-06-27T16:54:23Z</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・シーケンス変換における潜在分節とオンライン生成（Neural Sequence Transduction with Latent Segmentation）</news:title>
   <news:publication_date>2026-06-27T16:54:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705522</loc>
  <lastmod>2026-06-27T16:54:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変化する環境下で最適なオンライン学習を実現する手法（Adaptive Online Learning in Dynamic Environments）</news:title>
   <news:publication_date>2026-06-27T16:54:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705520</loc>
  <lastmod>2026-06-27T16:02:12Z</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をガウス過程の視点で見る（A Gaussian Process perspective on Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-27T16:02:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705518</loc>
  <lastmod>2026-06-27T16:01:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フラッシュX線単一粒子回折イメージングの教師あり分類手法（SUPERVISED CLASSIFICATION METHODS FOR FLASH X-RAY SINGLE PARTICLE DIFFRACTION IMAGING）</news:title>
   <news:publication_date>2026-06-27T16:01:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705516</loc>
  <lastmod>2026-06-27T16:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚に基づく視覚対話型学習の再設計（Perceptual Visual Interactive Learning）</news:title>
   <news:publication_date>2026-06-27T16:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705514</loc>
  <lastmod>2026-06-27T16:01:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的に頑健なガウス過程最適化（Adversarially Robust Optimization with Gaussian Processes）</news:title>
   <news:publication_date>2026-06-27T16:01:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705512</loc>
  <lastmod>2026-06-27T16:01:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語が数学の学びを変える（The Role of Language in Teaching and Learning Mathematics）</news:title>
   <news:publication_date>2026-06-27T16:01:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705510</loc>
  <lastmod>2026-06-27T16:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共分散推定によるRBMの効率的学習（EFFICIENT LEARNING OF RESTRICTED BOLTZMANN MACHINES USING COVARIANCE ESTIMATES）</news:title>
   <news:publication_date>2026-06-27T16:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705508</loc>
  <lastmod>2026-06-27T16:00:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可分化Bregman発散から導かれる計量に基づく幾何とクラスタリング（Geometry and clustering with metrics derived from separable Bregman divergences）</news:title>
   <news:publication_date>2026-06-27T16:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705506</loc>
  <lastmod>2026-06-27T15:08:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キーワードで“話者だけ”を強調する音声分離技術（SPEAKER SELECTIVE BEAMFORMER WITH KEYWORD MASK ESTIMATION）</news:title>
   <news:publication_date>2026-06-27T15:08:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705504</loc>
  <lastmod>2026-06-27T15:01:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法と敵対的機械学習（Law and Adversarial Machine Learning）</news:title>
   <news:publication_date>2026-06-27T15:01:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705502</loc>
  <lastmod>2026-06-27T15:01:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偽ノード攻撃が明かすGCNの脆弱性（Fake Node Attacks on Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-06-27T15:01:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705500</loc>
  <lastmod>2026-06-27T15:00:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Word Embedding based Edit Distance（Word Embedding based Edit Distance）</news:title>
   <news:publication_date>2026-06-27T15:00:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705498</loc>
  <lastmod>2026-06-27T14:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主成分分析に基づく量子データ圧縮（Quantum data compression by principal component analysis）</news:title>
   <news:publication_date>2026-06-27T14:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705496</loc>
  <lastmod>2026-06-27T14:59:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲート付きRNNから学ぶ解釈可能な構造（Learning with Interpretable Structure from Gated RNN）</news:title>
   <news:publication_date>2026-06-27T14:59:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705494</loc>
  <lastmod>2026-06-27T14:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ない追加パラメータで複数タスクを効率化する手法（FOR THE PRICE OF 1: PARAMETER-EFFICIENT MULTI-TASK AND TRANSFER LEARNING）</news:title>
   <news:publication_date>2026-06-27T14:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705492</loc>
  <lastmod>2026-06-27T14:07:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直線的に学ぶ辞書学習：サブグラデイント法が示す実用的回復性（Subgradient Descent Learns Orthogonal Dictionaries）</news:title>
   <news:publication_date>2026-06-27T14:07:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705490</loc>
  <lastmod>2026-06-27T14:07:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>東アフリカの現場が求めた機械学習研究一覧（Some Requests for Machine Learning Research from the East African Tech Scene）</news:title>
   <news:publication_date>2026-06-27T14:07:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705488</loc>
  <lastmod>2026-06-27T14:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフラプラシアンのスペクトルを深掘りするスペクトル埋め込みノルム（Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph Laplacian）</news:title>
   <news:publication_date>2026-06-27T14:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705486</loc>
  <lastmod>2026-06-27T14:06:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>口腔疾患の機械学習による自動化と全身健康との相関（Automated Process Incorporating Machine Learning Segmentation and Correlation of Oral Diseases with Systemic Health）</news:title>
   <news:publication_date>2026-06-27T14:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705484</loc>
  <lastmod>2026-06-27T14:06:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トランケーテッド逆伝播による双層最適化（Truncated Back-propagation for Bilevel Optimization）</news:title>
   <news:publication_date>2026-06-27T14:06:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705482</loc>
  <lastmod>2026-06-27T14:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SpiderBoostとMomentumによる高速な確率的分散削減アルゴリズム（SpiderBoost and Momentum: Faster Stochastic Variance Reduction Algorithms）</news:title>
   <news:publication_date>2026-06-27T14:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705480</loc>
  <lastmod>2026-06-27T14:05:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNAコンピューティングに学ぶニューラルネットワーク構造探索（Structure Learning of Deep Networks via DNA Computing Algorithm）</news:title>
   <news:publication_date>2026-06-27T14:05:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705478</loc>
  <lastmod>2026-06-27T13:14:52Z</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による組合せ最適化と誘導木探索（Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search）</news:title>
   <news:publication_date>2026-06-27T13:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705476</loc>
  <lastmod>2026-06-27T13:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像質問への理解・構成・応答（Understand, Compose and Respond - Answering Visual Questions by a Composition of Abstract Procedures）</news:title>
   <news:publication_date>2026-06-27T13:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705474</loc>
  <lastmod>2026-06-27T13:14:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スポーツ映像の単一フレームからのカメラ較正（Sports Camera Calibration via Synthetic Data）</news:title>
   <news:publication_date>2026-06-27T13:14:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705472</loc>
  <lastmod>2026-06-27T13:13:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタモデリングと深層強化学習による界面粘着則の自動発見（Meta-modeling game for deriving theoretical-consistent, micro-structural-based traction-separation laws via deep reinforcement learning）</news:title>
   <news:publication_date>2026-06-27T13:13:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705470</loc>
  <lastmod>2026-06-27T13:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンドフィードバックによる効率的ルーティング学習（Learning to Route Efficiently with End-to-End Feedback: The Value of Networked Structure）</news:title>
   <news:publication_date>2026-06-27T13:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705468</loc>
  <lastmod>2026-06-27T13:13:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体の非把持操作を効率的に学ぶための計画的初期状態導入（Learning with Planned Episodic Resets）</news:title>
   <news:publication_date>2026-06-27T13:13:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705466</loc>
  <lastmod>2026-06-27T13:13:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミンググラフニューラルネットワーク（Streaming Graph Neural Networks）</news:title>
   <news:publication_date>2026-06-27T13:13:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705464</loc>
  <lastmod>2026-06-27T12:22:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース化フロントエンドによる頑健な敵対的学習（Robust Adversarial Learning via Sparsifying Front Ends）</news:title>
   <news:publication_date>2026-06-27T12:22:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705462</loc>
  <lastmod>2026-06-27T12:21:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続学習における生成モデルを用いた分類学習（Continual Classification Learning Using Generative Models）</news:title>
   <news:publication_date>2026-06-27T12:21:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705460</loc>
  <lastmod>2026-06-27T12:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密度整合によるスピン模型のループ補正（Loop corrections in spin models through density consistency）</news:title>
   <news:publication_date>2026-06-27T12:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705458</loc>
  <lastmod>2026-06-27T12:21:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己正規化マルチンゲールの集中不等式に関する新知見 (NEW INSIGHTS ON CONCENTRATION INEQUALITIES FOR SELF-NORMALIZED MARTINGALES)</news:title>
   <news:publication_date>2026-06-27T12:21:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705456</loc>
  <lastmod>2026-06-27T12:20:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオゲームにおける逆強化学習の拡張（Inverse reinforcement learning for video games）</news:title>
   <news:publication_date>2026-06-27T12:20:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705454</loc>
  <lastmod>2026-06-27T12:20:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルによる量子状態再構築（Reconstructing quantum states with generative models）</news:title>
   <news:publication_date>2026-06-27T12:20:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705452</loc>
  <lastmod>2026-06-27T12:20:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スピーカー非依存のリップリーディング機械調査（The speaker-independent lipreading play-off; a survey of lipreading machines）</news:title>
   <news:publication_date>2026-06-27T12:20:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705450</loc>
  <lastmod>2026-06-27T11:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド量子コンピュータ上でのアルゴリズム展開フレームワーク（A framework for algorithm deployment on cloud-based quantum computers）</news:title>
   <news:publication_date>2026-06-27T11:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705448</loc>
  <lastmod>2026-06-27T11:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構を用いたハイパースペクトル帯域選択（Attention-based CNNs for Hyperspectral Band Selection）</news:title>
   <news:publication_date>2026-06-27T11:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705446</loc>
  <lastmod>2026-06-27T11:27:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>母集団レベルの原因分布を推定する正則化ベイズ転移学習（Regularized Bayesian transfer learning for population-level etiological distributions）</news:title>
   <news:publication_date>2026-06-27T11:27:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705444</loc>
  <lastmod>2026-06-27T11:26:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パッチベースの干渉位相推定（Patch-based Interferometric Phase Estimation via Mixture of Gaussian Density Modelling &amp;amp; Non-local Averaging in the Complex Domain）</news:title>
   <news:publication_date>2026-06-27T11:26:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705442</loc>
  <lastmod>2026-06-27T11:26:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床概念抽出における文脈的単語埋め込み（Clinical Concept Extraction with Contextual Word Embedding）</news:title>
   <news:publication_date>2026-06-27T11:26:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705440</loc>
  <lastmod>2026-06-27T11:26:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限体と応用における発見学習の授業設計（DISCOVERY LEARNING IN AN INTERDISCIPLINARY COURSE ON FINITE FIELDS AND APPLICATIONS）</news:title>
   <news:publication_date>2026-06-27T11:26:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705438</loc>
  <lastmod>2026-06-27T11:26:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠方X線クラスターにおける分子ガス量の環境依存性の解明 (Revealing environmental dependence of molecular gas content in a distant X-ray cluster at z = 2.51)</news:title>
   <news:publication_date>2026-06-27T11:26:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705436</loc>
  <lastmod>2026-06-27T10:34:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語・多表現のマルチビュー学習によるエンティティ型推定（Multi-Multi-View Learning: Multilingual and Multi-Representation Entity Typing）</news:title>
   <news:publication_date>2026-06-27T10:34:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705434</loc>
  <lastmod>2026-06-27T10:25:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍合意ネットワークによる密対応の学習（Neighbourhood Consensus Networks）</news:title>
   <news:publication_date>2026-06-27T10:25:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705432</loc>
  <lastmod>2026-06-27T10:25:01Z</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4K/8K映像に対する高速で高精度な物体検出（Fast and accurate object detection in high resolution 4K and 8K video using GPUs）</news:title>
   <news:publication_date>2026-06-27T10:25:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705430</loc>
  <lastmod>2026-06-27T10:24:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>矮小銀河の星間物質を機械学習で解く（The interstellar medium of dwarf galaxies: new insights from Machine Learning analysis of emission line spectra）</news:title>
   <news:publication_date>2026-06-27T10:24:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705428</loc>
  <lastmod>2026-06-27T10:24:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分量子状態の対角化（Variational Quantum State Diagonalization）</news:title>
   <news:publication_date>2026-06-27T10:24:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705426</loc>
