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   <news:title>DeepLens: 単一画像から生成する浅い被写界深度（DeepLens: Shallow Depth Of Field From A Single Image）</news:title>
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   <news:title>ノイズあり回折パターンからの辞書学習位相回復（Dictionary Learning Phase Retrieval from Noisy Diffraction Patterns）</news:title>
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   <news:title>矮小銀河の星形成履歴を復元する新手法（A new method to derive star formation histories in dwarf galaxies）</news:title>
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   <news:title>ヘリウム濃厚な準矮星O型星の可視・紫外スペクトルに対する定量的NLTE解析（A quantitative NLTE analysis of visual and ultraviolet spectra of four helium-rich subdwarf O stars）</news:title>
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   <news:title>平均後悔率を最小化する集合の探索（Finding Average Regret Ratio Minimizing Set in Database）</news:title>
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    <news:language>ja</news:language>
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   <news:title>ディスコースの文体装飾を学ぶ（Discourse Embellishment Using a Deep Encoder-Decoder Network）</news:title>
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    <news:language>ja</news:language>
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   <news:title>不完全な通信の数学理論とエネルギー効率性（A mathematical theory of imperfect communication: Energy efficiency considerations in multi-level coding）</news:title>
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    <news:language>ja</news:language>
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   <news:title>深層ReLUネットワークの適応性と次元の呪い回避（ADAPTIVITY OF DEEP RELU NETWORK FOR LEARNING IN BESOV AND MIXED SMOOTH BESOV SPACES）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>スマホ撮影画像における光学フォント認識と本人証明書偽造検出への応用（Optical Font Recognition in Smartphone-Captured Images, and its Applicability for ID Forgery Detection）</news:title>
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   <news:title>変分ノイズ対比推定の実務的意義（Variational Noise-Contrastive Estimation）</news:title>
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   <news:title>単一イオン量子ビットの高速・高忠実読み出しを機械学習で実現する（Fast and High-Fidelity Readout of Single Trapped-Ion Qubit via Machine Learning Methods）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>粒子衝突データの「雑音」除去が変わる——グラフニューラルネットワークによるパイルアップ緩和（Pileup mitigation at the Large Hadron Collider with Graph Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-25T01:58:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>浅潜から学ぶ深層学習：水中物体検出のためのソナー画像生成と訓練 (Deep Learning from Shallow Dives: Sonar Image Generation and Training for Underwater Object Detection)</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-25T01:06:07Z</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>カテゴリ別把持のための形状空間レジストレーションを通じた姿勢シナジー学習（Learning Postural Synergies for Categorical Grasping through Shape Space Registration）</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>LeukoNet: DCTベースのCNNによるB-ALL細胞分類（LEUKONET: DCT-BASED CNN ARCHITECTURE FOR THE CLASSIFICATION OF NORMAL VERSUS LEUKEMIC BLASTS IN B-ALL CANCER）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>観測誤差が因果探索に与える影響と上界推定による補正手法（An Upper Bound for Random Measurement Error in Causal Discovery）</news:title>
   <news:publication_date>2026-06-25T01:05:24Z</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>階層的マルチラベル分類における決定戦略と局所適合率（HIERLPR: DECISION MAKING IN HIERARCHICAL MULTI-LABEL CLASSIFICATION WITH LOCAL PRECISION RATES）</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>S-Net: JPEG圧縮アーティファクト削減のためのスケーラブルCNN（S-Net: A Scalable Convolutional Neural Network for JPEG Compression Artifact Reduction）</news:title>
   <news:publication_date>2026-06-25T01:04:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>教師なしニューラル文簡易化の実践（Unsupervised Neural Text Simplification）</news:title>
   <news:publication_date>2026-06-25T01:04:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>畳み込みニューラルネットワークによる乱流混合燃焼モデル化（Modelling turbulent premixed flames using convolutional neural networks）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-25T00:13:00Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ランダム化ベンチマーキングからのスピンキュービットノイズ分光（Spin-qubit noise spectroscopy from randomized benchmarking by supervised learning）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>スマートシティにおけるリアルタイム高精細大気質センシングネットワーク（Real-Time Fine-Grained Air Quality Sensing Networks in Smart City: Design, Implementation and Optimization）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-25T00:09:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>入力変数の影響を情報理論で解く：エントロピック変数射影による機械学習説明（Explaining machine learning models using entropic variable projection）</news:title>
   <news:publication_date>2026-06-25T00:09:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-25T00:08:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>合成画像から実世界の視線推定へ橋を架ける手法（Unsupervised Domain Adaptation for Learning Eye Gaze from a Million Synthetic Images: An Adversarial Approach）</news:title>
   <news:publication_date>2026-06-25T00:08:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-25T00:07:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>高次元におけるロバストスパース縮約ランク回帰（Robust Sparse Reduced Rank Regression in High Dimensions）</news:title>
   <news:publication_date>2026-06-25T00:07:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-25T00:07:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス均衡自己学習によるセマンティックセグメンテーションのドメイン適応（Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training）</news:title>
   <news:publication_date>2026-06-25T00:07:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-25T00:07:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深海面波におけるソリトンと極端事象の共存（Coexistence of solitons and extreme events in deep water surface waves）</news:title>
   <news:publication_date>2026-06-25T00:07:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/704503</loc>
  <lastmod>2026-06-24T23:15:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗号化トラフィック分類における深層学習の概観（Deep Learning for Encrypted Traffic Classification: An Overview）</news:title>
   <news:publication_date>2026-06-24T23:15:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/704501</loc>
  <lastmod>2026-06-24T23:15:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WikiHow: 大規模テキスト要約データセットの重要性（WikiHow: A Large Scale Text Summarization Dataset）</news:title>
   <news:publication_date>2026-06-24T23:15:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/704499</loc>
  <lastmod>2026-06-24T23:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測環境におけるポリシー勾配：近似と収束（Policy Gradient in Partially Observable Environments: Approximation and Convergence）</news:title>
   <news:publication_date>2026-06-24T23:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/704497</loc>
  <lastmod>2026-06-24T23:14:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>テスト時拡張を用いた畳み込みニューラルネットワークによる自動脳腫瘍セグメンテーション (Automatic Brain Tumor Segmentation using Convolutional Neural Networks with Test-Time Augmentation)</news:title>
   <news:publication_date>2026-06-24T23:14:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-24T23:13:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何光学極限におけるレンズ化重力波の分類を機械学習で行う（Classifying Lensed Gravitational Waves in the Geometrical Optics Limit with Machine Learning）</news:title>
   <news:publication_date>2026-06-24T23:13:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/704493</loc>
  <lastmod>2026-06-24T23:13:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光ナノ構造の最適設計を強化学習で探る（Finding the best design parameters for optical nanostructures using reinforcement learning）</news:title>
   <news:publication_date>2026-06-24T23:13:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/704491</loc>
  <lastmod>2026-06-24T23:13:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークの可視化と解釈（Analyzing and Interpreting Convolutional Neural Networks in NLP）</news:title>
   <news:publication_date>2026-06-24T23:13:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704489</loc>
  <lastmod>2026-06-24T22:22:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通信・ネットワークにおける深層強化学習の応用（Applications of Deep Reinforcement Learning in Communications and Networking: A Survey）</news:title>
   <news:publication_date>2026-06-24T22:22:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704487</loc>
  <lastmod>2026-06-24T22:22:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己組織化テンソル構造によるマルチビュークラスタリング（A Self-Organizing Tensor Architecture for Multi-View Clustering）</news:title>
   <news:publication_date>2026-06-24T22:22:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704485</loc>
  <lastmod>2026-06-24T22:21:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理教育における計算導入を促す要因の特定（Identifying features predictive of faculty integrating computation into physics courses）</news:title>
   <news:publication_date>2026-06-24T22:21:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704483</loc>
  <lastmod>2026-06-24T22:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EdgeSpeechNets：エッジ端末向け高効率音声認識ネットワーク（EdgeSpeechNets: Highly Efficient Deep Neural Networks for Speech Recognition on the Edge）</news:title>
   <news:publication_date>2026-06-24T22:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704481</loc>
  <lastmod>2026-06-24T22:20:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチバンド銀河形態分類の転移学習（Multiband galaxy morphologies for CLASH: a convolutional neural network transferred from CANDELS）</news:title>
   <news:publication_date>2026-06-24T22:20:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704479</loc>
  <lastmod>2026-06-24T22:20:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元シンプレックス学習によるアンミキシング問題の再考（On Statistical Learning of Simplices: Unmixing Problem Revisited）</news:title>
   <news:publication_date>2026-06-24T22:20:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704477</loc>
  <lastmod>2026-06-24T22:20:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズの多いデータの分散kクラスタリング（Distributed k-Clustering for Data with Heavy Noise）</news:title>
   <news:publication_date>2026-06-24T22:20:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704475</loc>
  <lastmod>2026-06-24T21:28:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核反応におけるクォーク・グルーオンの硬散乱とスケーリング（Hard Breakup and Spin in QCD）</news:title>
   <news:publication_date>2026-06-24T21:28:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704473</loc>
  <lastmod>2026-06-24T21:28:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心音記録の正常/異常分類をめぐる実務的視点（Classification of Normal/Abnormal Heart Sound Recordings based on Multi-Domain Features and Back Propagation Neural Network）</news:title>
   <news:publication_date>2026-06-24T21:28:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704471</loc>
  <lastmod>2026-06-24T21:27:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wasserstein変換（The Wasserstein Transform）</news:title>
   <news:publication_date>2026-06-24T21:27:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704469</loc>
  <lastmod>2026-06-24T21:27:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さなReLUネットワークは強力な記憶装置である（Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity）</news:title>
   <news:publication_date>2026-06-24T21:27:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704467</loc>
  <lastmod>2026-06-24T21:27:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期性に着目した並列時系列予測アルゴリズム（A Periodicity-based Parallel Time Series Prediction Algorithm in Cloud Computing Environments）</news:title>
   <news:publication_date>2026-06-24T21:27:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704465</loc>
  <lastmod>2026-06-24T21:26:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模PPIネットワークにおけるマルチソース学習を用いた並列タンパク質コミュニティ検出（Parallel Protein Community Detection in Large-scale PPI Networks Based on Multi-source Learning）</news:title>
   <news:publication_date>2026-06-24T21:26:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704463</loc>
  <lastmod>2026-06-24T21:26:44Z</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完全分散価値関数学習と線形収束の保証（Multi-Agent Fully Decentralized Value Function Learning with Linear Convergence Rates）</news:title>
   <news:publication_date>2026-06-24T21:26:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704461</loc>
  <lastmod>2026-06-24T20:35:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルにおけるオブジェクト構成性の検証（INVESTIGATING OBJECT COMPOSITIONALITY IN GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-06-24T20:35:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704459</loc>
  <lastmod>2026-06-24T20:35:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビッグデータマイニングとクラウドコンピューティングに基づく疾病診断・治療推奨システム（A Disease Diagnosis and Treatment Recommendation System Based on Big Data Mining and Cloud Computing）</news:title>
   <news:publication_date>2026-06-24T20:35:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704457</loc>
  <lastmod>2026-06-24T20:34:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼できないネットワーク上の分散学習（Distributed Learning over Unreliable Networks）</news:title>
   <news:publication_date>2026-06-24T20:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704455</loc>
  <lastmod>2026-06-24T20:33:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳構造の体積的形状表現を学習する畳み込みオートエンコーダ法（A Convolutional Autoencoder Approach to Learn Volumetric Shape Representations for Brain Structures）</news:title>
   <news:publication_date>2026-06-24T20:33:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704453</loc>
  <lastmod>2026-06-24T20:33:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PepCVAEによる抗菌ペプチド設計の半教師あり生成（PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Molecules）</news:title>
   <news:publication_date>2026-06-24T20:33:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704451</loc>
  <lastmod>2026-06-24T20:33:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模畳み込みニューラルネットワークのための二層並列学習アーキテクチャ（A Bi-layered Parallel Training Architecture for Large-scale Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-24T20:33:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704449</loc>
  <lastmod>2026-06-24T20:33:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UCR時系列アーカイブの拡張と実務的示唆（The UCR Time Series Archive）</news:title>
   <news:publication_date>2026-06-24T20:33:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704447</loc>
  <lastmod>2026-06-24T19:42:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と教えることでロボットが学ぶ映像物体分割（Video Object Segmentation using Teacher-Student Adaptation in a Human Robot Interaction (HRI) Setting）</news:title>
   <news:publication_date>2026-06-24T19:42:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704445</loc>
  <lastmod>2026-06-24T19:41:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>mass-Peak Patch法による高速ダークマターハローカタログ生成（The mass-Peak Patch algorithm for fast generation of deep all-sky dark matter halo catalogues and its N-Body validation）</news:title>
   <news:publication_date>2026-06-24T19:41:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704443</loc>
  <lastmod>2026-06-24T19:41:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロ次近接法による非凸非滑らか制約最適化の実務的示唆（A Proximal Zeroth-Order Algorithm for Nonconvex Nonsmooth Problems）</news:title>
   <news:publication_date>2026-06-24T19:41:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704441</loc>
  <lastmod>2026-06-24T19:40:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い線形ネットワークの損失地形を代数幾何学の視点で見る（The Loss Surface Of Deep Linear Networks Viewed Through The Algebraic Geometry Lens）</news:title>
   <news:publication_date>2026-06-24T19:40:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704439</loc>
  <lastmod>2026-06-24T19:40:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河団のX線質量推定に対する深層学習アプローチ（A Deep Learning Approach to Galaxy Cluster X-ray Masses）</news:title>
   <news:publication_date>2026-06-24T19:40:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704437</loc>
  <lastmod>2026-06-24T19:40:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RIn-Close CVC2による数値データのビクラスタ列挙の効率化（RIn-Close CVC2: an even more efficient enumerative algorithm for biclustering of numerical datasets）</news:title>
   <news:publication_date>2026-06-24T19:40:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704435</loc>
  <lastmod>2026-06-24T19:40:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深共晶溶媒がリン脂質単分子層の構造に与える影響のベイズ的解析（Bayesian determination of the effect of a deep eutectic solvent on the structure of lipid monolayers）</news:title>
   <news:publication_date>2026-06-24T19:40:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704433</loc>
  <lastmod>2026-06-24T18:49:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分最小二乗による深層ネットワークの剪定（Pruning Deep Networks using Partial Least Squares）</news:title>
   <news:publication_date>2026-06-24T18:49:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704431</loc>
