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   <news:title>座標変換で暴露された畳み込みニューラルネットワークの落とし穴（An intriguing failing of convolutional neural networks and the CoordConv solution）</news:title>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>量子ニューラルネットワークのベンチマーク—古典NNとの比較で示された効率性（Benchmarking Neural Networks For Quantum Computations）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>多目的進化的特徴選択による放射線画像の選別（Multi-objective Feature Selection with Modified Entropy Termination and Evidential Reasoning）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>発達期における抑制のブレインワイド発達を深層学習で探る（Exploring Brain-wide Development of Inhibition through Deep Learning）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>FHIRChainによる臨床データの安全かつスケーラブルな共有（FHIRChain: Applying Blockchain to Securely and Scalably Share Clinical Data）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>渦と磁場がつむぐ“大きさの逆転”──渦度・ヘリシティと双方向カスケードの概観（Helicity dynamics, inverse and bi-directional cascades in fluid and magnetohydrodynamic turbulence: A brief review）</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/693832</loc>
  <lastmod>2026-05-24T16:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>RNNを用いたNIDS強化の方法（RNNIDS: Enhancing Network Intrusion Detection Systems through Deep Learning）</news:title>
   <news:publication_date>2026-05-24T16:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/693830</loc>
  <lastmod>2026-05-24T16:19:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的モデル平均による効率的な分散深層学習（Efficient Decentralized Deep Learning by Dynamic Model Averaging）</news:title>
   <news:publication_date>2026-05-24T16:19:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-24T16:19:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーソナライズされた語彙学習チュータの設計と評価（Design and Evaluation of a Tutor Platform for Personalized Vocabulary Learning）</news:title>
   <news:publication_date>2026-05-24T16:19:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/693826</loc>
  <lastmod>2026-05-24T16:18:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>身近な材料と低コストセンサーで物理を学ぶ（Low-Cost Experiments with Everyday Objects for Homework Assignments）</news:title>
   <news:publication_date>2026-05-24T16:18:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延が未知のバンディット・オンライン学習（Bandit Online Learning with Unknown Delays）</news:title>
   <news:publication_date>2026-05-24T16:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/693822</loc>
  <lastmod>2026-05-24T16:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Thresholded ConvNet Ensemblesによるテクニカル予測の要点（Thresholded ConvNet Ensembles: Neural Networks for Technical Forecasting）</news:title>
   <news:publication_date>2026-05-24T16:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/693820</loc>
  <lastmod>2026-05-24T16:18:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似k空間モデルと深層学習による高速光音響再構成（Approximate k-space models and Deep Learning for fast photoacoustic reconstruction）</news:title>
   <news:publication_date>2026-05-24T16:18:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/693818</loc>
  <lastmod>2026-05-24T15:26:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エリートアスリートにおける心肺パラメータの因果経路発見（Discovery of causal paths in cardiorespiratory parameters: a time-independent approach in elite athletes）</news:title>
   <news:publication_date>2026-05-24T15:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/693816</loc>
  <lastmod>2026-05-24T15:25:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い文脈化単語埋め込み、アンサンブル、ツリーバンク連結によるUDパーシングの改善（Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank Concatenation）</news:title>
   <news:publication_date>2026-05-24T15:25:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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  <loc>https://aibr.jp/archives/693814</loc>
  <lastmod>2026-05-24T15:25:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースネットワークのためのBeta Neutral-to-the-Leftモデルのサンプリングと推論（Sampling and Inference for Beta Neutral-to-the-Left Models of Sparse Networks）</news:title>
   <news:publication_date>2026-05-24T15:25:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/693812</loc>
  <lastmod>2026-05-24T15:24:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層マルチモーダルクラスタリングによる教師なし音声映像学習（Deep Multimodal Clustering for Unsupervised Audiovisual Learning）</news:title>
   <news:publication_date>2026-05-24T15:24:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/693810</loc>
  <lastmod>2026-05-24T15:24:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形計測とニューラルネットワークによるMRPCの時間再構成法（The study of a new time reconstruction method for MRPC read out by waveform digitizer）</news:title>
   <news:publication_date>2026-05-24T15:24:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/693808</loc>
  <lastmod>2026-05-24T15:23:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NMT-Keras：対話型・継続学習に注力した柔軟な機械翻訳ツールキット（NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning）</news:title>
   <news:publication_date>2026-05-24T15:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/693806</loc>
  <lastmod>2026-05-24T15:23:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分実行で強化するText-to-SQL（Robust Text-to-SQL Generation with Execution-Guided Decoding）</news:title>
   <news:publication_date>2026-05-24T15:23:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/693804</loc>
