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   <news:title>ハイパーボリック空間におけるテキスト埋め込み（Embedding Text in Hyperbolic Spaces）</news:title>
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   <news:title>深層学習によるタービン翼の圧力予測 (Pressure Predictions of Turbine Blades with Deep Learning)</news:title>
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   <news:title>視覚に基づくパラフレーズ抽出（iParaphrasing: Extracting Visually Grounded Paraphrases via an Image）</news:title>
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   <news:title>超大規模特徴選択のためのMISSION（MISSION: Feature Selection via Sketching）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>多様なオンライン特徴選択（Diverse Online Feature Selection）</news:title>
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    <news:language>ja</news:language>
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   <news:title>比較不可能コーパスから学ぶ多言語トピック（Learning Multilingual Topics from Incomparable Corpora）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>NES音楽データベースが示す「作曲」と「演奏表現」の分離可能性（The NES Music Database: A multi-instrumental dataset with expressive performance attributes）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>スニペット（パッチ）学習を“説明”から理解する（UNDERSTANDING PATCH-BASED LEARNING BY EXPLAINING PREDICTIONS）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>構造化出力予測の高速化学習（Learning to Speed Up Structured Output Prediction）</news:title>
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    <news:language>ja</news:language>
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   <news:title>戻り値分布を使った探索の可能性（The Potential of the Return Distribution for Exploration in RL）</news:title>
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    <news:language>ja</news:language>
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   <news:title>タスク駆動型生成モデルによる教師なしドメイン適応とX線画像セグメンテーション（Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-15T16:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>顔モーフィング攻撃検出に向けた頑健で高精度なニューラルネットワーク（Accurate and Robust Neural Networks for Security Related Applications Exampled by Face Morphing Attacks）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-15T15:42:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>視覚分析データベースのための物理表現に基づく述語最適化（Physical Representation-based Predicate Optimization for a Visual Analytics Database）</news:title>
   <news:publication_date>2026-05-15T15:42:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>NeuroNetによる脳画像セグメンテーションの統合化（NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-15T15:41:44Z</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>環境一般化が証明された制御方策の学習（PAC-Bayes Control: Learning Policies that Provably Generalize to Novel Environments）</news:title>
   <news:publication_date>2026-05-15T15:41:44Z</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>ローカル説明手法の感度に関する考察（A NOTE ABOUT: LOCAL EXPLANATION METHODS FOR DEEP NEURAL NETWORKS LACK SENSITIVITY TO PARAMETER VALUES）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/690498</loc>
  <lastmod>2026-05-15T15:40:59Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>確率的ブロックモデルの普遍性（Universality of the stochastic block model）</news:title>
   <news:publication_date>2026-05-15T15:40:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-15T15:40:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>群れ行動に学ぶ確率最適化の高速化（Swarming for Faster Convergence in Stochastic Optimization）</news:title>
   <news:publication_date>2026-05-15T15:40:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/690494</loc>
  <lastmod>2026-05-15T15:40:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>3D畳み込みニューラルネットワークによる機能的コネクトームの分類（3D Convolutional Neural Networks for Classification of Functional Connectomes）</news:title>
   <news:publication_date>2026-05-15T15:40:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/690492</loc>
  <lastmod>2026-05-15T14:48:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>半パラメトリックBARTによる異質な治療効果評価手法（A semiparametric modeling approach using Bayesian Additive Regression Trees with an application to evaluate heterogeneous treatment effects）</news:title>
   <news:publication_date>2026-05-15T14:48:55Z</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>訓練中に重みの大部分を「追わない」学習法が示す意義（Full deep neural network training on a pruned weight budget）</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>情報パーコレーション法のグラフ上再構成問題への応用 (Application of information-percolation method to reconstruction problems on graphs)</news:title>
   <news:publication_date>2026-05-15T14:48:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/690486</loc>
  <lastmod>2026-05-15T14:47:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>構文木へ一直線：ニューラル合成距離による句構造解析（Straight to the Tree: Constituency Parsing with Neural Syntactic Distance）</news:title>
   <news:publication_date>2026-05-15T14:47:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/690484</loc>
  <lastmod>2026-05-15T14:47:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>敵対的事例に対する防御研究の俯瞰（Defense Against the Dark Arts: An overview of adversarial example security research and future research directions）</news:title>
   <news:publication_date>2026-05-15T14:47:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/690482</loc>
  <lastmod>2026-05-15T14:47:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>映像予測のための表現分解と分離学習（Learning to Decompose and Disentangle Representations for Video Prediction）</news:title>
   <news:publication_date>2026-05-15T14:47:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-15T14:47:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似学習による保証付きモデル予測制御（Learning an Approximate Model Predictive Controller with Guarantees）</news:title>
   <news:publication_date>2026-05-15T14:47:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/690478</loc>
  <lastmod>2026-05-15T13:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化プリマル・デュアル法と適応ステップ幅（Randomized Primal-Dual Methods with Adaptive Step Sizes）</news:title>
   <news:publication_date>2026-05-15T13:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/690476</loc>
  <lastmod>2026-05-15T13:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補完データで全天マップを鮮明化する機械学習手法（Sharpening up Galactic all-sky maps with complementary data: A machine learning approach）</news:title>
   <news:publication_date>2026-05-15T13:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/690474</loc>
  <lastmod>2026-05-15T13:55:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響生成におけるオートエンコーダの実用比較（Autoencoders for music sound modeling: a comparison of linear, shallow, deep, recurrent and variational models）</news:title>
   <news:publication_date>2026-05-15T13:55:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690472</loc>
  <lastmod>2026-05-15T13:54:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協力を促す適応的メカニズム設計（Adaptive Mechanism Design: Learning to Promote Cooperation）</news:title>
   <news:publication_date>2026-05-15T13:54:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/690470</loc>
  <lastmod>2026-05-15T13:54:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子分解に基づく通信効率化学習（Atomo: Communication-efficient Learning via Atomic Sparsification）</news:title>
   <news:publication_date>2026-05-15T13:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/690468</loc>
  <lastmod>2026-05-15T13:54:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>セマンティックに選択されたデータ増強による軽量人物再識別（Semantically Selective Augmentation for Deep Compact Person Re-Identification）</news:title>
   <news:publication_date>2026-05-15T13:54:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/690466</loc>
  <lastmod>2026-05-15T13:53:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープスペックル相関：散乱媒体越えのスケーラブルなイメージング（Deep speckle correlation: a deep learning approach towards scalable imaging through scattering media）</news:title>
   <news:publication_date>2026-05-15T13:53:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/690464</loc>
  <lastmod>2026-05-15T13:02:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRI系列における動き推定とセグメンテーションの共同学習（Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences）</news:title>
   <news:publication_date>2026-05-15T13:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690462</loc>
  <lastmod>2026-05-15T13:02:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CT画像に現実的な肺結節を生成してセグメンテーションを強化する技術（CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation）</news:title>
   <news:publication_date>2026-05-15T13:02:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690460</loc>
  <lastmod>2026-05-15T13:01:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データ強化（High Dimensional Data Enrichment: Interpretable, Fast, and Data-Efficient）</news:title>
   <news:publication_date>2026-05-15T13:01:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690458</loc>
  <lastmod>2026-05-15T13:01:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メールの追跡（トラッキング）を見抜く機械学習手法（Robust Identification of Email Tracking: A Machine Learning Approach）</news:title>
   <news:publication_date>2026-05-15T13:01:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690456</loc>
  <lastmod>2026-05-15T13:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的な平行移動不変構造を持つ信号の適応的雑音除去（Adaptive Denoising of Signals with Local Shift-Invariant Structure）</news:title>
   <news:publication_date>2026-05-15T13:00:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690454</loc>
  <lastmod>2026-05-15T13:00:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制御された悪天候画像データセットとそのベースライン（Baselines and a datasheet for the Cerema AWP dataset）</news:title>
   <news:publication_date>2026-05-15T13:00:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690452</loc>
  <lastmod>2026-05-15T13:00:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数非開示データをまたいだ予測の集約とプライバシー保全（Aggregating Predictions on Multiple Non-disclosed Datasets using Conformal Prediction）</news:title>
   <news:publication_date>2026-05-15T13:00:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690450</loc>
  <lastmod>2026-05-15T12:09:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間表現による形状解析と学習（Latent Space Representation for Shape Analysis and Learning）</news:title>
   <news:publication_date>2026-05-15T12:09:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690448</loc>
  <lastmod>2026-05-15T12:08:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>屋内照明推定の学習法（Learning to Estimate Indoor Lighting from 3D Objects）</news:title>
   <news:publication_date>2026-05-15T12:08:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690446</loc>
  <lastmod>2026-05-15T12:08:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形時間論理（LTL）からの学習手法の実務的意義（Learning Linear Temporal Properties）</news:title>
   <news:publication_date>2026-05-15T12:08:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690444</loc>
  <lastmod>2026-05-15T12:07:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系外惑星大気スペクトル解析のための教師あり機械学習（Supervised Machine Learning for Analysing Spectra of Exoplanetary Atmospheres）</news:title>
   <news:publication_date>2026-05-15T12:07:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690442</loc>
  <lastmod>2026-05-15T12:07:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-NN分類のための高速で簡単な回帰手法（A Fast and Easy Regression Technique for k-NN Classification Without Using Negative Pairs）</news:title>
   <news:publication_date>2026-05-15T12:07:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690440</loc>
  <lastmod>2026-05-15T12:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィードフォワードニューラルネットワークにおけるローカリスト表現の出現条件（When and where do feed-forward neural networks learn localist representations?）</news:title>
   <news:publication_date>2026-05-15T12:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690438</loc>
  <lastmod>2026-05-15T12:07:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルを分割して速さで差をつける学習法（GEAR TRAINING: A NEW WAY TO IMPLEMENT HIGH-PERFORMANCE MODEL-PARALLEL TRAINING）</news:title>
   <news:publication_date>2026-05-15T12:07:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690436</loc>
  <lastmod>2026-05-15T11:15:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語シーン文字認識における疎オートエンコーダを用いた効率的局所特徴表現（Multilingual Scene Character Recognition System using Sparse Auto-Encoder for Efficient Local Features Representation in Bag of Features）</news:title>
   <news:publication_date>2026-05-15T11:15:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690434</loc>
  <lastmod>2026-05-15T11:15:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Projective Splittingの収束率解析（Convergence Rates for Projective Splitting）</news:title>
   <news:publication_date>2026-05-15T11:15:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690432</loc>
  <lastmod>2026-05-15T11:15:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜の視神経乳頭（optic disc）領域をcGANで自動抽出する手法（Retinal Optic Disc Segmentation using Conditional Generative Adversarial Network）</news:title>
   <news:publication_date>2026-05-15T11:15:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690430</loc>
  <lastmod>2026-05-15T11:14:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混雑状況における深度ベースの6次元姿勢推定と共同登録（Multi-Task Deep Networks for Depth-Based 6D Object Pose and Joint Registration in Crowd Scenarios）</news:title>
   <news:publication_date>2026-05-15T11:14:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690428</loc>
  <lastmod>2026-05-15T11:14:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重パターン学習ネットワークの提案（Dual Pattern Learning Networks by Empirical Dual Prediction Risk Minimization）</news:title>
   <news:publication_date>2026-05-15T11:14:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690426</loc>
  <lastmod>2026-05-15T11:14:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波信号のフラクタル性とマルチフラクタル性の計測意義（Fractal and multifractal properties of electrographic recordings of human brain activity）</news:title>
   <news:publication_date>2026-05-15T11:14:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690424</loc>
  <lastmod>2026-05-15T11:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>調査データからの日常的な通勤・通学往復のマルチタスク学習（Multi-task learning of daily work and study round-trips from survey data）</news:title>
   <news:publication_date>2026-05-15T11:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690422</loc>
  <lastmod>2026-05-15T10:22:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SDN向けフロー基盤の多段階ハイブリッド侵入検知（An Efficient Flow-based Multi-level Hybrid Intrusion Detection System for Software-Defined Networks）</news:title>
   <news:publication_date>2026-05-15T10:22:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690420</loc>
  <lastmod>2026-05-15T10:22:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多述語間相互作用を距離に依存せず捉える日本語述語項構造解析（Distance-Free Modeling of Multi-Predicate Interactions in End-to-End Japanese Predicate-Argument Structure Analysis）</news:title>
   <news:publication_date>2026-05-15T10:22:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690418</loc>
  <lastmod>2026-05-15T10:22:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Kronecker-factored Eigenbasisによる高速近似ナチュラル勾配法（Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis）</news:title>
   <news:publication_date>2026-05-15T10:22:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690416</loc>
  <lastmod>2026-05-15T10:21:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>産業向け物体検出と追跡の評価基準と改良相関フィルタ（Object Detection and Tracking Benchmark in Industry Based on Improved Correlation Filter）</news:title>
   <news:publication_date>2026-05-15T10:21:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690414</loc>
  <lastmod>2026-05-15T10:21:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質ガンマターン予測におけるInception Capsule Networkの応用（Improving Protein Gamma-Turn Prediction Using Inception Capsule Networks）</news:title>
   <news:publication_date>2026-05-15T10:21:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690412</loc>
  <lastmod>2026-05-15T10:21:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地理空間ベクトル多角形の分類における深層学習（Deep Learning for Classification Tasks on Geospatial Vector Polygons）</news:title>
   <news:publication_date>2026-05-15T10:21:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690410</loc>
  <lastmod>2026-05-15T10:21:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模並列ビデオネットワーク（Massively Parallel Video Networks）</news:title>
   <news:publication_date>2026-05-15T10:21:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690408</loc>
  <lastmod>2026-05-15T09:30:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成パーフュージョンマップによるDSC-MRI欠損検出の深層学習（Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning）</news:title>
   <news:publication_date>2026-05-15T09:30:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690406</loc>
  <lastmod>2026-05-15T09:29:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>曖昧な指示を解くマルチモーダルGAN（A Multimodal Classifier Generative Adversarial Network for Carry and Place Tasks from Ambiguous Language Instructions）</news:title>
   <news:publication_date>2026-05-15T09:29:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690404</loc>
  <lastmod>2026-05-15T09:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>明示的正則化の代わりにデータ拡張を使う（Data augmentation instead of explicit regularization）</news:title>
   <news:publication_date>2026-05-15T09:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690402</loc>
  <lastmod>2026-05-15T09:28:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ継続学習の要点を経営視点で読む（Meta Continual Learning）</news:title>
   <news:publication_date>2026-05-15T09:28:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690400</loc>
  <lastmod>2026-05-15T09:28:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン知識フリーの機械学習による解析接続（Analytic continuation via domain-knowledge free machine learning）</news:title>
   <news:publication_date>2026-05-15T09:28:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690398</loc>
  <lastmod>2026-05-15T09:28:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数局所サンプラーを組み合わせる適応MCMC（Adaptive MCMC via Combining Local Samplers）</news:title>
   <news:publication_date>2026-05-15T09:28:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690396</loc>
  <lastmod>2026-05-15T09:28:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ的モデル不可知メタラーニングの要点解説（Bayesian Model-Agnostic Meta-Learning）</news:title>
   <news:publication_date>2026-05-15T09:28:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690394</loc>
  <lastmod>2026-05-15T08:36:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>候補群の依存性とアルゴリズム依存性を同時に扱う一般化誤差評価（Chaining Mutual Information and Tightening Generalization Bounds）</news:title>
   <news:publication_date>2026-05-15T08:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690392</loc>
  <lastmod>2026-05-15T08:27:22Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-15T08:27:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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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>メタ学習の自動アーキテクチャ探索（Automated Gradient Based Meta Learner Search）</news:title>