  <lastmod>2026-06-24T18:49:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライベートデータ商用化に対する逆張り契約設計（Adversarial Contract Design for Private Data Commercialization）</news:title>
   <news:publication_date>2026-06-24T18:49:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704429</loc>
  <lastmod>2026-06-24T18:48:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構の解析：ニューラル機械翻訳における語義曖昧性の検討（An Analysis of Attention Mechanisms: The Case of Word Sense Disambiguation in Neural Machine Translation）</news:title>
   <news:publication_date>2026-06-24T18:48:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704427</loc>
  <lastmod>2026-06-24T18:47:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>年齢不変顔認識のための直交深層特徴分解（Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition）</news:title>
   <news:publication_date>2026-06-24T18:47:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704425</loc>
  <lastmod>2026-06-24T18:47:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユニタリー不変な低ランク誘導ノルムの近接写像計算の効率化（Efficient Proximal Mapping Computation for Unitarily Invariant Low-Rank Inducing Norms）</news:title>
   <news:publication_date>2026-06-24T18:47:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704423</loc>
  <lastmod>2026-06-24T18:47:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミルザハニの地震流に関する研究（Mirzakhani’s Work on Earthquake Flow）</news:title>
   <news:publication_date>2026-06-24T18:47:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704421</loc>
  <lastmod>2026-06-24T18:47:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-24T18:47:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/704419</loc>
  <lastmod>2026-06-24T17:55:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経路ベースの非線形拡張率とラグランジュ不確実性の指標（Measures of Path-Based Nonlinear Expansion Rates and Lagrangian Uncertainty in Stochastic Flows）</news:title>
   <news:publication_date>2026-06-24T17:55:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704417</loc>
  <lastmod>2026-06-24T17:55:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳幼児の自由運動から学ぶ3D身体形状と追跡（Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences）</news:title>
   <news:publication_date>2026-06-24T17:55:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704415</loc>
  <lastmod>2026-06-24T17:55:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識ベース補完の評価を問い直す（On Evaluating Embedding Models for Knowledge Base Completion）</news:title>
   <news:publication_date>2026-06-24T17:55:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704413</loc>
  <lastmod>2026-06-24T17:54:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホログラフィックPomeronによる高エネルギー散乱の解析（DIS at small x and hadron-hadron scattering at high energies via the holographic Pomeron exchange）</news:title>
   <news:publication_date>2026-06-24T17:54:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704411</loc>
  <lastmod>2026-06-24T17:54:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLUネットワークの証明可能な堅牢性の向上（Provable Robustness of ReLU networks via Maximization of Linear Regions）</news:title>
   <news:publication_date>2026-06-24T17:54:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704409</loc>
  <lastmod>2026-06-24T17:54:23Z</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>2026-06-24T17:54:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704407</loc>
  <lastmod>2026-06-24T17:53:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ編集距離とトリプレットネットワークを組み合わせたオフライン署名認証（Offline Signature Verification by Combining Graph Edit Distance and Triplet Networks）</news:title>
   <news:publication_date>2026-06-24T17:53:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704405</loc>
  <lastmod>2026-06-24T17:03:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>矮小銀河レオAにおける星団と若い恒星集団（Star clusters and young populations in the dwarf irregular galaxy Leo A）</news:title>
   <news:publication_date>2026-06-24T17:03:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704403</loc>
  <lastmod>2026-06-24T17:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>矮小銀河レオAの明るい赤色星が示すもの（Bright-red stars in the dwarf irregular galaxy Leo A）</news:title>
   <news:publication_date>2026-06-24T17:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704401</loc>
  <lastmod>2026-06-24T17:02:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的モーメント法の実務的意義（Hierarchical Methods of Moments）</news:title>
   <news:publication_date>2026-06-24T17:02:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704399</loc>
  <lastmod>2026-06-24T17:01:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マゼラン系の三次元構造をOGLE変光星で解く（OGLE-ing the Magellanic System: Three-Dimensional Structure）</news:title>
   <news:publication_date>2026-06-24T17:01:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704397</loc>
  <lastmod>2026-06-24T17:01:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震の頻度―大きさ分布を一般化する非対称ラプラス混合モデル（Generalized Earthquake Frequency-Magnitude Distribution Described by Asymmetric Laplace Mixture Modelling）</news:title>
   <news:publication_date>2026-06-24T17:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704395</loc>
  <lastmod>2026-06-24T17:01:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>染色不変なCNNの学習戦略（STRATEGIES FOR TRAINING STAIN INVARIANT CNNS）</news:title>
   <news:publication_date>2026-06-24T17:01:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704393</loc>
  <lastmod>2026-06-24T17:01:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CADモデルのリバースエンジニアリング（Reverse engineering of CAD models via clustering and approximate implicitization）</news:title>
   <news:publication_date>2026-06-24T17:01:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704391</loc>
  <lastmod>2026-06-24T16:09:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRI取得差を吸収する表現の学習（LEARNING AN MR ACQUISITION-INVARIANT REPRESENTATION USING SIAMESE NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-24T16:09:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704389</loc>
  <lastmod>2026-06-24T16:08:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測データのバイアスを是正する敵対的重み付け（Adversarial Balancing for Causal Inference）</news:title>
   <news:publication_date>2026-06-24T16:08:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704387</loc>
  <lastmod>2026-06-24T15:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注視点のHMM推定誤差と必要サンプル数（EMHMM Simulation Study）</news:title>
   <news:publication_date>2026-06-24T15:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704385</loc>
  <lastmod>2026-06-24T15:59:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺気腫の範囲を定量化する学習：どのようなラベルが必要か（Learning to quantify emphysema extent: What labels do we need?）</news:title>
   <news:publication_date>2026-06-24T15:59:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704383</loc>
  <lastmod>2026-06-24T15:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列時系列ニューラル符号化ネットワーク（Parallel Temporal Neural Coding Network）</news:title>
   <news:publication_date>2026-06-24T15:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704381</loc>
  <lastmod>2026-06-24T15:58:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表情認識における一貫性制約（Coherence Constraints in Facial Expression Recognition）</news:title>
   <news:publication_date>2026-06-24T15:58:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704379</loc>
  <lastmod>2026-06-24T15:58:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>温熱ネットワークのデータ駆動型同定（Data-driven identification of a thermal network in multi-zone building）</news:title>
   <news:publication_date>2026-06-24T15:58:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704377</loc>
  <lastmod>2026-06-24T15:06:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的バイオメトリック特徴の認識（Recognizing Partial Biometric Patterns）</news:title>
   <news:publication_date>2026-06-24T15:06:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704375</loc>
  <lastmod>2026-06-24T15:05:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>鉄道事故の記述解析に深層学習を用いる意義（Analysis of Railway Accidents’ Narratives Using Deep Learning）</news:title>
   <news:publication_date>2026-06-24T15:05:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704373</loc>
  <lastmod>2026-06-24T15:05:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子上のハイブリッド物質波—マイクロ波ソリトン（Hybrid matter-wave - microwave solitons on the lattice）</news:title>
   <news:publication_date>2026-06-24T15:05:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704371</loc>
  <lastmod>2026-06-24T15:04:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化ゼロショット学習のための合成空間学習（Learning the Compositional Spaces for Generalized Zero-shot Learning）</news:title>
   <news:publication_date>2026-06-24T15:04:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704369</loc>
  <lastmod>2026-06-24T15:04:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテキスト付きバンディットにおける単純後悔最小化（Simple Regret Minimization for Contextual Bandits）</news:title>
   <news:publication_date>2026-06-24T15:04:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704367</loc>
  <lastmod>2026-06-24T15:04:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セファイドとRRラエイの時系列解析が示す新たな物理制約（Time-series analyses of Cepheid and RR Lyrae variables）</news:title>
   <news:publication_date>2026-06-24T15:04:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704365</loc>
  <lastmod>2026-06-24T15:04:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>漸進的重みプルーニングによる深層ニューラルネットワークの高率圧縮（PROGRESSIVE WEIGHT PRUNING OF DEEP NEURAL NETWORKS USING ADMM）</news:title>
   <news:publication_date>2026-06-24T15:04:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704363</loc>
  <lastmod>2026-06-24T14:12:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復収束型機械学習におけるフォールトトレランス（Fault Tolerance in Iterative-Convergent Machine Learning）</news:title>
   <news:publication_date>2026-06-24T14:12:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704361</loc>
  <lastmod>2026-06-24T14:12:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化オラクルを持つ非凸ゲーム学習の進展（Learning in Non-convex Games with an Optimization Oracle）</news:title>
   <news:publication_date>2026-06-24T14:12:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704359</loc>
  <lastmod>2026-06-24T14:11:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高エネルギーニュートリノと核反応の理解（High-energy neutrino-nucleus interactions）</news:title>
   <news:publication_date>2026-06-24T14:11:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704357</loc>
  <lastmod>2026-06-24T14:10:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Diabetologist（Deep Diabetologist: Learning to Prescribe Hypoglycemia Medications with Hierarchical Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-24T14:10:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704355</loc>
  <lastmod>2026-06-24T14:10:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム行列の小偏差不等式が示すもの（Small-Deviation Inequalities for Sums of Random Matrices）</news:title>
   <news:publication_date>2026-06-24T14:10:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704353</loc>
  <lastmod>2026-06-24T14:10:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>球面三角アルゴリズム：凸包メンバーシップ問合せの高速オラクル（Spherical Triangle Algorithm: A Fast Oracle for Convex Hull Membership Queries）</news:title>
   <news:publication_date>2026-06-24T14:10:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704351</loc>
  <lastmod>2026-06-24T14:10:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律的深層学習：動的環境の継続学習アプローチ（Autonomous Deep Learning: Continual Learning Approach for Dynamic Environments）</news:title>
   <news:publication_date>2026-06-24T14:10:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704349</loc>
  <lastmod>2026-06-24T13:18:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフカーネルと能動学習による分子の原子化エネルギー予測（Prediction of Atomization Energy Using Graph Kernel and Active Learning）</news:title>
   <news:publication_date>2026-06-24T13:18:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704347</loc>
  <lastmod>2026-06-24T13:17:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文ベクトル空間の探究と自動要約への応用（Exploring Sentence Vector Spaces through Automatic Summarization）</news:title>
   <news:publication_date>2026-06-24T13:17:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704345</loc>
  <lastmod>2026-06-24T13:17:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短い発話に強い話者認証のためのi-vectorマッピング（Deep neural network based i-vector mapping for speaker verification using short utterances）</news:title>
   <news:publication_date>2026-06-24T13:17:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704343</loc>
  <lastmod>2026-06-24T13:16:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SCALE-Simによるシストリック配列CNNアクセラレータ評価（SCALE-SIM: Systolic CNN Accelerator Simulator）</news:title>
   <news:publication_date>2026-06-24T13:16:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704341</loc>
  <lastmod>2026-06-24T13:16:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReDMark: 残差拡散フレームワークによるウォーターマーキング（ReDMark: Framework for Residual Diffusion）</news:title>
   <news:publication_date>2026-06-24T13:16:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704339</loc>
  <lastmod>2026-06-24T13:16:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインマルコフ復号の近似アルゴリズムと下限（Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms）</news:title>
   <news:publication_date>2026-06-24T13:16:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704337</loc>
  <lastmod>2026-06-24T13:15:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルマップ（Deep Neural Maps）</news:title>
   <news:publication_date>2026-06-24T13:15:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704335</loc>
  <lastmod>2026-06-24T12:24:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクロブログにおける自動イベント検出と増分学習（Automatic Event Detection in Microblogs using Incremental Machine Learning）</news:title>
   <news:publication_date>2026-06-24T12:24:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704333</loc>
  <lastmod>2026-06-24T12:23:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンハンサー関連転写因子結合の同定に向けた「signed iterative random forests（siRF）」の意義（Signed iterative random forests to identify enhancer-associated transcription factor binding）</news:title>
   <news:publication_date>2026-06-24T12:23:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704331</loc>
  <lastmod>2026-06-24T12:23:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過剰パラメータ化モデルにおけるSGDの高速収束（Fast and Faster Convergence of SGD for Over-Parameterized Models）</news:title>
   <news:publication_date>2026-06-24T12:23:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704329</loc>
  <lastmod>2026-06-24T12:22:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒト皮質における集団的抑制と興奮（Ensemble Inhibition and Excitation in the Human Cortex: an Ising Model Analysis with Uncertainties）</news:title>
   <news:publication_date>2026-06-24T12:22:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704327</loc>
  <lastmod>2026-06-24T12:22:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の反応速度で行う深層強化学習（At Human Speed: Deep Reinforcement Learning with Action Delay）</news:title>
   <news:publication_date>2026-06-24T12:22:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704325</loc>
  <lastmod>2026-06-24T12:22:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的差分プライバシー下の最適推定に関する考察（Optimal locally private estimation under ℓp loss for 1 ≤ p ≤ 2）</news:title>
   <news:publication_date>2026-06-24T12:22:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704323</loc>
  <lastmod>2026-06-24T12:22:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習における状態の「重要度（クリティカリティ）」の概念（The Concept of Criticality in Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-24T12:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704321</loc>
  <lastmod>2026-06-24T11:30:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Reduced-Gate Convolutional LSTM を用いた予測符号化による時空間予測（Reduced-Gate Convolutional LSTM Using Predictive Coding for Spatiotemporal Prediction）</news:title>
   <news:publication_date>2026-06-24T11:30:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704319</loc>
  <lastmod>2026-06-24T11:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AutoGraph：グラフベースの性能を備えた命令型スタイルのコーディング（AutoGraph: Imperative-Style Coding with Graph-Based Performance）</news:title>
   <news:publication_date>2026-06-24T11:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704317</loc>
  <lastmod>2026-06-24T11:30:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運動学と環境文脈を統合した逆強化学習によるオフロード車両軌跡予測（Integrating kinematics and environment context into deep inverse reinforcement learning for predicting off-road vehicle trajectories）</news:title>
   <news:publication_date>2026-06-24T11:30:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704315</loc>
  <lastmod>2026-06-24T11:29:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的な少数ショット学習と注意アトラクターネットワーク（Incremental Few-Shot Learning with Attention Attractor Networks）</news:title>