  <lastmod>2026-05-24T14:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓不整脈発生源のコンピュータ支援局在化（Computer Assisted Localization of a Heart Arrhythmia）</news:title>
   <news:publication_date>2026-05-24T14:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693802</loc>
  <lastmod>2026-05-24T14:31:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共分散と濃度グラフ行列のシミュレーション（SIMULATING COVARIANCE AND CONCENTRATION GRAPH MATRICES）</news:title>
   <news:publication_date>2026-05-24T14:31:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/693800</loc>
  <lastmod>2026-05-24T14:31:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画要約を分類で導く強化学習（Video Summarisation by Classification with Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-24T14:31:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693798</loc>
  <lastmod>2026-05-24T14:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次診断における能動学習ヒューリスティクスの評価（Evaluating Active Learning Heuristics for Sequential Diagnosis）</news:title>
   <news:publication_date>2026-05-24T14:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693796</loc>
  <lastmod>2026-05-24T14:31:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ChestNetによる胸部X線画像の診断向上（ChestNet: A Deep Neural Network for Classification of Thoracic Diseases on Chest Radiography）</news:title>
   <news:publication_date>2026-05-24T14:31:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/693794</loc>
  <lastmod>2026-05-24T14:30:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>精度学習に基づくニューラルネットワーク設計：平行線投影から扇形線投影への変換（Deriving Neural Network Architectures using Precision Learning: Parallel-to-fan beam Conversion）</news:title>
   <news:publication_date>2026-05-24T14:30:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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  <loc>https://aibr.jp/archives/693792</loc>
  <lastmod>2026-05-24T14:30:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークを用いた時間差分学習におけるリーケージ伝播の研究 (Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem)</news:title>
   <news:publication_date>2026-05-24T14:30:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693790</loc>
  <lastmod>2026-05-24T13:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌声処理における深層学習の到達点と実務への示唆（Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners）</news:title>
   <news:publication_date>2026-05-24T13:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693788</loc>
  <lastmod>2026-05-24T13:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位置認識型自己注意（Position-aware Self-attention）によるスロットフィリングの改良（Position-aware Self-attention with Relative Positional Encodings for Slot Filling）</news:title>
   <news:publication_date>2026-05-24T13:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693786</loc>
  <lastmod>2026-05-24T13:39:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>移動サービスロボットの自然言語命令理解を深層学習で実装する（A deep learning approach for understanding natural language commands for mobile service robots）</news:title>
   <news:publication_date>2026-05-24T13:39:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693784</loc>
  <lastmod>2026-05-24T13:39:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Glow：可逆1×1畳み込みを用いた生成フロー（Glow: Generative Flow with Invertible 1×1 Convolutions）</news:title>
   <news:publication_date>2026-05-24T13:39:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693782</loc>
  <lastmod>2026-05-24T13:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Pioneer Networks: Progressively Growing Generative Autoencoder（Pioneer Networks: Progressively Growing Generative Autoencoder）</news:title>
   <news:publication_date>2026-05-24T13:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693780</loc>
  <lastmod>2026-05-24T13:38:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形・循環・潜在交絡を扱う制約ベース因果探索（Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders）</news:title>
   <news:publication_date>2026-05-24T13:38:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693778</loc>
  <lastmod>2026-05-24T13:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>血糖値予測のための畳み込み再帰型ニューラルネットワーク（Convolutional Recurrent Neural Networks for Glucose Prediction）</news:title>
   <news:publication_date>2026-05-24T13:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693776</loc>
  <lastmod>2026-05-24T12:47:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実写に近い合成画像で高精度なシーンテキスト検出・認識を実現する手法（Verisimilar Image Synthesis for Accurate Detection and Recognition of Texts in Scenes）</news:title>
   <news:publication_date>2026-05-24T12:47:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693774</loc>
  <lastmod>2026-05-24T12:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OntoSenseNetを用いた語義注釈と感情分析の接点（Towards Enhancing Lexical Resource and Using Sense-annotations of OntoSenseNet for Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-24T12:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693772</loc>
  <lastmod>2026-05-24T12:46:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XNOR Neural Engine: マイクロコントローラ向けBNNアクセラレータ（XNOR Neural Engine: a Hardware Accelerator IP for 21.6 fJ/op Binary Neural Network Inference）</news:title>
   <news:publication_date>2026-05-24T12:46:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693770</loc>
  <lastmod>2026-05-24T12:45:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Restricted Boltzmann Machineのサイズ削減手法（Decreasing the size of the Restricted Boltzmann machine）</news:title>