   <news:publication_date>2026-05-15T08:26:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数データセット横断の人物再識別と類似性保持生成対向ネットワーク（Cross-dataset Person Re-Identification Using Similarity Preserved Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-15T08:25:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690384</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-15T08:25:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690382</loc>
  <lastmod>2026-05-15T08:25:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈認識型ポリシー再利用（Context-Aware Policy Reuse）</news:title>
   <news:publication_date>2026-05-15T08:25:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690380</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子データに対する微分幾何学ベースの幾何学的学習（DG-GL: Differential geometry based geometric learning of molecular datasets）</news:title>
   <news:publication_date>2026-05-15T07:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690378</loc>
  <lastmod>2026-05-15T07:33:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像からの物体オクルージョン境界検出の深層手法（DOOBNet: Deep Object Occlusion Boundary Detection from an Image）</news:title>
   <news:publication_date>2026-05-15T07:33:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690376</loc>
  <lastmod>2026-05-15T07:33:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク幅が大規模バッチ学習性能に与える影響（The Effect of Network Width on the Performance of Large-batch Training）</news:title>
   <news:publication_date>2026-05-15T07:33:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690374</loc>
  <lastmod>2026-05-15T07:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次元Dzyaloshinskii–Moriya強磁性体への機械学習応用（Machine Learning Application to Two-Dimensional Dzyaloshinskii-Moriya Ferromagnets）</news:title>
   <news:publication_date>2026-05-15T07:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690372</loc>
  <lastmod>2026-05-15T07:33:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平滑化解析による低ランク手法の評価（Smoothed analysis of the low-rank approach for smooth semidefinite programs）</news:title>
   <news:publication_date>2026-05-15T07:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690370</loc>
  <lastmod>2026-05-15T07:32:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークの状態空間表現（State Space Representations of Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-15T07:32:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690368</loc>
  <lastmod>2026-05-15T07:32:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絶滅危機言語Grikoの品詞タグ付け資源と評価（Part-of-Speech Tagging on an Endangered Language: a Parallel Griko-Italian Resource）</news:title>
   <news:publication_date>2026-05-15T07:32:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690366</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈付き形態変化のための構造化変分オートエンコーダ（A Structured Variational Autoencoder for Contextual Morphological Inflection）</news:title>
   <news:publication_date>2026-05-15T06:41:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690364</loc>
  <lastmod>2026-05-15T06:41:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同形語による形態曖昧性を無監督で解消する手法（Unsupervised Disambiguation of Syncretism in Inflected Lexicons）</news:title>
   <news:publication_date>2026-05-15T06:41:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690362</loc>
  <lastmod>2026-05-15T06:40:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応型セッションベース推薦のためのコンテキストツリー（Context Tree for Adaptive Session-based Recommendation）</news:title>
   <news:publication_date>2026-05-15T06:40:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690360</loc>
  <lastmod>2026-05-15T06:40:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Smallify: 学習中にネットワークサイズを決める（Smallify: Learning Network Size while Training）</news:title>
   <news:publication_date>2026-05-15T06:40:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690358</loc>
  <lastmod>2026-05-15T06:39:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回答埋め込みを学習するVisual QA（Learning Answer Embeddings for Visual Question Answering）</news:title>
   <news:publication_date>2026-05-15T06:39:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690356</loc>
  <lastmod>2026-05-15T06:39:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスデータセット適応によるVisual QAの汎化（Cross-Dataset Adaptation for Visual Question Answering）</news:title>
   <news:publication_date>2026-05-15T06:39:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690354</loc>
  <lastmod>2026-05-15T06:39:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層生成モデルを用いた確率的地震波形インバージョン（Stochastic Seismic Waveform Inversion using Generative Adversarial Networks as a Geological Prior）</news:title>
   <news:publication_date>2026-05-15T06:39:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690352</loc>
  <lastmod>2026-05-15T05:47:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>建設現場の油・重金属汚染土壌のバイオレメディエーション事例（Bioremediation of oil and heavy metal contaminated soil in construction sites: a case study of using bioventing-biosparging and phytoextraction techniques）</news:title>
   <news:publication_date>2026-05-15T05:47:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690350</loc>
  <lastmod>2026-05-15T05:47:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>噂（Rumour）検証のためのオールインワン・マルチタスク学習（All-in-one: Multi-task Learning for Rumour Verification）</news:title>
   <news:publication_date>2026-05-15T05:47:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690348</loc>
  <lastmod>2026-05-15T05:46:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中国語のゼロ代名詞解決に深層強化学習を使う意義（Deep Reinforcement Learning for Chinese Zero Pronoun Resolution）</news:title>
   <news:publication_date>2026-05-15T05:46:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690346</loc>
  <lastmod>2026-05-15T05:46:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型乱流モデルのための深層ニューラルネットワーク（Deep Neural Networks for Data-Driven Turbulence Models）</news:title>
   <news:publication_date>2026-05-15T05:46:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690344</loc>
  <lastmod>2026-05-15T05:46:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デコンボリューションを用いたグローバルデコーディングによる機械翻訳（Deconvolution-Based Global Decoding for Neural Machine Translation）</news:title>
   <news:publication_date>2026-05-15T05:46:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690342</loc>
  <lastmod>2026-05-15T05:45:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無監督動画間変換（Unsupervised Video-to-Video Translation）</news:title>
   <news:publication_date>2026-05-15T05:45:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690340</loc>
  <lastmod>2026-05-15T05:45:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法務・規制文書のための自然言語処理と情報抽出（LexNLP: Natural language processing and information extraction for legal and regulatory texts）</news:title>
   <news:publication_date>2026-05-15T05:45:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690338</loc>
  <lastmod>2026-05-15T04:54:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>散逸性理論による確率的分散削減の加速化（Dissipativity Theory for Accelerating Stochastic Variance Reduction）</news:title>
   <news:publication_date>2026-05-15T04:54:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690336</loc>
  <lastmod>2026-05-15T04:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス確率的グラフィカルモデルの識別可能性（Identifiability in Gaussian Graphical Models）</news:title>
   <news:publication_date>2026-05-15T04:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690334</loc>
  <lastmod>2026-05-15T04:54:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選ばれた個体の共分散は景観のヘッセ行列の逆に近づく（On the Covariance-Hessian Relation in Evolution Strategies）</news:title>
   <news:publication_date>2026-05-15T04:54:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690332</loc>
  <lastmod>2026-05-15T04:53:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>鉛管探索のための能動的除去（ActiveRemediation: The Search for Lead Pipes in Flint, Michigan）</news:title>
   <news:publication_date>2026-05-15T04:53:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690330</loc>
  <lastmod>2026-05-15T04:53:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字ベースのBiLSTM+CRFによる疾患固有表現抽出（Neural Disease Named Entity Extraction with Character-based BiLSTM+CRF in Japanese Medical Text）</news:title>
   <news:publication_date>2026-05-15T04:53:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690328</loc>
  <lastmod>2026-05-15T04:53:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的環境における深層好奇心ループ（Deep Curiosity Loops in Social Environments）</news:title>
   <news:publication_date>2026-05-15T04:53:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690326</loc>
  <lastmod>2026-05-15T04:52:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きノイズ対比推定による非正規化モデルの推定（Conditional Noise-Contrastive Estimation of Unnormalised Models）</news:title>
   <news:publication_date>2026-05-15T04:52:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690324</loc>
  <lastmod>2026-05-15T04:01:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-15T04:01:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690322</loc>
  <lastmod>2026-05-15T04:00:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間文脈を取り入れた音声単語埋め込みの学習（Learning Acoustic Word Embeddings with Temporal Context for Query-by-Example Speech Search）</news:title>
   <news:publication_date>2026-05-15T04:00:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/690320</loc>
  <lastmod>2026-05-15T04:00:28Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
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    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-15T02:15:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-14T23:26:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-14T23:26:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-14T23:26:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Angular Softmax損失を用いたエンドツーエンド話者認証（Angular Softmax Loss for End-to-end Speaker Verification）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690242</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相対的重要度を測るハイブリッド・アプローチ（A hybrid econometric-machine learning approach for relative importance analysis: Prioritizing food policy）</news:title>
   <news:publication_date>2026-05-14T23:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前知識を取り入れた階層的クラスタリング（Hierarchical Clustering with Prior Knowledge）</news:title>
   <news:publication_date>2026-05-14T22:34:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-14T22:34:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-14T22:34:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690234</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互結合を考慮した希薄ベイズ学習による方向推定（Direction Finding based on Sparse Bayesian Learning with Mutual Coupling）</news:title>
   <news:publication_date>2026-05-14T22:33:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690232</loc>
  <lastmod>2026-05-14T22:33:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストレッチ回帰（Deterministic Stretchy Regression）</news:title>
   <news:publication_date>2026-05-14T22:33:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690230</loc>
  <lastmod>2026-05-14T22:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローレンツモデルによる連続階層の学習（Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry）</news:title>
   <news:publication_date>2026-05-14T22:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690228</loc>
  <lastmod>2026-05-14T22:33:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>茎位置検出と作物・雑草分類による植物特異的処理（Joint Stem Detection and Crop-Weed Classification for Plant-specific Treatment）</news:title>
   <news:publication_date>2026-05-14T22:33:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690226</loc>
  <lastmod>2026-05-14T21:41:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトメトリック赤方偏移と銀河形態の大規模カタログ化（A catalog of photometric redshift and the distribution of broad galaxy morphologies）</news:title>
   <news:publication_date>2026-05-14T21:41:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690224</loc>
  <lastmod>2026-05-14T21:41:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表形式データの合成とプライバシー保護（Data Synthesis based on Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-14T21:41:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690222</loc>
  <lastmod>2026-05-14T21:40:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>間接的な同所性リンクを持つグラフモデル（A Graph Model with Indirect Co-location Links）</news:title>
   <news:publication_date>2026-05-14T21:40:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690220</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文化投資と都市の社会経済発展：ジオソーシャルネットワークの視点から（Cultural Investment and Urban Socio-Economic Development: A Geo-Social Network Approach）</news:title>
   <news:publication_date>2026-05-14T21:39:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PipeDreamによる高速で効率的なパイプライン並列DNN訓練（PipeDream: Fast and Efficient Pipeline Parallel DNN Training）</news:title>
   <news:publication_date>2026-05-14T21:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690216</loc>
  <lastmod>2026-05-14T21:39:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図の不整脈自動注釈を行う深層ネットワークの手法（Method to Annotate Arrhythmias by Deep Network）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690214</loc>
  <lastmod>2026-05-14T21:39:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮センシング画像による視覚的質問応答（CS-VQA: VISUAL QUESTION ANSWERING WITH COMPRESSIVELY SENSED IMAGES）</news:title>
   <news:publication_date>2026-05-14T21:39:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己監督信号による物体発見と検出（Self-supervisory Signals for Object Discovery and Detection）</news:title>
   <news:publication_date>2026-05-14T20:47:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-14T20:37:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>窓の中身で人を見分ける融合手法の提案（A Content-Based Late Fusion Approach Applied to Pedestrian Detection）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690206</loc>
  <lastmod>2026-05-14T20:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DSSLIC：深層セマンティック分割に基づく多層画像圧縮（Deep Semantic Segmentation-based Layered Image Compression）</news:title>
   <news:publication_date>2026-05-14T20:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690204</loc>
  <lastmod>2026-05-14T20:36:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-14T20:36:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690202</loc>
  <lastmod>2026-05-14T20:35:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>High cadence観測が切り拓く小惑星検出の新領域（Asteroids in the High Cadence Transient Survey）</news:title>
   <news:publication_date>2026-05-14T20:35:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690200</loc>
  <lastmod>2026-05-14T20:35:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Web情報からサイバー攻撃を予測する技術（Discovering Signals from Web Sources to Predict Cyber Attacks）</news:title>
   <news:publication_date>2026-05-14T20:35:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690198</loc>
  <lastmod>2026-05-14T19:44:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化事前関数による強化学習の不確実性制御（Randomized Prior Functions for Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-14T19:44:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690196</loc>
  <lastmod>2026-05-14T19:43:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手術動作の教師なし表現学習—未来予測でモーションを捉える（Unsupervised Learning for Surgical Motion by Learning to Predict the Future）</news:title>
   <news:publication_date>2026-05-14T19:43:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690194</loc>
  <lastmod>2026-05-14T19:42:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>4トン級デモンストレーターによる大規模二相液体アルゴンTPCの実証（A 4 tonne demonstrator for large-scale dual-phase liquid argon time projection chambers）</news:title>
   <news:publication_date>2026-05-14T19:42:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690192</loc>
  <lastmod>2026-05-14T19:42:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュートリノ実験におけるミリチャージ粒子の探索（Millicharged particles in neutrino experiments）</news:title>
   <news:publication_date>2026-05-14T19:42:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690190</loc>
  <lastmod>2026-05-14T19:42:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きマルチセットオートマトンと正規表現のアルゴリズムと学習（Algorithms and Training for Weighted Multiset Automata and Regular Expressions）</news:title>
   <news:publication_date>2026-05-14T19:42:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690188</loc>
  <lastmod>2026-05-14T19:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的サンプルを想定したメタラーニングの実践（Adversarial Meta-Learning）</news:title>
   <news:publication_date>2026-05-14T19:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690186</loc>
  <lastmod>2026-05-14T19:41:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Slalom: 信頼できるハードウェア上での高速・検証可能・プライベートなニューラルネットワーク実行（SLALOM: FAST, VERIFIABLE AND PRIVATE EXECUTION OF NEURAL NETWORKS IN TRUSTED HARDWARE）</news:title>
   <news:publication_date>2026-05-14T19:41:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690184</loc>
  <lastmod>2026-05-14T18:50:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>順序情報で次元の呪いを逃れる回帰（Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information）</news:title>
   <news:publication_date>2026-05-14T18:50:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690182</loc>
  <lastmod>2026-05-14T18:50:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pricing Engine: 実務データで因果推定を組み込むための実装（Pricing Engine: Estimating Causal Impacts in Real World Business Settings）</news:title>
   <news:publication_date>2026-05-14T18:50:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-14T18:50:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビッグデータからのデータラーニング（Data learning from big data）</news:title>
   <news:publication_date>2026-05-14T18:50:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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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>分布ベース均衡とRBF分類器によるソフトウェア欠陥予測の最適化（DBBRBF - Convalesce optimization for software defect prediction problem using hybrid distribution base balance instance selection and radial basis Function classifier）</news:title>
   <news:publication_date>2026-05-14T18:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690174</loc>
  <lastmod>2026-05-14T18:48:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話型レコメンダーシステムの統合的提案（Conversational Recommender System）</news:title>
   <news:publication_date>2026-05-14T18:48:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690172</loc>
  <lastmod>2026-05-14T18:48:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗闇の正義：暗号化された敏感属性による公平性（Blind Justice: Fairness with Encrypted Sensitive Attributes）</news:title>
   <news:publication_date>2026-05-14T18:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690170</loc>
  <lastmod>2026-05-14T17:56:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>掘削ビットでの岩石種識別を実現するデータ駆動モデル（Data-driven model for the identification of the rock type at a drilling bit）</news:title>