  <lastmod>2026-06-27T10:23:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠様スローオシレーションが視覚分類を改善する仕組み（Sleep-like slow oscillations improve visual classification through synaptic homeostasis and memory association in a thalamo-cortical model）</news:title>
   <news:publication_date>2026-06-27T10:23:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705424</loc>
  <lastmod>2026-06-27T10:23:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>詩の作者分類に関するテキスト分類研究（Poetry Authorship Classification）</news:title>
   <news:publication_date>2026-06-27T10:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705422</loc>
  <lastmod>2026-06-27T09:32:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化された疾病軌跡の予測（Forecasting Individualized Disease Trajectories using Interpretable Deep Learning）</news:title>
   <news:publication_date>2026-06-27T09:32:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705420</loc>
  <lastmod>2026-06-27T09:32:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>降水ナウキャスティング：双方向LSTMと1次元CNNの活用 (Precipitation Nowcasting: Leveraging bidirectional LSTM and 1D CNN)</news:title>
   <news:publication_date>2026-06-27T09:32:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705418</loc>
  <lastmod>2026-06-27T09:31:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段階近似を使った雑音下のブラックボックス最適化（Noisy Blackbox Optimization with Multi-Fidelity Queries: A Tree Search Approach）</news:title>
   <news:publication_date>2026-06-27T09:31:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705416</loc>
  <lastmod>2026-06-27T09:30:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>流体メタンの状態方程式と機械学習ポテンシャル（Equation of state of fluid methane from first principles with machine learning potentials）</news:title>
   <news:publication_date>2026-06-27T09:30:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705414</loc>
  <lastmod>2026-06-27T09:30:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合高次仮想要素法の基礎部品：射影作用素と微分作用素（Bricks for the mixed high-order virtual element method: projectors and differential operators）</news:title>
   <news:publication_date>2026-06-27T09:30:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705412</loc>
  <lastmod>2026-06-27T09:30:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択分析における深層ニューラルネットワーク（Deep Neural Networks for Choice Analysis: A Statistical Learning Theory Perspective）</news:title>
   <news:publication_date>2026-06-27T09:30:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705410</loc>
  <lastmod>2026-06-27T09:29:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交差点における車同士の交渉行動の学習（Learning Negotiating Behavior Between Cars in Intersections using Deep Q-Learning）</news:title>
   <news:publication_date>2026-06-27T09:29:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705408</loc>
  <lastmod>2026-06-27T08:38:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微小循環画像からの敗血症判別を目指す機械学習（Machine Learning Algorithms for Classification of Microcirculation Images from Septic and Non-Septic Patients）</news:title>
   <news:publication_date>2026-06-27T08:38:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705406</loc>
  <lastmod>2026-06-27T08:38:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データがモデル構築と予測で果たす役割（The Role of Data in Model Building and Prediction: A Survey Through Examples）</news:title>
   <news:publication_date>2026-06-27T08:38:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705404</loc>
  <lastmod>2026-06-27T08:37:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>性能最適化した生徒モデルによる蒸留（Distilling with Performance Enhanced Students）</news:title>
   <news:publication_date>2026-06-27T08:37:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705402</loc>
  <lastmod>2026-06-27T08:37:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAV画像向け高解像度セマンティックセグメンテーションデータセット「UAVid」（UAVid: A Semantic Segmentation Dataset for UAV Imagery）</news:title>
   <news:publication_date>2026-06-27T08:37:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705400</loc>
  <lastmod>2026-06-27T08:36:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Transformerを用いた変分半教師付きアスペクト項目感情分析（Variational Semi-supervised Aspect-term Sentiment Analysis via Transformer）</news:title>
   <news:publication_date>2026-06-27T08:36:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705398</loc>
  <lastmod>2026-06-27T08:36:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタデータを使い分ける地図方程式（A Map Equation with Metadata: Varying the Role of Attributes in Community Detection）</news:title>
   <news:publication_date>2026-06-27T08:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705396</loc>
  <lastmod>2026-06-27T08:36:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車車間通信における効率的な情報伝播のための深層学習アプローチ（A Deep Learning Approach to Efficient Information Dissemination in Vehicular Floating Content）</news:title>
   <news:publication_date>2026-06-27T08:36:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705394</loc>
  <lastmod>2026-06-27T07:44:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地下多相流の縮約モデル化とDR-RNNによる高速近似（Reduced order modeling of subsurface multiphase flow models using deep residual recurrent neural networks）</news:title>
   <news:publication_date>2026-06-27T07:44:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705392</loc>
  <lastmod>2026-06-27T07:44:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>双方向テレオペレーションによるスクーピング動作の深層学習（Deep Learning Scooping Motion using Bilateral Teleoperations）</news:title>
   <news:publication_date>2026-06-27T07:44:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705390</loc>
  <lastmod>2026-06-27T07:43:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAVネットワークにおけるマルチエージェント強化学習による資源配分（Multi-Agent Reinforcement Learning Based Resource Allocation for UAV Networks）</news:title>
   <news:publication_date>2026-06-27T07:43:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705388</loc>
  <lastmod>2026-06-27T07:43:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GBDTの速度ベンチマークが皆間違っている理由（Why every GBDT speed benchmark is wrong）</news:title>
   <news:publication_date>2026-06-27T07:43:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705386</loc>
  <lastmod>2026-06-27T07:42:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像として扱う自然言語理解（Image-based Natural Language Understanding Using 2D Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-27T07:42:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705384</loc>
  <lastmod>2026-06-27T07:42:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロヘキサキャビティピクセル検出器の動作と性能（Operation and Performance of Microhexcavity Pixel Detector in Gas Discharge and Avalanche Mode）</news:title>
   <news:publication_date>2026-06-27T07:42:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705382</loc>
  <lastmod>2026-06-27T07:42:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CatBoost: カテゴリ変数対応の勾配ブースティング（CatBoost: gradient boosting with categorical features）</news:title>
   <news:publication_date>2026-06-27T07:42:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705380</loc>
  <lastmod>2026-06-27T06:51:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散領域におけるスパースガウス過程（Sparse Gaussian Processes on Discrete Domains）</news:title>
   <news:publication_date>2026-06-27T06:51:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705378</loc>
  <lastmod>2026-06-27T06:51:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国電力システムの脱炭素における水力・蓄電・送電の役割（The role of hydro power, storage and transmission in the decarbonization of the Chinese power system）</news:title>
   <news:publication_date>2026-06-27T06:51:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705376</loc>
  <lastmod>2026-06-27T06:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>G-SMOTEによる不均衡学習の高次元合成少数オーバーサンプリング（G-SMOTE: A GMM-BASED SYNTHETIC MINORITY OVERSAMPLING TECHNIQUE FOR IMBALANCED LEARNING）</news:title>
   <news:publication_date>2026-06-27T06:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705374</loc>
  <lastmod>2026-06-27T06:50:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル比率から個別ラベルを復元するためのラベル伝播法（Label Propagation for Learning with Label Proportions）</news:title>
   <news:publication_date>2026-06-27T06:50:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705372</loc>
  <lastmod>2026-06-27T06:49:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外部情報のノイズを見抜く学習法（Learning to Discriminate Noises for Incorporating External Information in Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-27T06:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705370</loc>
  <lastmod>2026-06-27T06:49:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工ニューラルネットワークによる量子計算のエミュレーション（Emulating quantum computation with artificial neural networks）</news:title>
   <news:publication_date>2026-06-27T06:49:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705368</loc>
  <lastmod>2026-06-27T06:49:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3DコーンビームCTにおける歯科病変検出（Dental pathology detection in 3D cone-beam CT）</news:title>
   <news:publication_date>2026-06-27T06:49:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705366</loc>
  <lastmod>2026-06-27T05:57:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間中心サイバーフィジカルシステムにおけるセグメンテーション解析（Segmentation Analysis in Human Centric Cyber-Physical Systems using Graphical Lasso）</news:title>
   <news:publication_date>2026-06-27T05:57:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705364</loc>
  <lastmod>2026-06-27T05:57:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成画像の色空間適応で実画像セグメンテーションを改善する手法（Learning Color Space Adaptation from Synthetic to Real Images of Cirrus Clouds）</news:title>
   <news:publication_date>2026-06-27T05:57:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705362</loc>
  <lastmod>2026-06-27T05:56:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数データで学習する音声分類器の訓練（TRAINING NEURAL AUDIO CLASSIFIERS WITH FEW DATA）</news:title>
   <news:publication_date>2026-06-27T05:56:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705360</loc>
  <lastmod>2026-06-27T05:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト誘導型ランキングネットワークによる注意機構付き画像リツイート予測（Textually Guided Ranking Network for Attentional Image Retweet Modeling）</news:title>
   <news:publication_date>2026-06-27T05:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705358</loc>
  <lastmod>2026-06-27T05:56:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路ネットワークにおけるマルチステップ速度予測（Multistep Speed Prediction on Traffic Networks: A Graph Convolutional Sequence-to-Sequence Learning Approach with Attention Mechanism）</news:title>
   <news:publication_date>2026-06-27T05:56:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705356</loc>
  <lastmod>2026-06-27T05:55:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載向けフローティングコンテンツ管理に対する深層学習戦略（A Deep Learning Strategy for Vehicular Floating Content Management）</news:title>
   <news:publication_date>2026-06-27T05:55:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705354</loc>
  <lastmod>2026-06-27T05:55:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コードスイッチを学習するデータ増強法（LEARN TO CODE-SWITCH: DATA AUGMENTATION USING COPY MECHANISM ON LANGUAGE MODELING）</news:title>
   <news:publication_date>2026-06-27T05:55:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705352</loc>
  <lastmod>2026-06-27T05:04:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱凸弱凹ミンマックス問題に対する一階収束理論（First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems）</news:title>
   <news:publication_date>2026-06-27T05:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705350</loc>
  <lastmod>2026-06-27T05:04:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DSFD: Dual Shot Face Detector（DSFD: Dual Shot Face Detector）</news:title>
   <news:publication_date>2026-06-27T05:04:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705348</loc>
  <lastmod>2026-06-27T05:03:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブワードでULMFiTを多層化する意義（Universal Language Model Fine-Tuning with Subword Tokenization for Polish）</news:title>
   <news:publication_date>2026-06-27T05:03:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705346</loc>
  <lastmod>2026-06-27T05:03:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PN接合の粒子シミュレーションにおけるポアソン方程式の深層学習による解法（Solving Poisson’s Equation using Deep Learning in Particle Simulation of PN Junction）</news:title>
   <news:publication_date>2026-06-27T05:03:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705344</loc>
  <lastmod>2026-06-27T05:03:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層表現を活用したニューラル機械翻訳の改良（Exploiting Deep Representations for Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-27T05:03:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705342</loc>
  <lastmod>2026-06-27T05:03:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子凝集型バイオセンサーの高スループット解析を可能にする深層学習とホログラフィー（Deep learning enables high-throughput analysis of particle-aggregation-based bio-sensors imaged using holography）</news:title>
   <news:publication_date>2026-06-27T05:03:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705340</loc>
  <lastmod>2026-06-27T05:03:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚と触覚を「同時に学ぶ」ことで接触を伴う作業が劇的に効率化する（Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks）</news:title>
   <news:publication_date>2026-06-27T05:03:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705338</loc>
  <lastmod>2026-06-27T04:11:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習された最適化器の訓練における病理の理解と是正（Understanding and correcting pathologies in the training of learned optimizers）</news:title>
   <news:publication_date>2026-06-27T04:11:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705336</loc>
  <lastmod>2026-06-27T04:11:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模知識ベースからの検索のためのテキスト埋め込み（Text Embeddings for Retrieval from a Large Knowledge Base）</news:title>
   <news:publication_date>2026-06-27T04:11:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705334</loc>
  <lastmod>2026-06-27T04:11:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン映画知識ライブラリに基づくデータ駆動型ブロックバスター企画（Data-driven Blockbuster Planning on Online Movie Knowledge Library）</news:title>
   <news:publication_date>2026-06-27T04:11:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705332</loc>