   <news:publication_date>2026-06-24T11:29:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704313</loc>
  <lastmod>2026-06-24T11:29:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間一次差分による横断面の不可観測ヘテロ接収の扱い（Accounting for Unobservable Heterogeneity in Cross Section Using Spatial First Differences）</news:title>
   <news:publication_date>2026-06-24T11:29:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704311</loc>
  <lastmod>2026-06-24T11:29:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>映像と文章を階層的に結び付ける手法の要点（Cross-Modal and Hierarchical Modeling of Video and Text）</news:title>
   <news:publication_date>2026-06-24T11:29:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704309</loc>
  <lastmod>2026-06-24T11:28:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的生成モデルによる制御可能な音声合成（Hierarchical Generative Modeling for Controllable Speech Synthesis）</news:title>
   <news:publication_date>2026-06-24T11:28:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704307</loc>
  <lastmod>2026-06-24T10:37:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実務者視点の不均衡データ対策の実証的評価（An empirical evaluation of imbalanced data strategies from a practitioner&amp;#039;s point of view）</news:title>
   <news:publication_date>2026-06-24T10:37:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704305</loc>
  <lastmod>2026-06-24T10:37:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォールトトレラント量子計算のための強化学習デコーダ（Reinforcement Learning Decoders for Fault-Tolerant Quantum Computation）</news:title>
   <news:publication_date>2026-06-24T10:37:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704303</loc>
  <lastmod>2026-06-24T10:37:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブサンプリングを用いたラインサーチ法の第二次保証（A Subsampling Line-Search Method with Second-Order Results）</news:title>
   <news:publication_date>2026-06-24T10:37:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704301</loc>
  <lastmod>2026-06-24T10:36:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光を使った物理的攻撃が示す脆弱性（Projecting Trouble: Light Based Adversarial Attacks on Deep Learning Classifiers）</news:title>
   <news:publication_date>2026-06-24T10:36:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704299</loc>
  <lastmod>2026-06-24T10:36:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形回帰モデルにおける差別的プロキシの探索（Hunting for Discriminatory Proxies in Linear Regression Models）</news:title>
   <news:publication_date>2026-06-24T10:36:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704297</loc>
  <lastmod>2026-06-24T10:36:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合可能な行動条件予測器（Composable Action-Conditioned Predictors）</news:title>
   <news:publication_date>2026-06-24T10:36:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704295</loc>
  <lastmod>2026-06-24T10:36:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程によるデータアソシエーション（Data Association with Gaussian Processes）</news:title>
   <news:publication_date>2026-06-24T10:36:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704293</loc>
  <lastmod>2026-06-24T09:45:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多体系SU(N)対称性をもつ超冷却フェルミン原子の有効相互作用（Effective multi-body SU(N)-symmetric interactions of ultracold fermionic atoms on a 3-D lattice）</news:title>
   <news:publication_date>2026-06-24T09:45:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704291</loc>
  <lastmod>2026-06-24T09:44:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さなデータで効くサブワード・セマンティックハッシング（Subword Semantic Hashing for Intent Classification on Small Datasets）</news:title>
   <news:publication_date>2026-06-24T09:44:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704289</loc>
  <lastmod>2026-06-24T09:44:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メトロポリス・ヘイスティングス視点から見た変分推論と敵対的訓練（Metropolis-Hastings View on Variational Inference and Adversarial Training）</news:title>
   <news:publication_date>2026-06-24T09:44:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704287</loc>
  <lastmod>2026-06-24T09:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>過学習とは違う「記憶化」——過パラメータ化オートエンコーダの挙動を読み解く (Memorization in Overparameterized Autoencoders)</news:title>
   <news:publication_date>2026-06-24T09:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704285</loc>
  <lastmod>2026-06-24T09:43:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深宇宙電波連続波調査の新しいパラメータ空間（New Parameter Space for Deep Field Radio Continuum Surveys）</news:title>
   <news:publication_date>2026-06-24T09:43:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704283</loc>
  <lastmod>2026-06-24T09:42:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共変量による影響を考慮した精度行列の共同非パラメトリック推定（Joint Nonparametric Precision Matrix Estimation with Confounding）</news:title>
   <news:publication_date>2026-06-24T09:42:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704281</loc>
  <lastmod>2026-06-24T09:42:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習と統計モデルによるデータ品質改善（Improving Data Quality Through Deep Learning and Statistical Models）</news:title>
   <news:publication_date>2026-06-24T09:42:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704279</loc>
  <lastmod>2026-06-24T08:50:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KPZ方程式の裾野確率と一般初期データ（KPZ equation tails for general initial data）</news:title>
   <news:publication_date>2026-06-24T08:50:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704277</loc>
  <lastmod>2026-06-24T08:50:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元可変インデックス係数モデルとSteinの恒等式（High-dimensional Varying Index Coefficient Models via Stein’s Identity）</news:title>
   <news:publication_date>2026-06-24T08:50:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704275</loc>
  <lastmod>2026-06-24T08:50:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CoNLL–SIGMORPHON 2018 共有タスク：普遍的形態素再帰生成の意義（The CoNLL–SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection）</news:title>
   <news:publication_date>2026-06-24T08:50:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704273</loc>
  <lastmod>2026-06-24T08:49:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分学習による抽象的離散プランニング領域と連続的観測への写像（Incremental learning abstract discrete planning domains and mappings to continuous perceptions）</news:title>
   <news:publication_date>2026-06-24T08:49:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704271</loc>
  <lastmod>2026-06-24T08:49:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビデオ顕著領域検出における深層非局所ニューラルネットワーク（Salient Object Detection in Video using Deep Non-Local Neural Networks）</news:title>
   <news:publication_date>2026-06-24T08:49:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704269</loc>
  <lastmod>2026-06-24T08:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大量の模倣学習用ロボット実演データを作る（Multiple Interactions Made Easy (MIME): Large Scale Demonstrations Data for Imitation）</news:title>
   <news:publication_date>2026-06-24T08:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704267</loc>
  <lastmod>2026-06-24T08:49:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビザンチン耐性を備えた分散状態推定の有限時間保証（Finite-time Guarantees for Byzantine-Resilient Distributed State Estimation with Noisy Measurements）</news:title>
   <news:publication_date>2026-06-24T08:49:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704265</loc>
  <lastmod>2026-06-24T07:57:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>INFODENS: テキスト表現学習のためのオープンフレームワーク（INFODENS: An Open-source Framework for Learning Text Representations）</news:title>
   <news:publication_date>2026-06-24T07:57:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704263</loc>
  <lastmod>2026-06-24T07:57:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模出力空間における負例の確率的選別（Stochastic Negative Mining for Learning with Large Output Spaces）</news:title>
   <news:publication_date>2026-06-24T07:57:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704261</loc>
  <lastmod>2026-06-24T07:57:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1次元と2次元の深層畳み込みニューラルネットワークによる心電図分類の比較（A Comparison of 1-D and 2-D Deep Convolutional Neural Networks in ECG Classification）</news:title>
   <news:publication_date>2026-06-24T07:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704259</loc>
  <lastmod>2026-06-24T07:56:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半包絡的深部散乱における縦二重スピン非対称性（Longitudinal double-spin asymmetries in semi-inclusive deep-inelastic scattering）</news:title>
   <news:publication_date>2026-06-24T07:56:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704257</loc>
  <lastmod>2026-06-24T07:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈情報融合構造を備えた多段階フレームワークによる皮膚病変分割（A MULTI-STAGE FRAMEWORK WITH CONTEXT INFORMATION FUSION STRUCTURE FOR SKIN LESION SEGMENTATION）</news:title>
   <news:publication_date>2026-06-24T07:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704255</loc>
  <lastmod>2026-06-24T07:56:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疎検出に適応するサブバンド適応フィルタの罰則付き学習（Study of Sparsity-Aware Subband Adaptive Filtering Algorithms with Adjustable Penalties）</news:title>
   <news:publication_date>2026-06-24T07:56:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704253</loc>
  <lastmod>2026-06-24T07:55:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Shallow-Deep Networksによる過考の可視化と対策（Shallow-Deep Networks: Understanding and Mitigating Network Overthinking）</news:title>
   <news:publication_date>2026-06-24T07:55:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704251</loc>
  <lastmod>2026-06-24T07:04:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己誘導型で密なアノテーションを生成する弱教師ありセマンティックセグメンテーション（Generating Self-Guided Dense Annotations for Weakly Supervised Semantic Segmentation）</news:title>
   <news:publication_date>2026-06-24T07:04:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704249</loc>
  <lastmod>2026-06-24T07:04:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースフィア埋め込みの内向きスケーリング学習（LEARNING INWARD SCALED HYPERSPHERE EMBEDDING: EXPLORING PROJECTIONS IN HIGHER DIMENSIONS）</news:title>
   <news:publication_date>2026-06-24T07:04:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704247</loc>
  <lastmod>2026-06-24T07:03:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非平滑複合問題に対する効率的な貪欲座標降下（Efficient Greedy Coordinate Descent for Composite Problems）</news:title>
   <news:publication_date>2026-06-24T07:03:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704245</loc>
  <lastmod>2026-06-24T07:02:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SCPNetによる全体と部分の人物再識別の統合（SCPNet: Spatial-Channel Parallelism Network for Joint Holistic and Partial Person Re-Identification）</news:title>
   <news:publication_date>2026-06-24T07:02:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704243</loc>
  <lastmod>2026-06-24T07:02:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集団に接近するロボットの社会的行動学習（Learning Socially Appropriate Robot Approaching Behavior Toward Groups using Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-24T07:02:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704241</loc>
  <lastmod>2026-06-24T07:02:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴レベルの変動分解を可能にする共変量付きGPLVM（Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models）</news:title>
   <news:publication_date>2026-06-24T07:02:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704239</loc>
  <lastmod>2026-06-24T07:02:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰動的ダイナミクスを要さない生物学的に尤もらしいオンライン主成分分析（Biologically Plausible Online Principal Component Analysis Without Recurrent Neural Dynamics）</news:title>
   <news:publication_date>2026-06-24T07:02:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704237</loc>
  <lastmod>2026-06-24T06:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルウェア・トリアージによるAPT活動の早期特定（Malware triage for early identification of Advanced Persistent Threat activities）</news:title>
   <news:publication_date>2026-06-24T06:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704235</loc>
  <lastmod>2026-06-24T06:10:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的トリプレット損失による深層距離学習（Deep Metric Learning with Hierarchical Triplet Loss）</news:title>
   <news:publication_date>2026-06-24T06:10:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704233</loc>
  <lastmod>2026-06-24T06:10:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みフィルタの構造を学ぶ事前分布：Deep Weight Prior（The Deep Weight Prior）</news:title>
   <news:publication_date>2026-06-24T06:10:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704231</loc>
  <lastmod>2026-06-24T06:09:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNによる前処理でWatershedベースの3D細胞セグメンテーションを最適化する手法（CNN-BASED PREPROCESSING TO OPTIMIZE WATERSHED-BASED CELL SEGMENTATION IN 3D CONFOCAL MICROSCOPY IMAGES）</news:title>
   <news:publication_date>2026-06-24T06:09:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704229</loc>
  <lastmod>2026-06-24T06:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャンネル注意機構と多レベル特徴融合による単一画像超解像（Channel Attention and Multi-level Features Fusion for Single Image Super-Resolution）</news:title>
   <news:publication_date>2026-06-24T06:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704227</loc>
  <lastmod>2026-06-24T06:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパープロセスモデルによる回帰向けゼロショット学習（Hyper-Process Model: A Zero-Shot Learning algorithm for Regression Problems based on Shape Analysis）</news:title>
   <news:publication_date>2026-06-24T06:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704225</loc>
  <lastmod>2026-06-24T06:08:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピカル・ノード埋め込みでネットワーク表現を強化する手法（TNE: A Latent Model for Representation Learning on Networks）</news:title>
   <news:publication_date>2026-06-24T06:08:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704223</loc>
  <lastmod>2026-06-24T05:16:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クリーンデータでのファインチューニングによる音声翻訳改善（Fine-tuning on Clean Data for End-to-End Speech Translation: FBK @ IWSLT 2018）</news:title>
   <news:publication_date>2026-06-24T05:16:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704221</loc>
  <lastmod>2026-06-24T05:16:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的確率的主成分分析によるテクスチャ生成モデル（A Generative Model of Textures Using Hierarchical Probabilistic Principal Component Analysis）</news:title>
   <news:publication_date>2026-06-24T05:16:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704219</loc>
  <lastmod>2026-06-24T05:15:19Z</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『新しいペルシャ詩人』を生み出す試み（Creating a New Persian Poet Based on Machine Learning）</news:title>
   <news:publication_date>2026-06-24T05:15:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704217</loc>
  <lastmod>2026-06-24T05:15:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法務文書向けマルチタスク深層学習の実務意義（Multi-Task Deep Learning for Legal Document Translation, Summarization and Multi-Label Classification）</news:title>
   <news:publication_date>2026-06-24T05:15:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704215</loc>
  <lastmod>2026-06-24T05:14:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対敵的機械学習の安全性概観（SECURITY MATTERS: A SURVEY ON ADVERSARIAL MACHINE LEARNING）</news:title>
   <news:publication_date>2026-06-24T05:14:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704213</loc>
  <lastmod>2026-06-24T05:14:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木にデータを語らせる潜在表現 — LORACs prior for VAEs (The LORACs prior for VAEs: Letting the Trees Speak for the Data)</news:title>
   <news:publication_date>2026-06-24T05:14:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704211</loc>
  <lastmod>2026-06-24T05:14:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数データセンターにまたがる協調深層学習（Collaborative Deep Learning Across Multiple Data Centers）</news:title>
   <news:publication_date>2026-06-24T05:14:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704209</loc>
  <lastmod>2026-06-24T04:23:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速化されたランダム化SVDによる行列補完の高速化（Faster Matrix Completion Using Randomized SVD）</news:title>
   <news:publication_date>2026-06-24T04:23:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704207</loc>
  <lastmod>2026-06-24T04:23:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レジリエントなIoTのロードマップ（A Roadmap Towards Resilient Internet of Things for Cyber-Physical Systems）</news:title>
   <news:publication_date>2026-06-24T04:23:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704205</loc>
  <lastmod>2026-06-24T04:22:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声変換のためのシーケンス・ツー・シーケンス音響モデリング（Sequence-to-Sequence Acoustic Modeling for Voice Conversion）</news:title>
   <news:publication_date>2026-06-24T04:22:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704203</loc>
  <lastmod>2026-06-24T04:22:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限標本解析におけるM推定量と自己整合性の応用（Finite-sample analysis of M-estimators using self-concordance）</news:title>