   <news:publication_date>2026-05-14T17:56:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690168</loc>
  <lastmod>2026-05-14T17:56:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全自動断面検出による撮像ビュー計画の革新（Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents）</news:title>
   <news:publication_date>2026-05-14T17:56:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690166</loc>
  <lastmod>2026-05-14T17:56:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長さ正規化を組み込んだエンドツーエンド話者認証の解析（Analysis of Length Normalization in End-to-End Speaker Verification System）</news:title>
   <news:publication_date>2026-05-14T17:56:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690164</loc>
  <lastmod>2026-05-14T17:55:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>整数潜在変数モデルにおける学習と入れ子自動微分（Learning in Integer Latent Variable Models with Nested Automatic Differentiation）</news:title>
   <news:publication_date>2026-05-14T17:55:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690162</loc>
  <lastmod>2026-05-14T17:55:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>よく調整されたラッソ（The Well Tempered Lasso）</news:title>
   <news:publication_date>2026-05-14T17:55:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690160</loc>
  <lastmod>2026-05-14T17:54:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wave-U-Netによる時間領域エンドツーエンド音源分離（WAVE-U-NET: A MULTI-SCALE NEURAL NETWORK FOR END-TO-END AUDIO SOURCE SEPARATION）</news:title>
   <news:publication_date>2026-05-14T17:54:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690158</loc>
  <lastmod>2026-05-14T17:54:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データを量子化に合わせる発想の転換（Spreading Vectors for Similarity Search）</news:title>
   <news:publication_date>2026-05-14T17:54:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690156</loc>
  <lastmod>2026-05-14T17:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語感情分析：少量データ向けRNNフレームワーク（Multilingual Sentiment Analysis: An RNN-Based Framework for Limited Data）</news:title>
   <news:publication_date>2026-05-14T17:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690154</loc>
  <lastmod>2026-05-14T17:03:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CBRに基づくBAM切替えの類似度関数評価（Evaluating CBR Similarity Functions for BAM Switching in Networks with Dynamic Traffic Profile）</news:title>
   <news:publication_date>2026-05-14T17:03:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690152</loc>
  <lastmod>2026-05-14T17:02:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理制約付き逆解析による土壌水分と植生水分の高解像度取得（A Physically Constrained Inversion for Super-resolved Passive Microwave Retrieval of Soil Moisture and Vegetation Water Content in L-band）</news:title>
   <news:publication_date>2026-05-14T17:02:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690150</loc>
  <lastmod>2026-05-14T17:01:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フィデリティに基づく確率的Q学習による量子システム制御（Fidelity-based Probabilistic Q-learning for Control of Quantum Systems）</news:title>
   <news:publication_date>2026-05-14T17:01:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690148</loc>
  <lastmod>2026-05-14T17:01:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ更新を伴うニューラルメッセージパッシングによる分子・材料の性質予測（Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials）</news:title>
   <news:publication_date>2026-05-14T17:01:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690146</loc>
  <lastmod>2026-05-14T17:01:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子システムの推定とロバスト制御に関する最近の進展（Several recent developments in estimation and robust control of quantum systems）</news:title>
   <news:publication_date>2026-05-14T17:01:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690144</loc>
  <lastmod>2026-05-14T17:00:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックスFDRの実用化（Black Box FDR）</news:title>
   <news:publication_date>2026-05-14T17:00:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690142</loc>
  <lastmod>2026-05-14T16:10:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型GANによる具現化された自己認識モデルの学習（HIERARCHY OF GANS FOR LEARNING EMBODIED SELF-AWARENESS MODEL）</news:title>
   <news:publication_date>2026-05-14T16:10:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690140</loc>
  <lastmod>2026-05-14T16:09:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習によるCICY三次元多様体の解析（Machine Learning CICY Threefolds）</news:title>
   <news:publication_date>2026-05-14T16:09:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690138</loc>
  <lastmod>2026-05-14T16:09:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語サブスペースによるテキスト分類（Text Classification based on Word Subspace with Term-Frequency）</news:title>
   <news:publication_date>2026-05-14T16:09:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690136</loc>
  <lastmod>2026-05-14T16:08:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間差分変分オートエンコーダ（Temporal Difference Variational Auto-Encoder）</news:title>
   <news:publication_date>2026-05-14T16:08:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690134</loc>
  <lastmod>2026-05-14T16:08:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stein変分ニュートン法（A Stein variational Newton method）</news:title>
   <news:publication_date>2026-05-14T16:08:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690132</loc>
  <lastmod>2026-05-14T16:08:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確かさを利用したサニティチェックによる術後脳腫瘍腔セグメンテーション（Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation）</news:title>
   <news:publication_date>2026-05-14T16:08:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690130</loc>
  <lastmod>2026-05-14T16:07:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回転対称性を活かした病理画像向け畳み込みニューラルネットワーク（Rotation Equivariant CNNs for Digital Pathology）</news:title>
   <news:publication_date>2026-05-14T16:07:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690128</loc>
  <lastmod>2026-05-14T15:16:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人物認識における同定と文脈学習の統合（Unifying Identification and Context Learning for Person Recognition）</news:title>
   <news:publication_date>2026-05-14T15:16:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690126</loc>
  <lastmod>2026-05-14T15:16:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディップル図における深非弾的散乱のNLO軟グルーオン発散の因数分解（Factorization of the soft gluon divergence from the dipole picture deep inelastic scattering cross sections at next-to-leading order）</news:title>
   <news:publication_date>2026-05-14T15:16:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690124</loc>
  <lastmod>2026-05-14T15:15:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からの深度推定における深層マルチスケール構造（DEEP MULTI-SCALE ARCHITECTURES FOR MONOCULAR DEPTH ESTIMATION）</news:title>
   <news:publication_date>2026-05-14T15:15:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690122</loc>
  <lastmod>2026-05-14T15:15:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D FCN特徴駆動回帰フォレストによる膵臓局在化とセグメンテーション（3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation）</news:title>
   <news:publication_date>2026-05-14T15:15:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690120</loc>
  <lastmod>2026-05-14T15:14:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ID対スポット顔認証における大規模二枚学習（Large-scale Bisample Learning on ID Versus Spot Face Recognition）</news:title>
   <news:publication_date>2026-05-14T15:14:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690118</loc>
  <lastmod>2026-05-14T15:14:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路上の車種・型式識別に向けた教師なし特徴学習（Unsupervised Feature Learning Toward a Real-time Vehicle Make and Model Recognition）</news:title>
   <news:publication_date>2026-05-14T15:14:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690116</loc>
  <lastmod>2026-05-14T15:13:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新生児けいれん検出における深い全畳み込みネットワークの適用（A Fully Convolutional Architecture for Neonatal Seizure Detection）</news:title>
   <news:publication_date>2026-05-14T15:13:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690114</loc>
  <lastmod>2026-05-14T14:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細菌群集の空間認識（Spatial Awareness of a Bacterial Swarm）</news:title>
   <news:publication_date>2026-05-14T14:22:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690112</loc>
  <lastmod>2026-05-14T14:14:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星画像上の航空機のドメイン適応生成（Domain Adaptive Generation of Aircraft on Satellite Imagery via Simulated and Unsupervised Learning）</news:title>
   <news:publication_date>2026-05-14T14:14:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690110</loc>
  <lastmod>2026-05-14T14:14:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大腸内視鏡追跡のための機械学習に基づく大腸変形推定法（Machine learning-based colon deformation estimation method for colonoscope tracking）</news:title>
   <news:publication_date>2026-05-14T14:14:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690108</loc>
  <lastmod>2026-05-14T14:13:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ付加による可視化手法の理論解析（Noise-adding Methods of Saliency Map as Series of Higher Order Partial Derivative）</news:title>
   <news:publication_date>2026-05-14T14:13:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690106</loc>
  <lastmod>2026-05-14T14:13:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>q空間における新奇検出と変分オートエンコーダ（q-Space Novelty Detection with Variational Autoencoders）</news:title>
   <news:publication_date>2026-05-14T14:13:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690104</loc>
  <lastmod>2026-05-14T14:12:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学レベルの遠隔授業用ロボット望遠鏡（A Robotic Telescope For University-Level Distance Teaching）</news:title>
   <news:publication_date>2026-05-14T14:12:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690102</loc>
  <lastmod>2026-05-14T14:12:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲートをほぼ0/1へ誘導するLSTM訓練法（Towards Binary-Valued Gates for Robust LSTM Training）</news:title>
   <news:publication_date>2026-05-14T14:12:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690100</loc>
  <lastmod>2026-05-14T13:20:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車種細分類のための最新深層学習アーキテクチャの体系的評価（A Systematic Evaluation of Recent Deep Learning Architectures for Fine-Grained Vehicle Classification）</news:title>
   <news:publication_date>2026-05-14T13:20:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690098</loc>
  <lastmod>2026-05-14T13:20:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファイアーム画像の精密検索を改善する手法（DeepFirearm: Learning Discriminative Feature Representation for Fine-grained Firearm Retrieval）</news:title>
   <news:publication_date>2026-05-14T13:20:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690096</loc>
  <lastmod>2026-05-14T13:19:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続時間価値関数近似とカーネル手法の統合（Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces）</news:title>
   <news:publication_date>2026-05-14T13:19:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690094</loc>
  <lastmod>2026-05-14T13:19:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PACランキングとMNLモデルの適応的探索（PAC Ranking from Pairwise and Listwise Queries: Lower Bounds and Upper Bounds）</news:title>
   <news:publication_date>2026-05-14T13:19:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690092</loc>
  <lastmod>2026-05-14T13:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モンジュ輸送がベイズを鈍らせる：敵対的訓練の困難性（Monge blunts Bayes: Hardness Results for Adversarial Training）</news:title>
   <news:publication_date>2026-05-14T13:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690090</loc>
  <lastmod>2026-05-14T13:18:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JointGANによる多領域結合分布学習（JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets）</news:title>
   <news:publication_date>2026-05-14T13:18:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690088</loc>
  <lastmod>2026-05-14T13:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銅表面拡散のためのニューラルネットワーク適用（Application of artificial neural networks for rigid lattice kinetic Monte Carlo studies of Cu surface diffusion）</news:title>
   <news:publication_date>2026-05-14T13:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690086</loc>
  <lastmod>2026-05-14T12:27:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なフル行列適応正則化（Efficient Full-Matrix Adaptive Regularization）</news:title>
   <news:publication_date>2026-05-14T12:27:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690084</loc>
  <lastmod>2026-05-14T12:26:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車とオートバイが同じ道路を通行する際のブラジルナッツ効果（Brazil Nut Effect in Roads that Allow Cars and Motorbikes to Pass Through）</news:title>
   <news:publication_date>2026-05-14T12:26:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690082</loc>
  <lastmod>2026-05-14T12:26:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識ベース記述から学ぶエンティティと文書表現（Representation Learning of Entities and Documents from Knowledge Base Descriptions）</news:title>
   <news:publication_date>2026-05-14T12:26:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690080</loc>
  <lastmod>2026-05-14T12:25:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群セグメンテーションのための正則化グラフCNN（RGCNN: Regularized Graph CNN for Point Cloud Segmentation）</news:title>
   <news:publication_date>2026-05-14T12:25:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690078</loc>
  <lastmod>2026-05-14T12:25:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元ランダム偏微分方程式に対する深層ニューラルネットワーク代替モデル（A Deep Neural Network Surrogate for High-Dimensional Random Partial Differential Equations）</news:title>
   <news:publication_date>2026-05-14T12:25:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690076</loc>
  <lastmod>2026-05-14T12:24:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dank Learning: ミーム生成における深層ニューラルネットワークの応用（Dank Learning: Generating Memes Using Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-14T12:24:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690074</loc>
  <lastmod>2026-05-14T12:24:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コミュニティベースのベイズ的真実発見におけるソーシャルネットワーク情報の活用（Using Social Network Information in Community-based Bayesian Truth Discovery）</news:title>
   <news:publication_date>2026-05-14T12:24:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690072</loc>
  <lastmod>2026-05-14T11:33:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SupportNetで解く増分学習の壊滅的忘却（SupportNet: solving catastrophic forgetting in class incremental learning with support data）</news:title>
   <news:publication_date>2026-05-14T11:33:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690070</loc>
  <lastmod>2026-05-14T11:33:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布距離に基づく因果効果（Causal effects based on distributional distances）</news:title>
   <news:publication_date>2026-05-14T11:33:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690068</loc>
  <lastmod>2026-05-14T11:33:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列残差を用いた畳み込み型動画ステガノグラフィ（Convolutional Video Steganography with Temporal Residual Modeling）</news:title>
   <news:publication_date>2026-05-14T11:33:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690066</loc>
  <lastmod>2026-05-14T11:32:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による探索誘導型プログラム合成（Program Synthesis Through Reinforcement Learning Guided Tree Search）</news:title>
   <news:publication_date>2026-05-14T11:32:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690064</loc>
  <lastmod>2026-05-14T11:32:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙分布の勾配推定に対するスペクトル手法（A Spectral Approach to Gradient Estimation for Implicit Distributions）</news:title>
   <news:publication_date>2026-05-14T11:32:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690062</loc>
  <lastmod>2026-05-14T11:31:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近隣から学ぶ：少数注釈から多様な出力を学習する手法（Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations）</news:title>
   <news:publication_date>2026-05-14T11:31:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690060</loc>
  <lastmod>2026-05-14T11:31:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ拡張で無限化した問題に対する軽量確率的最適化（Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data）</news:title>
   <news:publication_date>2026-05-14T11:31:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690058</loc>
  <lastmod>2026-05-14T10:40:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的リスクの再検討（Revisiting Adversarial Risk）</news:title>
   <news:publication_date>2026-05-14T10:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690056</loc>
  <lastmod>2026-05-14T10:40:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数型データ分類における再帰的最大探索による特徴選択（Feature selection in functional data classification with recursive maxima hunting）</news:title>
   <news:publication_date>2026-05-14T10:40:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690054</loc>
  <lastmod>2026-05-14T10:39:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語翻訳における線形性の限界を測る（Characterizing Departures from Linearity in Word Translation）</news:title>
   <news:publication_date>2026-05-14T10:39:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690052</loc>
  <lastmod>2026-05-14T10:39:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像復元のための非局所再帰ネットワーク（Non-Local Recurrent Network for Image Restoration）</news:title>
   <news:publication_date>2026-05-14T10:39:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690050</loc>
  <lastmod>2026-05-14T10:38:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CapsGANによる回転に強い画像生成の実現（CapsGAN: Using Dynamic Routing for Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-14T10:38:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690048</loc>
  <lastmod>2026-05-14T10:38:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損データの補完にGANを応用する手法（GAIN: Missing Data Imputation using Generative Adversarial Nets）</news:title>
   <news:publication_date>2026-05-14T10:38:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690046</loc>
  <lastmod>2026-05-14T10:38:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カラーセイル：深層カラー探索のための離散・連続パレット（Color Sails: Discrete-Continuous Palettes for Deep Color Exploration）</news:title>
   <news:publication_date>2026-05-14T10:38:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690044</loc>
  <lastmod>2026-05-14T09:47:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ExoGANによる系外惑星大気の高速逆推定（ExoGAN: Retrieving Exoplanetary Atmospheres Using Deep Convolutional Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-14T09:47:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690042</loc>
  <lastmod>2026-05-14T09:46:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数意味を確率的に表現する単語埋め込み（Probabilistic FastText for Multi-Sense Word Embeddings）</news:title>
   <news:publication_date>2026-05-14T09:46:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690040</loc>