  <lastmod>2026-06-27T04:10:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸・非滑らかなスパース最適化の適応的反復再重み付け法（Nonconvex and Nonsmooth Sparse Optimization via Adaptively Iterative Reweighted Methods）</news:title>
   <news:publication_date>2026-06-27T04:10:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705330</loc>
  <lastmod>2026-06-27T04:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化勾配ブースティング機械（Randomized Gradient Boosting Machine）</news:title>
   <news:publication_date>2026-06-27T04:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705328</loc>
  <lastmod>2026-06-27T04:10:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長短期記憶を用いた時系列予測の深層学習的アプローチ（Deep Learning with Long Short-Term Memory for Time Series Prediction）</news:title>
   <news:publication_date>2026-06-27T04:10:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705326</loc>
  <lastmod>2026-06-27T04:09:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>窒化物半導体のバンドギャップ・バンド整合の機械学習予測（Band gap and band alignment prediction of nitride based semiconductors using machine learning）</news:title>
   <news:publication_date>2026-06-27T04:09:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705324</loc>
  <lastmod>2026-06-27T03:19:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファッション属性検出のための深層学習モデル（A Deep-Learning-Based Fashion Attributes Detection Model）</news:title>
   <news:publication_date>2026-06-27T03:19:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705322</loc>
  <lastmod>2026-06-27T03:18:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FewRelをめぐる実務的解説—大規模少ショット関係分類データセット（FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation）</news:title>
   <news:publication_date>2026-06-27T03:18:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705320</loc>
  <lastmod>2026-06-27T03:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知無線ベースのブロックチェーンネットワークにおける取引伝送とチャネル選択の共同最適化（JOINT TRANSACTION TRANSMISSION AND CHANNEL SELECTION IN COGNITIVE RADIO BASED BLOCKCHAIN NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH）</news:title>
   <news:publication_date>2026-06-27T03:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705318</loc>
  <lastmod>2026-06-27T03:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込みの局所ホモロジー（Local Homology of Word Embeddings）</news:title>
   <news:publication_date>2026-06-27T03:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705316</loc>
  <lastmod>2026-06-27T03:18:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平滑化された回帰とLQR制御のためのオンラインアルゴリズム（An Online Algorithm for Smoothed Regression and LQR Control）</news:title>
   <news:publication_date>2026-06-27T03:18:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705314</loc>
  <lastmod>2026-06-27T03:17:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制約付きK平均クラスタリングへの2値最適化アプローチ（A Binary Optimization Approach for Constrained K-Means Clustering）</news:title>
   <news:publication_date>2026-06-27T03:17:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705312</loc>
  <lastmod>2026-06-27T03:17:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エリア注意機構が変える注意の粒度（Area Attention）</news:title>
   <news:publication_date>2026-06-27T03:17:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705310</loc>
  <lastmod>2026-06-27T02:26:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>nGraph-HEによる同型暗号下での深層学習コンパイラ（nGraph-HE: A Graph Compiler for Deep Learning on Homomorphically Encrypted Data）</news:title>
   <news:publication_date>2026-06-27T02:26:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705308</loc>
  <lastmod>2026-06-27T02:26:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fisherカーネルによるブラックボックス予測の解釈（Interpreting Black Box Predictions using Fisher Kernels）</news:title>
   <news:publication_date>2026-06-27T02:26:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705306</loc>
  <lastmod>2026-06-27T02:26:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PoPPy: PyTorchベースの点過程ツールボックス（PoPPy: A Point Process Toolbox Based on PyTorch）</news:title>
   <news:publication_date>2026-06-27T02:26:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705304</loc>
  <lastmod>2026-06-27T02:25:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークにおける意味表現の数学理論（A mathematical theory of semantic development in deep neural networks）</news:title>
   <news:publication_date>2026-06-27T02:25:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705302</loc>
  <lastmod>2026-06-27T02:25:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRIからのエンドツーエンド診断とセグメンテーション学習（End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging）</news:title>
   <news:publication_date>2026-06-27T02:25:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705300</loc>
  <lastmod>2026-06-27T02:25:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>損失のある観測からの生成モデル再現（Reproducing AmbientGAN: Generative models from lossy measurements）</news:title>
   <news:publication_date>2026-06-27T02:25:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705298</loc>
  <lastmod>2026-06-27T02:25:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習ベースの逆問題解法：肺EITのシミュレーション研究（A Learning-Based Method for Solving Ill-Posed Nonlinear Inverse Problems: A Simulation Study of Lung EIT）</news:title>
   <news:publication_date>2026-06-27T02:25:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705296</loc>
  <lastmod>2026-06-27T01:33:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Autowarpによる時系列類似度の自動学習（Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders）</news:title>
   <news:publication_date>2026-06-27T01:33:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705294</loc>
  <lastmod>2026-06-27T01:32:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重なり合う銀河のデブレンディングにおける分岐型生成対抗ネットワーク（Deblending galaxy superpositions with branched generative adversarial networks）</news:title>
   <news:publication_date>2026-06-27T01:32:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705292</loc>
  <lastmod>2026-06-27T01:32:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルフリー階層的強化学習における表現学習（Learning Representations in Model-Free Hierarchical Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-27T01:32:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705290</loc>
  <lastmod>2026-06-27T01:32:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NestDNNによるリソース対応型マルチテナント端末上深層学習（NestDNN: Resource-Aware Multi-Tenant On-Device Deep Learning for Continuous Mobile Vision）</news:title>
   <news:publication_date>2026-06-27T01:32:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705288</loc>
  <lastmod>2026-06-27T01:31:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小二乗における早期停止の連続時間的考察 (A Continuous-Time View of Early Stopping for Least Squares)</news:title>
   <news:publication_date>2026-06-27T01:31:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705286</loc>
  <lastmod>2026-06-27T01:31:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負値行列因子分解のモデル選択（Model Selection for Nonnegative Matrix Factorization by Support Union Recovery）</news:title>
   <news:publication_date>2026-06-27T01:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705284</loc>
  <lastmod>2026-06-27T01:31:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>成人の国勢調査データによる所得階層予測の統計的アプローチ（A Statistical Approach to Adult Census Income Level Prediction）</news:title>
   <news:publication_date>2026-06-27T01:31:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705282</loc>
  <lastmod>2026-06-27T00:40:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランクテンソル分解の統計力学的分析（Statistical mechanics of low-rank tensor decomposition）</news:title>
   <news:publication_date>2026-06-27T00:40:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705280</loc>
  <lastmod>2026-06-27T00:40:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ類似度の畳み込み的集合照合（Convolutional Set Matching for Graph Similarity）</news:title>
   <news:publication_date>2026-06-27T00:40:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705278</loc>
  <lastmod>2026-06-27T00:39:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無効結果の価値――物理教育研究における「何も起きなかった」ことの意味（Nothing’s plenty: The significance of null results in physics education research）</news:title>
   <news:publication_date>2026-06-27T00:39:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705276</loc>
  <lastmod>2026-06-27T00:39:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Graph Laplacian Mixture Modelの解説（Graph Laplacian Mixture Model）</news:title>
   <news:publication_date>2026-06-27T00:39:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705274</loc>
  <lastmod>2026-06-27T00:38:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で量子デバイスの計測を効率化する手法（Efficiently measuring a quantum device using machine learning）</news:title>
   <news:publication_date>2026-06-27T00:38:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705272</loc>
  <lastmod>2026-06-27T00:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NormADに基づく多層スパイキングニューラルネットワークの学習（TRAINING MULTI-LAYER SPIKING NEURAL NETWORKS USING NORMAD BASED SPATIO-TEMPORAL ERROR BACKPROPAGATION）</news:title>
   <news:publication_date>2026-06-27T00:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705270</loc>
  <lastmod>2026-06-27T00:38:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似的な二乗輸送距離をほぼ線形時間で計算する手法（Approximating the Quadratic Transportation Metric in Near-Linear Time）</news:title>
   <news:publication_date>2026-06-27T00:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705268</loc>
  <lastmod>2026-06-26T23:47:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単層・多層フィードフォワードニューラルネットワークの近似に関する負の結果（NEGATIVE RESULTS FOR APPROXIMATION USING SINGLE LAYER AND MULTILAYER FEEDFORWARD NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-26T23:47:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705266</loc>
  <lastmod>2026-06-26T23:47:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レーザー照明画像のスペックルノイズ低減を学ぶ（DeepLSR: a deep learning approach for laser speckle reduction）</news:title>
   <news:publication_date>2026-06-26T23:47:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705264</loc>
  <lastmod>2026-06-26T23:46:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情認識の深層化と可視化：EmotionalDANによる顔ランドマーク統合学習（Classifying and Visualizing Emotions with Emotional DAN）</news:title>
   <news:publication_date>2026-06-26T23:46:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705262</loc>
  <lastmod>2026-06-26T23:45:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスター環境で小型の星形成銀河が急速に消光するメカニズム（Compact star-forming galaxies preferentially quenched to become PSBs in z &amp;lt; 1 clusters）</news:title>
   <news:publication_date>2026-06-26T23:45:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705260</loc>
  <lastmod>2026-06-26T23:45:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延する作業者（Straggler）を許容する分散学習の計算スケジューリング（Computation Scheduling for Distributed Machine Learning with Straggling Workers）</news:title>
   <news:publication_date>2026-06-26T23:45:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705258</loc>
  <lastmod>2026-06-26T23:45:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みエンコーダによる構造化データからのテキスト生成（Deep Graph Convolutional Encoders for Structured Data to Text Generation）</news:title>
   <news:publication_date>2026-06-26T23:45:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705256</loc>
  <lastmod>2026-06-26T23:45:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的代替学習によるグラデーション隠蔽への攻撃（Stochastic Substitute Training）</news:title>
   <news:publication_date>2026-06-26T23:45:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705254</loc>
  <lastmod>2026-06-26T22:53:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ学習によるマルチタスク通信（META-LEARNING MULTI-TASK COMMUNICATION）</news:title>
   <news:publication_date>2026-06-26T22:53:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705252</loc>
  <lastmod>2026-06-26T22:53:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークによる低消費電力強化学習（Learning First-to-Spike Policies for Neuromorphic Control Using Policy Gradients）</news:title>
   <news:publication_date>2026-06-26T22:53:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705250</loc>
  <lastmod>2026-06-26T22:53:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分集合の好みによる能動ランキング（Active Ranking with Subset-wise Preferences）</news:title>
   <news:publication_date>2026-06-26T22:53:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705248</loc>
  <lastmod>2026-06-26T22:52:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>矮小銀河の低金属間質（Dwarf Galaxies: Their Low Metallicity Interstellar Medium）</news:title>
   <news:publication_date>2026-06-26T22:52:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705246</loc>
  <lastmod>2026-06-26T22:52:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注文板データから価格予測へ──非定常性を克服する特徴設計（Using Deep Learning for price prediction by exploiting stationary limit order book features）</news:title>
   <news:publication_date>2026-06-26T22:52:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705244</loc>
  <lastmod>2026-06-26T22:52:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GhostVLADによる集合ベース顔認証の要点整理（GhostVLAD for set-based face recognition）</news:title>
   <news:publication_date>2026-06-26T22:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705242</loc>
  <lastmod>2026-06-26T22:52:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>λリターンとエクスペリエンスリプレイの調和（Reconciling λ-Returns with Experience Replay）</news:title>
   <news:publication_date>2026-06-26T22:52:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705240</loc>
  <lastmod>2026-06-26T22:01:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リカレント深層学習で脳画像を読む（Analyzing Neuroimaging Data Through Recurrent Deep Learning Models）</news:title>
   <news:publication_date>2026-06-26T22:01:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705238</loc>
  <lastmod>2026-06-26T22:01:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話行為を段階的に獲得するロボット学習（Stepwise Acquisition of Dialogue Act Through Human-Robot Interaction）</news:title>
   <news:publication_date>2026-06-26T22:01:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705236</loc>
  <lastmod>2026-06-26T22:00:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前処理選択とAutoMLパイプライン設計（Preprocessor Selection for Machine Learning Pipelines）</news:title>
   <news:publication_date>2026-06-26T22:00:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705234</loc>