   <news:publication_date>2026-06-24T04:22:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704201</loc>
  <lastmod>2026-06-24T04:22:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散損失を扱う学習理論の鋭い解析（Sharp Analysis of Learning with Discrete Losses）</news:title>
   <news:publication_date>2026-06-24T04:22:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704199</loc>
  <lastmod>2026-06-24T04:21:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>導関数不要の最適化による単調DR-部分モジュラ連続関数の最大化（Maximizing Monotone DR-submodular Continuous Functions by Derivative-free Optimization）</news:title>
   <news:publication_date>2026-06-24T04:21:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704197</loc>
  <lastmod>2026-06-24T04:21:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味注意に基づく深層物体共分割（Semantic Aware Attention Based Deep Object Co-segmentation）</news:title>
   <news:publication_date>2026-06-24T04:21:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704195</loc>
  <lastmod>2026-06-24T03:30:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>静止特徴と動き特徴を制御して映像の行動認識を高める手法（Combined Static and Motion Features for Deep-Networks Based Activity Recognition in Videos）</news:title>
   <news:publication_date>2026-06-24T03:30:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704193</loc>
  <lastmod>2026-06-24T03:30:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疎データ向け高速ランダム化PCA（Fast Randomized PCA for Sparse Data）</news:title>
   <news:publication_date>2026-06-24T03:30:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704191</loc>
  <lastmod>2026-06-24T03:30:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種ワイヤレスネットワークのためのキャリアセンス多重アクセスと深層強化学習（Carrier-Sense Multiple Access for Heterogeneous Wireless Networks Using Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-24T03:30:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704189</loc>
  <lastmod>2026-06-24T03:28:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュートン・スキーム：運動法則を深層学習に組み込む手法（The Newton Scheme for Deep Learning）</news:title>
   <news:publication_date>2026-06-24T03:28:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704187</loc>
  <lastmod>2026-06-24T03:28:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画理解のための柔軟な3D CNNアクセラレータ（Morph: Flexible Acceleration for 3D CNN-based Video Understanding）</news:title>
   <news:publication_date>2026-06-24T03:28:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704185</loc>
  <lastmod>2026-06-24T03:28:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>品質重視の無線ビデオ伝送における深層学習を用いた送信電力制御（Deep Learning Based Power Control for Quality-Driven Wireless Video Transmissions）</news:title>
   <news:publication_date>2026-06-24T03:28:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704183</loc>
  <lastmod>2026-06-24T03:28:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共マニフォールド学習と欠損データの取り扱い（CO-MANIFOLD LEARNING WITH MISSING DATA）</news:title>
   <news:publication_date>2026-06-24T03:28:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704181</loc>
  <lastmod>2026-06-24T02:36:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>準ハイパーボリック・モーメントとQHAdamが変えた最適化の常識（QUASI-HYPERBOLIC MOMENTUM AND ADAM FOR DEEP LEARNING）</news:title>
   <news:publication_date>2026-06-24T02:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704179</loc>
  <lastmod>2026-06-24T02:36:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接メタ方策探索（Proximal Meta-Policy Search）</news:title>
   <news:publication_date>2026-06-24T02:36:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704177</loc>
  <lastmod>2026-06-24T02:35:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称入力下での二層ニューラルネットワーク学習（Learning Two-layer Neural Networks with Symmetric Inputs）</news:title>
   <news:publication_date>2026-06-24T02:35:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704175</loc>
  <lastmod>2026-06-24T02:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SINE: 大規模かつ不完全なネットワークで使える埋め込み技術（SINE: Scalable Incomplete Network Embedding）</news:title>
   <news:publication_date>2026-06-24T02:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704173</loc>
  <lastmod>2026-06-24T02:34:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的確率的勾配降下法（Evolutionary Stochastic Gradient Descent）</news:title>
   <news:publication_date>2026-06-24T02:34:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704171</loc>
  <lastmod>2026-06-24T02:34:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Approximate Fisher Information Matrixで深層学習の訓練を可視化する（Approximate Fisher Information Matrix to Characterise the Training of Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-24T02:34:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704169</loc>
  <lastmod>2026-06-24T02:34:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による超解像MRI（Super-resolution MRI through Deep Learning）</news:title>
   <news:publication_date>2026-06-24T02:34:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704167</loc>
  <lastmod>2026-06-24T01:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DN-ResNet：効率的な深層残差ネットワークによる画像ノイズ除去（DN-ResNet: Efficient Deep Residual Network for Image Denoising）</news:title>
   <news:publication_date>2026-06-24T01:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704165</loc>
  <lastmod>2026-06-24T01:43:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期臨床記録の自動匿名化に関する総説（A survey of automatic de-identification of longitudinal clinical narratives）</news:title>
   <news:publication_date>2026-06-24T01:43:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704163</loc>
  <lastmod>2026-06-24T01:42:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乱流の深層学習から物理情報学習への展開（From Deep to Physics-Informed Learning of Turbulence: Diagnostics）</news:title>
   <news:publication_date>2026-06-24T01:42:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704161</loc>
  <lastmod>2026-06-24T01:42:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ領域で公平な表現を見つける（Discovering Fair Representations in the Data Domain）</news:title>
   <news:publication_date>2026-06-24T01:42:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704159</loc>
  <lastmod>2026-06-24T01:42:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適回転座標系による適応型スパースグリッド最小二乗回帰（Optimally rotated coordinate systems for adaptive least-squares regression on sparse grids）</news:title>
   <news:publication_date>2026-06-24T01:42:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704157</loc>
  <lastmod>2026-06-24T01:41:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時フィルタリングとパラメータ推定のためのブロック座標降下近接法（A Block Coordinate Descent Proximal Method for Simultaneous Filtering and Parameter Estimation）</news:title>
   <news:publication_date>2026-06-24T01:41:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704155</loc>
  <lastmod>2026-06-24T01:41:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANの出力を「選りすぐる」手法で質を高める（Discriminator Rejection Sampling, DRS）</news:title>
   <news:publication_date>2026-06-24T01:41:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704153</loc>
  <lastmod>2026-06-24T00:50:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットアームの連続制御における深層強化学習の応用（Using Deep Reinforcement Learning for the Continuous Control of Robotic Arms）</news:title>
   <news:publication_date>2026-06-24T00:50:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704151</loc>
  <lastmod>2026-06-24T00:49:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味的一致性が多感覚統合と衝突解決に与える寄与の評価（Assessing the Contribution of Semantic Congruency to Multisensory Integration and Conflict Resolution）</news:title>
   <news:publication_date>2026-06-24T00:49:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704149</loc>
  <lastmod>2026-06-24T00:48:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>段階的強化学習による物体検出（MULTI-STAGE REINFORCEMENT LEARNING FOR OBJECT DETECTION）</news:title>
   <news:publication_date>2026-06-24T00:48:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704147</loc>
  <lastmod>2026-06-24T00:48:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認知的誤謬の整理法（Bringing Order to the Cognitive Fallacy Zoo）</news:title>
   <news:publication_date>2026-06-24T00:48:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704145</loc>
  <lastmod>2026-06-24T00:48:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形拡散に基づく教師なし学習（Learning by Unsupervised Nonlinear Diffusion）</news:title>
   <news:publication_date>2026-06-24T00:48:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704143</loc>
  <lastmod>2026-06-24T00:48:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病変領域に着目した超解像の実践（Lesion Focused Super-Resolution）</news:title>
   <news:publication_date>2026-06-24T00:48:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704141</loc>
  <lastmod>2026-06-24T00:47:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブロックチェーン活動データに基づくデジタル資産市場予測（Predicting digital asset market based on blockchain activity data）</news:title>
   <news:publication_date>2026-06-24T00:47:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704139</loc>
  <lastmod>2026-06-23T23:56:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カラムジェネレーションを用いた分類木の数理ヒューリスティック（Column generation based math-heuristic for classification trees）</news:title>
   <news:publication_date>2026-06-23T23:56:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704137</loc>
  <lastmod>2026-06-23T23:56:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トレリスネットワークによる系列モデリングの再定義（Trellis Networks for Sequence Modeling）</news:title>
   <news:publication_date>2026-06-23T23:56:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704135</loc>
  <lastmod>2026-06-23T23:56:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速に学び、遅く忘れる：反復作業を行う未知かつ変化する動力学を持つシステムの安全な予測学習制御（Learn Fast, Forget Slow: Safe Predictive Learning Control for Systems with Unknown and Changing Dynamics Performing Repetitive Tasks）</news:title>
   <news:publication_date>2026-06-23T23:56:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704133</loc>
  <lastmod>2026-06-23T23:55:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト要約のための深層転移強化学習（Deep Transfer Reinforcement Learning for Text Summarization）</news:title>
   <news:publication_date>2026-06-23T23:55:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704131</loc>
  <lastmod>2026-06-23T23:55:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法務文書の固有表現リンクにおける転移学習の応用（Named-Entity Linking Using Deep Learning For Legal Documents: A Transfer Learning Approach）</news:title>
   <news:publication_date>2026-06-23T23:55:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704129</loc>
  <lastmod>2026-06-23T23:55:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラピディティ・マス行列を使ったイベント分類の標準化（Machine learning using rapidity-mass matrices for event classification problems in HEP）</news:title>
   <news:publication_date>2026-06-23T23:55:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704127</loc>
  <lastmod>2026-06-23T23:54:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地域と機会をつなぐngVLA（Reaching Communities and Creating New Opportunities with the ngVLA）</news:title>
   <news:publication_date>2026-06-23T23:54:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704125</loc>
  <lastmod>2026-06-23T23:04:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不適切コメントの検出を高めるマルチタスク深層学習（Stop Illegal Comments: A Multi-Task Deep Learning Approach）</news:title>
   <news:publication_date>2026-06-23T23:04:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704123</loc>
  <lastmod>2026-06-23T23:04:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルデータサイエンスの実務応用（Mobile Data Science: Towards Understanding Data-Driven Intelligent Mobile Applications）</news:title>
   <news:publication_date>2026-06-23T23:04:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704121</loc>
  <lastmod>2026-06-23T23:03:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マグリブ方言アラビア語の母音付加（Diacritization of Maghrebi Arabic Sub-Dialects）</news:title>
   <news:publication_date>2026-06-23T23:03:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704119</loc>
  <lastmod>2026-06-23T23:03:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ngVLAによる超大質量ブラックホールの高精度質量測定（Precision Gas-dynamical Mass Measurement of Supermassive Black Holes with the ngVLA）</news:title>
   <news:publication_date>2026-06-23T23:03:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704117</loc>
  <lastmod>2026-06-23T23:02:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ToDoリストによるOWL推論器のヒューリスティック最適化（Optimizing Heuristics for Tableau-based OWL Reasoners）</news:title>
   <news:publication_date>2026-06-23T23:02:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704115</loc>
  <lastmod>2026-06-23T22:12:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コヒーレントイメージングにおけるディープラーニングを用いた超解像（Deep learning-based super-resolution in coherent imaging systems）</news:title>
   <news:publication_date>2026-06-23T22:12:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704113</loc>
  <lastmod>2026-06-23T22:11:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凍結ガウス近似を用いた深層学習による地震サブ構造検出（Deep Learning Seismic Substructure Detection Using the Frozen Gaussian Approximation）</news:title>
   <news:publication_date>2026-06-23T22:11:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704111</loc>
  <lastmod>2026-06-23T22:11:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙時代のフィードバックを分子ガスのアウトフローで描く（Characterizing Feedback Through Molecular Outflows Across Cosmic Time）</news:title>
   <news:publication_date>2026-06-23T22:11:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704109</loc>
  <lastmod>2026-06-23T22:11:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形オーディオエフェクトを終端まで学習するディープニューラルネットワーク（MODELING NONLINEAR AUDIO EFFECTS WITH END-TO-END DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-06-23T22:11:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704107</loc>
  <lastmod>2026-06-23T22:11:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍の低質量銀河における降着型超巨大ブラックホールの検出可能性（Accreting Supermassive Black Holes in Nearby Low-mass Galaxies）</news:title>
   <news:publication_date>2026-06-23T22:11:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704105</loc>
  <lastmod>2026-06-23T22:10:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的訓練によるニューラルネットの簡潔な説明（Concise Explanations of Neural Networks using Adversarial Training）</news:title>
   <news:publication_date>2026-06-23T22:10:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704103</loc>
  <lastmod>2026-06-23T22:10:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スティックブレイキング事前分布の感度評価（Evaluating Sensitivity to the Stick-Breaking Prior in Bayesian Nonparametrics）</news:title>
   <news:publication_date>2026-06-23T22:10:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704101</loc>
  <lastmod>2026-06-23T21:19:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Poincaré GloVeによる単語表現の再設計（POINCARÉ GLOVE: HYPERBOLIC WORD EMBEDDINGS）</news:title>
   <news:publication_date>2026-06-23T21:19:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704099</loc>
  <lastmod>2026-06-23T21:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーン事前知識を使った視覚意味的ナビゲーション（Visual Semantic Navigation Using Scene Priors）</news:title>
   <news:publication_date>2026-06-23T21:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704097</loc>
  <lastmod>2026-06-23T21:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層イミテーションモデルによる目標指向プランニングと制御（Deep Imitative Models for Flexible Inference, Planning, and Control）</news:title>
   <news:publication_date>2026-06-23T21:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704095</loc>
  <lastmod>2026-06-23T21:18:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体表面の視点依存輝度を神経網で再現する手法（Deep Surface Light Fields）</news:title>
   <news:publication_date>2026-06-23T21:18:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704093</loc>
  <lastmod>2026-06-23T21:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Successor Uncertaintiesによる探索と時間的差分学習の不確実性（Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning）</news:title>
   <news:publication_date>2026-06-23T21:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704091</loc>
  <lastmod>2026-06-23T21:17:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化されたコンテンツ保持による教師なしテキストスタイル変換（Structured Content Preservation for Unsupervised Text Style Transfer）</news:title>
   <news:publication_date>2026-06-23T21:17:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704089</loc>
  <lastmod>2026-06-23T21:17:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因数分解された機械の自己確信と意思決定エージェント（Factorized Machine Self-Confidence for Decision-Making Agents）</news:title>
   <news:publication_date>2026-06-23T21:17:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704087</loc>
  <lastmod>2026-06-23T20:26:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測と補正で方策学習を加速する枠組み（Predictor-Corrector Policy Optimization）</news:title>