  <lastmod>2026-05-14T09:46:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TRGBによる銀河距離計測の高精度化（THE CARNEGIE-CHICAGO HUBBLE PROGRAM. IV. THE DISTANCES TO NGC 4424, NGC 4526, AND NGC 4536 VIA THE TIP OF THE RED GIANT BRANCH）</news:title>
   <news:publication_date>2026-05-14T09:46:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690038</loc>
  <lastmod>2026-05-14T09:45:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モード分離で学習を高速化する手法（Training Faster by Separating Modes of Variation in Batch-normalized Models）</news:title>
   <news:publication_date>2026-05-14T09:45:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690036</loc>
  <lastmod>2026-05-14T09:45:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム回折像の逆変換を可能にする深層生成ネットワーク（Real-time coherent diffraction inversion using deep generative networks）</news:title>
   <news:publication_date>2026-05-14T09:45:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690034</loc>
  <lastmod>2026-05-14T09:45:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模自転車シェアリングの動的再配置に関する包括的枠組み（A COMPREHENSIVE FRAMEWORK FOR DYNAMIC BIKE REBALANCING IN A LARGE BIKE SHARING NETWORK）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690032</loc>
  <lastmod>2026-05-14T09:45:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNにおける個々のユニットの重要性の再検討（Revisiting the Importance of Individual Units in CNNs via Ablation）</news:title>
   <news:publication_date>2026-05-14T09:45:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690030</loc>
  <lastmod>2026-05-14T08:53:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏ったデータから生じる残余的不公平（Residual Unfairness in Fair Machine Learning from Prejudiced Data）</news:title>
   <news:publication_date>2026-05-14T08:53:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690028</loc>
  <lastmod>2026-05-14T08:53:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚テクスチャに対する深層ニューラルネットワークと脳の対応（Correspondence of Deep Neural Networks and the Brain for Visual Textures）</news:title>
   <news:publication_date>2026-05-14T08:53:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690026</loc>
  <lastmod>2026-05-14T08:53:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ICU患者の異種集団に対するマルチタスク学習の課題（Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU）</news:title>
   <news:publication_date>2026-05-14T08:53:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690024</loc>
  <lastmod>2026-05-14T08:53:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠測応答を扱うカーネル機械の設計（Kernel Machines With Missing Responses）</news:title>
   <news:publication_date>2026-05-14T08:53:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690022</loc>
  <lastmod>2026-05-14T08:52:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散変分オートエンコーダに対するarg maxの直接最適化（Direct Optimization through arg max for Discrete Variational Auto-Encoder）</news:title>
   <news:publication_date>2026-05-14T08:52:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690020</loc>
  <lastmod>2026-05-14T08:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース環境での感情分類に効く半教師あり・転移学習の実践（SEMI‑SUPERVISED AND TRANSFER LEARNING APPROACHES FOR LOW RESOURCE SENTIMENT CLASSIFICATION）</news:title>
   <news:publication_date>2026-05-14T08:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690018</loc>
  <lastmod>2026-05-14T08:52:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラジルと米国における信頼性の低いニュース分類の探究（An Exploration of Unreliable News Classification in Brazil and The U.S.）</news:title>
   <news:publication_date>2026-05-14T08:52:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690016</loc>
  <lastmod>2026-05-14T08:01:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルな自然勾配ランジュバン力学の実践（Scalable Natural Gradient Langevin Dynamics in Practice）</news:title>
   <news:publication_date>2026-05-14T08:01:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690014</loc>
  <lastmod>2026-05-14T08:00:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等尺性変形する薄膜物体の検出に向けたモデルベース能動学習（Model-based active learning to detect an isometric deformable object in the wild with a deep architecture）</news:title>
   <news:publication_date>2026-05-14T08:00:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690012</loc>
  <lastmod>2026-05-14T08:00:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>常識推論のための単純な手法（A Simple Method for Commonsense Reasoning）</news:title>
   <news:publication_date>2026-05-14T08:00:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690010</loc>
  <lastmod>2026-05-14T07:59:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データの要約を二段階で効率化する手法（Data Summarization at Scale: A Two-Stage Submodular Approach）</news:title>
   <news:publication_date>2026-05-14T07:59:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690008</loc>
  <lastmod>2026-05-14T07:59:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レイヤードスパースコード設計によるプライバシー保護識別（Privacy-Preserving Identification via Layered Sparse Code Design: Distributed Servers and Multiple Access Authorization）</news:title>
   <news:publication_date>2026-05-14T07:59:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690006</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長周期変光星を機械学習で標準光源化する手法（Calibrating Long Period Variables as Standard Candles with Machine Learning）</news:title>
   <news:publication_date>2026-05-14T07:58:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690004</loc>
  <lastmod>2026-05-14T07:58:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的MAMLによる少ショット学習の不確実性表現（Probabilistic Model-Agnostic Meta-Learning）</news:title>
   <news:publication_date>2026-05-14T07:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690002</loc>
  <lastmod>2026-05-14T07:07:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低資源医療固有表現認識のための埋め込み転移 — 患者の移動性に関する事例研究（Embedding Transfer for Low-Resource Medical Named Entity Recognition: A Case Study on Patient Mobility）</news:title>
   <news:publication_date>2026-05-14T07:07:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/690000</loc>
  <lastmod>2026-05-14T07:07:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己整合的軌跡オートエンコーダ（Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings）</news:title>
   <news:publication_date>2026-05-14T07:07:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689998</loc>
  <lastmod>2026-05-14T07:06:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リーマン多様体上の加速勾配法の提案（Towards Riemannian Accelerated Gradient Methods）</news:title>
   <news:publication_date>2026-05-14T07:06:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689996</loc>
  <lastmod>2026-05-14T07:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化方針の価値を偏りなく推定する方法（Unbiased Estimation of the Value of an Optimized Policy）</news:title>
   <news:publication_date>2026-05-14T07:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689994</loc>
  <lastmod>2026-05-14T07:06:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声認識の頑健性を高める敵対的事例による学習拡張（Training Augmentation with Adversarial Examples for Robust Speech Recognition）</news:title>
   <news:publication_date>2026-05-14T07:06:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689992</loc>
  <lastmod>2026-05-14T07:05:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アクセントに強い音声認識を実現する領域敵対的学習（Domain Adversarial Training for Accented Speech Recognition）</news:title>
   <news:publication_date>2026-05-14T07:05:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689990</loc>
  <lastmod>2026-05-14T07:05:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配のいらないStein変分勾配降下法（Stein Variational Gradient Descent Without Gradient）</news:title>
   <news:publication_date>2026-05-14T07:05:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689988</loc>
  <lastmod>2026-05-14T06:14:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間を発見する―感覚運動経験から空間の位相と計量的規則性を自律的に学ぶ（Discovering space - Grounding spatial topology and metric regularity in a naive agent’s sensorimotor experience）</news:title>
   <news:publication_date>2026-05-14T06:14:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689986</loc>
  <lastmod>2026-05-14T06:14:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短文の自動主題付与に関するコンテンツベース品質推定（Content-Based Quality Estimation for Automatic Subject Indexing of Short Texts under Precision and Recall Constraints）</news:title>
   <news:publication_date>2026-05-14T06:14:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689984</loc>
  <lastmod>2026-05-14T06:13:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>話者–追従モデルによる視覚と言語ナビゲーション（Speaker-Follower Models for Vision-and-Language Navigation）</news:title>
   <news:publication_date>2026-05-14T06:13:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689982</loc>
  <lastmod>2026-05-14T06:13:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化行列分割アルゴリズムによる複合関数最適化（A Generalized Matrix Splitting Algorithm）</news:title>
   <news:publication_date>2026-05-14T06:13:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689980</loc>
  <lastmod>2026-05-14T06:12:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EVバッテリーのSOC推定とサイバー攻撃の危険性（A Study of EV BMS Cyber Security Based on Neural Network SOC Prediction）</news:title>
   <news:publication_date>2026-05-14T06:12:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689978</loc>
  <lastmod>2026-05-14T06:12:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の確率的Optimal Transportと新しい距離尺度（Randomized Optimal Transport on a Graph: framework and new distance measures）</news:title>
   <news:publication_date>2026-05-14T06:12:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689976</loc>
  <lastmod>2026-05-14T06:12:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なセマンティック画像分割とスーパー ピクセルプーリング（Efficient semantic image segmentation with superpixel pooling）</news:title>
   <news:publication_date>2026-05-14T06:12:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689974</loc>
  <lastmod>2026-05-14T05:21:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間の緊密クラスタリングによる半教師あり学習（Semi-Supervised Learning via Compact Latent Space Clustering）</news:title>
   <news:publication_date>2026-05-14T05:21:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689972</loc>
  <lastmod>2026-05-14T05:21:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人に合わせて支援する人機システムの評価手法（Methodological Approach for the Evaluation of an Adaptive and Assistive Human-Machine System）</news:title>
   <news:publication_date>2026-05-14T05:21:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689970</loc>
  <lastmod>2026-05-14T05:20:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型理論化学の潮流（Data-enabled Theoretical Chemistry）</news:title>
   <news:publication_date>2026-05-14T05:20:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689968</loc>
  <lastmod>2026-05-14T05:20:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性の確率的AND‑ORグルーピングによるゼロショット学習（Probabilistic AND-OR Attribute Grouping for Zero-Shot Learning）</news:title>
   <news:publication_date>2026-05-14T05:20:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689966</loc>
  <lastmod>2026-05-14T05:19:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケーラブルな多クラスベイズSVMの要点解説（Scalable Multi-Class Bayesian Support Vector Machines for Structured and Unstructured Data）</news:title>
   <news:publication_date>2026-05-14T05:19:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689964</loc>
  <lastmod>2026-05-14T05:19:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>評価の再考――Nash averaging が変えたベンチマークの見方 (Re-evaluating Evaluation)</news:title>
   <news:publication_date>2026-05-14T05:19:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-05-14T05:19:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>水素化した単層MoS2におけるドーピング制御（Tunable Doping in Hydrogenated Single Layered Molybdenum Disulfide）</news:title>
   <news:publication_date>2026-05-14T05:19:30Z</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>経路レベルのネットワーク変換による効率的なアーキテクチャ探索（Path-Level Network Transformation for Efficient Architecture Search）</news:title>
   <news:publication_date>2026-05-14T04:28:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689958</loc>
  <lastmod>2026-05-14T04:28:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトラルネットワーク埋め込み：スパース性による高速でスケーラブルな手法（Spectral Network Embedding: A Fast and Scalable Method via Sparsity）</news:title>
   <news:publication_date>2026-05-14T04:28:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689956</loc>
  <lastmod>2026-05-14T04:27:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重力ポテンシャルにおける位相速度と光の曲がり（Phase velocity and light bending in a gravitational potential）</news:title>
   <news:publication_date>2026-05-14T04:27:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689954</loc>
  <lastmod>2026-05-14T04:27:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>写本の筆跡不変深層学習モデルによる整合手法の実務的意義（Writing Style Invariant Deep Learning Model for Historical Manuscripts）</news:title>
   <news:publication_date>2026-05-14T04:27:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689952</loc>
  <lastmod>2026-05-14T04:26:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>次元駆動学習によるラベルノイズ耐性の向上（Dimensionality-Driven Learning with Noisy Labels）</news:title>
   <news:publication_date>2026-05-14T04:26:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689950</loc>
  <lastmod>2026-05-14T04:26:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非凸最適化のための非同期確率的準ニュートンMCMC（Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization）</news:title>
   <news:publication_date>2026-05-14T04:26:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689948</loc>
  <lastmod>2026-05-14T04:26:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRI信号強度の正規化のための非パラメトリック密度フロー（Nonparametric Density Flows for MRI Intensity Normalisation）</news:title>
   <news:publication_date>2026-05-14T04:26:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689946</loc>
  <lastmod>2026-05-14T03:35:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間運転から学ぶ自律車両のマルチモーダル自己認識モデル（Learning Multi-Modal Self-Awareness Models for Autonomous Vehicles from Human Driving）</news:title>
   <news:publication_date>2026-05-14T03:35:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689944</loc>
  <lastmod>2026-05-14T03:34:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高スペクトル画像の現実的な合成を可能にする生成的敵対ネットワーク（Generative Adversarial Networks for Realistic Synthesis of Hyperspectral Samples）</news:title>
   <news:publication_date>2026-05-14T03:34:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689942</loc>
  <lastmod>2026-05-14T03:34:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>制御付き平方根Zゲートの実験的実現（Experimental realization of Controlled Square Root of Z Gate Using IBM&amp;#039;s Cloud Quantum Experience Platform）</news:title>
   <news:publication_date>2026-05-14T03:34:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689940</loc>
  <lastmod>2026-05-14T03:34:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絵文字を活用した表現学習によるクロスリンガル感情分類（Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification）</news:title>
   <news:publication_date>2026-05-14T03:34:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689938</loc>
  <lastmod>2026-05-14T03:33:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OctApps：連続重力波データ解析のためのOctave関数ライブラリ（OctApps: a library of Octave functions for continuous gravitational-wave data analysis）</news:title>
   <news:publication_date>2026-05-14T03:33:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689936</loc>
  <lastmod>2026-05-14T03:33:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>綴りと算数学習のためのインテリジェント教育ゲームに関する10年の研究（Ten Years of Research on Intelligent Educational Games for Learning Spelling and Mathematics）</news:title>
   <news:publication_date>2026-05-14T03:33:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689934</loc>
  <lastmod>2026-05-14T03:33:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察者間差異が医療画像セグメンテーションの不確かさ推定を変える（On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation）</news:title>
   <news:publication_date>2026-05-14T03:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689932</loc>
  <lastmod>2026-05-14T02:41:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布型太陽光発電の短期予測に向けたGrouped Gaussian Processes（Grouped Gaussian Processes for Solar Power Prediction）</news:title>
   <news:publication_date>2026-05-14T02:41:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689930</loc>
  <lastmod>2026-05-14T02:41:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在クラスタを用いたセグメント別信用スコアリング（Segment-Based Credit Scoring Using Latent Clusters in the Variational Autoencoder）</news:title>
   <news:publication_date>2026-05-14T02:41:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689928</loc>
  <lastmod>2026-05-14T02:41:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報最大化サンプリングによる追跡強化（INFORMATION-MAXIMIZING SAMPLING TO PROMOTE TRACKING-BY-DETECTION）</news:title>
   <news:publication_date>2026-05-14T02:41:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689926</loc>
  <lastmod>2026-05-14T02:40:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要度重み付き生成ネットワーク（Importance Weighted Generative Networks）</news:title>
   <news:publication_date>2026-05-14T02:40:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689924</loc>
  <lastmod>2026-05-14T02:40:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-14T02:40:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689922</loc>
  <lastmod>2026-05-14T02:39:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半動的ロードバランシングによる非専用環境での効率的分散学習（Semi-Dynamic Load Balancing: Efficient Distributed Learning in Non-Dedicated Environments）</news:title>
   <news:publication_date>2026-05-14T02:39:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689920</loc>
  <lastmod>2026-05-14T02:39:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-14T02:39:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689918</loc>
  <lastmod>2026-05-14T01:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>報酬設計を分割して簡素化する手法（Simplifying Reward Design through Divide-and-Conquer）</news:title>
   <news:publication_date>2026-05-14T01:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689916</loc>
  <lastmod>2026-05-14T01:47:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模分類問題に対するLabel Mapping（Large scale classification in deep neural network with Label Mapping）</news:title>
   <news:publication_date>2026-05-14T01:47:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689914</loc>
  <lastmod>2026-05-14T01:47:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き確率をRBMで直接求める非線形システム同定の提案（Conditional probability calculation using restricted Boltzmann machine with application to system identification）</news:title>
   <news:publication_date>2026-05-14T01:47:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689912</loc>
  <lastmod>2026-05-14T01:46:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三十メートル望遠鏡の革新性（The Thirty Meter Telescope International Observatory facilitating transformative astrophysical science）</news:title>