   <news:publication_date>2026-05-24T12:45:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693768</loc>
  <lastmod>2026-05-24T12:45:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市環境における視覚的ローカリゼーションのための動的物体セグメンテーション (Dynamic Objects Segmentation for Visual Localization in Urban Environments)</news:title>
   <news:publication_date>2026-05-24T12:45:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693766</loc>
  <lastmod>2026-05-24T12:45:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ネットワークでの関数学習はモジュール性を要し多主体ダイナミクスを生む（Learning Functions in Large Networks requires Modularity and produces Multi-Agent Dynamics）</news:title>
   <news:publication_date>2026-05-24T12:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693764</loc>
  <lastmod>2026-05-24T12:45:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヘッダービッディングにおけるSSP入札戦略の最適化（Optimization of a SSP’s Header Bidding Strategy using Thompson Sampling）</news:title>
   <news:publication_date>2026-05-24T12:45:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693762</loc>
  <lastmod>2026-05-24T11:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍探索のための学習型インデックス（Learning to Index for Nearest Neighbor Search）</news:title>
   <news:publication_date>2026-05-24T11:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693760</loc>
  <lastmod>2026-05-24T11:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分グラフパターンと非線形モデルの同時学習（Jointly learning relevant subgraph patterns and nonlinear models of their indicators）</news:title>
   <news:publication_date>2026-05-24T11:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693758</loc>
  <lastmod>2026-05-24T11:53:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多体局在と熱化の境界を機械学習で可視化する（Interpretable Machine Learning Study of Many-Body Localization Transition in Disordered Quantum Ising Spin Chains）</news:title>
   <news:publication_date>2026-05-24T11:53:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693756</loc>
  <lastmod>2026-05-24T11:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適化されたコミュニティの統計的有意性の検定（Computing the statistical significance of optimized communities in networks）</news:title>
   <news:publication_date>2026-05-24T11:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693754</loc>
  <lastmod>2026-05-24T11:52:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドメイン語義記述子なしでのゼロショットドメイン適応（Zero-shot Domain Adaptation without Domain Semantic Descriptors）</news:title>
   <news:publication_date>2026-05-24T11:52:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693752</loc>
  <lastmod>2026-05-24T11:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的アフィン変換を階層的に学習するPARN（Pyramidal Affine Regression Networks for Dense Semantic Correspondence）</news:title>
   <news:publication_date>2026-05-24T11:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693750</loc>
  <lastmod>2026-05-24T11:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周囲と調和する車両画像生成（Vehicle Image Generation Going Well with the Surroundings）</news:title>
   <news:publication_date>2026-05-24T11:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693748</loc>
  <lastmod>2026-05-24T11:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CSI学習に基づく能動的安全符号化方式（CSI Learning Based Active Secure Coding Scheme For Detectable Wiretap Channel）</news:title>
   <news:publication_date>2026-05-24T11:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693746</loc>
  <lastmod>2026-05-24T11:00:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Domain2Vecによるドメイン一般化の設計（Domain2Vec: Deep Domain Generalization）</news:title>
   <news:publication_date>2026-05-24T11:00:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693744</loc>
  <lastmod>2026-05-24T10:59:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール注意によるセマンティックセグメンテーションの改良（Attention to Refine through Multi-Scales for Semantic Segmentation）</news:title>
   <news:publication_date>2026-05-24T10:59:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693742</loc>
  <lastmod>2026-05-24T10:58:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分方策ベース強化学習による3D医療画像のランドマーク検出（Partial Policy-based Reinforcement Learning for Anatomical Landmark Localization in 3D Medical Images）</news:title>
   <news:publication_date>2026-05-24T10:58:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693740</loc>
  <lastmod>2026-05-24T10:58:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線画像分類の脆弱性解析（Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks）</news:title>
   <news:publication_date>2026-05-24T10:58:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693738</loc>
  <lastmod>2026-05-24T10:58:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル非依存の教師付き局所説明（Model Agnostic Supervised Local Explanations）</news:title>
   <news:publication_date>2026-05-24T10:58:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693736</loc>
  <lastmod>2026-05-24T10:58:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アラビア語感情分析のためのCNNとLSTMの統合モデル（A Combined CNN and LSTM Model for Arabic Sentiment Analysis）</news:title>
   <news:publication_date>2026-05-24T10:58:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693734</loc>
  <lastmod>2026-05-24T10:06:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RANSモデルの構造的不確かさを定量化するベイジアン深層ニューラルネットワーク（Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks）</news:title>