   <news:publication_date>2026-06-23T20:26:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704085</loc>
  <lastmod>2026-06-23T20:25:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成セグメンテーションで「ラベル不要」の医用画像解析をめざす（SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth）</news:title>
   <news:publication_date>2026-06-23T20:25:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704083</loc>
  <lastmod>2026-06-23T20:24:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光度観測による超新星分類を深層学習で改善する（Improved Photometric Classification of Supernovae using Deep Learning）</news:title>
   <news:publication_date>2026-06-23T20:24:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704081</loc>
  <lastmod>2026-06-23T20:24:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンコーダ・デコーダ特徴と識別器で拓くリモートセンシング画像マッチング（Unsupervised Deep Features for Remote Sensing Image Matching via Discriminator Network）</news:title>
   <news:publication_date>2026-06-23T20:24:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704079</loc>
  <lastmod>2026-06-23T20:24:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一MR画像の超解像におけるチャネル分割ネットワーク（Channel Splitting Network for Single MR Image Super-Resolution）</news:title>
   <news:publication_date>2026-06-23T20:24:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704077</loc>
  <lastmod>2026-06-23T20:24:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>匿名化MRI画像からの顔再構成（REFACING: RECONSTRUCTING ANONYMIZED FACIAL FEATURES USING GANS）</news:title>
   <news:publication_date>2026-06-23T20:24:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704075</loc>
  <lastmod>2026-06-23T20:24:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘッジングアルゴリズムと反復行列ゲームの示唆（Hedging Algorithms and Repeated Matrix Games）</news:title>
   <news:publication_date>2026-06-23T20:24:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704073</loc>
  <lastmod>2026-06-23T19:33:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電話の「止めどき」を自動で見つける研究（SilentPhone: Inferring User Unavailability based Opportune Moments to Minimize Call Interruptions）</news:title>
   <news:publication_date>2026-06-23T19:33:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704071</loc>
  <lastmod>2026-06-23T19:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デジタル病理における組織染色の仮想化（Virtualization of Tissue Staining in Digital Pathology Using an Unsupervised Deep Learning Approach）</news:title>
   <news:publication_date>2026-06-23T19:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704069</loc>
  <lastmod>2026-06-23T19:32:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ中心の社会的文脈が個人化モバイルアプリに与える役割（Understanding the Role of Data-Centric Social Context in Personalized Mobile Applications）</news:title>
   <news:publication_date>2026-06-23T19:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704067</loc>
  <lastmod>2026-06-23T19:31:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Isingモデル近似による教師なしアンサンブル学習とフェノタイピング予測への応用（Unsupervised Ensemble Learning via Ising Model Approximation with Application to Phenotyping Prediction）</news:title>
   <news:publication_date>2026-06-23T19:31:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704065</loc>
  <lastmod>2026-06-23T19:31:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>障害に強い科学ワークフローの効率的スケジューリング（An Efficient Fault Tolerant Workflow Scheduling Approach using Replication Heuristics and Checkpointing in the Cloud）</news:title>
   <news:publication_date>2026-06-23T19:31:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704063</loc>
  <lastmod>2026-06-23T19:31:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Translocatome：細胞内タンパク質の「移動」を可視化するデータベース（Translocatome: a novel resource for the analysis of protein translocation between cellular organelles）</news:title>
   <news:publication_date>2026-06-23T19:31:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/704061</loc>
  <lastmod>2026-06-23T19:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二層ニューラルネットワークの母集団リスクに関する先験的評価（A Priori Estimates of the Population Risk for Two-Layer Neural Networks）</news:title>
   <news:publication_date>2026-06-23T19:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/704059</loc>
  <lastmod>2026-06-23T18:39:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習の概要と実務的意義 (Deep Reinforcement Learning: An Overview)</news:title>
   <news:publication_date>2026-06-23T18:39:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704057</loc>
  <lastmod>2026-06-23T18:39:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車両の細粒度分類におけるResNetと局所化、空間重み付きプーリングの有効性（Vehicle classification using ResNets, localisation and spatially-weighted pooling）</news:title>
   <news:publication_date>2026-06-23T18:39:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/704055</loc>
  <lastmod>2026-06-23T18:38:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己注意型オートエンコーダに基づく普遍言語表現（Self-Attentive Autoencoder-based Universal Language Representation for Machine Translation）</news:title>
   <news:publication_date>2026-06-23T18:38:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704053</loc>
  <lastmod>2026-06-23T18:38:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重イオン衝突におけるジェット運動量の機械学習補正（Machine Learning based jet momentum reconstruction in heavy-ion collisions）</news:title>
   <news:publication_date>2026-06-23T18:38:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704051</loc>
  <lastmod>2026-06-23T18:38:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポリフォニック音イベント検出におけるカプセルニューラルネットワーク（Polyphonic Sound Event Detection by using Capsule Neural Networks）</news:title>
   <news:publication_date>2026-06-23T18:38:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704049</loc>
  <lastmod>2026-06-23T18:38:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮計測領域での画像認識が変える現場（Compressively Sensed Image Recognition）</news:title>
   <news:publication_date>2026-06-23T18:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704047</loc>
  <lastmod>2026-06-23T18:37:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽光の短期予測を深層学習で行う（Deep Photovoltaic Nowcasting）</news:title>
   <news:publication_date>2026-06-23T18:37:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704045</loc>
  <lastmod>2026-06-23T17:46:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在特徴語表現を用いたトピックモデルの改善（Improving Topic Models with Latent Feature Word Representations）</news:title>
   <news:publication_date>2026-06-23T17:46:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704043</loc>
  <lastmod>2026-06-23T17:46:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>帯域幅と後悔のトレードオフ（Regret vs. Bandwidth Trade-off for Recommendation Systems）</news:title>
   <news:publication_date>2026-06-23T17:46:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704041</loc>
  <lastmod>2026-06-23T17:45:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布的転移によるハイパーパラメータ学習（Hyperparameter Learning via Distributional Transfer）</news:title>
   <news:publication_date>2026-06-23T17:45:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704039</loc>
  <lastmod>2026-06-23T17:44:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BshapeNet：境界形状マスクで精度を上げる物体検出とインスタンス分割（BshapeNet: Object Detection and Instance Segmentation with Bounding Shape Masks）</news:title>
   <news:publication_date>2026-06-23T17:44:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704037</loc>
  <lastmod>2026-06-23T17:44:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランキングデータの次元削減と（バケット）ランキング：質量輸送アプローチ (Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach)</news:title>
   <news:publication_date>2026-06-23T17:44:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704035</loc>
  <lastmod>2026-06-23T17:44:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層畳み込みニューラルネットワークの特徴表現解析と二段階フィーチャー転移（Feature Representation Analysis of Deep Convolutional Neural Network using Two-stage Feature Transfer）</news:title>
   <news:publication_date>2026-06-23T17:44:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704033</loc>
  <lastmod>2026-06-23T17:44:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律的目標選択とモジュール化学習による強化学習の進化（CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-23T17:44:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704031</loc>
  <lastmod>2026-06-23T16:52:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈対応型カプセルネットワークによるマルチラベル分類（A Context-aware Capsule Network for Multi-label Classification）</news:title>
   <news:publication_date>2026-06-23T16:52:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704029</loc>
  <lastmod>2026-06-23T16:51:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疎視点CT再構成における畳み込みスパースコーディング（SPARSE-VIEW CT RECONSTRUCTION VIA CONVOLUTIONAL SPARSE CODING）</news:title>
   <news:publication_date>2026-06-23T16:51:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704027</loc>
  <lastmod>2026-06-23T16:51:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的時系列伸縮法による時間的グラフ比較（Comparing Temporal Graphs Using Dynamic Time Warping）</news:title>
   <news:publication_date>2026-06-23T16:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704025</loc>
  <lastmod>2026-06-23T16:51:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スムーズ乗法ノイズを用いたロバスト降下（Robust descent using smoothed multiplicative noise）</news:title>
   <news:publication_date>2026-06-23T16:51:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704023</loc>
  <lastmod>2026-06-23T16:50:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドローンレースにおける最適手法と学習の融合（Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing）</news:title>
   <news:publication_date>2026-06-23T16:50:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704021</loc>
  <lastmod>2026-06-23T16:50:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像における主観的名詞属性予測のためのFocus-Aspect-Polarityモデル（The Focus-Aspect-Polarity Model for Predicting Subjective Noun Attributes in Images）</news:title>
   <news:publication_date>2026-06-23T16:50:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704019</loc>
  <lastmod>2026-06-23T16:50:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>監督付きCOSMOSオートエンコーダー：ユークリッド損失を超える学習（Supervised COSMOS Autoencoder: Learning Beyond the Euclidean Loss!）</news:title>
   <news:publication_date>2026-06-23T16:50:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704017</loc>
  <lastmod>2026-06-23T15:59:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAV支援ネットワークにおける3D配置とユーザ割当の分散機構（Learn to Fly: A Distributed Mechanism for Joint 3D Placement and Users Association in UAVs-assisted Networks）</news:title>
   <news:publication_date>2026-06-23T15:59:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704015</loc>
  <lastmod>2026-06-23T15:59:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>省略された代名詞の同時翻訳と予測を学習する共有再構築機構（Learning to Jointly Translate and Predict Dropped Pronouns with a Shared Reconstruction Mechanism）</news:title>
   <news:publication_date>2026-06-23T15:59:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704013</loc>
  <lastmod>2026-06-23T15:58:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>触覚センサからの力推定のロバスト学習（Robust Learning of Tactile Force Estimation through Robot Interaction）</news:title>
   <news:publication_date>2026-06-23T15:58:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704011</loc>
  <lastmod>2026-06-23T15:58:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次型機械教育の最適制御アプローチ (An Optimal Control Approach to Sequential Machine Teaching)</news:title>
   <news:publication_date>2026-06-23T15:58:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704009</loc>
  <lastmod>2026-06-23T15:58:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Batch Normalizationの最適化的再考と改良手法（Revisit Batch Normalization: New Understanding from an Optimization View and a Reﬁnement via Composition Optimization）</news:title>
   <news:publication_date>2026-06-23T15:58:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704007</loc>
  <lastmod>2026-06-23T15:57:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ABACUSによる無監督多変量変化検出（ABACUS: Unsupervised Multivariate Change Detection via Bayesian Source Separation）</news:title>
   <news:publication_date>2026-06-23T15:57:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704005</loc>
  <lastmod>2026-06-23T15:57:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速列車向けmmWave通信のためのバンディットに着想を得たビーム探索法（Bandit Inspired Beam Searching Scheme for mmWave High-Speed Train Communications）</news:title>
   <news:publication_date>2026-06-23T15:57:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704003</loc>
  <lastmod>2026-06-23T15:06:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SpotNetによる免疫アッセイ画像でのセル検出（SPOTNET – LEARNED ITERATIONS FOR CELL DETECTION IN IMAGE-BASED IMMUNOASSAYS）</news:title>
   <news:publication_date>2026-06-23T15:06:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/704001</loc>
  <lastmod>2026-06-23T14:56:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽磁気構造に関連する深部音響源の起源（Origin of Deep Acoustic Sources Associated with Solar Magnetic Structures）</news:title>
   <news:publication_date>2026-06-23T14:56:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703999</loc>
  <lastmod>2026-06-23T14:56:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>虚数周波数グリーン関数からのスペクトルデータ抽出における過学習抑制（Suppression of Overﬁtting in Extraction of Spectral Data from Imaginary Frequency Green Function Using Maximum Entropy Method）</news:title>
   <news:publication_date>2026-06-23T14:56:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703997</loc>
  <lastmod>2026-06-23T14:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>破壊進展を秒で予測する――脆性材料のグラフ再帰学習（Learning to Fail: Predicting Fracture Evolution in Brittle Material Models using Recurrent Graph Convolutional Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703995</loc>
  <lastmod>2026-06-23T14:55:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセル単位での同時学習が拓く3D幾何と運動の理解（Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分ニューラルネットワーク：層とニューロンごとに最適な活性化関数を学習する（Variational Neural Networks: Every Layer and Neuron Can Be Unique）</news:title>
   <news:publication_date>2026-06-23T14:55:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PRETZEL: 機械学習のブラックボックスを開く予測サービングの白箱化（PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems）</news:title>
   <news:publication_date>2026-06-23T14:54:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703989</loc>
  <lastmod>2026-06-23T14:03:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GW170817が示すベクトル相互作用の示唆（What do we learn about vector interactions from GW170817?）</news:title>
   <news:publication_date>2026-06-23T14:03:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703987</loc>
  <lastmod>2026-06-23T14:02:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>追跡再構成のための新しい深層学習手法（Novel deep learning methods for track reconstruction）</news:title>
   <news:publication_date>2026-06-23T14:02:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703985</loc>
  <lastmod>2026-06-23T14:02:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>料理レシピと画像のクロスモーダル埋め込み学習のための大規模データセット（Recipe1M+: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images）</news:title>
   <news:publication_date>2026-06-23T14:02:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703983</loc>
  <lastmod>2026-06-23T14:01:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小二乗回帰におけるスケッチの漸近解析（Asymptotics for Sketching in Least Squares Regression）</news:title>
   <news:publication_date>2026-06-23T14:01:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703981</loc>
  <lastmod>2026-06-23T14:01:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力レンズを高解像度望遠鏡として活用する（Gravitational Lenses as High-Resolution Telescopes）</news:title>
   <news:publication_date>2026-06-23T14:01:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703979</loc>
  <lastmod>2026-06-23T14:01:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>古典的Q学習のポテンシャル評価（Assessing the Potential of Classical Q-learning in General Game Playing）</news:title>
   <news:publication_date>2026-06-23T14:01:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703977</loc>
  <lastmod>2026-06-23T14:01:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファジー結合拡張による全身組織分割（A Novel Extension to Fuzzy Connectivity for Body Composition Analysis）</news:title>
   <news:publication_date>2026-06-23T14:01:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703975</loc>
  <lastmod>2026-06-23T13:09:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散環境での深層ニューラルネットワーク学習（Distributed learning of deep neural network over multiple agents）</news:title>
   <news:publication_date>2026-06-23T13:09:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703973</loc>
  <lastmod>2026-06-23T13:08:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>子宮頸部細胞の精密分類：形態情報と外観情報を組み合わせたCNN手法（Fine-Grained Classification of Cervical Cells Using Morphological and Appearance Based Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-23T13:08:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703971</loc>