   <news:publication_date>2026-05-14T01:46:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689910</loc>
  <lastmod>2026-05-14T01:46:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-14T01:46:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689908</loc>
  <lastmod>2026-05-14T01:46:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レイアウト設計のための深層学習に基づく逆問題手法（Deep learning based inverse method for layout design）</news:title>
   <news:publication_date>2026-05-14T01:46:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689906</loc>
  <lastmod>2026-05-14T01:45:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ブロックモデルは離散的表面張力である（STOCHASTIC BLOCK MODELS ARE A DISCRETE SURFACE TENSION）</news:title>
   <news:publication_date>2026-05-14T01:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689904</loc>
  <lastmod>2026-05-14T00:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目的志向の分子グラフ生成のためのグラフ畳み込み方策ネットワーク（Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation）</news:title>
   <news:publication_date>2026-05-14T00:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689902</loc>
  <lastmod>2026-05-14T00:54:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光格子中スピン軌道結合フェルミオンのBloch束縛状態（Bloch bound state of spin-orbit-coupled fermions in an optical lattice）</news:title>
   <news:publication_date>2026-05-14T00:54:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689900</loc>
  <lastmod>2026-05-14T00:53:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークの深さと幅が仮説空間に与える影響（The effect of the choice of neural network depth and breadth on the size of its hypothesis space）</news:title>
   <news:publication_date>2026-05-14T00:53:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689898</loc>
  <lastmod>2026-05-14T00:53:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無限状態ジャンプ過程におけるベイズ推論の効率的データ増補（On Bayesian inferential tasks with infinite-state jump processes: efficient data augmentation）</news:title>
   <news:publication_date>2026-05-14T00:53:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689896</loc>
  <lastmod>2026-05-14T00:52:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人の修正から学ぶ際に不確実性を取り込む意義（Including Uncertainty when Learning from Human Corrections）</news:title>
   <news:publication_date>2026-05-14T00:52:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689894</loc>
  <lastmod>2026-05-14T00:52:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的モジュールネットワークによる視覚的推論（Visual Reasoning by Progressive Module Networks）</news:title>
   <news:publication_date>2026-05-14T00:52:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689892</loc>
  <lastmod>2026-05-14T00:52:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MEBN-RM：リレーショナルデータから確率論的知識を組み立てる方法論（MEBN-RM: A Mapping between Multi-Entity Bayesian Network and Relational Model）</news:title>
   <news:publication_date>2026-05-14T00:52:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689890</loc>
  <lastmod>2026-05-14T00:00:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>干渉制約ネットワークにおける共同電力配分の分散協調学習（Joint Power Allocation in Interference-Limited Networks via Distributed Coordinated Learning）</news:title>
   <news:publication_date>2026-05-14T00:00:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689886</loc>
  <lastmod>2026-05-13T23:59:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像から深さを「順序」で学ぶ新手法（Deep Ordinal Regression Network for Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-05-13T23:59:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689884</loc>
  <lastmod>2026-05-13T23:59:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>難読化耐性を持つ実行可能ファイル検索（Obfuscation Resilient Search through Executable Classification）</news:title>
   <news:publication_date>2026-05-13T23:59:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689882</loc>
  <lastmod>2026-05-13T23:59:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線画像再考：BraTSに対する様々な手法の比較（Rethinking Radiology: An Analysis of Different Approaches to BraTS）</news:title>
   <news:publication_date>2026-05-13T23:59:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689880</loc>
  <lastmod>2026-05-13T23:59:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインベイズ実験設計によるハミルトニアン学習の実践（Hamiltonian Learning with Online Bayesian Experiment Design in Practice）</news:title>
   <news:publication_date>2026-05-13T23:59:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689878</loc>
  <lastmod>2026-05-13T23:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測問題に対する深い変分強化学習（Deep Variational Reinforcement Learning for POMDPs）</news:title>
   <news:publication_date>2026-05-13T23:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689876</loc>
  <lastmod>2026-05-13T23:07:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆と雑多な背景でのリアルタイム行動認識（Action4D: Real-time Action Recognition in the Crowd and Clutter）</news:title>
   <news:publication_date>2026-05-13T23:07:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689874</loc>
  <lastmod>2026-05-13T23:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説得力のある議論を見つけるための大規模ベイズ的選好学習（Finding Convincing Arguments Using Scalable Bayesian Preference Learning）</news:title>
   <news:publication_date>2026-05-13T23:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689872</loc>
  <lastmod>2026-05-13T23:07:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電力網の確率的挙動と連鎖故障のシミュレーション（Simulating the stochastic dynamics and cascade failure of power networks）</news:title>
   <news:publication_date>2026-05-13T23:07:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689870</loc>
  <lastmod>2026-05-13T23:06:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所構造を利用した構造化予測（Localized Structured Prediction）</news:title>
   <news:publication_date>2026-05-13T23:06:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689868</loc>
  <lastmod>2026-05-13T23:06:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>任意条件付き変分オートエンコーダ（Variational Autoencoder with Arbitrary Conditioning）</news:title>
   <news:publication_date>2026-05-13T23:06:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689866</loc>
  <lastmod>2026-05-13T23:06:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性ごとの差を扱うプライバシー機構の設計（Not All Attributes are Created Equal: dX-Private Mechanisms for Linear Queries）</news:title>
   <news:publication_date>2026-05-13T23:06:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689864</loc>
  <lastmod>2026-05-13T23:06:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的確率過程と変分推論が切り開く関数空間のベイズ化（Variational Implicit Processes）</news:title>
   <news:publication_date>2026-05-13T23:06:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689862</loc>
  <lastmod>2026-05-13T22:14:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果介入による公正性設計（Causal Interventions for Fairness）</news:title>
   <news:publication_date>2026-05-13T22:14:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689860</loc>
  <lastmod>2026-05-13T22:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ構造データに対する敵対的攻撃（Adversarial Attack on Graph Structured Data）</news:title>
   <news:publication_date>2026-05-13T22:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689858</loc>
  <lastmod>2026-05-13T22:13:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械から新たな物理を学ぶ（Learning New Physics from a Machine）</news:title>
   <news:publication_date>2026-05-13T22:13:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689856</loc>
  <lastmod>2026-05-13T22:11:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイヤレス給電センサネットワークにおける最適化と強化学習の比較（Optimization vs. Reinforcement Learning for Wirelessly Powered Sensor Networks）</news:title>
   <news:publication_date>2026-05-13T22:11:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689854</loc>
  <lastmod>2026-05-13T22:11:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的データ収集におけるバイアス低減と差分プライバシーの接点（Mitigating Bias in Adaptive Data Gathering via Differential Privacy）</news:title>
   <news:publication_date>2026-05-13T22:11:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689852</loc>
  <lastmod>2026-05-13T22:11:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き線形回帰（Conditional Linear Regression）</news:title>
   <news:publication_date>2026-05-13T22:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689850</loc>
  <lastmod>2026-05-13T22:11:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値確率変数のコルモゴロフモデル学習（Learning Kolmogorov Models for Binary Random Variables）</news:title>
   <news:publication_date>2026-05-13T22:11:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689848</loc>
  <lastmod>2026-05-13T21:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化された価値関数と乗法的正規化フロー（Randomized Value Functions via Multiplicative Normalizing Flows）</news:title>
   <news:publication_date>2026-05-13T21:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689846</loc>
  <lastmod>2026-05-13T21:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの信頼性指標の方向性（Towards Dependability Metrics for Neural Networks）</news:title>
   <news:publication_date>2026-05-13T21:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689844</loc>
  <lastmod>2026-05-13T21:16:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GianCarlo Ghirardiとの出会いと教育の本質（My life with GianCarlo Ghirardi）</news:title>
   <news:publication_date>2026-05-13T21:16:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689842</loc>
  <lastmod>2026-05-13T21:16:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>血管セグメンテーションにおけるグラフ結合学習（Deep Vessel Segmentation By Learning Graphical Connectivity）</news:title>
   <news:publication_date>2026-05-13T21:16:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689840</loc>
  <lastmod>2026-05-13T21:15:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検索分野における深層ランキングモデルの実運用化（Deploying Deep Ranking Models for Search Verticals）</news:title>
   <news:publication_date>2026-05-13T21:15:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689838</loc>
  <lastmod>2026-05-13T21:15:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の探索における逐次的探索と停止の最適化（Finding the bandit in a graph: Sequential search-and-stop）</news:title>
   <news:publication_date>2026-05-13T21:15:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689836</loc>
  <lastmod>2026-05-13T21:15:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データ駆動で個別化された確率的脳アトラスを作る手法（Data-driven Probabilistic Atlases Capture Whole-brain Individual Variation）</news:title>
   <news:publication_date>2026-05-13T21:15:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689834</loc>
  <lastmod>2026-05-13T20:23:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果バンディットにおける伝播推論の扱い（Causal Bandits with Propagating Inference）</news:title>
   <news:publication_date>2026-05-13T20:23:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689832</loc>
  <lastmod>2026-05-13T20:23:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数学習者による敵対的回帰（Adversarial Regression with Multiple Learners）</news:title>
   <news:publication_date>2026-05-13T20:23:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689830</loc>
  <lastmod>2026-05-13T20:23:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常ストリーミングデータに対する二重ロバストなベイズ推論（Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences）</news:title>
   <news:publication_date>2026-05-13T20:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689828</loc>
  <lastmod>2026-05-13T20:22:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TopRank: オンライン確率的ランキングの実践アルゴリズム（TopRank: A Practical Algorithm for Online Stochastic Ranking）</news:title>
   <news:publication_date>2026-05-13T20:22:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689826</loc>
  <lastmod>2026-05-13T20:22:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ADMMを用いた分散アルゴリズムの精度とプライバシーの同時改善（Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms）</news:title>
   <news:publication_date>2026-05-13T20:22:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689824</loc>
  <lastmod>2026-05-13T20:22:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>腹部多臓器セグメンテーションのための3D全畳み込みネットワークのマルチスケールピラミッド（A multi-scale pyramid of 3D fully convolutional networks for abdominal multi-organ segmentation）</news:title>
   <news:publication_date>2026-05-13T20:22:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689822</loc>
  <lastmod>2026-05-13T20:21:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シリコン中の鉄—水素相互作用の第一原理解析（First-principles calculations of iron-hydrogen reactions in silicon）</news:title>
   <news:publication_date>2026-05-13T20:21:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689820</loc>
  <lastmod>2026-05-13T19:30:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチブランチ構造を備えた深層ニューラルネットワークは非凸性が低い（Deep Neural Networks with Multi-Branch Architectures Are Less Non-Convex）</news:title>
   <news:publication_date>2026-05-13T19:30:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689818</loc>
  <lastmod>2026-05-13T19:29:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトル推論ネットワークが変える表現学習の地平（Spectral Inference Networks: Unifying Deep and Spectral Learning）</news:title>
   <news:publication_date>2026-05-13T19:29:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689816</loc>
  <lastmod>2026-05-13T19:29:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データの解釈可能な離散表現学習（SOM-VAE: Interpretable Discrete Representation Learning on Time Series）</news:title>
   <news:publication_date>2026-05-13T19:29:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689814</loc>
  <lastmod>2026-05-13T19:29:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックス変分推論のブースティング（Boosting Black Box Variational Inference）</news:title>
   <news:publication_date>2026-05-13T19:29:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689812</loc>
  <lastmod>2026-05-13T19:29:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GraKeL: グラフカーネルライブラリの実務的理解（GraKeL: A Graph Kernel Library in Python）</news:title>
   <news:publication_date>2026-05-13T19:29:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689810</loc>
  <lastmod>2026-05-13T19:28:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層知識トレースの一貫性問題とその解決（Addressing Two Problems in Deep Knowledge Tracing via Prediction-Consistent Regularization）</news:title>
   <news:publication_date>2026-05-13T19:28:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689808</loc>
  <lastmod>2026-05-13T19:28:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習履歴から進路を予測する知識状態の活用（Incorporating Features Learned by an Enhanced Deep Knowledge Tracing Model for STEM/Non-STEM Job Prediction）</news:title>
   <news:publication_date>2026-05-13T19:28:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689806</loc>
  <lastmod>2026-05-13T18:37:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群からの剛体運動推定のための表現学習（PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds）</news:title>
   <news:publication_date>2026-05-13T18:37:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689804</loc>
  <lastmod>2026-05-13T18:36:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SBAF――恒星外惑星の居住可能性分類に向けた新しい活性化関数（SBAF: A New Activation Function for Artificial Neural Net based Habitability Classification）</news:title>
   <news:publication_date>2026-05-13T18:36:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689802</loc>
  <lastmod>2026-05-13T18:36:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非並列多対多音声変換を可能にするStarGAN-VC（STARGAN-VC: NON-PARALLEL MANY-TO-MANY VOICE CONVERSION WITH STAR GENERATIVE ADVERSARIAL NETWORKS）</news:title>
   <news:publication_date>2026-05-13T18:36:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689800</loc>
  <lastmod>2026-05-13T18:35:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチチャートによる3D形状生成の革新（Multi-chart Generative Surface Modeling）</news:title>
   <news:publication_date>2026-05-13T18:35:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689798</loc>
  <lastmod>2026-05-13T18:35:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ベイズ回帰モデルの要点と経営者の視点（Deep Bayesian regression models）</news:title>
   <news:publication_date>2026-05-13T18:35:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689796</loc>
  <lastmod>2026-05-13T18:35:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声に基づく感情認識のための敵対的オートエンコーダ（Adversarial Auto-encoders for Speech Based Emotion Recognition）</news:title>
   <news:publication_date>2026-05-13T18:35:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689794</loc>
  <lastmod>2026-05-13T18:34:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>道路網の位相的特徴による都市比較（Topological street-network characterization through feature-vector and cluster analysis）</news:title>
   <news:publication_date>2026-05-13T18:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689792</loc>
  <lastmod>2026-05-13T17:43:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜血管の分岐点検出のためのマルチタスクネットワーク（A Multi-task Network to Detect Junctions in Retinal Vasculature）</news:title>
   <news:publication_date>2026-05-13T17:43:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689790</loc>
  <lastmod>2026-05-13T17:33:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低温MOSトランジスタの物理モデル（Cryogenic MOS Transistor Model）</news:title>
   <news:publication_date>2026-05-13T17:33:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689788</loc>
  <lastmod>2026-05-13T17:33:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データに強いグラフベースの二標本検定の改良（On High-dimensional Modifications of Some Graph-based Two-sample Tests）</news:title>
   <news:publication_date>2026-05-13T17:33:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689786</loc>
  <lastmod>2026-05-13T17:32:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ユニタリ変換のためのロバスト学習制御設計（Robust Learning Control Design for Quantum Unitary Transformations）</news:title>
   <news:publication_date>2026-05-13T17:32:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689784</loc>
  <lastmod>2026-05-13T17:32:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高効率な微分可能プログラミングの実現（Efficient Differentiable Programming in a Functional Array-Processing Language）</news:title>
   <news:publication_date>2026-05-13T17:32:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689782</loc>
  <lastmod>2026-05-13T17:32:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜血管セグメンテーションにおける追加ラベル付き深層監視（Deep supervision with additional labels for retinal vessel segmentation task）</news:title>
   <news:publication_date>2026-05-13T17:32:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689780</loc>
  <lastmod>2026-05-13T17:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TextRayによる胸部X線の全体理解（TextRay: Mining Clinical Reports to Gain a Broad Understanding of Chest X-rays）</news:title>
   <news:publication_date>2026-05-13T17:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689778</loc>
  <lastmod>2026-05-13T16:40:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PSD制約による一意復元と暗黙の正則化（Implicit regularization and solution uniqueness in over-parameterized matrix sensing）</news:title>