  <lastmod>2026-06-26T22:00:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形時系列のクラスタリング：ベイズ非パラメトリックと粒子法の接合（Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach）</news:title>
   <news:publication_date>2026-06-26T22:00:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705232</loc>
  <lastmod>2026-06-26T22:00:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブランドはロゴだけでは語れない（Brand &amp;gt; Logo: Visual Analysis of Fashion Brands）</news:title>
   <news:publication_date>2026-06-26T22:00:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705230</loc>
  <lastmod>2026-06-26T21:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>方策勾配で学ぶ古典的プランニング戦略（Learning Classical Planning Strategies with Policy Gradient）</news:title>
   <news:publication_date>2026-06-26T21:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705228</loc>
  <lastmod>2026-06-26T21:59:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で加速するライクリー・フリーなイベント再構成（Machine Learning Accelerated Likelihood-Free Event Reconstruction in Dark Matter Direct Detection）</news:title>
   <news:publication_date>2026-06-26T21:59:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705226</loc>
  <lastmod>2026-06-26T21:08:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DIREによる動的尤度フリー推論（Dynamic Likelihood-free Inference via Ratio Estimation）</news:title>
   <news:publication_date>2026-06-26T21:08:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705224</loc>
  <lastmod>2026-06-26T21:07:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種大規模データの統合とバッチ補正（Heterogeneous large datasets integration using Bayesian factor regression）</news:title>
   <news:publication_date>2026-06-26T21:07:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705222</loc>
  <lastmod>2026-06-26T21:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙モデルのための効率的ベイズ実験設計（Efficient Bayesian Experimental Design for Implicit Models）</news:title>
   <news:publication_date>2026-06-26T21:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705220</loc>
  <lastmod>2026-06-26T21:07:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチクラウド環境における異常検知と攻撃分類の機械学習（Machine Learning for Anomaly Detection and Categorization in Multi-cloud Environments）</news:title>
   <news:publication_date>2026-06-26T21:07:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705218</loc>
  <lastmod>2026-06-26T21:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平面調和系の量子散逸：Maxwell–Chern–Simons理論（Quantum dissipation of planar harmonic systems: Maxwell-Chern-Simons theory）</news:title>
   <news:publication_date>2026-06-26T21:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705216</loc>
  <lastmod>2026-06-26T21:06:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドセキュリティにおける教師あり機械学習の適用可能性（Feasibility of Supervised Machine Learning for Cloud Security）</news:title>
   <news:publication_date>2026-06-26T21:06:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705214</loc>
  <lastmod>2026-06-26T21:06:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Juliaプログラムと機械学習モデルの自動完全コンパイルをCloud TPUへ（Compiling Julia to TPUs）</news:title>
   <news:publication_date>2026-06-26T21:06:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705212</loc>
  <lastmod>2026-06-26T20:15:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語長を削減した深層ニューラルネットワーク推論（DEEP NEURAL NETWORK INFERENCE WITH REDUCED WORD LENGTH）</news:title>
   <news:publication_date>2026-06-26T20:15:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705210</loc>
  <lastmod>2026-06-26T20:14:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DropFilter: 畳み込み層のためのドロップアウト最適化（DropFilter: Dropout for Convolutions）</news:title>
   <news:publication_date>2026-06-26T20:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705208</loc>
  <lastmod>2026-06-26T20:14:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層依存型クロスプラットフォーム多視点特徴学習による施設カテゴリ推定（Hierarchy-Dependent Cross-Platform Multi-View Feature Learning for Venue Category Prediction）</news:title>
   <news:publication_date>2026-06-26T20:14:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705206</loc>
  <lastmod>2026-06-26T20:13:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一筆書きで注目領域を守る仕組み――Self-Erasing Networkによる弱教師ありオブジェクト注意の改善 (Self-Erasing Network for Integral Object Attention)</news:title>
   <news:publication_date>2026-06-26T20:13:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705204</loc>
  <lastmod>2026-06-26T20:13:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DCSVMによる高速多クラス分類（DCSVM: FAST MULTI-CLASS CLASSIFICATION USING SUPPORT VECTOR MACHINES）</news:title>
   <news:publication_date>2026-06-26T20:13:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705202</loc>
  <lastmod>2026-06-26T20:13:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANの訓練を安定化する混合ナッシュ均衡への接近（Finding Mixed Nash Equilibria of Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-26T20:13:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705200</loc>
  <lastmod>2026-06-26T20:12:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点発見と理解のためのネットワーク手法（Viewpoint Discovery and Understanding in Social Networks）</news:title>
   <news:publication_date>2026-06-26T20:12:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705198</loc>
  <lastmod>2026-06-26T19:21:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かな通信環境下での遠隔状態推定における最適スケジューリング学習（Learning Optimal Scheduling Policy for Remote State Estimation under Uncertain Channel Condition）</news:title>
   <news:publication_date>2026-06-26T19:21:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705196</loc>
  <lastmod>2026-06-26T19:21:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幼児語彙を用いた大規模照応解決データセット PreCo（PreCo: A Large-scale Dataset in Preschool Vocabulary for Coreference Resolution）</news:title>
   <news:publication_date>2026-06-26T19:21:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705194</loc>
  <lastmod>2026-06-26T19:20:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小売店向け果物・野菜識別に機械学習を使う試み（Fruit and Vegetable Identification Using Machine Learning for Retail Applications）</news:title>
   <news:publication_date>2026-06-26T19:20:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705192</loc>
  <lastmod>2026-06-26T19:19:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市交通における歩行者の行動・意図認識（Action and intention recognition of pedestrians in urban traffic）</news:title>
   <news:publication_date>2026-06-26T19:19:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705190</loc>
  <lastmod>2026-06-26T19:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M87のイオン化ガスフィラメントの特性（Properties of the ionised gas filament of M87）</news:title>
   <news:publication_date>2026-06-26T19:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705188</loc>
  <lastmod>2026-06-26T19:19:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SING: 軽量な波形生成で音を合成する新流儀（SING: Symbol-to-Instrument Neural Generator）</news:title>
   <news:publication_date>2026-06-26T19:19:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705186</loc>
  <lastmod>2026-06-26T19:19:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>算術的操作法からみるSobolev–Jacobi多項式（Operational Methods in the Study of Sobolev-Jacobi Polynomials）</news:title>
   <news:publication_date>2026-06-26T19:19:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705184</loc>
  <lastmod>2026-06-26T18:27:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトメトリック赤方偏移の確率密度関数の統計解析（Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies）</news:title>
   <news:publication_date>2026-06-26T18:27:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705182</loc>
  <lastmod>2026-06-26T18:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間とコーパスに敏感なエンティティ関連度の評価（Time-Aware and Corpus-Specific Entity Relatedness）</news:title>
   <news:publication_date>2026-06-26T18:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705180</loc>
  <lastmod>2026-06-26T18:27:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的意味再ランク付けによるテキストスポッティングの改善（Visual Semantic Re-ranker for Text Spotting）</news:title>
   <news:publication_date>2026-06-26T18:27:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705178</loc>
  <lastmod>2026-06-26T18:26:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LoGAN：色を条件にロゴを生成するAI（LoGAN: Generating Logos with a Generative Adversarial Neural Network Conditioned on color）</news:title>
   <news:publication_date>2026-06-26T18:26:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705176</loc>
  <lastmod>2026-06-26T18:26:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きスキップ接続による原子表現の解析（Analysis of Atomistic Representations Using Weighted Skip-Connections）</news:title>
   <news:publication_date>2026-06-26T18:26:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705174</loc>
  <lastmod>2026-06-26T18:26:18Z</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自然言語推論における汎化力の検証（Testing the Generalization Power of Neural Network Models Across NLI Benchmarks）</news:title>
   <news:publication_date>2026-06-26T18:26:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705172</loc>
  <lastmod>2026-06-26T18:25:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフォレストのPAC-ベイズ境界に関する考察（On PAC-Bayesian Bounds for Random Forests）</news:title>
   <news:publication_date>2026-06-26T18:25:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705170</loc>
  <lastmod>2026-06-26T17:34:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OCAPIS：Scalaで構築されたR向け序数データ処理パッケージ（OCAPIS: R package for Ordinal Classification And Preprocessing In Scala）</news:title>
   <news:publication_date>2026-06-26T17:34:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705168</loc>
  <lastmod>2026-06-26T17:34:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチUAVによるサイバーフィジカルシステム設計の課題と展望（Multi-UAV Design Challenges for Cyber-Physical Systems）</news:title>
   <news:publication_date>2026-06-26T17:34:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705166</loc>
  <lastmod>2026-06-26T17:34:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>領域選択型コスト効率的アクティブラーニングによるセマンティックセグメンテーション（CEREALS: Cost-Effective REgion-based Active Learning for Semantic Segmentation）</news:title>
   <news:publication_date>2026-06-26T17:34:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705164</loc>
  <lastmod>2026-06-26T17:33:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適切な交通規制の自動発見（Finding Appropriate Traffic Regulations via Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-06-26T17:33:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705162</loc>
  <lastmod>2026-06-26T17:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cheeger変形による正のリッチ曲率の再考（Positive Ricci curvature through Cheeger deformations）</news:title>
   <news:publication_date>2026-06-26T17:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705160</loc>
  <lastmod>2026-06-26T17:33:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語からの構造対応プログラム合成（Structure-Aware Program Synthesis from Natural Language）</news:title>
   <news:publication_date>2026-06-26T17:33:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705158</loc>
  <lastmod>2026-06-26T17:32:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からのSVBRDF推定とレンダリング認識型深層ネットワーク（Single-Image SVBRDF Capture with a Rendering-Aware Deep Network）</news:title>
   <news:publication_date>2026-06-26T17:32:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705156</loc>
  <lastmod>2026-06-26T16:42:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一枚画像から光と色を分ける方法（Consistency-aware Shading Orders Selective Fusion for Intrinsic Image Decomposition）</news:title>
   <news:publication_date>2026-06-26T16:42:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705154</loc>
  <lastmod>2026-06-26T16:41:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習におけるセキュリティ問題と未解決の課題（The Faults in Our π∗s: Security Issues and Open Challenges in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-26T16:41:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705152</loc>
  <lastmod>2026-06-26T16:41:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フリジア語─オランダ語の混合音声に対する半教師あり音響モデル訓練（Semi-supervised acoustic model training for speech with code-switching）</news:title>
   <news:publication_date>2026-06-26T16:41:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705150</loc>
  <lastmod>2026-06-26T16:40:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SwitchNetによる散乱問題の順逆写像学習（SWITCHNET: A NEURAL NETWORK MODEL FOR FORWARD AND INVERSE SCATTERING PROBLEMS）</news:title>
   <news:publication_date>2026-06-26T16:40:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705148</loc>
  <lastmod>2026-06-26T16:40:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値関数の類似性を学習するグラフ埋め込み（Unsupervised Features Extraction for Binary Similarity Using Graph Embedding Neural Networks）</news:title>
   <news:publication_date>2026-06-26T16:40:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705146</loc>
  <lastmod>2026-06-26T16:39:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サーバーレスで学ぶ線形代数の実行基盤（numpywren: Serverless Linear Algebra）</news:title>
   <news:publication_date>2026-06-26T16:39:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705144</loc>
  <lastmod>2026-06-26T16:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的フィードバックと切替コスト下のオンライン学習（Online learning with feedback graphs and switching costs）</news:title>
   <news:publication_date>2026-06-26T16:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705142</loc>
  <lastmod>2026-06-26T15:47:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序的な希薄3Dデータからの顔認識と深層登録（Face Recognition from Sequential Sparse 3D Data via Deep Registration）</news:title>
   <news:publication_date>2026-06-26T15:47:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705140</loc>
  <lastmod>2026-06-26T15:47:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ化された行動空間における階層的強化学習の提案（Hierarchical Approaches for Reinforcement Learning in Parameterized Action Space）</news:title>
   <news:publication_date>2026-06-26T15:47:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705138</loc>
  <lastmod>2026-06-26T15:47:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナップサック付きバンディット問題の統一化（Unifying the stochastic and the adversarial Bandits with Knapsack）</news:title>