  <lastmod>2026-06-23T13:08:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的情報に強いニューラル要約システムの提案（Robust Neural Abstractive Summarization Systems and Evaluation against Adversarial Information）</news:title>
   <news:publication_date>2026-06-23T13:08:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703969</loc>
  <lastmod>2026-06-23T13:07:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドロップアウト正則化のETF的視点 (An ETF View of Dropout Regularization)</news:title>
   <news:publication_date>2026-06-23T13:07:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703967</loc>
  <lastmod>2026-06-23T13:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多指ハンドの現場学習による巧緻操作の実現（Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost）</news:title>
   <news:publication_date>2026-06-23T13:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703965</loc>
  <lastmod>2026-06-23T13:07:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態集約のための適応的低非負ランク近似（ADAPTIVE LOW-NONNEGATIVE-RANK APPROXIMATION FOR STATE AGGREGATION OF MARKOV CHAINS）</news:title>
   <news:publication_date>2026-06-23T13:07:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703963</loc>
  <lastmod>2026-06-23T13:07:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係経路を用いた知識ベース補完の共同敵対的学習（Modeling Relation Paths for Knowledge Base Completion via Joint Adversarial Training）</news:title>
   <news:publication_date>2026-06-23T13:07:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703961</loc>
  <lastmod>2026-06-23T12:15:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>免疫シナプスのパターンを能動的に調整すると認識精度が向上する（Active tuning of synaptic patterns enhances immune discrimination）</news:title>
   <news:publication_date>2026-06-23T12:15:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703959</loc>
  <lastmod>2026-06-23T12:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミング前処理ライブラリDPASFの実務意義（DPASF: A Flink Library for Streaming Data preprocessing）</news:title>
   <news:publication_date>2026-06-23T12:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703957</loc>
  <lastmod>2026-06-23T12:14:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星間深部光電離によるC3系分子の天体生成（Astronomical Creation of Cyclic-C3H2 and Chain-C3 Due to Interstellar Deep Photoionization）</news:title>
   <news:publication_date>2026-06-23T12:14:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703955</loc>
  <lastmod>2026-06-23T12:14:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Trajectronによる確率的マルチエージェント軌跡予測（The Trajectron: Probabilistic Multi-Agent Trajectory Modeling With Dynamic Spatiotemporal Graphs）</news:title>
   <news:publication_date>2026-06-23T12:14:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703953</loc>
  <lastmod>2026-06-23T12:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ほぼ最適なラッソ解の凸包近似（Convex Hull Approximation of Nearly Optimal Lasso Solutions）</news:title>
   <news:publication_date>2026-06-23T12:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703951</loc>
  <lastmod>2026-06-23T12:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像における肺構造強調手法の実用化可能性（Lung Structures Enhancement in Chest Radiographs via CT based FCNN Training）</news:title>
   <news:publication_date>2026-06-23T12:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703949</loc>
  <lastmod>2026-06-23T12:13:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノード予測を先に作って広げる──PPNPとAPPNPによるグラフ分類の刷新（PREDICT THEN PROPAGATE: GRAPH NEURAL NETWORKS MEET PERSONALIZED PAGERANK）</news:title>
   <news:publication_date>2026-06-23T12:13:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703947</loc>
  <lastmod>2026-06-23T11:22:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期軌道周辺の三体問題における鋭いネホロシェフ見積もり（Sharp Nekhoroshev estimates for the three-body problem around periodic orbits）</news:title>
   <news:publication_date>2026-06-23T11:22:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703945</loc>
  <lastmod>2026-06-23T11:22:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習の理論的保証（Theoretical Guarantees of Transfer Learning）</news:title>
   <news:publication_date>2026-06-23T11:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703943</loc>
  <lastmod>2026-06-23T11:22:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療相談掲示板から「似た質問」を見つける技術（Finding Similar Medical Questions from Question Answering Websites）</news:title>
   <news:publication_date>2026-06-23T11:22:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703941</loc>
  <lastmod>2026-06-23T11:21:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分飽和砂充填体における気体輸送の法則性（Gas transport in partially-saturated sand packs）</news:title>
   <news:publication_date>2026-06-23T11:21:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703939</loc>
  <lastmod>2026-06-23T11:20:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>比較に基づくCNNによる子宮頸部細胞検出（Comparison-Based Convolutional Neural Networks for Cervical Cell/Clumps Detection in the Limited Data Scenario）</news:title>
   <news:publication_date>2026-06-23T11:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703937</loc>
  <lastmod>2026-06-23T11:20:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>落書きを学ぶ（Learning to Doodle with Deep Q-Networks and Demonstrated Strokes）</news:title>
   <news:publication_date>2026-06-23T11:20:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703935</loc>
  <lastmod>2026-06-23T11:20:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DDSLによる分散・動的グラフ上の効率的部分グラフ列挙（DDSL: Efficient Subgraph Listing on Distributed and Dynamic Graphs）</news:title>
   <news:publication_date>2026-06-23T11:20:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703933</loc>
  <lastmod>2026-06-23T10:28:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延制約下のカバート通信とフルデュプレックス受信機の役割（Delay-Constrained Covert Communications with A Full-Duplex Receiver）</news:title>
   <news:publication_date>2026-06-23T10:28:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703931</loc>
  <lastmod>2026-06-23T10:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>灌漑システムのロバスト予測制御とデータ駆動の不確実性学習（Robust Model Predictive Control of Irrigation Systems with Active Uncertainty Learning and Data Analytics）</news:title>
   <news:publication_date>2026-06-23T10:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703929</loc>
  <lastmod>2026-06-23T10:18:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Varifocal-Netによる染色体分類の革新（Varifocal-Net: A Chromosome Classification Approach Using Deep Convolutional Networks）</news:title>
   <news:publication_date>2026-06-23T10:18:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703927</loc>
  <lastmod>2026-06-23T10:17:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間時間密接結合畳み込みネットワークによるCO2漏洩検出（Spatial-Temporal Densely Connected Convolutional Networks: An Application to CO2 Leakage Detection）</news:title>
   <news:publication_date>2026-06-23T10:17:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703925</loc>
  <lastmod>2026-06-23T10:17:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル密度推定器の一様収束と内在的体積次元への適応（Uniform Convergence of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension）</news:title>
   <news:publication_date>2026-06-23T10:17:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703923</loc>
  <lastmod>2026-06-23T10:16:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二者対戦：サイバーアラート検査システムの敵対的評価（Two Can Play That Game: An Adversarial Evaluation of a Cyber-alert Inspection System）</news:title>
   <news:publication_date>2026-06-23T10:16:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703921</loc>
  <lastmod>2026-06-23T10:16:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震波データと時空間密結合畳み込みニューラルネットワークによるCO2漏洩のデータ駆動検出 (A Data-Driven CO2 Leakage Detection Using Seismic Data and Spatial-Temporal Densely Connected Convolutional Neural Networks)</news:title>
   <news:publication_date>2026-06-23T10:16:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703919</loc>
  <lastmod>2026-06-23T09:24:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>参照なしの画像ノイズ除去品質評価法（No-reference Image Denoising Quality Assessment）</news:title>
   <news:publication_date>2026-06-23T09:24:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703917</loc>
  <lastmod>2026-06-23T09:24:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で読み解く非平衡な量子熱機の揺らぎ（Nonequilibrium fluctuations of a driven quantum heat engine via machine learning）</news:title>
   <news:publication_date>2026-06-23T09:24:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703915</loc>
  <lastmod>2026-06-23T09:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コリン動態の比較研究：分子動力学シミュレーションと中性子散乱による解析（Deep diving into the comparative study of Choline dynamics using molecular dynamics simulation and neutron scattering technique）</news:title>
   <news:publication_date>2026-06-23T09:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703913</loc>
  <lastmod>2026-06-23T09:23:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子合意に基づく線形化可能な複製状態機械（Linearizable Replicated State Machines with Lattice Agreement）</news:title>
   <news:publication_date>2026-06-23T09:23:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703911</loc>
  <lastmod>2026-06-23T09:23:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いたチャネル推定の新展開（Deep Learning-Based Channel Estimation）</news:title>
   <news:publication_date>2026-06-23T09:23:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703909</loc>
  <lastmod>2026-06-23T09:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知で雑然とした環境における頑健な物体検出のための漸進的深層学習（Incremental Deep Learning for Robust Object Detection in Unknown Cluttered Environments）</news:title>
   <news:publication_date>2026-06-23T09:22:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703907</loc>
  <lastmod>2026-06-23T09:22:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>眼科における組込み深層学習（Embedded deep learning in ophthalmology: Making ophthalmic imaging smarter）</news:title>
   <news:publication_date>2026-06-23T09:22:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703905</loc>
  <lastmod>2026-06-23T08:31:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次妨害における貪欲型と戦略型回避者（On Greedy and Strategic Evaders in Sequential Interdiction Settings with Incomplete Information）</news:title>
   <news:publication_date>2026-06-23T08:31:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703903</loc>
  <lastmod>2026-06-23T08:31:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大型磁場の別の変換を用いる太陽ダイナモと黒点生成（A Model of Solar Dynamo with Alternative Conversion of Large-Scale Magnetic Field and Production of Sunspots）</news:title>
   <news:publication_date>2026-06-23T08:31:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703901</loc>
  <lastmod>2026-06-23T08:30:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意駆動型人物再識別（Attention Driven Person Re-identification）</news:title>
   <news:publication_date>2026-06-23T08:30:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703899</loc>
  <lastmod>2026-06-23T08:30:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交互最小二乗法（ALS）へのネステロフ加速—モメンタムのステップサイズとリスタート機構（Nesterov Acceleration of Alternating Least Squares for Canonical Tensor Decomposition: Momentum Step Size Selection and Restart Mechanisms）</news:title>
   <news:publication_date>2026-06-23T08:30:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703897</loc>
  <lastmod>2026-06-23T08:30:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味情報を活用した敵対的訓練による画像レベルドメイン適応（Exploiting Semantics in Adversarial Training for Image-Level Domain Adaptation）</news:title>
   <news:publication_date>2026-06-23T08:30:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703895</loc>
  <lastmod>2026-06-23T08:30:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延により制御される多層ネットワークの爆発的同期（Delay Regulated Explosive Synchronization in Multiplex Networks）</news:title>
   <news:publication_date>2026-06-23T08:30:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703893</loc>
  <lastmod>2026-06-23T08:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MOOCにおける相互作用と受講離脱 (Interaction and Student Dropout in Massive Open Online Courses)</news:title>
   <news:publication_date>2026-06-23T08:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703891</loc>
  <lastmod>2026-06-23T07:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ学習の圏論的視点（Categorical Aspects of Parameter Learning）</news:title>
   <news:publication_date>2026-06-23T07:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703889</loc>
  <lastmod>2026-06-23T07:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株価変動予測を強化する敵対的学習（Enhancing Stock Movement Prediction with Adversarial Training）</news:title>
   <news:publication_date>2026-06-23T07:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703887</loc>
  <lastmod>2026-06-23T07:37:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なマルチレベル相関による視覚追跡（Efficient Multi-level Correlating for Visual Tracking）</news:title>
   <news:publication_date>2026-06-23T07:37:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703885</loc>
  <lastmod>2026-06-23T07:37:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mixture of Expert/Imitator Networksによる拡張可能な半教師あり学習（Mixture of Expert/Imitator Networks: Scalable Semi-supervised Learning Framework）</news:title>
   <news:publication_date>2026-06-23T07:37:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703883</loc>
  <lastmod>2026-06-23T07:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群を生成するGANの仕組みと実用可能性（Point Cloud GAN）</news:title>
   <news:publication_date>2026-06-23T07:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703881</loc>
  <lastmod>2026-06-23T07:36:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト記述による画像の大域的編集学習（Learning to Globally Edit Images with Textual Description）</news:title>
   <news:publication_date>2026-06-23T07:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703879</loc>
  <lastmod>2026-06-23T07:36:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中〜高解像度リモートセンシング画像のための深層学習ベースの雲検出（Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors）</news:title>
   <news:publication_date>2026-06-23T07:36:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703877</loc>
  <lastmod>2026-06-23T06:45:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像における雲検出を深層学習で高精度化する方法（A Cloud Detection Algorithm for Remote Sensing Images Using Fully Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-23T06:45:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703875</loc>
  <lastmod>2026-06-23T06:45:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トポグラフィック表現と量子機械学習（Topographic Representation for Quantum Machine Learning）</news:title>
   <news:publication_date>2026-06-23T06:45:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703873</loc>
  <lastmod>2026-06-23T06:45:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転対称性を持つ物体の姿勢推定（Pose Estimation for Objects with Rotational Symmetry）</news:title>
   <news:publication_date>2026-06-23T06:45:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703871</loc>
  <lastmod>2026-06-23T06:44:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ISAM：計算とハードウェアに依存しない深層学習コンパイラ（ISAM: A Compute and Hardware Agnostic Deep Learning Compiler）</news:title>
   <news:publication_date>2026-06-23T06:44:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703869</loc>
  <lastmod>2026-06-23T06:44:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一RGB画像から影領域を検出するCPNetの要点（CPNet: A Context Preserver Convolutional Neural Network for Detecting Shadows in Single RGB Images）</news:title>
   <news:publication_date>2026-06-23T06:44:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703867</loc>
  <lastmod>2026-06-23T06:44:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動プログラミングのためのモデル（A Model for Auto-Programming for General Purposes）</news:title>
   <news:publication_date>2026-06-23T06:44:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703865</loc>
  <lastmod>2026-06-23T06:43:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GPUで加速するロボットシミュレーションが変える分散強化学習（GPU-Accelerated Robotic Simulation for Distributed Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-23T06:43:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703863</loc>
  <lastmod>2026-06-23T05:52:17Z</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情報流（Estimating Information Flow in Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-23T05:52:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703861</loc>
  <lastmod>2026-06-23T05:43:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ・ハイパーネットワークによるニューラルアーキテクチャ探索（Graph HyperNetworks for Neural Architectural Search）</news:title>
   <news:publication_date>2026-06-23T05:43:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703859</loc>
  <lastmod>2026-06-23T05:43:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合線形回帰に対するEMアルゴリズムの全局収束（Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression）</news:title>