   <news:publication_date>2026-05-13T16:40:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689776</loc>
  <lastmod>2026-05-13T16:31:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込み型シーケンス・トゥ・シーケンスによる非侵襲型負荷監視（Convolutional Sequence to Sequence Non-intrusive Load Monitoring）</news:title>
   <news:publication_date>2026-05-13T16:31:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689774</loc>
  <lastmod>2026-05-13T16:31:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PieAPP: ペア比較で学ぶ視覚的画像誤差評価（PieAPP: Perceptual Image-Error Assessment through Pairwise Preference）</news:title>
   <news:publication_date>2026-05-13T16:31:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689772</loc>
  <lastmod>2026-05-13T16:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ化流体シミュレーションの生成モデル（Deep Fluids: A Generative Network for Parameterized Fluid Simulations）</news:title>
   <news:publication_date>2026-05-13T16:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689770</loc>
  <lastmod>2026-05-13T16:30:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みオートエンコーダの学習のための空間周波数損失（Spatial Frequency Loss for Learning Convolutional Autoencoders）</news:title>
   <news:publication_date>2026-05-13T16:30:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689768</loc>
  <lastmod>2026-05-13T16:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボールドウィン効果によるメタ学習（Meta-Learning by the Baldwin Effect）</news:title>
   <news:publication_date>2026-05-13T16:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689766</loc>
  <lastmod>2026-05-13T16:29:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的フィードバックから学ぶ階層化商品カテゴリー（Learning Hierarchical Item Categories from Implicit Feedback Data for Efficient Recommendations and Browsing）</news:title>
   <news:publication_date>2026-05-13T16:29:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689764</loc>
  <lastmod>2026-05-13T15:37:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークの隠れ層を因子分解の観点から覗く（A Peek Into the Hidden Layers of a Convolutional Neural Network Through a Factorization Lens）</news:title>
   <news:publication_date>2026-05-13T15:37:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689762</loc>
  <lastmod>2026-05-13T15:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間依存注意機構による医療概念の埋め込み（Medical Concept Embedding with Time-Aware Attention）</news:title>
   <news:publication_date>2026-05-13T15:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689760</loc>
  <lastmod>2026-05-13T15:30:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-meansの自由度とモデル選択（Degrees of Freedom and Model Selection for k-means Clustering）</news:title>
   <news:publication_date>2026-05-13T15:30:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689758</loc>
  <lastmod>2026-05-13T15:29:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gaussian Processを用いた複数の試験時攻撃の関係性の解析（Killing four birds with one Gaussian process）</news:title>
   <news:publication_date>2026-05-13T15:29:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689756</loc>
  <lastmod>2026-05-13T15:28:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Set-based Obfuscationによる強いPUFの機械学習耐性強化（Set-based Obfuscation for Strong PUFs against Machine Learning Attacks）</news:title>
   <news:publication_date>2026-05-13T15:28:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689754</loc>
  <lastmod>2026-05-13T15:28:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人工膝関節置換術におけるリアルタイム手術器具認識（Real-time Surgical Tools Recognition in Total Knee Arthroplasty Using Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-13T15:28:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689752</loc>
  <lastmod>2026-05-13T15:27:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルゴリズム指向のニューラルネット設計（Deep Algorithms: designs for networks）</news:title>
   <news:publication_date>2026-05-13T15:27:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689750</loc>
  <lastmod>2026-05-13T14:35:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運動計画のための暗黙的サンプリング分布学習 (Learning Implicit Sampling Distributions for Motion Planning)</news:title>
   <news:publication_date>2026-05-13T14:35:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689748</loc>
  <lastmod>2026-05-13T14:27:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造を超えた分類手法（Beyond Trees: Classification with Sparse Pairwise Dependencies）</news:title>
   <news:publication_date>2026-05-13T14:27:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689746</loc>
  <lastmod>2026-05-13T14:27:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>検閲された生存データのランキング学習（Learning to rank for censored survival data）</news:title>
   <news:publication_date>2026-05-13T14:27:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689744</loc>
  <lastmod>2026-05-13T14:26:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込み辞書学習によるスパイクソーティング（Spike Sorting by Convolutional Dictionary Learning）</news:title>
   <news:publication_date>2026-05-13T14:26:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689742</loc>
  <lastmod>2026-05-13T14:26:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列の疑似逆を小さなサブセットで推定する逆反復ボリュームサンプリング（Reverse Iterative Volume Sampling for Linear Regression）</news:title>
   <news:publication_date>2026-05-13T14:26:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689740</loc>
  <lastmod>2026-05-13T14:26:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Web規模レコメンデーションにおけるグラフ畳み込みの実用化（Graph Convolutional Neural Networks for Web-Scale Recommender Systems）</news:title>
   <news:publication_date>2026-05-13T14:26:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689738</loc>
  <lastmod>2026-05-13T14:25:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シリコン中の深い二重ドナーであるマグネシウムのさらなる研究（Further investigations of the deep double donor magnesium in silicon）</news:title>
   <news:publication_date>2026-05-13T14:25:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689736</loc>
  <lastmod>2026-05-13T13:33:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点異常と集合的異常の線形時間検出法（A linear time method for the detection of point and collective anomalies）</news:title>
   <news:publication_date>2026-05-13T13:33:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689734</loc>
  <lastmod>2026-05-13T13:25:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MILD-Netによる腺組織のインスタンス分割の意義（MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images）</news:title>
   <news:publication_date>2026-05-13T13:25:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689732</loc>
  <lastmod>2026-05-13T13:25:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚から言語への翻訳を複数モデルの合意で高精度化する手法（Mining for meaning: from vision to language through multiple networks consensus）</news:title>
   <news:publication_date>2026-05-13T13:25:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689730</loc>
  <lastmod>2026-05-13T13:24:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による脆性破壊の簡易化モデル化（Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications）</news:title>
   <news:publication_date>2026-05-13T13:24:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689728</loc>
  <lastmod>2026-05-13T13:24:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>命令文から目的を学ぶ仕組みの解説（LEARNING TO UNDERSTAND GOAL SPECIFICATIONS BY MODELLING REWARD）</news:title>
   <news:publication_date>2026-05-13T13:24:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689726</loc>
  <lastmod>2026-05-13T13:23:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生態学に着想を得た遺伝的アプローチによるニューラルネット構造探索（EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching from Scratch）</news:title>
   <news:publication_date>2026-05-13T13:23:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689724</loc>
  <lastmod>2026-05-13T13:23:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能なニューラルネットワークと加法指標モデル（Explainable Neural Networks based on Additive Index Models）</news:title>
   <news:publication_date>2026-05-13T13:23:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689722</loc>
  <lastmod>2026-05-13T12:31:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単調関数の非母数推定の統一的研究（A unified study of nonparametric inference for monotone functions）</news:title>
   <news:publication_date>2026-05-13T12:31:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689720</loc>
  <lastmod>2026-05-13T12:31:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ReLU活性化ニューラルネットワークの線形領域数に関する上界構成フレームワーク（A Framework for the construction of upper bounds on the number of affine linear regions of ReLU feed-forward neural networks）</news:title>
   <news:publication_date>2026-05-13T12:31:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689718</loc>
  <lastmod>2026-05-13T12:30:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WIYNのOne Degree Imagerの拡張と広視野撮像能力の向上（The WIYN One Degree Imager in 2018: An Extended 30-Detector Focal Plane）</news:title>
   <news:publication_date>2026-05-13T12:30:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689716</loc>
  <lastmod>2026-05-13T12:30:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い教師付きから学ぶ自動オブジェクト除去（Adversarial Scene Editing: Automatic Object Removal from Weak Supervision）</news:title>
   <news:publication_date>2026-05-13T12:30:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689714</loc>
  <lastmod>2026-05-13T12:29:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRPC: 因果グラフ推定を実用に近づけるRパッケージ（MRPC: An R package for accurate inference of causal graphs）</news:title>
   <news:publication_date>2026-05-13T12:29:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689712</loc>
  <lastmod>2026-05-13T12:29:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的深層学習とランダム化された和積ネットワーク（Probabilistic Deep Learning using Random Sum-Product Networks）</news:title>
   <news:publication_date>2026-05-13T12:29:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689710</loc>
  <lastmod>2026-05-13T12:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Y-Netによる大腸ポリープ検出の実務的意義（Y-Net: A deep Convolutional Neural Network for Polyp Detection）</news:title>
   <news:publication_date>2026-05-13T12:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689708</loc>
  <lastmod>2026-05-13T11:38:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体の状態分類における転移学習の実践（State Classification with CNN）</news:title>
   <news:publication_date>2026-05-13T11:38:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689706</loc>
  <lastmod>2026-05-13T11:37:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>交通用ステレオ画像のセマンティックセグメンテーション性能評価（Performance Evaluation of Deep Learning Networks for Semantic Segmentation of Traffic Stereo-Pair Images）</news:title>
   <news:publication_date>2026-05-13T11:37:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689704</loc>
  <lastmod>2026-05-13T11:37:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形計画法におけるエントロピー罰則の明示的解析（An explicit analysis of the entropic penalty in linear programming）</news:title>
   <news:publication_date>2026-05-13T11:37:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689702</loc>
  <lastmod>2026-05-13T11:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>F理論のTASI講義 (TASI Lectures on F-theory)</news:title>
   <news:publication_date>2026-05-13T11:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689700</loc>
  <lastmod>2026-05-13T11:36:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mg II放射と吸収から読み解く星形成銀河の物理（Mg II emission and absorption in star-forming galaxies）</news:title>
   <news:publication_date>2026-05-13T11:36:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689698</loc>
  <lastmod>2026-05-13T11:36:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量分布のパスワイズ導関数（Pathwise Derivatives for Multivariate Distributions）</news:title>
   <news:publication_date>2026-05-13T11:36:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689696</loc>
  <lastmod>2026-05-13T11:36:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EEGを生成するGANの枠組みと実用性（EEG-GAN: Generative adversarial networks for electroencephalographic (EEG) brain signals）</news:title>
   <news:publication_date>2026-05-13T11:36:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689694</loc>
  <lastmod>2026-05-13T10:44:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異値変換による量子行列演算の飛躍的改善（Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics）</news:title>
   <news:publication_date>2026-05-13T10:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689692</loc>
  <lastmod>2026-05-13T10:43:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hubble Deep UV Legacy Surveyの意義と実務への示唆（The Hubble Deep UV Legacy Survey）</news:title>
   <news:publication_date>2026-05-13T10:43:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689690</loc>
  <lastmod>2026-05-13T10:43:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再パラメータ化トリックを超えるパスワイズ導関数（Pathwise Derivatives Beyond the Reparameterization Trick）</news:title>
   <news:publication_date>2026-05-13T10:43:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689688</loc>
  <lastmod>2026-05-13T10:42:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dynaにおける計画の“形”が高次元状態空間で与える影響（The Effect of Planning Shape on Dyna-style Planning in High-dimensional State Spaces）</news:title>
   <news:publication_date>2026-05-13T10:42:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689686</loc>
  <lastmod>2026-05-13T10:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中位表現に柔軟正規化を統合する（Integrating Flexible Normalization into Mid-Level Representations of Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-05-13T10:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689684</loc>
  <lastmod>2026-05-13T10:41:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペア比較から性能指標を引き出す仕組み（Performance Metric Elicitation from Pairwise Classifier Comparisons）</news:title>
   <news:publication_date>2026-05-13T10:41:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689682</loc>
  <lastmod>2026-05-13T10:41:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リレーショナルな視点で強化学習を変える（Relational Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-13T10:41:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689680</loc>
  <lastmod>2026-05-13T09:49:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係的再帰ニューラルネットワーク（Relational recurrent neural networks）</news:title>
   <news:publication_date>2026-05-13T09:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689678</loc>
  <lastmod>2026-05-13T09:49:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTM 実装のベンチマークが示したもの（LSTM Benchmarks for Deep Learning Frameworks）</news:title>
   <news:publication_date>2026-05-13T09:49:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689676</loc>
  <lastmod>2026-05-13T09:48:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>擾乱ニューラルネットワーク（Perturbative Neural Networks）</news:title>
   <news:publication_date>2026-05-13T09:48:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689674</loc>
  <lastmod>2026-05-13T09:48:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物体検出器に対する敵対的パッチ攻撃（DPATCH: An Adversarial Patch Attack on Object Detectors）</news:title>
   <news:publication_date>2026-05-13T09:48:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689672</loc>
  <lastmod>2026-05-13T09:47:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次的Attend, Infer, Repeatによる移動物体の生成モデリング (Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects)</news:title>
   <news:publication_date>2026-05-13T09:47:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689670</loc>
  <lastmod>2026-05-13T09:47:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AdaGrad のステップサイズ：非凸問題での鋭い収束（AdaGrad stepsizes: Sharp convergence over nonconvex landscapes）</news:title>
   <news:publication_date>2026-05-13T09:47:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689668</loc>
  <lastmod>2026-05-13T09:47:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離可能データ上の確率的勾配降下法：固定学習率でも収束するという発見（Stochastic Gradient Descent on Separable Data: Exact Convergence with a Fixed Learning Rate）</news:title>
   <news:publication_date>2026-05-13T09:47:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689666</loc>
  <lastmod>2026-05-13T08:55:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mix &amp;amp; Match によるエージェント・カリキュラム（Mix &amp;amp; Match – Agent Curricula for Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-13T08:55:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689664</loc>
  <lastmod>2026-05-13T08:55:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイクル一貫性をベイズ的に解釈する（Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference）</news:title>
   <news:publication_date>2026-05-13T08:55:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689662</loc>
  <lastmod>2026-05-13T08:54:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>証拠に基づく深層学習による分類不確実性の定量化（Evidential Deep Learning to Quantify Classification Uncertainty）</news:title>
   <news:publication_date>2026-05-13T08:54:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689660</loc>
  <lastmod>2026-05-13T08:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル＋カーネルで解く条件付き確率密度推定（Neural-Kernelized Conditional Density Estimation）</news:title>
   <news:publication_date>2026-05-13T08:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689658</loc>
  <lastmod>2026-05-13T08:54:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非一様サンプリング点群に対するモンテカルロ畳み込み（Monte Carlo Convolution for Learning on Non-Uniformly Sampled Point Clouds）</news:title>
   <news:publication_date>2026-05-13T08:54:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689656</loc>
  <lastmod>2026-05-13T08:54:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銘柄選択のための機械学習フレームワーク (A Machine Learning Framework for Stock Selection)</news:title>
   <news:publication_date>2026-05-13T08:54:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689654</loc>
  <lastmod>2026-05-13T08:53:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>概念志向深層学習の本質（Concept-Oriented Deep Learning）</news:title>
   <news:publication_date>2026-05-13T08:53:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689652</loc>
  <lastmod>2026-05-13T08:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライマン連続体放射の逃亡調査：z=3.1における[O III]強出源からの電離放射（THE LYMAN CONTINUUM ESCAPE SURVEY: IONIZING RADIATION FROM [O III]-STRONG SOURCES AT A REDSHIFT OF 3.1）</news:title>
   <news:publication_date>2026-05-13T08:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689650</loc>
  <lastmod>2026-05-13T08:01:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イールドカーブの特徴抽出における機械学習の応用（Machine Learning for Yield Curve Feature Extraction: Application to Illiquid Corporate Bonds）</news:title>
   <news:publication_date>2026-05-13T08:01:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689648</loc>
  <lastmod>2026-05-13T08:00:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みネットワークを用いた疾病予測（Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer’s Disease）</news:title>