   <news:publication_date>2026-06-26T15:47:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705136</loc>
  <lastmod>2026-06-26T15:46:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像キャプションのニューラル合成パラダイム（A Neural Compositional Paradigm for Image Captioning）</news:title>
   <news:publication_date>2026-06-26T15:46:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705134</loc>
  <lastmod>2026-06-26T15:46:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック表現：トピックモデルでより代表的な単語を見つける（Topic representation: finding more representative words in topic models）</news:title>
   <news:publication_date>2026-06-26T15:46:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705132</loc>
  <lastmod>2026-06-26T15:45:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>冗長性が原因だった：敵対的事例を「1ビット」で理解する（ONE BIT MATTERS: UNDERSTANDING ADVERSARIAL EXAMPLES AS THE ABUSE OF REDUNDANCY）</news:title>
   <news:publication_date>2026-06-26T15:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705130</loc>
  <lastmod>2026-06-26T15:45:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群を用いた場所認識にCNNを応用する手法（Point-cloud-based Place Recognition using CNN）</news:title>
   <news:publication_date>2026-06-26T15:45:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705128</loc>
  <lastmod>2026-06-26T14:54:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生体内血栓力学の計測（IN VIVO MEASUREMENT OF BLOOD CLOT MECHANICS FROM COMPUTATIONAL FLUID DYNAMICS BASED ON INTRAVITAL MICROSCOPY IMAGES）</news:title>
   <news:publication_date>2026-06-26T14:54:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705126</loc>
  <lastmod>2026-06-26T14:53:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドソーシング予測のための深層ニューラルランキング（Deep Neural Ranking for Crowdsourced Geopolitical Event Forecasting）</news:title>
   <news:publication_date>2026-06-26T14:53:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705124</loc>
  <lastmod>2026-06-26T14:53:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース化されたDNNの敵対的耐性の向上（Sparse DNNs with Improved Adversarial Robustness）</news:title>
   <news:publication_date>2026-06-26T14:53:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705122</loc>
  <lastmod>2026-06-26T14:53:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテの多層埋め込みによる予測医療の強化（Multilevel Medical Embedding of Electronic Health Records）</news:title>
   <news:publication_date>2026-06-26T14:53:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705120</loc>
  <lastmod>2026-06-26T14:52:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シンドローム損失による誤り訂正デコーダの学習（Learning from the Syndrome）</news:title>
   <news:publication_date>2026-06-26T14:52:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705118</loc>
  <lastmod>2026-06-26T14:52:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Airbnbの検索にディープラーニングを適用する（Applying Deep Learning To Airbnb Search）</news:title>
   <news:publication_date>2026-06-26T14:52:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705116</loc>
  <lastmod>2026-06-26T14:52:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疾病概念に基づく生物医学文書のクラスタリングと可視化（Biomedical Document Clustering and Visualization based on the Concepts of Diseases）</news:title>
   <news:publication_date>2026-06-26T14:52:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705114</loc>
  <lastmod>2026-06-26T14:01:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル選択技術の概観（Model Selection Techniques —An Overview）</news:title>
   <news:publication_date>2026-06-26T14:01:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705112</loc>
  <lastmod>2026-06-26T14:01:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記譜形式音楽における和音認識：セグメント型CRFとセグメント特徴の比較評価 (Chord Recognition in Symbolic Music: A Segmental CRF Model, Segment-Level Features, and Comparative Evaluations on Classical and Popular Music)</news:title>
   <news:publication_date>2026-06-26T14:01:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705110</loc>
  <lastmod>2026-06-26T14:00:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OCTベースのモーション補償のためのシステムパラメータ較正に向けた二経路3D CNN（Two-path 3D CNNs for calibration of system parameters for OCT-based motion compensation）</news:title>
   <news:publication_date>2026-06-26T14:00:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705108</loc>
  <lastmod>2026-06-26T14:00:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cosmic Visionsと21cmステージII実験が示す宇宙観の拡張（Cosmic Visions Dark Energy: Inflation and Early Dark Energy with a Stage II Hydrogen Intensity Mapping Experiment）</news:title>
   <news:publication_date>2026-06-26T14:00:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705106</loc>
  <lastmod>2026-06-26T13:59:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全アテンション型情報検索器（A Fully Attention-Based Information Retriever）</news:title>
   <news:publication_date>2026-06-26T13:59:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705104</loc>
  <lastmod>2026-06-26T13:59:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロクルステスとクラシカルスケーリングの摂動境界とその応用（Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning）</news:title>
   <news:publication_date>2026-06-26T13:59:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705102</loc>
  <lastmod>2026-06-26T13:59:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生体吸収性スキャフォールドのIVOCT画像可視化におけるCNNと弱教師あり局所化の応用（Bioresorbable Scaffold Visualization in IVOCT Images Using CNNs and Weakly Supervised Localization）</news:title>
   <news:publication_date>2026-06-26T13:59:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705100</loc>
  <lastmod>2026-06-26T13:08:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空港周辺の確率的飛行経路モデルの学習（Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace from Position Data）</news:title>
   <news:publication_date>2026-06-26T13:08:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705098</loc>
  <lastmod>2026-06-26T13:07:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル空間に曲率を導入する（Introducing Curvature to the Label Space）</news:title>
   <news:publication_date>2026-06-26T13:07:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705096</loc>
  <lastmod>2026-06-26T13:07:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム多変量最適化のための効率的バンディットアルゴリズム（An Efficient Bandit Algorithm for Realtime Multivariate Optimization）</news:title>
   <news:publication_date>2026-06-26T13:07:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705094</loc>
  <lastmod>2026-06-26T13:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルで加速する観測シミュレーション（Using Generative Models to Simulate Cosmogenic Radiation）</news:title>
   <news:publication_date>2026-06-26T13:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705092</loc>
  <lastmod>2026-06-26T13:07:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語埋め込みモデルの比較と調整の可視化ツール（LAMVI-2: A Visual Tool for Comparing and Tuning Word Embedding Models）</news:title>
   <news:publication_date>2026-06-26T13:07:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705090</loc>
  <lastmod>2026-06-26T13:06:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ordered Neuronsが示した「階層的言語理解」の回路設計（ORDERED NEURONS: INTEGRATING TREE STRUCTURES INTO RECURRENT NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-26T13:06:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/705088</loc>
  <lastmod>2026-06-26T13:06:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像からの空間密度推定を弱教師ありで学ぶ（A Weakly Supervised Approach for Estimating Spatial Density Functions from High-Resolution Satellite Imagery）</news:title>
   <news:publication_date>2026-06-26T13:06:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705086</loc>
  <lastmod>2026-06-26T12:15:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数変換による敵対的リスク上界の導出（Adversarial risk bounds via function transformation）</news:title>
   <news:publication_date>2026-06-26T12:15:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705084</loc>
  <lastmod>2026-06-26T12:15:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前光学選別による潮汐破壊事象の同定（Identifying Tidal Disruption Events via Prior Photometric Selection of Their Preferred Hosts）</news:title>
   <news:publication_date>2026-06-26T12:15:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705082</loc>
  <lastmod>2026-06-26T12:14:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterからの出生異常報告を自動検出する方法（Automatically Detecting Self-Reported Birth Defect Outcomes on Twitter for Large-scale Epidemiological Research）</news:title>
   <news:publication_date>2026-06-26T12:14:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705080</loc>
  <lastmod>2026-06-26T12:14:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAMLの実用化を加速する改良点（How to Train Your MAML）</news:title>
   <news:publication_date>2026-06-26T12:14:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705078</loc>
  <lastmod>2026-06-26T12:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層特徴に基づく皮膚鏡画像の類似検索の診断精度（Diagnostic Accuracy of Content Based Dermatoscopic Image Retrieval with Deep Classification Features）</news:title>
   <news:publication_date>2026-06-26T12:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705076</loc>
  <lastmod>2026-06-26T12:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンゴ園における果実検出とカウントの比較研究（A Comparative Study of Fruit Detection and Counting Methods for Yield Mapping in Apple Orchards）</news:title>
   <news:publication_date>2026-06-26T12:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705074</loc>
  <lastmod>2026-06-26T12:13:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からのエンドツーエンド条件付きGANによるデハジング（End-to-End Single-Image Dehazing with Conditional GAN）</news:title>
   <news:publication_date>2026-06-26T12:13:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705072</loc>
  <lastmod>2026-06-26T11:22:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自由飛行における抗力係数の正確なレーダー測定（Accurate Radar Measurements of Drag Coefficients in Free Flight）</news:title>
   <news:publication_date>2026-06-26T11:22:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705070</loc>
  <lastmod>2026-06-26T11:21:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動選択により同定された低光度アクティブ銀河核の候補（VARIABILITY-SELECTED LOW-LUMINOSITY ACTIVE GALACTIC NUCLEI CANDIDATES IN THE 7 MS CHANDRA DEEP FIELD-SOUTH）</news:title>
   <news:publication_date>2026-06-26T11:21:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705068</loc>
  <lastmod>2026-06-26T11:21:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少ないサンプルでがんサブタイプを見分ける学習法（Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data）</news:title>
   <news:publication_date>2026-06-26T11:21:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705066</loc>
  <lastmod>2026-06-26T11:20:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大気汚染モニタリングと予測を広げる深層学習（Using Deep Learning to Extend the Range of Air Pollution Monitoring and Forecasting）</news:title>
   <news:publication_date>2026-06-26T11:20:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705064</loc>
  <lastmod>2026-06-26T11:20:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Nタイムスライス動的チェーンイベントグラフの性質（Properties of an N Time-Slice Dynamic Chain Event Graph）</news:title>
   <news:publication_date>2026-06-26T11:20:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705062</loc>
  <lastmod>2026-06-26T11:20:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SGDで得られる最終モデルの最適性（Optimality of the Final Model Found via Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-06-26T11:20:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705060</loc>
  <lastmod>2026-06-26T11:20:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RNNにおけるドロップアウトの効果検証（An Exploration of Dropout with RNNs for Natural Language Inference）</news:title>
   <news:publication_date>2026-06-26T11:20:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705058</loc>
  <lastmod>2026-06-26T10:28:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手の仕草で描く2D/3D形状の視覚レンダリング（Visual Rendering of Shapes on 2D Display Devices Guided by Hand Gestures）</news:title>
   <news:publication_date>2026-06-26T10:28:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705056</loc>
  <lastmod>2026-06-26T10:28:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現地で即時判断する自然災害監視（Event-triggered Natural Hazard Monitoring with Convolutional Neural Networks on the Edge）</news:title>
   <news:publication_date>2026-06-26T10:28:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705054</loc>
  <lastmod>2026-06-26T10:27:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン行列分解推薦のための交互線形バンディット（Alternating Linear Bandits for Online Matrix-Factorization Recommendation）</news:title>
   <news:publication_date>2026-06-26T10:27:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705052</loc>
  <lastmod>2026-06-26T10:27:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的リジェクションサンプリングの最小最大準最適アルゴリズム（A minimax near-optimal algorithm for adaptive rejection sampling）</news:title>
   <news:publication_date>2026-06-26T10:27:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705050</loc>
  <lastmod>2026-06-26T10:27:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Differentiable Point Cloudsによる形状と姿勢の教師なし学習（Unsupervised Learning of Shape and Pose with Differentiable Point Clouds）</news:title>
   <news:publication_date>2026-06-26T10:27:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705048</loc>
  <lastmod>2026-06-26T10:27:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非一様ユークリッド初通過パーコレーションと距離学習（NONHOMOGENEOUS EUCLIDEAN FIRST-PASSAGE PERCOLATION AND DISTANCE LEARNING）</news:title>
   <news:publication_date>2026-06-26T10:27:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705046</loc>
  <lastmod>2026-06-26T10:27:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模連続学習を神経回路風に解く—オンラインクラスタリングと階層的予測符号化（A neuro-inspired architecture for unsupervised continual learning based on online clustering and hierarchical predictive coding）</news:title>
   <news:publication_date>2026-06-26T10:27:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705044</loc>
  <lastmod>2026-06-26T09:36:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車両の縦横同時制御を深層学習で実現する（Coupled Longitudinal and Lateral Control of a Vehicle using Deep Learning）</news:title>
   <news:publication_date>2026-06-26T09:36:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705042</loc>
  <lastmod>2026-06-26T09:35:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳腫瘍画像の類似検索を多タスク学習で改善する手法（BRAIN TUMOR IMAGE RETRIEVAL VIA MULTITASK LEARNING）</news:title>