   <news:publication_date>2026-06-23T05:43:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703857</loc>
  <lastmod>2026-06-23T05:43:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>戦略最適化によるポリシー転移（Policy Transfer with Strategy Optimization）</news:title>
   <news:publication_date>2026-06-23T05:43:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703855</loc>
  <lastmod>2026-06-23T05:42:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系列データ上のブラックボックスを説明する加重オートマトン抽出（Explaining Black Boxes on Sequential Data using Weighted Automata）</news:title>
   <news:publication_date>2026-06-23T05:42:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703853</loc>
  <lastmod>2026-06-23T05:42:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MeanSumによる教師なし抽象的要約の実用可能性検討（MeanSum: A Neural Model for Unsupervised Multi-Document Abstractive Summarization）</news:title>
   <news:publication_date>2026-06-23T05:42:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703851</loc>
  <lastmod>2026-06-23T05:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列逆問題に対する系列エンコーダーデコーダの一般化改善（Improving Generalization of Sequence Encoder-Decoder Networks for Inverse Imaging of Cardiac Transmembrane Potential）</news:title>
   <news:publication_date>2026-06-23T05:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703849</loc>
  <lastmod>2026-06-23T04:51:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能性志向の畳み込みフィルタ剪定（Functionality-Oriented Convolutional Filter Pruning）</news:title>
   <news:publication_date>2026-06-23T04:51:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703847</loc>
  <lastmod>2026-06-23T04:50:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小型銀河の星間媒質と星形成（The Interstellar Medium and Star Formation in Dwarf Galaxies）</news:title>
   <news:publication_date>2026-06-23T04:50:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703845</loc>
  <lastmod>2026-06-23T04:50:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-メドイド法を実務で速く回す技術（Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms）</news:title>
   <news:publication_date>2026-06-23T04:50:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703843</loc>
  <lastmod>2026-06-23T04:49:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションと現実のギャップを閉じる手法（Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience）</news:title>
   <news:publication_date>2026-06-23T04:49:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703841</loc>
  <lastmod>2026-06-23T04:49:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>惑星による塵環における塵のフィードバックの影響（Impacts of dust feedback on a dust ring induced by a planet in a protoplanetary disk）</news:title>
   <news:publication_date>2026-06-23T04:49:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703839</loc>
  <lastmod>2026-06-23T04:49:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的近接点法の拡張と安定性――aProxファミリが示す収束性と順応性（Stochastic (Approximate) Proximal Point Methods: Convergence, Optimality, and Adaptivity）</news:title>
   <news:publication_date>2026-06-23T04:49:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703837</loc>
  <lastmod>2026-06-23T04:48:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波面制御によって光学的複雑媒質を再構成可能な線形演算器にする（Turning Optical Complex Media into Universal Reconfigurable Linear Operators by Wavefront Shaping）</news:title>
   <news:publication_date>2026-06-23T04:48:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703835</loc>
  <lastmod>2026-06-23T03:57:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己位置をベクトルで、自己運動を行列で表すグリッド細胞モデル（LEARNING GRID CELLS AS VECTOR REPRESENTATION OF SELF-POSITION COUPLED WITH MATRIX REPRESENTATION OF SELF-MOTION）</news:title>
   <news:publication_date>2026-06-23T03:57:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703833</loc>
  <lastmod>2026-06-23T03:57:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォンのセンサで「歩行」と「車載」を見分ける実装ガイド（Custom Dual Transportation Mode Detection by Smartphone Devices Exploiting Sensor Diversity）</news:title>
   <news:publication_date>2026-06-23T03:57:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703831</loc>
  <lastmod>2026-06-23T03:56:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ターゲットラベルのバランス調整による公平性調整（TUNING FAIRNESS BY BALANCING TARGET LABELS）</news:title>
   <news:publication_date>2026-06-23T03:56:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703829</loc>
  <lastmod>2026-06-23T03:56:14Z</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深層強化学習の調査と批評 (A Survey and Critique of Multiagent Deep Reinforcement Learning)</news:title>
   <news:publication_date>2026-06-23T03:56:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703827</loc>
  <lastmod>2026-06-23T03:56:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低x領域のDGLAP進化における吸収効果とべき乗補正（Absorptive effects and power corrections in low x DGLAP evolution）</news:title>
   <news:publication_date>2026-06-23T03:56:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703825</loc>
  <lastmod>2026-06-23T03:55:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>液体状態に学習されたガウス過程による原子力の転移可能性（Machine learning forces trained by Gaussian process in liquid states: Transferability to temperature and pressure）</news:title>
   <news:publication_date>2026-06-23T03:55:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703823</loc>
  <lastmod>2026-06-23T03:55:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PointGrowによる点群生成の自己回帰モデル（PointGrow: Autoregressively Learned Point Cloud Generation with Self-Attention）</news:title>
   <news:publication_date>2026-06-23T03:55:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703821</loc>
  <lastmod>2026-06-23T03:04:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相関パターン抽出と凝縮表現（Extraction of Correlated Patterns and Condensed Representations）</news:title>
   <news:publication_date>2026-06-23T03:04:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703819</loc>
  <lastmod>2026-06-23T03:04:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類器の過信を暴く施設配置型ユーティリティ（Facility Locations Utility for Uncovering Classifier Overconfidence）</news:title>
   <news:publication_date>2026-06-23T03:04:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703817</loc>
  <lastmod>2026-06-23T03:04:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>海上交通の目的地と到着時刻のリアルタイム予測（Grand Challenge: Real-time Destination and ETA Prediction for Maritime Traffic）</news:title>
   <news:publication_date>2026-06-23T03:04:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703815</loc>
  <lastmod>2026-06-23T03:03:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Bayesian Monte Carlo（Variational Bayesian Monte Carlo）</news:title>
   <news:publication_date>2026-06-23T03:03:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703813</loc>
  <lastmod>2026-06-23T03:03:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WebはHTTP/2のServer Pushに準備できているか（Is the Web ready for HTTP/2 Server Push?）</news:title>
   <news:publication_date>2026-06-23T03:03:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703811</loc>
  <lastmod>2026-06-23T03:02:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察者が付与する「自分の意図」を推測する――公開的自己認識をベイズで推定する視点（Bayesian Inference of Self-intention Attributed by Observer）</news:title>
   <news:publication_date>2026-06-23T03:02:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703809</loc>
  <lastmod>2026-06-23T03:02:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像劣化がCNNベースの画像分類に与える影響（Effects of Image Degradations to CNN-based Image Classification）</news:title>
   <news:publication_date>2026-06-23T03:02:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703807</loc>
  <lastmod>2026-06-23T02:11:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元状態監視信号における異常検出のための特徴学習（FEATURE LEARNING FOR FAULT DETECTION IN HIGH-DIMENSIONAL CONDITION-MONITORING SIGNALS）</news:title>
   <news:publication_date>2026-06-23T02:11:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703805</loc>
  <lastmod>2026-06-23T02:01:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの不確実性推定を近似ベイズ化するアンサンブル手法（Uncertainty in Neural Networks: Approximately Bayesian Ensembling）</news:title>
   <news:publication_date>2026-06-23T02:01:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703803</loc>
  <lastmod>2026-06-23T02:00:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子化による予測不確実性の推定（PREDICTIVE UNCERTAINTY THROUGH QUANTIZATION）</news:title>
   <news:publication_date>2026-06-23T02:00:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703801</loc>
  <lastmod>2026-06-23T02:00:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの迅速な量子化展開（Quantization for Rapid Deployment of Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-23T02:00:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703799</loc>
  <lastmod>2026-06-23T01:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>持続的な公開参与が学習成果を上げる――実証された効果と導入上の検討点 (Impact arising from sustained public engagement: A measured increase in learning outcomes)</news:title>
   <news:publication_date>2026-06-23T01:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703797</loc>
  <lastmod>2026-06-23T01:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限定精度での深層ニューラルネットワークの学習（Training Deep Neural Network in Limited Precision）</news:title>
   <news:publication_date>2026-06-23T01:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703795</loc>
  <lastmod>2026-06-23T01:59:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U–Netによる未解答問題を扱う機械読解の統合モデル（U-Net: Machine Reading Comprehension with Unanswerable Questions）</news:title>
   <news:publication_date>2026-06-23T01:59:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703793</loc>
  <lastmod>2026-06-23T01:08:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適複雑度を持つ安全なグリッド探索（Safe Grid Search with Optimal Complexity）</news:title>
   <news:publication_date>2026-06-23T01:08:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703791</loc>
  <lastmod>2026-06-23T01:08:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Flickrタグと構造化データで場所を埋め込む方法（Embedding Geographic Locations for Modelling the Natural Environment using Flickr Tags and Structured Data）</news:title>
   <news:publication_date>2026-06-23T01:08:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703789</loc>
  <lastmod>2026-06-23T01:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モード正規化の提案（Mode Normalization）</news:title>
   <news:publication_date>2026-06-23T01:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703787</loc>
  <lastmod>2026-06-23T01:06:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トピック多様性測定のための階層的トピックモデル再推定（HiTR: Hierarchical Topic Model Re-estimation for Measuring Topical Diversity of Documents）</news:title>
   <news:publication_date>2026-06-23T01:06:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703785</loc>
  <lastmod>2026-06-23T01:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対応関係のない線形回帰を代数幾何で解く（An algebraic-geometric approach for linear regression without correspondences）</news:title>
   <news:publication_date>2026-06-23T01:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703783</loc>
  <lastmod>2026-06-23T01:06:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム自己適応深層ステレオ（Real-time self-adaptive deep stereo）</news:title>
   <news:publication_date>2026-06-23T01:06:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703781</loc>
  <lastmod>2026-06-23T01:06:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然画像か医療画像か：転移学習の最適な出発点を問う（Cats or CAT scans: transfer learning from natural or medical image source datasets?）</news:title>
   <news:publication_date>2026-06-23T01:06:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703771</loc>
  <lastmod>2026-06-23T00:14:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepScoresとDeep Watershed Detectionの現状と課題（DeepScores and Deep Watershed Detection: current state and open issues）</news:title>
   <news:publication_date>2026-06-23T00:14:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703769</loc>
  <lastmod>2026-06-23T00:14:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クライオ電子顕微鏡像の質を深層学習で改善する手法の実務的解説（CRYO-CARE: CONTENT-AWARE IMAGE RESTORATION FOR CRYO-TRANSMISSION ELECTRON MICROSCOPY DATA）</news:title>
   <news:publication_date>2026-06-23T00:14:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703767</loc>
  <lastmod>2026-06-23T00:14:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズのあるフィードバック下での深層強化学習オートエンコーダ（Deep Reinforcement Learning Autoencoder with Noisy Feedback）</news:title>
   <news:publication_date>2026-06-23T00:14:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703765</loc>
  <lastmod>2026-06-23T00:13:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像処理におけるディープラーニング入門（A Gentle Introduction to Deep Learning in Medical Image Processing）</news:title>
   <news:publication_date>2026-06-23T00:13:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703763</loc>
  <lastmod>2026-06-23T00:13:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最後の数件を見つけ出す対話型検索――Yes/No質問で総当たりを減らす方法（Technology Assisted Reviews: Finding the Last Few Relevant Documents by Asking Yes/No Questions to Reviewers）</news:title>
   <news:publication_date>2026-06-23T00:13:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703761</loc>
  <lastmod>2026-06-23T00:12:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的環境における動作予測の逐次学習（Sequential Learning of Movement Prediction in Dynamic Environments using LSTM Autoencoder）</news:title>
   <news:publication_date>2026-06-23T00:12:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703759</loc>
  <lastmod>2026-06-23T00:12:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>熱赤外画像のカラー化を可能にする条件付き敵対的生成ネットワーク（Thermal Infrared Colorization via Conditional Generative Adversarial Network）</news:title>
   <news:publication_date>2026-06-23T00:12:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703757</loc>
  <lastmod>2026-06-22T23:21:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド変分ニューラル協調フィルタリングが変える推薦の精度（Neural Variational Hybrid Collaborative Filtering）</news:title>
   <news:publication_date>2026-06-22T23:21:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703755</loc>
  <lastmod>2026-06-22T23:21:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業機器の残存使用可能寿命を予測する時間畳み込みメモリネットワーク（Temporal Convolutional Memory Networks for Remaining Useful Life Estimation of Industrial Machinery）</news:title>
   <news:publication_date>2026-06-22T23:21:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703753</loc>
  <lastmod>2026-06-22T23:20:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化が決め手になる時代：ニューラルネットと誘導カーネルの違い（Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel）</news:title>
   <news:publication_date>2026-06-22T23:20:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703751</loc>
  <lastmod>2026-06-22T23:20:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乗法的重み更新法が示す制約付き最適化での強収束性（Multiplicative Weights Update as a Distributed Constrained Optimization Algorithm: Convergence to Second-order Stationary Points Almost Always）</news:title>
   <news:publication_date>2026-06-22T23:20:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703749</loc>
  <lastmod>2026-06-22T23:19:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適な階層的学習パス設計と強化学習の応用（Optimal Hierarchical Learning Path Design with Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-22T23:19:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703747</loc>
  <lastmod>2026-06-22T23:19:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔スケッチから写真を生成する非教師あり学習による幾何学学習（Unsupervised Facial Geometry Learning for Sketch to Photo Synthesis）</news:title>
   <news:publication_date>2026-06-22T23:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703745</loc>
  <lastmod>2026-06-22T23:19:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種感度を持つ深層ニューラルネットワークの効率化（Efficient Architecture for Deep Neural Networks with Heterogeneous Sensitivity）</news:title>
   <news:publication_date>2026-06-22T23:19:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703743</loc>
  <lastmod>2026-06-22T22:28:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パノラミック深度マップによる4D人体対応関係の学習（4D Human Body Correspondences from Panoramic Depth Maps）</news:title>
   <news:publication_date>2026-06-22T22:28:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703741</loc>
  <lastmod>2026-06-22T22:27:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の異種多重リファレンス整列と単粒子再構成への応用（Heterogeneous multireference alignment for images with application to 2-D classification in single particle reconstruction）</news:title>
   <news:publication_date>2026-06-22T22:27:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703739</loc>
  <lastmod>2026-06-22T22:27:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的チャネルプルーニングによる計算効率化（Dynamic Channel Pruning: Feature Boosting and Suppression）</news:title>
   <news:publication_date>2026-06-22T22:27:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703737</loc>