   <news:publication_date>2026-05-13T08:00:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689646</loc>
  <lastmod>2026-05-13T08:00:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競合する予測アルゴリズムのゲーム理論的分析（Competing Prediction Algorithms）</news:title>
   <news:publication_date>2026-05-13T08:00:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689644</loc>
  <lastmod>2026-05-13T07:59:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間のような一般化を機械が行う方法（Human-like generalization in a machine through predicate learning）</news:title>
   <news:publication_date>2026-05-13T07:59:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689642</loc>
  <lastmod>2026-05-13T07:59:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PBILのレベル別解析（Level-Based Analysis of the Population-Based Incremental Learning Algorithm）</news:title>
   <news:publication_date>2026-05-13T07:59:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689640</loc>
  <lastmod>2026-05-13T07:59:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ構造推定に基づくスパーシファイング変換学習（Graph topology inference based on sparsifying transform learning）</news:title>
   <news:publication_date>2026-05-13T07:59:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689638</loc>
  <lastmod>2026-05-13T07:07:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>距離制約最適化の射影法（A Projection Method for Metric-Constrained Optimization）</news:title>
   <news:publication_date>2026-05-13T07:07:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689636</loc>
  <lastmod>2026-05-13T06:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原始惑星系円盤中の大気リサイクル抑制と浮力障壁（Suppression of atmospheric recycling of planets embedded in a protoplanetary disc by buoyancy barrier）</news:title>
   <news:publication_date>2026-05-13T06:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689634</loc>
  <lastmod>2026-05-13T06:57:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実用的なディープステレオ（Practical Deep Stereo）</news:title>
   <news:publication_date>2026-05-13T06:57:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689632</loc>
  <lastmod>2026-05-13T06:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベル付き文字列から複数言語を学ぶ手法（Learning Several Languages from Labeled Strings: State Merging and Evolutionary Approaches）</news:title>
   <news:publication_date>2026-05-13T06:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689630</loc>
  <lastmod>2026-05-13T06:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基底空間の双曲性に関する進展（ON THE HYPERBOLICITY OF BASE SPACES FOR MAXIMALLY VARIATIONAL FAMILIES OF SMOOTH PROJECTIVE VARIETIES）</news:title>
   <news:publication_date>2026-05-13T06:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689628</loc>
  <lastmod>2026-05-13T06:56:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均が有限でない潜在分布を持つ生成モデルに関する考察（On Latent Distributions Without Finite Mean in Generative Models）</news:title>
   <news:publication_date>2026-05-13T06:56:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689626</loc>
  <lastmod>2026-05-13T06:56:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みカーネルを用いた深いガウス過程（Deep Gaussian Processes with Convolutional Kernels）</news:title>
   <news:publication_date>2026-05-13T06:56:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689624</loc>
  <lastmod>2026-05-13T06:04:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成可能な可逆ネットワークの訓練戦略（Training Generative Reversible Networks）</news:title>
   <news:publication_date>2026-05-13T06:04:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689622</loc>
  <lastmod>2026-05-13T05:55:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語順を説明して意味表現から統語構造を取り除く（Explaining Away Syntactic Structure in Semantic Document Representations）</news:title>
   <news:publication_date>2026-05-13T05:55:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689620</loc>
  <lastmod>2026-05-13T05:54:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索空間の縁問題を回避するベイズ最適化手法（BOCK : Bayesian Optimization with Cylindrical Kernels）</news:title>
   <news:publication_date>2026-05-13T05:54:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689618</loc>
  <lastmod>2026-05-13T05:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>加速ランダム座標降下法による確率的最適化とオンライン学習（Accelerated Randomized Coordinate Descent Algorithms for Stochastic Optimization and Online Learning）</news:title>
   <news:publication_date>2026-05-13T05:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689616</loc>
  <lastmod>2026-05-13T05:53:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外生的状態変数と報酬を見つけて除去する手法（Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-13T05:53:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689614</loc>
  <lastmod>2026-05-13T05:53:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層の重み回転が示す汎化性能の強力な指標（Layer rotation: a surprisingly powerful indicator of generalization in deep networks?）</news:title>
   <news:publication_date>2026-05-13T05:53:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689612</loc>
  <lastmod>2026-05-13T05:53:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパボリックタンジェント減衰による学習率スケジューリング（Stochastic Gradient Descent with Hyperbolic-Tangent Decay on Classification）</news:title>
   <news:publication_date>2026-05-13T05:53:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689610</loc>
  <lastmod>2026-05-13T05:01:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量画像超解像ネットワークの適応的重要度学習（Adaptive Importance Learning for Improving Lightweight Image Super-resolution Network）</news:title>
   <news:publication_date>2026-05-13T05:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689608</loc>
  <lastmod>2026-05-13T04:52:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GuideR: ユーザー主導のルール学習がもたらす現場導入の革新（GuideR: a guided separate-and-conquer rule learning in classification, regression, and survival settings）</news:title>
   <news:publication_date>2026-05-13T04:52:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689606</loc>
  <lastmod>2026-05-13T04:51:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファジィC-平均法の視覚的品質指標（A Visual Quality Index for Fuzzy C-Means）</news:title>
   <news:publication_date>2026-05-13T04:51:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689604</loc>
  <lastmod>2026-05-13T04:50:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幼鳥ハトの局所生存とユーメラニン色彩（Eumelanin-based colouration reflects local survival of juvenile feral pigeons in an urban pigeon house）</news:title>
   <news:publication_date>2026-05-13T04:50:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689602</loc>
  <lastmod>2026-05-13T04:50:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化と信頼性を両立する医療時系列予測：Deep Mixed Effect Model using Gaussian Processes（Deep Mixed Effect Model using Gaussian Processes）</news:title>
   <news:publication_date>2026-05-13T04:50:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689600</loc>
  <lastmod>2026-05-13T04:50:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数アルゴリズムを組み合わせる新しいアンサンブル結合法（Combining Multiple Algorithms in Classifier Ensembles using Generalized Mixture Functions）</news:title>
   <news:publication_date>2026-05-13T04:50:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689598</loc>
  <lastmod>2026-05-13T04:49:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数ラベルと大量未ラベルを活かす半教師ありクラスタリング（Semi-Supervised Clustering with Neural Networks）</news:title>
   <news:publication_date>2026-05-13T04:49:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689596</loc>
  <lastmod>2026-05-13T03:58:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>浅い埋め込みによる深いMixture of Experts（Deep Mixture of Experts via Shallow Embedding）</news:title>
   <news:publication_date>2026-05-13T03:58:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689594</loc>
  <lastmod>2026-05-13T03:58:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Leolani：社会的コミュニケーションのための心の理論を持つ参照マシン（Leolani: a reference machine with a theory of mind for social communication）</news:title>
   <news:publication_date>2026-05-13T03:58:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689592</loc>
  <lastmod>2026-05-13T03:57:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限幅の深層ReLUネットワークの普遍近似力（The Universal Approximation Power of Finite-Width Deep ReLU Networks）</news:title>
   <news:publication_date>2026-05-13T03:57:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689590</loc>
  <lastmod>2026-05-13T03:56:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ℓpハイパーパラメータ学習のバイレベル非滑らか最適化（On ℓp-hyperparameter Learning via Bilevel Nonsmooth Optimization）</news:title>
   <news:publication_date>2026-05-13T03:56:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689588</loc>
  <lastmod>2026-05-13T03:56:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース会話コーパスに対するニューラル意味役割ラベリングのマルチタスク能動学習（Multi-Task Active Learning for Neural Semantic Role Labeling on Low Resource Conversational Corpus）</news:title>
   <news:publication_date>2026-05-13T03:56:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689586</loc>
  <lastmod>2026-05-13T03:56:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビジネスアーキテクチャのデータ駆動解析：グラフ理論の活用提案 (Data-driven Analytics for Business Architectures: Proposed Use of Graph Theory)</news:title>
   <news:publication_date>2026-05-13T03:56:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689584</loc>
  <lastmod>2026-05-13T03:56:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AIDA言語による科学的主張の形式化（Using the AIDA Language to Formally Organize Scientific Claims）</news:title>
   <news:publication_date>2026-05-13T03:56:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689582</loc>
  <lastmod>2026-05-13T03:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意機構付き全畳み込みネットワークによる音声感情認識（Attention Based Fully Convolutional Network for Speech Emotion Recognition）</news:title>
   <news:publication_date>2026-05-13T03:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689580</loc>
  <lastmod>2026-05-13T03:03:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>退屈が好奇心を駆動する仕組み：Homeo-Heterostatic Value Gradients（Boredom-driven curious learning by Homeo-Heterostatic Value Gradients）</news:title>
   <news:publication_date>2026-05-13T03:03:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689578</loc>
  <lastmod>2026-05-13T03:03:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド深層画像圧縮（Deep Image Compression via End-to-End Learning）</news:title>
   <news:publication_date>2026-05-13T03:03:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689576</loc>
  <lastmod>2026-05-13T03:02:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>μSR用FPGA実装32チャンネルTDCの設計と評価（32-channel TDC Implemented in FPGA for μSR Spectrometer）</news:title>
   <news:publication_date>2026-05-13T03:02:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689574</loc>
  <lastmod>2026-05-13T03:02:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2D周辺ヒートマップによる3D人体姿勢推定（3D Human Pose Estimation with 2D Marginal Heatmaps）</news:title>
   <news:publication_date>2026-05-13T03:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689572</loc>
  <lastmod>2026-05-13T03:02:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>犯罪予測に関する深層学習の試み（Forecasting Crime with Deep Learning）</news:title>
   <news:publication_date>2026-05-13T03:02:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689570</loc>
  <lastmod>2026-05-13T03:01:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果分析入門（A Primer on Causal Analysis）</news:title>
   <news:publication_date>2026-05-13T03:01:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689568</loc>
  <lastmod>2026-05-13T02:10:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SoPhie: 社会的・物理的制約に従う軌跡を予測する注意型GAN（SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints）</news:title>
   <news:publication_date>2026-05-13T02:10:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689566</loc>
  <lastmod>2026-05-13T02:10:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダルでソーシャルメディアを理解するJTAV（JTAV: Jointly Learning Social Media Content Representation by Fusing Textual, Acoustic, and Visual Features）</news:title>
   <news:publication_date>2026-05-13T02:10:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689564</loc>
  <lastmod>2026-05-13T02:10:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説明可能な敵対的頑健性指標（An Explainable Adversarial Robustness Metric for Deep Learning Neural Networks）</news:title>
   <news:publication_date>2026-05-13T02:10:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689562</loc>
  <lastmod>2026-05-13T02:08:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>(24) Themis における塵放出の探索とその示唆（Search for Dust Emission from (24) Themis Using the Gemini-North Telescope）</news:title>
   <news:publication_date>2026-05-13T02:08:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689560</loc>
  <lastmod>2026-05-13T02:07:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>正則化スペクトラルクラスタリングとグラフ導電率の再解釈（Understanding Regularized Spectral Clustering via Graph Conductance）</news:title>
   <news:publication_date>2026-05-13T02:07:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689558</loc>
  <lastmod>2026-05-13T02:07:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き相互情報量を用いた適応エラスティックネットによるマイクロアレイ遺伝子選択（Informative Gene Selection for Microarray Classification via Adaptive Elastic Net with Conditional Mutual Information）</news:title>
   <news:publication_date>2026-05-13T02:07:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689556</loc>
  <lastmod>2026-05-13T02:07:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回避型敵対者下でのPAC学習の限界（PAC-learning in the presence of evasion adversaries）</news:title>
   <news:publication_date>2026-05-13T02:07:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689554</loc>
  <lastmod>2026-05-13T01:15:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星の対流層における磁場がもたらすTaylor–Proudman平衡の破れ（Breaking Taylor-Proudman balance by magnetic field in stellar convection zone）</news:title>
   <news:publication_date>2026-05-13T01:15:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689552</loc>
  <lastmod>2026-05-13T01:14:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結合論理クエリを埋め込む知識グラフの技術（Embedding Logical Queries on Knowledge Graphs）</news:title>
   <news:publication_date>2026-05-13T01:14:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689550</loc>
  <lastmod>2026-05-13T01:14:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間変動ネットワークの固有表現（EigenNetworks）</news:title>
   <news:publication_date>2026-05-13T01:14:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689548</loc>
  <lastmod>2026-05-13T01:13:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合周辺尤度によるランダム効用モデルの推定（Composite Marginal Likelihood Methods for Random Utility Models）</news:title>
   <news:publication_date>2026-05-13T01:13:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689546</loc>
  <lastmod>2026-05-13T01:13:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BindsNET: 機械学習志向のスパイキングニューラルネットワークライブラリ（BindsNET: A machine learning-oriented spiking neural networks library in Python）</news:title>
   <news:publication_date>2026-05-13T01:13:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689544</loc>
  <lastmod>2026-05-13T01:13:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ空間ノイズで深層Q学習の方策改ざん攻撃を緩和する（Mitigation of Policy Manipulation Attacks on Deep Q-Networks with Parameter-Space Noise）</news:title>
   <news:publication_date>2026-05-13T01:13:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689542</loc>
  <lastmod>2026-05-13T01:13:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DAWNBENCHのTTA評価が示す現場での示唆（Analysis of DAWNBench: Time-to-Accuracy）</news:title>
   <news:publication_date>2026-05-13T01:13:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689540</loc>
  <lastmod>2026-05-13T00:22:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CFCM: Coarse-to-Fine Context Memoryを用いた医用画像セグメンテーション（CFCM: Segmentation via Coarse to Fine Context Memory）</news:title>
   <news:publication_date>2026-05-13T00:22:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689538</loc>
  <lastmod>2026-05-13T00:21:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FlowNet3Dによる3次元点群のシーンフロー学習（FlowNet3D: Learning Scene Flow in 3D Point Clouds）</news:title>
   <news:publication_date>2026-05-13T00:21:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689536</loc>
  <lastmod>2026-05-13T00:21:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在構造ランダムグラフの推定と推論（On estimation and inference in latent structure random graphs）</news:title>
   <news:publication_date>2026-05-13T00:21:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689534</loc>
  <lastmod>2026-05-13T00:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンザフライ追跡のための粒子フィルタと焼きなまし重み付けQPSO（Learning to track on-the-fly using a particle filter with annealed-weighted QPSO modeled after a singular Dirac delta potential）</news:title>
   <news:publication_date>2026-05-13T00:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689532</loc>
  <lastmod>2026-05-13T00:20:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>累積報酬を超えるバンディット枠組みの一般化（A General Framework for Bandit Problems Beyond Cumulative Objectives）</news:title>
   <news:publication_date>2026-05-13T00:20:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689530</loc>
  <lastmod>2026-05-13T00:19:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な人間の移動データを用いた長期犯罪予測（Mining large-scale human mobility data for long-term crime prediction）</news:title>
   <news:publication_date>2026-05-13T00:19:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689528</loc>
  <lastmod>2026-05-13T00:19:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因子分解型敵対的ネットワークによる教師なしドメイン適応（Factorized Adversarial Networks for Unsupervised Domain Adaptation）</news:title>
   <news:publication_date>2026-05-13T00:19:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689526</loc>
  <lastmod>2026-05-12T23:27:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>6つのニューロンでアタリを攻略する方法（Playing Atari with Six Neurons）</news:title>
   <news:publication_date>2026-05-12T23:27:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689524</loc>
  <lastmod>2026-05-12T23:27:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的強化学習による自律走行車の衝突回避ベンチマーク化（Adversarial Reinforcement Learning Framework for Benchmarking Collision Avoidance Mechanisms in Autonomous Vehicles）</news:title>
   <news:publication_date>2026-05-12T23:27:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689522</loc>
  <lastmod>2026-05-12T23:26:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前処理の違いを超えて学ぶ―前立腺組織スライド分類のための敵対的ドメイン適応（Adversarial Domain Adaptation for Classification of Prostate Histopathology Whole-Slide Images）</news:title>
   <news:publication_date>2026-05-12T23:26:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689520</loc>
  <lastmod>2026-05-12T23:26:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T23:26:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バックドロップ：確率的逆伝播の直感と実務的意義（Backdrop: Stochastic Backpropagation）</news:title>