   <news:publication_date>2026-06-26T09:35:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705040</loc>
  <lastmod>2026-06-26T09:35:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ensmallenによるC++最適化の実務入門（ensmallen: a flexible C++ library for efficient function optimization）</news:title>
   <news:publication_date>2026-06-26T09:35:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705038</loc>
  <lastmod>2026-06-26T09:34:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタープリタブルモデルの安定性評価（Assessing the Stability of Interpretable Models）</news:title>
   <news:publication_date>2026-06-26T09:34:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705036</loc>
  <lastmod>2026-06-26T09:34:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一撮影レントゲンから仮想デュアルエネルギー画像を生成する（Generation of Virtual Dual Energy Images from Standard Single-Shot Radiographs using Multi-scale and Conditional Adversarial Network）</news:title>
   <news:publication_date>2026-06-26T09:34:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705034</loc>
  <lastmod>2026-06-26T09:34:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ下の敵対的オンライン学習の基礎と示唆（Adversarial Online Learning with noise）</news:title>
   <news:publication_date>2026-06-26T09:34:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705032</loc>
  <lastmod>2026-06-26T09:34:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歴史文書のベースライン検出（Baseline Detection in Historical Documents using Convolutional U-Nets）</news:title>
   <news:publication_date>2026-06-26T09:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705030</loc>
  <lastmod>2026-06-26T08:42:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子アニーリングを学習的に活用する探索法（Quantum Annealing Learning Search for solving QUBO problems）</news:title>
   <news:publication_date>2026-06-26T08:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705028</loc>
  <lastmod>2026-06-26T08:42:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルフリー強化学習におけるロバスト性の回復（Recovering Robustness in Model-Free Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-26T08:42:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705026</loc>
  <lastmod>2026-06-26T08:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医学生におけるゲーミフィケーションが自主学習に与える影響の評価（Assessing the Impact of Gamification on Self-Directed Learning in Medical Students）</news:title>
   <news:publication_date>2026-06-26T08:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705024</loc>
  <lastmod>2026-06-26T08:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話型ソーシャルエージェント「Ruuh」の設計と示唆（Ruuh: A Deep Learning Based Conversational Social Agent）</news:title>
   <news:publication_date>2026-06-26T08:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705022</loc>
  <lastmod>2026-06-26T08:41:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BioSentVec：バイオ医療テキストのための文埋め込み作成（BioSentVec: creating sentence embeddings for biomedical texts）</news:title>
   <news:publication_date>2026-06-26T08:41:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705020</loc>
  <lastmod>2026-06-26T08:41:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードからソフトへ：深層ネットワークの非線形性をVQと統計推論で理解する（FROM HARD TO SOFT: UNDERSTANDING DEEP NETWORK NONLINEARITIES VIA VECTOR QUANTIZATION AND STATISTICAL INFERENCE）</news:title>
   <news:publication_date>2026-06-26T08:41:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705018</loc>
  <lastmod>2026-06-26T08:40:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かさ推定を伴う暗黙的モデルによるIVIMイメージング（IMPLICIT MODELING WITH UNCERTAINTY ESTIMATION FOR INTRAVOXEL INCOHERENT MOTION IMAGING）</news:title>
   <news:publication_date>2026-06-26T08:40:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/705016</loc>
  <lastmod>2026-06-26T07:49:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-26T07:49:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705014</loc>
  <lastmod>2026-06-26T07:46:40Z</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>2026-06-26T07:46:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705012</loc>
  <lastmod>2026-06-26T07:46:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多剤併用による副作用を知識グラフで予測する（Knowledge Graph Completion to Predict Polypharmacy Side Effects）</news:title>
   <news:publication_date>2026-06-26T07:46:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705010</loc>
  <lastmod>2026-06-26T07:45:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コスト感度のある頑健性──重要攻撃に重点を置く防御戦略（COST-SENSITIVE ROBUSTNESS AGAINST ADVERSARIAL EXAMPLES）</news:title>
   <news:publication_date>2026-06-26T07:45:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705008</loc>
  <lastmod>2026-06-26T07:45:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハザード比の解釈に潜む微妙さ（Subtleties in the interpretation of hazard ratios）</news:title>
   <news:publication_date>2026-06-26T07:45:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705006</loc>
  <lastmod>2026-06-26T07:45:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調を生む強化学習：GCPNを用いたマルチエージェントActor‑Criticの要点解説（MULTI‑AGENT ACTOR‑CRITIC WITH GENERATIVE COOPERATIVE POLICY NETWORK）</news:title>
   <news:publication_date>2026-06-26T07:45:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705004</loc>
  <lastmod>2026-06-26T07:44:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込み強化学習の要点（Graph Convolutional Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-26T07:44:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705002</loc>
  <lastmod>2026-06-26T06:53:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の深層学習による固有表現の曖昧性解消（Named Entity Disambiguation using Deep Learning on Graphs）</news:title>
   <news:publication_date>2026-06-26T06:53:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/705000</loc>
  <lastmod>2026-06-26T06:46:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バックプロパゲーションでスパース変換を学ぶ（Learning sparse transformations through backpropagation）</news:title>
   <news:publication_date>2026-06-26T06:46:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704998</loc>
  <lastmod>2026-06-26T06:45:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成符号化カプセルネットワークとK-Meansルーティングによるテキスト分類（Compositional Coding Capsule Network with K-Means Routing for Text Classification）</news:title>
   <news:publication_date>2026-06-26T06:45:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704996</loc>
  <lastmod>2026-06-26T06:45:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有向グラフのためのノード表現学習（Node Representation Learning for Directed Graphs）</news:title>
   <news:publication_date>2026-06-26T06:45:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704994</loc>
  <lastmod>2026-06-26T06:44:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検閲された需要予測のアンサンブル手法（Ensemble Method for Censored Demand Prediction）</news:title>
   <news:publication_date>2026-06-26T06:44:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704992</loc>
  <lastmod>2026-06-26T06:44:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超平面の配置による多クラス分類の最適化（Optimal arrangements of hyperplanes for multiclass classification）</news:title>
   <news:publication_date>2026-06-26T06:44:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704990</loc>
  <lastmod>2026-06-26T06:44:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>莫高窟の古代壁画の年代推定（Dating Ancient Paintings of Mogao Grottoes Using Deeply Learnt Visual Codes）</news:title>
   <news:publication_date>2026-06-26T06:44:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704988</loc>
  <lastmod>2026-06-26T05:52:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔属性の相関を探るグラフ注意ネットワーク（Exploring Correlations for Multiple Facial Attributes Recognition through Graph Attention Network）</news:title>
   <news:publication_date>2026-06-26T05:52:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704986</loc>
  <lastmod>2026-06-26T05:52:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過学習とパラメータのジャミング転移（A jamming transition from under- to over-parametrization affects generalization in deep learning）</news:title>
   <news:publication_date>2026-06-26T05:52:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704984</loc>
  <lastmod>2026-06-26T05:52:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ分類のためのシンプルなベースラインアルゴリズム（A Simple Baseline Algorithm for Graph Classification）</news:title>
   <news:publication_date>2026-06-26T05:52:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704982</loc>
  <lastmod>2026-06-26T05:51:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均値に基づくリアルタイム計画探索（Mean-based Heuristic Search for Real-Time Planning）</news:title>
   <news:publication_date>2026-06-26T05:51:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704980</loc>
  <lastmod>2026-06-26T05:51:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計画問題における有用なマクロアクションの発見（Mining useful Macro-actions in Planning）</news:title>
   <news:publication_date>2026-06-26T05:51:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704978</loc>
  <lastmod>2026-06-26T05:51:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DNNを使った音質評価最適化（DNN-based Source Enhancement to Increase Objective Sound Quality Assessment Score）</news:title>
   <news:publication_date>2026-06-26T05:51:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704976</loc>
  <lastmod>2026-06-26T05:51:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルは自分の無知を知っているか（DO DEEP GENERATIVE MODELS KNOW WHAT THEY DON’T KNOW?）</news:title>
   <news:publication_date>2026-06-26T05:51:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704974</loc>
  <lastmod>2026-06-26T04:59:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リスク感応型強化学習の方策勾配探索（Risk-Sensitive Reinforcement Learning via Policy Gradient Search）</news:title>
   <news:publication_date>2026-06-26T04:59:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704972</loc>
  <lastmod>2026-06-26T04:59:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響異常検知におけるオートエンコーダとネイマン・ピアソン補題の応用（Unsupervised Detection of Anomalous Sound based on Deep Learning and the Neyman-Pearson Lemma）</news:title>
   <news:publication_date>2026-06-26T04:59:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704970</loc>
  <lastmod>2026-06-26T04:58:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心房瘢痕の自動分割を可能にするグラフカットと学習ポテンシャル（Atrial scar segmentation via potential learning in the graph-cut framework）</news:title>
   <news:publication_date>2026-06-26T04:58:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704968</loc>
  <lastmod>2026-06-26T04:58:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Bregmanコード発散の概念と応用（The Bregman Chord Divergence）</news:title>
   <news:publication_date>2026-06-26T04:58:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704966</loc>
  <lastmod>2026-06-26T04:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホロニック制御アーキテクチャの進化とIndustry 4.0への接続（Evolution of holonic control architectures towards Industry 4.0: A short overview）</news:title>
   <news:publication_date>2026-06-26T04:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704964</loc>
  <lastmod>2026-06-26T04:58:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運動イメージEEGの高精度デコードを可能にする多重ウェーブレット時頻度因果性とブーステッドConvNets（Boosted Convolutional Neural Networks for Motor Imagery EEG Decoding with Multiwavelet-based Time-Frequency Conditional Granger Causality Analysis）</news:title>
   <news:publication_date>2026-06-26T04:58:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704962</loc>
  <lastmod>2026-06-26T04:58:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーン変化検出のための畳み込みシアミーズ距離学習（Learning to Measure Changes: Fully Convolutional Siamese Metric Networks for Scene Change Detection）</news:title>
   <news:publication_date>2026-06-26T04:58:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704960</loc>
  <lastmod>2026-06-26T04:06:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GreedyAC：条件付きクロスエントロピーで方針改善を行う新手法（GREEDY ACTOR-CRITIC: A NEW CONDITIONAL CROSS-ENTROPY METHOD FOR POLICY IMPROVEMENT）</news:title>
   <news:publication_date>2026-06-26T04:06:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704958</loc>
  <lastmod>2026-06-26T04:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重みの直交性を活かす訓練法の効果検証（Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?）</news:title>
   <news:publication_date>2026-06-26T04:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704956</loc>
  <lastmod>2026-06-26T04:06:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノームレンジ分割が変えるLSHベースのMIPS（Norm-Range Partition: A Universal Catalyst for LSH based Maximum Inner Product Search）</news:title>
   <news:publication_date>2026-06-26T04:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704954</loc>
  <lastmod>2026-06-26T04:05:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロンのバーストとトニック発火に基づく一般学習システム（A general learning system based on neuron bursting and tonic firing）</news:title>
   <news:publication_date>2026-06-26T04:05:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704952</loc>
  <lastmod>2026-06-26T04:05:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンショット画像セグメンテーションを導く類似度ガイダンス（SG-One: Similarity Guidance Network for One-Shot Semantic Segmentation）</news:title>
   <news:publication_date>2026-06-26T04:05:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704950</loc>
  <lastmod>2026-06-26T04:05:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス可加モデルの公理的解釈性（Axiomatic Interpretability for Multiclass Additive Models）</news:title>
   <news:publication_date>2026-06-26T04:05:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704948</loc>
  <lastmod>2026-06-26T04:05:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態空間モデルのための確率勾配MCMC（Stochastic Gradient MCMC for State Space Models）</news:title>
   <news:publication_date>2026-06-26T04:05:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704946</loc>
  <lastmod>2026-06-26T03:13:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ComNet：専門知識と深層学習を組み合わせたOFDM受信機（ComNet: Combination of Deep Learning and Expert Knowledge in OFDM Receivers）</news:title>
   <news:publication_date>2026-06-26T03:13:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704944</loc>
  <lastmod>2026-06-26T03:13:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピックのスパース性を捉える新しいニューラル手法（Sparsemax and Relaxed Wasserstein for Topic Sparsity）</news:title>