  <lastmod>2026-06-22T22:26:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深部準位の同定に第一原理計算を適用する手法（Defect identification based on first-principles calculations for deep level transient spectroscopy）</news:title>
   <news:publication_date>2026-06-22T22:26:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703735</loc>
  <lastmod>2026-06-22T22:26:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分帯域ベースの時系列ニューラル音声合成モデル（A Fully Time-domain Neural Model for Subband-based Speech Synthesizer）</news:title>
   <news:publication_date>2026-06-22T22:26:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703733</loc>
  <lastmod>2026-06-22T22:26:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブロック安定性によるMAP推定の解析（Block Stability for MAP Inference）</news:title>
   <news:publication_date>2026-06-22T22:26:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703731</loc>
  <lastmod>2026-06-22T22:25:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による推論の自動化（Learning to Reason: Theorem proving at first order via reinforcement learning）</news:title>
   <news:publication_date>2026-06-22T22:25:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703729</loc>
  <lastmod>2026-06-22T21:34:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変更毎のテストを予測で絞る仕組み（Predictive Test Selection）</news:title>
   <news:publication_date>2026-06-22T21:34:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703727</loc>
  <lastmod>2026-06-22T21:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン多クラスブースティングとバンディットフィードバック（Online Multiclass Boosting with Bandit Feedback）</news:title>
   <news:publication_date>2026-06-22T21:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703725</loc>
  <lastmod>2026-06-22T21:34:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SIGNSGDと多数決による頑健で通信効率の良い分散学習（SIGNSGD WITH MAJORITY VOTE IS COMMUNICATION EFFICIENT AND FAULT TOLERANT）</news:title>
   <news:publication_date>2026-06-22T21:34:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703723</loc>
  <lastmod>2026-06-22T21:32:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク剪定の再考（RETHINKING THE VALUE OF NETWORK PRUNING）</news:title>
   <news:publication_date>2026-06-22T21:32:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703721</loc>
  <lastmod>2026-06-22T21:32:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドローン撮影による大規模車両軌跡データセットの構築と意義（The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems）</news:title>
   <news:publication_date>2026-06-22T21:32:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703719</loc>
  <lastmod>2026-06-22T21:32:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習を使わない敵対的テキスト生成（Adversarial Text Generation Without Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-22T21:32:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703717</loc>
  <lastmod>2026-06-22T21:32:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意の線形方程式に収束する二重確率的ガウス・ザイデル法（A Linearly Convergent Doubly Stochastic Gauss-Seidel Algorithm）</news:title>
   <news:publication_date>2026-06-22T21:32:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703715</loc>
  <lastmod>2026-06-22T20:40:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誰でも即興ピアノ演奏を可能にする「Piano Genie」の仕組み（Piano Genie）</news:title>
   <news:publication_date>2026-06-22T20:40:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703713</loc>
  <lastmod>2026-06-22T20:39:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>送電線故障のリアルタイム局所化とPMU設置最適化（Real-time Faulted Line Localization and PMU Placement in Power Systems through Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-06-22T20:39:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703711</loc>
  <lastmod>2026-06-22T20:39:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書ごとに最適なキーフレーズ数を生成・評価する方法（One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrases）</news:title>
   <news:publication_date>2026-06-22T20:39:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703709</loc>
  <lastmod>2026-06-22T20:38:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実用的な設計空間探索の手法（Practical Design Space Exploration）</news:title>
   <news:publication_date>2026-06-22T20:38:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703707</loc>
  <lastmod>2026-06-22T20:38:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>在庫配分とオンライン学習の統合による収益最適化（Inventory Balancing with Online Learning）</news:title>
   <news:publication_date>2026-06-22T20:38:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703705</loc>
  <lastmod>2026-06-22T20:38:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データのサブサンプリングによる効率的なデータ拡張（EFFICIENT AUGMENTATION VIA DATA SUBSAMPLING）</news:title>
   <news:publication_date>2026-06-22T20:38:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703703</loc>
  <lastmod>2026-06-22T20:37:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MDGANによる異常検知の強化（MDGAN: Boosting Anomaly Detection Using Multi-Discriminator Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-22T20:37:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703701</loc>
  <lastmod>2026-06-22T19:46:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布ロバストな送電網拡張計画（Distributionally Robust Transmission Expansion Planning）</news:title>
   <news:publication_date>2026-06-22T19:46:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703699</loc>
  <lastmod>2026-06-22T19:46:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムフーリエ特徴を用いたカーネル導関数近似（On Kernel Derivative Approximation with Random Fourier Features）</news:title>
   <news:publication_date>2026-06-22T19:46:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703697</loc>
  <lastmod>2026-06-22T19:46:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚認識のための敵対的メッシュ（MeshAdv: Adversarial Meshes for Visual Recognition）</news:title>
   <news:publication_date>2026-06-22T19:46:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703695</loc>
  <lastmod>2026-06-22T19:45:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユニットレベルで見るベイズニューラルネットワークの事前分布の理解（Understanding Priors in Bayesian Neural Networks at the Unit Level）</news:title>
   <news:publication_date>2026-06-22T19:45:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/703693</loc>
  <lastmod>2026-06-22T19:45:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モンテカルロ法のための量子システムと分数確率過程への応用 (Quantum Systems for Monte Carlo Methods and Applications to Fractional Stochastic Processes)</news:title>
   <news:publication_date>2026-06-22T19:45:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703691</loc>
  <lastmod>2026-06-22T19:44:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Riemannの未発表ノートが示した解析的整数論の道筋（On Riemann’s Nachlass for Analytic Number Theory）</news:title>
   <news:publication_date>2026-06-22T19:44:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703689</loc>
  <lastmod>2026-06-22T19:44:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インフレーションを情報ボトルネックとして捉える戦略（Inflation as an Information Bottleneck: A strategy for identifying universality classes and making robust predictions）</news:title>
   <news:publication_date>2026-06-22T19:44:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703687</loc>
  <lastmod>2026-06-22T18:53:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>若い星J1407の環を持つ伴星の軌道周期の制約（Constraining the period of the ringed secondary companion to the young star J1407）</news:title>
   <news:publication_date>2026-06-22T18:53:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703685</loc>
  <lastmod>2026-06-22T18:45:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒト細胞アトラス（The Human Cell Atlas）</news:title>
   <news:publication_date>2026-06-22T18:45:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703683</loc>
  <lastmod>2026-06-22T18:45:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>赤方偏移空間マップからのベイズ的宇宙密度復元（Bayesian cosmography from redshift space maps）</news:title>
   <news:publication_date>2026-06-22T18:45:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703681</loc>
  <lastmod>2026-06-22T18:43:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二乗でも1/2乗でもない低ランク復元の実用性を高める手法（Bilinear Factor Matrix Norm Minimization for Robust PCA）</news:title>
   <news:publication_date>2026-06-22T18:43:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703679</loc>
  <lastmod>2026-06-22T18:43:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アプリレビューからの機能抽出における注釈ガイドラインとデータの影響（The Impact of Annotation Guidelines and Annotated Data on Extracting App Features from App Reviews）</news:title>
   <news:publication_date>2026-06-22T18:43:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703677</loc>
  <lastmod>2026-06-22T18:43:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インフレーションを学ぶ（Learning to Inflate: A Gradient Ascent Approach to Random Inflation）</news:title>
   <news:publication_date>2026-06-22T18:43:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703675</loc>
  <lastmod>2026-06-22T18:42:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギーフローネットワーク：粒子ジェットのためのDeep Sets（Energy Flow Networks: Deep Sets for Particle Jets）</news:title>
   <news:publication_date>2026-06-22T18:42:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703673</loc>
  <lastmod>2026-06-22T17:51:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミススペシファイドな目的空間下での学習（Learning under Misspecified Objective Spaces）</news:title>
   <news:publication_date>2026-06-22T17:51:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703671</loc>
  <lastmod>2026-06-22T17:49:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボトムアップ注意（Bottom-up Attention, Models of）</news:title>
   <news:publication_date>2026-06-22T17:49:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703669</loc>
  <lastmod>2026-06-22T17:48:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャネル数が多いベイズ畳み込みニューラルネットワークはガウス過程である（Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes）</news:title>
   <news:publication_date>2026-06-22T17:48:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703667</loc>
  <lastmod>2026-06-22T17:48:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間的一貫性情報に基づく敵対的事例の特徴付け（Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation）</news:title>
   <news:publication_date>2026-06-22T17:48:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703665</loc>
  <lastmod>2026-06-22T17:48:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理法則に基づく深層ニューラルネットの正則化（Physics-Driven Regularization of Deep Neural Networks for Enhanced Engineering Design and Analysis）</news:title>
   <news:publication_date>2026-06-22T17:48:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703663</loc>
  <lastmod>2026-06-22T17:47:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続ランダムエネルギーモデルにおけるアルゴリズム的困難度の閾値（The algorithmic hardness threshold for continuous random energy models）</news:title>
   <news:publication_date>2026-06-22T17:47:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703661</loc>
  <lastmod>2026-06-22T17:47:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な機械による複数の秩序パラメータ学習（Learning multiple order parameters with interpretable machines）</news:title>
   <news:publication_date>2026-06-22T17:47:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703659</loc>
  <lastmod>2026-06-22T16:56:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文間をまたぐ関係抽出のニューラル手法（Neural Relation Extraction Within and Across Sentence Boundaries）</news:title>
   <news:publication_date>2026-06-22T16:56:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703657</loc>
  <lastmod>2026-06-22T16:55:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現実世界のネットワークの統計物理学（The Statistical Physics of Real-World Networks）</news:title>
   <news:publication_date>2026-06-22T16:55:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703655</loc>
  <lastmod>2026-06-22T16:55:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳児脳MRIのボクセル単位セグメンテーションを効率化するInfiNet（INFINET: FULLY CONVOLUTIONAL NETWORKS FOR INFANT BRAIN MRI SEGMENTATION）</news:title>
   <news:publication_date>2026-06-22T16:55:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703653</loc>
  <lastmod>2026-06-22T16:55:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>18F-FDG PETイメージングの最適な深層射影学習によるパーキンソン症候群の早期鑑別診断（Learning Optimal Deep Projection of 18F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes）</news:title>
   <news:publication_date>2026-06-22T16:55:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703651</loc>
  <lastmod>2026-06-22T16:54:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形パラメトリック偏微分方程式のバイアス排除型ディープソルバー（Unbiased Deep Solvers for Linear Parametric PDEs）</news:title>
   <news:publication_date>2026-06-22T16:54:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703649</loc>
  <lastmod>2026-06-22T16:54:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交差エントロピーの抑制版が示す頑健性の道筋（Taming the Cross Entropy Loss）</news:title>
   <news:publication_date>2026-06-22T16:54:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703647</loc>
  <lastmod>2026-06-22T16:54:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化付き文脈バンディット（Regularized Contextual Bandits）</news:title>
   <news:publication_date>2026-06-22T16:54:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703645</loc>
  <lastmod>2026-06-22T16:02:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍探索モデルの理論に基づく実践評価（A Theory-Based Evaluation of Nearest Neighbor Models Put Into Practice）</news:title>
   <news:publication_date>2026-06-22T16:02:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703643</loc>
  <lastmod>2026-06-22T16:02:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた画像デノイジングの概観（Deep Learning for Image Denoising: A Survey）</news:title>
   <news:publication_date>2026-06-22T16:02:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703641</loc>
  <lastmod>2026-06-22T16:01:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希薄ハドロンにおけるグルーオン密度の揺らぎ（Gluon density fluctuations in dilute hadrons）</news:title>
   <news:publication_date>2026-06-22T16:01:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703639</loc>
  <lastmod>2026-06-22T16:00:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンショット高忠実度模倣学習（ONE-SHOT HIGH-FIDELITY IMITATION: TRAINING LARGE-SCALE DEEP NETS WITH RL）</news:title>
   <news:publication_date>2026-06-22T16:00:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703637</loc>
  <lastmod>2026-06-22T16:00:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚特徴を用いた階層注意による食品推薦（Hierarchical Attention Network for Visually-aware Food Recommendation）</news:title>
   <news:publication_date>2026-06-22T16:00:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703635</loc>
  <lastmod>2026-06-22T16:00:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見た目から判断する適正速度予測の新領域（ISA2: Intelligent Speed Adaptation from Appearance）</news:title>
   <news:publication_date>2026-06-22T16:00:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703633</loc>
  <lastmod>2026-06-22T16:00:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>曲率が導く終末加速と永遠回帰の宇宙モデル（Curvature Late-Time Acceleration in an Eternal Universe）</news:title>
   <news:publication_date>2026-06-22T16:00:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703631</loc>
  <lastmod>2026-06-22T15:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チェリーピッキングへの簡単な対処法（A Simple Way to Deal with Cherry-picking）</news:title>
   <news:publication_date>2026-06-22T15:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703629</loc>
  <lastmod>2026-06-22T15:08:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SingleGANによる単一ジェネレータでのマルチドメイン画像変換（SingleGAN: Image-to-Image Translation by a Single-Generator Network using Multiple Generative Adversarial Learning）</news:title>
   <news:publication_date>2026-06-22T15:08:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703627</loc>
  <lastmod>2026-06-22T15:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分数階微分方程式を解くための人工ニューラルネットワーク手法（Artificial Neural Network Approach for Solving Fractional order initial value problems）</news:title>
   <news:publication_date>2026-06-22T15:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703625</loc>
  <lastmod>2026-06-22T15:07:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーシステンス・ランドスケープとその性質（The persistence landscape and some of its properties）</news:title>
   <news:publication_date>2026-06-22T15:07:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703623</loc>
  <lastmod>2026-06-22T15:07:15Z</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>2026-06-22T15:07:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/703621</loc>
  <lastmod>2026-06-22T15:07:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-22T15:07:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/703619</loc>
  <lastmod>2026-06-22T15:06:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-06-22T15:06:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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