   <news:publication_date>2026-05-12T23:25:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T23:25:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689514</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プラトー関数の精密ランタイム解析（Precise Runtime Analysis for Plateau Functions）</news:title>
   <news:publication_date>2026-05-12T23:25:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689512</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純で強力な単語埋め込みの整列手法（Closed Form Word Embedding Alignment）</news:title>
   <news:publication_date>2026-05-12T22:33:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689510</loc>
  <lastmod>2026-05-12T22:32:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Next-Door解析によるポストモデル検討（Post model-fitting exploration via a “Next-Door” analysis）</news:title>
   <news:publication_date>2026-05-12T22:32:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689508</loc>
  <lastmod>2026-05-12T22:32:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動による電力系の撹乱位置推定と大きさの推定（Data-driven Localization and Estimation of Disturbance in the Interconnected Power System）</news:title>
   <news:publication_date>2026-05-12T22:32:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689506</loc>
  <lastmod>2026-05-12T22:31:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークにおけるフィッシャー情報の普遍統計（Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach）</news:title>
   <news:publication_date>2026-05-12T22:31:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689504</loc>
  <lastmod>2026-05-12T22:31:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Y-Net: 乳房生検画像のための同時セグメンテーションと分類（Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images）</news:title>
   <news:publication_date>2026-05-12T22:31:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689502</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M33銀河におけるGMCスケールの星形成則（The star-formation law at GMC scales in M33, the Triangulum Galaxy）</news:title>
   <news:publication_date>2026-05-12T22:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689500</loc>
  <lastmod>2026-05-12T22:30:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳線維配向のエンドツーエンド推定（End to End Brain Fiber Orientation Estimation Using Deep Learning）</news:title>
   <news:publication_date>2026-05-12T22:30:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689498</loc>
  <lastmod>2026-05-12T21:39:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼自己教師あり深度推定の深掘り（Digging Into Self-Supervised Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-05-12T21:39:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689496</loc>
  <lastmod>2026-05-12T21:38:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習で設計する非線形向け符号化（Learning a Code: Machine Learning for Approximate Non-Linear Coded Computation）</news:title>
   <news:publication_date>2026-05-12T21:38:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689494</loc>
  <lastmod>2026-05-12T21:38:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合意ベース学習（Agreement-based Learning）</news:title>
   <news:publication_date>2026-05-12T21:38:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689492</loc>
  <lastmod>2026-05-12T21:38:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T21:38:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689490</loc>
  <lastmod>2026-05-12T21:37:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理法則は反事実的通信を禁止しない（The laws of physics do not prohibit counterfactual communication）</news:title>
   <news:publication_date>2026-05-12T21:37:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689488</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル向けRNN圧縮の動的階層革新：DirNet（Dynamically Hierarchy Revolution: DirNet for Compressing Recurrent Neural Network on Mobile Devices）</news:title>
   <news:publication_date>2026-05-12T21:37:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689486</loc>
  <lastmod>2026-05-12T21:37:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ML-Leaksによる学習データ漏洩の実態（ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models）</news:title>
   <news:publication_date>2026-05-12T21:37:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689484</loc>
  <lastmod>2026-05-12T20:45:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Graphsの提案と意義（Deep Graphs）</news:title>
   <news:publication_date>2026-05-12T20:45:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689482</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディフェオモルフィック学習の要点と経営への示唆（Diffeomorphic Learning）</news:title>
   <news:publication_date>2026-05-12T20:45:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689480</loc>
  <lastmod>2026-05-12T20:45:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフニューラルネットワークによる学習可能な物理エンジン（Graph Networks as Learnable Physics Engines for Inference and Control）</news:title>
   <news:publication_date>2026-05-12T20:45:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689478</loc>
  <lastmod>2026-05-12T20:44:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元強化学習における進化戦略の課題（Challenges in High-dimensional Reinforcement Learning with Evolution Strategies）</news:title>
   <news:publication_date>2026-05-12T20:44:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689476</loc>
  <lastmod>2026-05-12T20:44:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>眼鏡耐性を持つ顔認識のための顔合成（Face Synthesis for Eyeglass-Robust Face Recognition）</news:title>
   <news:publication_date>2026-05-12T20:44:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689474</loc>
  <lastmod>2026-05-12T20:44:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-12T20:44:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689472</loc>
  <lastmod>2026-05-12T20:43:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と機械における物理的構築のための関係性誘導バイアス（Relational inductive bias for physical construction in humans and machines）</news:title>
   <news:publication_date>2026-05-12T20:43:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689470</loc>
  <lastmod>2026-05-12T19:53:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>副作用の罰則に関するステップワイズ相対到達可能性（Penalizing side effects using stepwise relative reachability）</news:title>
   <news:publication_date>2026-05-12T19:53:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689468</loc>
  <lastmod>2026-05-12T19:52:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非対称相互制約を持つ深層連続条件付き確率場によるオンライン多物体追跡（Deep Continuous Conditional Random Fields with Asymmetric Inter-object Constraints for Online Multi-object Tracking）</news:title>
   <news:publication_date>2026-05-12T19:52:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689466</loc>
  <lastmod>2026-05-12T19:51:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dual-tree複素ウェーブレット変換のための勾配ベースフィルタ設計（Gradient-based Filter Design for the Dual-tree Wavelet Transform）</news:title>
   <news:publication_date>2026-05-12T19:51:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689464</loc>
  <lastmod>2026-05-12T19:50:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏極された深部散乱における電弱パラメータの決定（Determination of electroweak parameters in polarised deep-inelastic scattering at HERA）</news:title>
   <news:publication_date>2026-05-12T19:50:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689462</loc>
  <lastmod>2026-05-12T19:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互推薦のオンライン学習と理論的保証（Online Reciprocal Recommendation with Theoretical Performance Guarantees）</news:title>
   <news:publication_date>2026-05-12T19:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689460</loc>
  <lastmod>2026-05-12T19:50:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TDか否か：深層強化学習における時間差分の役割（TD OR NOT TD: ANALYZING THE ROLE OF TEMPORAL DIFFERENCING IN DEEP REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-05-12T19:50:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689458</loc>
  <lastmod>2026-05-12T19:50:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>K-meansによる効率的かつ拡張性の高いバッチベイズ最適化（Efficient and Scalable Batch Bayesian Optimization Using K-Means）</news:title>
   <news:publication_date>2026-05-12T19:50:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689456</loc>
  <lastmod>2026-05-12T18:57:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>天王星におけるメタン分布と極域の明るさ変化（THE METHANE DISTRIBUTION AND POLAR BRIGHTENING ON URANUS）</news:title>
   <news:publication_date>2026-05-12T18:57:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689454</loc>
  <lastmod>2026-05-12T18:56:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事例とプロトタイプから学ぶ分類の考え方（Learning from Exemplars and Prototypes in Machine Learning and Psychology）</news:title>
   <news:publication_date>2026-05-12T18:56:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689452</loc>
  <lastmod>2026-05-12T18:56:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストを脳地図に翻訳する手法（Text to brain: predicting the spatial distribution of neuroimaging observations from text reports）</news:title>
   <news:publication_date>2026-05-12T18:56:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689450</loc>
  <lastmod>2026-05-12T18:56:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形時系列とニューラルネットによるRed Hatのボラティリティ解析（Non-linear Time Series and Artificial Neural Network of Red Hat Volatility）</news:title>
   <news:publication_date>2026-05-12T18:56:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689448</loc>
  <lastmod>2026-05-12T18:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間依存交絡因子の最適バランシングによる周辺構造モデルの改善（Optimal balancing of time-dependent confounders for marginal structural models）</news:title>
   <news:publication_date>2026-05-12T18:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689446</loc>
  <lastmod>2026-05-12T18:55:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群ごとの定常ノイズを調整してICAを堅牢化する（Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise）</news:title>
   <news:publication_date>2026-05-12T18:55:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689444</loc>
  <lastmod>2026-05-12T18:55:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層多構造形状解析：神経解剖学への応用（Deep Multi-Structural Shape Analysis: Application to Neuroanatomy）</news:title>
   <news:publication_date>2026-05-12T18:55:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689442</loc>
  <lastmod>2026-05-12T18:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個体間公平性に基づくデータ表現学習の意義（iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making）</news:title>
   <news:publication_date>2026-05-12T18:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689440</loc>
  <lastmod>2026-05-12T18:03:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキサス・オクラホマ・カンザス州におけるPGA・PGV予測のためのニューラルネットワーク方程式（Neural Network-Based Equations for Predicting PGA and PGV in Texas, Oklahoma, and Kansas）</news:title>
   <news:publication_date>2026-05-12T18:03:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689438</loc>
  <lastmod>2026-05-12T18:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RedNet：残差エンコーダ・デコーダによる屋内RGB-Dセマンティックセグメンテーション（RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-12T18:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689436</loc>
  <lastmod>2026-05-12T18:01:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペロブスカイト酸化物の熱力学的安定性予測（Predicting the thermodynamic stability of perovskite oxides using machine learning models）</news:title>
   <news:publication_date>2026-05-12T18:01:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689434</loc>
  <lastmod>2026-05-12T18:01:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自閉スペクトラム症支援を目的としたモバイルアプリの実務的レビュー（Applications for mobile devices focused on support for autism spectrum disorder population and / or people in their immediate environment in their daily lives: a systematic and practical review from a Spanish-speaking perspective）</news:title>
   <news:publication_date>2026-05-12T18:01:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689432</loc>
  <lastmod>2026-05-12T18:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳画像データの規範的モデリングとスケーラブルなマルチタスクガウス過程（Normative Modeling of Neuroimaging Data using Scalable Multi-Task Gaussian Processes）</news:title>
   <news:publication_date>2026-05-12T18:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689430</loc>
  <lastmod>2026-05-12T18:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多ユーザ向け多アンテナマルチキャストの遅延性能（Delay Performance of Multi-Antenna Multicasting in Wireless Networks）</news:title>
   <news:publication_date>2026-05-12T18:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689428</loc>
  <lastmod>2026-05-12T17:09:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膵嚢胞の画像診断を変える一歩（Differential Diagnosis for Pancreatic Cysts in CT Scans Using Densely-Connected Convolutional Networks）</news:title>
   <news:publication_date>2026-05-12T17:09:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689426</loc>
  <lastmod>2026-05-12T17:08:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークポテンシャルと古典力場の適応結合（Adaptive coupling of a deep neural network potential to a classical force field）</news:title>
   <news:publication_date>2026-05-12T17:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689424</loc>
  <lastmod>2026-05-12T17:07:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形ヌーリングによるメタラーニングの考え方と実務的含意（Meta-Learner with Linear Nulling）</news:title>
   <news:publication_date>2026-05-12T17:07:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689422</loc>
  <lastmod>2026-05-12T17:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的二重レベル多目的進化による単層・多層エコーステートネットワーク自己符号化器の進化（Hierarchical Bi-level Multi-Objective Evolution of Single- and Multi-layer Echo State Network Autoencoders for Data Representations）</news:title>
   <news:publication_date>2026-05-12T17:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689420</loc>
  <lastmod>2026-05-12T17:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度マルチモードファイバー内視鏡による深部脳イメージングの進展（High-fidelity multimode fibre-based endoscopy for deep‑brain in vivo imaging）</news:title>
   <news:publication_date>2026-05-12T17:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689418</loc>
  <lastmod>2026-05-12T17:05:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木構造グラフ上の全変動正則化推定量の理論と実務的示唆（On the total variation regularized estimator over a class of tree graphs）</news:title>
   <news:publication_date>2026-05-12T17:05:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689416</loc>
  <lastmod>2026-05-12T17:05:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データで熱赤外（TIR）トラッキングを変える（Synthetic data generation for end-to-end thermal infrared tracking）</news:title>
   <news:publication_date>2026-05-12T17:05:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689414</loc>
  <lastmod>2026-05-12T16:14:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互評価から学ぶ分散学習（Distributed Learning from Interactions in Social Networks）</news:title>
   <news:publication_date>2026-05-12T16:14:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689412</loc>
  <lastmod>2026-05-12T16:13:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>提案したエポックとMFCC特徴を用いたDNN-HMMベースの話者適応感情認識（DNN-HMM based Speaker Adaptive Emotion Recognition using Proposed Epoch and MFCC Features）</news:title>
   <news:publication_date>2026-05-12T16:13:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689410</loc>
  <lastmod>2026-05-12T16:12:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所適応大マージンを導入する深層埋め込み学習（ALMN: Deep Embedding Learning with Geometrical Virtual Point Generating）</news:title>
   <news:publication_date>2026-05-12T16:12:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689408</loc>
  <lastmod>2026-05-12T16:12:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汚れたカテゴリ変数の学習のための類似度エンコーディング (Similarity encoding for learning with dirty categorical variables)</news:title>
   <news:publication_date>2026-05-12T16:12:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689406</loc>
  <lastmod>2026-05-12T16:12:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークプロトコルの自動抽象化と弱教師ありクラスタリング（Automatic clustering of a network protocol with weakly-supervised clustering）</news:title>
   <news:publication_date>2026-05-12T16:12:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689404</loc>
  <lastmod>2026-05-12T16:11:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小平均の逐次検定：ThompsonからMurphyサンプリングへ（Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling）</news:title>
   <news:publication_date>2026-05-12T16:11:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689402</loc>
  <lastmod>2026-05-12T16:10:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師データなしで学習する画像デノイザ（Training deep learning based image denoisers from undersampled measurements without ground truth and without image prior）</news:title>
   <news:publication_date>2026-05-12T16:10:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689400</loc>
  <lastmod>2026-05-12T15:19:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライベートPAC学習は有限のLittlestone次元を示唆する（Private PAC learning implies finite Littlestone dimension）</news:title>
   <news:publication_date>2026-05-12T15:19:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689398</loc>
  <lastmod>2026-05-12T15:19:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配／ミラー降下法：ミニマックス最適性と暗黙の正則化（STOCHASTIC GRADIENT/MIRROR DESCENT: MINI-MAX OPTIMALITY AND IMPLICIT REGULARIZATION）</news:title>
   <news:publication_date>2026-05-12T15:19:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689396</loc>
  <lastmod>2026-05-12T15:18:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>安定化された自由空間光周波数伝送（Stabilized free-space optical frequency transfer）</news:title>
   <news:publication_date>2026-05-12T15:18:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689394</loc>
  <lastmod>2026-05-12T15:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小児X線画像におけるカテーテル自動検出（Automatic catheter detection in pediatric X-ray images using a scale-recurrent network and synthetic data）</news:title>
   <news:publication_date>2026-05-12T15:17:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689392</loc>
  <lastmod>2026-05-12T15:17:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ホログラフィックニューラルアーキテクチャ（Holographic Neural Architectures）</news:title>
   <news:publication_date>2026-05-12T15:17:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689390</loc>
  <lastmod>2026-05-12T15:17:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚仕様からのプログラム合成（Program Synthesis from Visual Specification）</news:title>
   <news:publication_date>2026-05-12T15:17:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/689388</loc>
  <lastmod>2026-05-12T15:16:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散計算の安全性と可用性を同時に高める設計 — Lagrange Coded Computing（Lagrange Coded Computing: Optimal Design for Resiliency, Security, and Privacy）</news:title>
   <news:publication_date>2026-05-12T15:16:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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