   <news:publication_date>2026-06-26T03:13:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/704942</loc>
  <lastmod>2026-06-26T03:12:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声で種を認識する機械学習の実践（OUR PRACTICE OF USING MACHINE LEARNING TO RECOGNIZE SPECIES BY VOICE）</news:title>
   <news:publication_date>2026-06-26T03:12:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704940</loc>
  <lastmod>2026-06-26T03:12:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルとレンジ空間から学ぶ（Learning from the Kernel and the Range Space）</news:title>
   <news:publication_date>2026-06-26T03:12:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704938</loc>
  <lastmod>2026-06-26T03:11:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイドチャネルでニューラルネットワークを丸裸にする方法（CSI Neural Network: Using Side-channels to Recover Your Artificial Neural Network Information）</news:title>
   <news:publication_date>2026-06-26T03:11:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704936</loc>
  <lastmod>2026-06-26T03:11:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像から場所を特定する技術の要点（Where is this? Video geolocation based on neural network features）</news:title>
   <news:publication_date>2026-06-26T03:11:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704934</loc>
  <lastmod>2026-06-26T03:11:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モノラル前処理による堅牢な音声認識の検討（INVESTIGATION OF MONAURAL FRONT-END PROCESSING FOR ROBUST ASR WITHOUT RETRAINING OR JOINT-TRAINING）</news:title>
   <news:publication_date>2026-06-26T03:11:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704932</loc>
  <lastmod>2026-06-26T02:19:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>辞書学習に基づく頑健なオンライン分類手法とウェアラブルセンサ応用（A Method for Robust Online Classification using Dictionary Learning）</news:title>
   <news:publication_date>2026-06-26T02:19:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704930</loc>
  <lastmod>2026-06-26T02:19:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱ラベル下の音声イベント検出における5種のMultiple Instance Learningプーリング関数比較（A COMPARISON OF FIVE MULTIPLE INSTANCE LEARNING POOLING FUNCTIONS FOR SOUND EVENT DETECTION WITH WEAK LABELING）</news:title>
   <news:publication_date>2026-06-26T02:19:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704928</loc>
  <lastmod>2026-06-26T02:19:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>代表性の基準を探る：マサチューセッツ州における共和党の不振（Locating the Representational Baseline: Republicans in Massachusetts）</news:title>
   <news:publication_date>2026-06-26T02:19:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704926</loc>
  <lastmod>2026-06-26T02:18:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形学習と進化ゲームにおける学習優位性（Nonlinear learning and learning advantages in evolutionary games）</news:title>
   <news:publication_date>2026-06-26T02:18:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704924</loc>
  <lastmod>2026-06-26T02:18:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚科医レベルのダーモスコピー皮膚がん分類（Dermatologist Level Dermoscopy Skin Cancer Classification Using Different Deep Learning Convolutional Neural Networks Algorithms）</news:title>
   <news:publication_date>2026-06-26T02:18:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704922</loc>
  <lastmod>2026-06-26T02:18:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インラインホログラムから深層学習で粒子体積を再構築する方法（Digital holographic particle volume reconstruction using a deep neural network）</news:title>
   <news:publication_date>2026-06-26T02:18:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704920</loc>
  <lastmod>2026-06-26T02:17:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不規則観察と病勢進行を考慮した患者サブタイピング（Patient Subtyping with Disease Progression and Irregular Observation Trajectories）</news:title>
   <news:publication_date>2026-06-26T02:17:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704918</loc>
  <lastmod>2026-06-26T01:26:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RLgraph：深層強化学習のためのモジュラー計算グラフ（RLgraph: Modular Computation Graphs for Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-26T01:26:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704916</loc>
  <lastmod>2026-06-26T01:26:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深さと非線形性はResNetにおいて悪い局所最小値を生まない（Depth with nonlinearity creates no bad local minima in ResNets）</news:title>
   <news:publication_date>2026-06-26T01:26:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704914</loc>
  <lastmod>2026-06-26T01:26:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測マルチエージェント環境におけるアクター・クリティック最適化（Actor-Critic Policy Optimization in Partially Observable Multiagent Environments）</news:title>
   <news:publication_date>2026-06-26T01:26:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704912</loc>
  <lastmod>2026-06-26T01:25:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セミグループ値メトリック空間とRamsey理論の接続（Semigroup-valued Metric Spaces and Ramsey Theory）</news:title>
   <news:publication_date>2026-06-26T01:25:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704910</loc>
  <lastmod>2026-06-26T01:25:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非漸近的かつ鋭い下側尾部確率の下界（On the Non-asymptotic and Sharp Lower Tail Bounds of Random Variables）</news:title>
   <news:publication_date>2026-06-26T01:25:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704908</loc>
  <lastmod>2026-06-26T01:25:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードディスクの残存寿命予測における特徴正規化とLSTM応用の仕組み（Mechanisms for Integrated Feature Normalization and Remaining Useful Life Estimation Using LSTMs Applied to Hard-Disks）</news:title>
   <news:publication_date>2026-06-26T01:25:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704906</loc>
  <lastmod>2026-06-26T01:25:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AT-TPCの軌跡分類における機械学習手法（Machine Learning Methods for Track Classification in the AT-TPC）</news:title>
   <news:publication_date>2026-06-26T01:25:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704904</loc>
  <lastmod>2026-06-26T00:33:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多観測サーベイを横断する変光星分類の深層学習（Deep multi-survey classification of variable stars）</news:title>
   <news:publication_date>2026-06-26T00:33:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704902</loc>
  <lastmod>2026-06-26T00:33:45Z</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学習の並列制御と実行スケジューリング（Runtime Concurrency Control and Operation Scheduling for High Performance Neural Network Training）</news:title>
   <news:publication_date>2026-06-26T00:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704900</loc>
  <lastmod>2026-06-26T00:33:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D表面上のスペクトル変換ネットワークによる非剛体形状解析（Learning Spectral Transform Network on 3D Surface for Non-rigid Shape Analysis）</news:title>
   <news:publication_date>2026-06-26T00:33:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704898</loc>
  <lastmod>2026-06-26T00:32:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インターネットアドレス空間の経路認識型分割によるCDNのサーバー選定最適化（Routing-Aware Partitioning of the Internet Address Space for Server Ranking in CDNs）</news:title>
   <news:publication_date>2026-06-26T00:32:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704896</loc>
  <lastmod>2026-06-26T00:32:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教示を通じて逆強化学習エージェントを育てる—特徴とデモンストレーションで教える方法（Teaching Inverse Reinforcement Learners via Features and Demonstrations）</news:title>
   <news:publication_date>2026-06-26T00:32:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704894</loc>
  <lastmod>2026-06-26T00:32:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNを用いた株式市場予測の実践的枠組み（CNNPred: CNN-based stock market prediction using several data sources）</news:title>
   <news:publication_date>2026-06-26T00:32:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704892</loc>
  <lastmod>2026-06-26T00:32:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的指数族モデルの学習―因果・側方依存性を持つニューロモルフィック計算のために (Training Dynamic Exponential Family Models with Causal and Lateral Dependencies for Generalized Neuromorphic Computing)</news:title>
   <news:publication_date>2026-06-26T00:32:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704890</loc>
  <lastmod>2026-06-25T23:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報ボトルネックによる非2進LDPC復号（Decoding of Non-Binary LDPC Codes Using the Information Bottleneck Method）</news:title>
   <news:publication_date>2026-06-25T23:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704888</loc>
  <lastmod>2026-06-25T23:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルノイズ除去による単調性分類の改善（Label Noise Filtering Techniques to Improve Monotonic Classification）</news:title>
   <news:publication_date>2026-06-25T23:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704886</loc>
  <lastmod>2026-06-25T23:39:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度常微分方程式による加速現象の理解（Understanding the Acceleration Phenomenon via High-Resolution Differential Equations）</news:title>
   <news:publication_date>2026-06-25T23:39:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704884</loc>
  <lastmod>2026-06-25T23:39:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的平均拡散とランダム座標更新（DYNAMIC AVERAGE DIFFUSION WITH RANDOMIZED COORDINATE UPDATES）</news:title>
   <news:publication_date>2026-06-25T23:39:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704882</loc>
  <lastmod>2026-06-25T23:39:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングが変えたアナログ→デジタル変換の世界（Analog-to-digital Conversion Revolutionized by Deep Learning）</news:title>
   <news:publication_date>2026-06-25T23:39:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704880</loc>
  <lastmod>2026-06-25T23:38:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み機器における深層学習モデル圧縮の適用判断（To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference）</news:title>
   <news:publication_date>2026-06-25T23:38:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704878</loc>
  <lastmod>2026-06-25T23:38:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Instagram上のフーカー（ウォーターパイプ）画像の自動識別（Automated identification of hookahs (waterpipes) on Instagram: an application in feature extraction using Convolutional Neural Network and Support Vector Machine classification）</news:title>
   <news:publication_date>2026-06-25T23:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704876</loc>
  <lastmod>2026-06-25T22:47:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多チャンネルポリソムノグラフィーからの睡眠覚醒検出（Sleep Arousal Detection from Polysomnography using the Scattering Transform and Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-25T22:47:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704874</loc>
  <lastmod>2026-06-25T22:46:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種多数コア向け3D NoC設計を学習で自動化する研究（Learning-based Application-Agnostic 3D NoC Design for Heterogeneous Manycore Systems）</news:title>
   <news:publication_date>2026-06-25T22:46:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704872</loc>
  <lastmod>2026-06-25T22:46:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続領域のDPPからの多項式時間MCMC法（A Polynomial Time MCMC Method for Sampling from Continuous DPPs）</news:title>
   <news:publication_date>2026-06-25T22:46:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704870</loc>
  <lastmod>2026-06-25T22:45:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語ペア埋め込みによる跨文推論の改善（pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference）</news:title>
   <news:publication_date>2026-06-25T22:45:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704868</loc>
  <lastmod>2026-06-25T22:45:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学/近赤外アフターグロウにおける縁が明るいジェットの証拠（Evidence for a Bright-Edged Jet in the Optical/NIR Afterglow of GRB 160625B）</news:title>
   <news:publication_date>2026-06-25T22:45:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704866</loc>
  <lastmod>2026-06-25T22:45:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>供給網におけるサービス障害予測のデータモデル (Data models for service failure prediction in supply-chain networks)</news:title>
   <news:publication_date>2026-06-25T22:45:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704864</loc>
  <lastmod>2026-06-25T22:44:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層ごとの最適ビット幅でモデルを圧縮する新手法（Differentiable Fine-grained Quantization for Deep Neural Network Compression）</news:title>
   <news:publication_date>2026-06-25T22:44:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704862</loc>
  <lastmod>2026-06-25T21:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペアワイズ選好集約を効率化するHybrid-MST（Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation）</news:title>
   <news:publication_date>2026-06-25T21:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704860</loc>
  <lastmod>2026-06-25T21:53:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習が脳活動と結合性を異なる形で再編成する（Learning differentially reorganizes brain activity and connectivity）</news:title>
   <news:publication_date>2026-06-25T21:53:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704858</loc>
  <lastmod>2026-06-25T21:52:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動タイトフレームによるクライオEM画像のノイズ除去とコンフォメーショナル分類（Data-Driven Tight Frame for Cryo-EM Image Denoising and Conformational Classification）</news:title>
   <news:publication_date>2026-06-25T21:52:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704856</loc>
  <lastmod>2026-06-25T21:52:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Interactive Reinforcement Learningエージェントの自己説明手法（Autonomous Self-Explanation of Behavior for Interactive Reinforcement Learning Agents）</news:title>
   <news:publication_date>2026-06-25T21:52:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704854</loc>
  <lastmod>2026-06-25T21:52:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習における公平性の最前線（The Frontiers of Fairness in Machine Learning）</news:title>
   <news:publication_date>2026-06-25T21:52:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704852</loc>
  <lastmod>2026-06-25T21:51:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アウトラインを用いた階層的テキスト生成（Hierarchical Text Generation using an Outline）</news:title>
   <news:publication_date>2026-06-25T21:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704850</loc>
  <lastmod>2026-06-25T21:51:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合ラベルを用いたニューラル形態素タグ付け（Modeling Composite Labels for Neural Morphological Tagging）</news:title>
   <news:publication_date>2026-06-25T21:51:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704848</loc>
  <lastmod>2026-06-25T21:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフォレストで記述するレイノルズ応力テンソルのデータ駆動モデリング（Data-Driven Modelling of the Reynolds Stress Tensor using Random Forests with Invariance）</news:title>
   <news:publication_date>2026-06-25T21:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704846</loc>
  <lastmod>2026-06-25T21:00:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様なデータからの集合学習による現場対応型エンティティ分類（Collective Learning From Diverse Datasets for Entity Typing in the Wild）</news:title>
   <news:publication_date>2026-06-25T21:00:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704844</loc>
  <lastmod>2026-06-25T20:59:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANに基づく顔画像のセマンティック修復の改良技術（Improved Techniques for GAN based Facial Inpainting）</news:title>
   <news:publication_date>2026-06-25T20:59:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704842</loc>
  <lastmod>2026-06-25T20:58:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動き推定と補償で駆動するニューラルネットワークによる映像補間と強調（MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and Enhancement）</news:title>
   <news:publication_date>2026-06-25T20:58:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704840</loc>
  <lastmod>2026-06-25T20:58:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボルツマンマシンの自由エネルギーの厳密論点（Free energies of Boltzmann Machines: self-averaging, annealed and replica symmetric approximations in the thermodynamic limit）</news:title>
   <news:publication_date>2026-06-25T20:58:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704838</loc>
  <lastmod>2026-06-25T20:58:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球内部の超イオン性水素の発見と意義（Superionic hydrogen in Earth’s deep interior）</news:title>
   <news:publication_date>2026-06-25T20:58:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704836</loc>
  <lastmod>2026-06-25T20:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性対応協調フィルタリングの俯瞰と分類（Atribute-aware Collaborative Filtering: Survey and Classification）</news:title>
   <news:publication_date>2026-06-25T20:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704834</loc>
  <lastmod>2026-06-25T20:06:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BCR-Netによる非標準ウェーブレット形式に基づくニューラルネットワーク（BCR-Net: a neural network based on the nonstandard wavelet form）</news:title>
   <news:publication_date>2026-06-25T20:06:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704832</loc>
  <lastmod>2026-06-25T20:06:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布ロバスト最適化による均一性能学習（Learning Models with Uniform Performance via Distributionally Robust Optimization）</news:title>
   <news:publication_date>2026-06-25T20:06:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704830</loc>
  <lastmod>2026-06-25T20:06:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OCTデータで学習した深層学習による眼底写真からの緑内障定量評価（FROM MACHINE TO MACHINE: AN OCT-TRAINED DEEP LEARNING ALGORITHM FOR OBJECTIVE QUANTIFICATION OF GLAUCOMATOUS DAMAGE IN FUNDUS PHOTOGRAPHS）</news:title>
   <news:publication_date>2026-06-25T20:06:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704828</loc>
  <lastmod>2026-06-25T20:05:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索負担の定量化とフリーライディングの不公平性（Quantifying the Burden of Exploration and the Unfairness of Free Riding）</news:title>
   <news:publication_date>2026-06-25T20:05:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704826</loc>
  <lastmod>2026-06-25T20:05:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MMLSparkが変えた大規模機械学習の実務導入像（MMLSpark: Unifying Machine Learning Ecosystems at Massive Scales）</news:title>
   <news:publication_date>2026-06-25T20:05:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704824</loc>
  <lastmod>2026-06-25T20:05:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間的近接性が導く属性類似性（Temporal Proximity induces Attributes Similarity）</news:title>
   <news:publication_date>2026-06-25T20:05:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704822</loc>
  <lastmod>2026-06-25T20:04:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続値ドメインにおけるGaussianネットワークの新しいスコアリング基準（Renormalized Normalized Maximum Likelihood and Three-Part Code Criteria For Learning Gaussian Networks）</news:title>
   <news:publication_date>2026-06-25T20:04:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704820</loc>
  <lastmod>2026-06-25T19:13:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterにおけるトルコ語の固有表現認識の半教師あり埋め込み手法（Named Entity Recognition on Twitter for Turkish using Semi-supervised Learning with Word Embeddings）</news:title>
   <news:publication_date>2026-06-25T19:13:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704818</loc>
  <lastmod>2026-06-25T19:13:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測と制御のためのコップマン固有関数の最適構築（Optimal construction of Koopman eigenfunctions for prediction and control）</news:title>
   <news:publication_date>2026-06-25T19:13:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704816</loc>
  <lastmod>2026-06-25T19:12:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>素材認識に基づく3D局所記述子学習（Learning Material-Aware Local Descriptors for 3D Shapes）</news:title>
   <news:publication_date>2026-06-25T19:12:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704814</loc>
  <lastmod>2026-06-25T19:12:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジスティック回帰の条件数解析が示す実務的示唆（Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods）</news:title>
   <news:publication_date>2026-06-25T19:12:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704812</loc>
  <lastmod>2026-06-25T19:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ocean Tensor Packageの要点と経営視点での意味（The Ocean Tensor Package）</news:title>
   <news:publication_date>2026-06-25T19:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704810</loc>
  <lastmod>2026-06-25T19:11:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SL2MFによるがんにおける合成致死性の予測（SL2MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization）</news:title>
   <news:publication_date>2026-06-25T19:11:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704808</loc>
  <lastmod>2026-06-25T19:11:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>6自由度惑星着陸のための深層強化学習（Deep Reinforcement Learning for Six Degree-of-Freedom Planetary Powered Descent and Landing）</news:title>
   <news:publication_date>2026-06-25T19:11:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704806</loc>
  <lastmod>2026-06-25T18:20:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話から人物像を学習する注意型メモリネットワーク（Learning Personas from Dialogue with Attentive Memory Networks）</news:title>
   <news:publication_date>2026-06-25T18:20:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704804</loc>
  <lastmod>2026-06-25T18:20:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル不確実性推定による安全な強化学習（Safe Reinforcement Learning with Model Uncertainty Estimates）</news:title>
   <news:publication_date>2026-06-25T18:20:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704802</loc>
  <lastmod>2026-06-25T18:19:28Z</lastmod>
  <news:news>
   <news:publication>
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    <news:language>ja</news:language>
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   <news:title>ゲシュタルト理論から読み解く深層畳み込みネットワーク（Understanding Deep Convolutional Networks through Gestalt Theory）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>マルチタスク学習を活用した公平な分類の実現（Taking Advantage of Multitask Learning for Fair Classification）</news:title>
   <news:publication_date>2026-06-25T18:18:52Z</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>分子最適化を深層強化学習で行う（Optimization of Molecules via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-25T18:18:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>日常活動の音声認識を大規模埋め込みで学習する（Audio-Based Activities of Daily Living (ADL) Recognition with Large-Scale Acoustic Embeddings from Online Videos）</news:title>
   <news:publication_date>2026-06-25T18:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/704794</loc>
  <lastmod>2026-06-25T18:18:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ケーブルニュースにおける比喩的暴力の分類のためのニューラルネットワーク（A neural network to classify metaphorical violence on cable news）</news:title>
   <news:publication_date>2026-06-25T18:18:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-25T17:26:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>社会的影響を内発的動機付けとするマルチエージェント深層強化学習（Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-25T17:26:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボランティアコンピューティングにおけるエネルギー浪費削減に機械学習を使う（Using Machine Learning to reduce the energy wasted in Volunteer Computing Environments）</news:title>
   <news:publication_date>2026-06-25T17:26:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/704788</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ニューラルネットワーク活性化に対するサブセットスキャニング（Subset Scanning Over Neural Network Activations）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/704786</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>CLEVERの拡張：ニューラルネットワーク堅牢性評価アルゴリズムの拡張（ON EXTENSIONS OF CLEVER: A NEURAL NETWORK ROBUSTNESS EVALUATION ALGORITHM）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/704784</loc>
  <lastmod>2026-06-25T17:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OGLEサーベイで発見された高赤方偏移クエasar二件（Discovery of two quasars at z = 5 from the OGLE Survey）</news:title>
   <news:publication_date>2026-06-25T17:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/704782</loc>
  <lastmod>2026-06-25T17:25:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランキング評価における母集団・経験的PR曲線の扱い（Population and Empirical PR Curves to Assess Ranking Algorithms）</news:title>
   <news:publication_date>2026-06-25T17:25:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/704780</loc>
  <lastmod>2026-06-25T17:25:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速で頑健な複数ColorChecker検出法（Fast and Robust Multiple ColorChecker Detection using Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-25T17:25:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/704778</loc>
  <lastmod>2026-06-25T16:33:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的非同期システム向けモデル並列近接確率的勾配法（A Model Parallel Proximal Stochastic Gradient Algorithm for Partially Asynchronous Systems）</news:title>
   <news:publication_date>2026-06-25T16:33:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ニューラルネットワークにおけるバイアス・バリアンスの再考（A Modern Take on the Bias-Variance Tradeoff in Neural Networks）</news:title>
   <news:publication_date>2026-06-25T16:33:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/704774</loc>
  <lastmod>2026-06-25T16:32:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一参照拡張による夜間航空画像の都市検出（Detecting cities in aerial night-time images by learning structural invariants using single reference augmentation）</news:title>
   <news:publication_date>2026-06-25T16:32:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/704772</loc>
  <lastmod>2026-06-25T16:32:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>離れた区間から成る固有表現を学習する方法（Learning to Recognize Discontiguous Entities）</news:title>
   <news:publication_date>2026-06-25T16:32:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/704770</loc>
  <lastmod>2026-06-25T16:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>消費者の購買行動が示す概念組織（Conceptual Organization is Revealed by Consumer Activity Patterns）</news:title>
   <news:publication_date>2026-06-25T16:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704768</loc>
  <lastmod>2026-06-25T16:31:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>積演算を活性化関数として活用する手法（Leveraging Product as an Activation Function in Deep Networks）</news:title>
   <news:publication_date>2026-06-25T16:31:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704766</loc>
  <lastmod>2026-06-25T16:31:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限られた試行で自律的に歩行を獲得する腱駆動肢の学習（Autonomous Functional Locomotion in a Tendon-Driven Limb via Limited Experience）</news:title>
   <news:publication_date>2026-06-25T16:31:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/704764</loc>
  <lastmod>2026-06-25T15:40:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い専門家を増幅して強い学習者を監督する（Supervising strong learners by amplifying weak experts）</news:title>
   <news:publication_date>2026-06-25T15:40:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/704762</loc>
  <lastmod>2026-06-25T15:39:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的データアソシエーションのための深層人物再識別（Deep Person Re-identification for Probabilistic Data Association in Multiple Pedestrian Tracking）</news:title>
   <news:publication_date>2026-06-25T15:39:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704760</loc>
  <lastmod>2026-06-25T15:39:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lomax delegate racingによる生存分析の新展開（Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks）</news:title>
   <news:publication_date>2026-06-25T15:39:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704758</loc>
  <lastmod>2026-06-25T15:38:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公正さは誰のためか—ナッシュ福祉積による再定義（Fairness for Whom? Critically Reframing Fairness with Nash Welfare Product）</news:title>
   <news:publication_date>2026-06-25T15:38:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/704756</loc>
  <lastmod>2026-06-25T15:38:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>勾配ターゲット伝搬が示した学習則の一般化（Gradient Target Propagation）</news:title>
   <news:publication_date>2026-06-25T15:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/704754</loc>
  <lastmod>2026-06-25T15:38:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散医療データベースにおけるフェデレーテッドラーニングの実用性（Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data）</news:title>
   <news:publication_date>2026-06-25T15:38:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/704752</loc>
  <lastmod>2026-06-25T15:38:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形積分微分作用素の回帰とニューラルネットワーク（Nonlinear integro–differential operator regression with neural networks）</news:title>
   <news:publication_date>2026-06-25T15:38:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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