   <news:publication_date>2026-05-24T10:06:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693732</loc>
  <lastmod>2026-05-24T10:06:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語の具体性と画像想起性の予測（Predicting Concreteness and Imageability of Words Within and Across Languages via Word Embeddings）</news:title>
   <news:publication_date>2026-05-24T10:06:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693730</loc>
  <lastmod>2026-05-24T10:06:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EL画像による太陽電池モジュールセルの欠陥自動分類（Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images）</news:title>
   <news:publication_date>2026-05-24T10:06:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693728</loc>
  <lastmod>2026-05-24T10:05:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習ベースのアクター・クリティックによる自動深層圧縮（Auto Deep Compression by Reinforcement Learning Based Actor-Critic Structure）</news:title>
   <news:publication_date>2026-05-24T10:05:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693726</loc>
  <lastmod>2026-05-24T10:05:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SuperBITによる高解像度広視野バルーン望遠鏡の概観と成果（Overview, design, and flight results from SuperBIT: a high-resolution, wide-field, visible-to-near-UV balloon-borne astronomical telescope）</news:title>
   <news:publication_date>2026-05-24T10:05:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693724</loc>
  <lastmod>2026-05-24T10:05:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグラフのコミュニティ検出における統計的限界と半正定値緩和（Stochastic Block Model for Hypergraphs: Statistical limits and a semidefinite programming approach）</news:title>
   <news:publication_date>2026-05-24T10:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693722</loc>
  <lastmod>2026-05-24T10:04:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バグ・チケット自動ラベリングにおける階層注意機構を用いたRNN手法（Automated labeling of bugs and tickets using attention-based mechanisms in recurrent neural networks）</news:title>
   <news:publication_date>2026-05-24T10:04:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693720</loc>
  <lastmod>2026-05-24T09:13:19Z</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基づく無線資源配分（Resource Allocation Based on Deep Neural Networks for Cognitive Radio Networks）</news:title>
   <news:publication_date>2026-05-24T09:13:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693718</loc>
  <lastmod>2026-05-24T09:06:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイエネルギー物理学における機械学習の共同ホワイトペーパー（Machine Learning in High Energy Physics Community White Paper）</news:title>
   <news:publication_date>2026-05-24T09:06:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693716</loc>
  <lastmod>2026-05-24T09:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離可能性を最優先にするのは最善ではない（Separability Is Not the Best Goal for Machine Learning）</news:title>
   <news:publication_date>2026-05-24T09:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693714</loc>
  <lastmod>2026-05-24T09:05:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きなマージンを用いた少数ショット学習（Large Margin Few-Shot Learning）</news:title>
   <news:publication_date>2026-05-24T09:05:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693712</loc>
  <lastmod>2026-05-24T09:04:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チケットシステムにおける非対称テキスト類似学習の実務的応用（Replicated Siamese LSTM in Ticketing System for Similarity Learning and Retrieval in Asymmetric Texts）</news:title>
   <news:publication_date>2026-05-24T09:04:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693710</loc>
  <lastmod>2026-05-24T09:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>準パラメトリック画像修復（Semi-parametric Image Inpainting）</news:title>
   <news:publication_date>2026-05-24T09:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693708</loc>
  <lastmod>2026-05-24T09:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列情報を学習するリカレントニューラルネットワーク（Learning The Sequential Temporal Information with Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-24T09:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693706</loc>
  <lastmod>2026-05-24T08:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gaia GraLによる天体重力レンズ探索の盲検的検出（Gaia GraL: Gaia DR2 Gravitational Lens Systems. III. A systematic blind search for new lensed systems）</news:title>
   <news:publication_date>2026-05-24T08:12:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693704</loc>
  <lastmod>2026-05-24T08:11:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的確率的グラフレット埋め込み（Hierarchical Stochastic Graphlet Embedding）</news:title>
   <news:publication_date>2026-05-24T08:11:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693702</loc>
  <lastmod>2026-05-24T08:10:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深く監督された回転等変性ネットワークによる皮膚鏡画像の病変セグメンテーション（Deeply Supervised Rotation Equivariant Network for Lesion Segmentation in Dermoscopy Images）</news:title>
   <news:publication_date>2026-05-24T08:10:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693700</loc>
  <lastmod>2026-05-24T08:10:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>802.11ネットワークにおけるMAC層レート制御の総括（MAC-Layer Rate Control for 802.11 Networks: Lesson Learned and Looking Forward）</news:title>
   <news:publication_date>2026-05-24T08:10:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693698</loc>
  <lastmod>2026-05-24T08:10:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイジアン最適化入門（A Tutorial on Bayesian Optimization）</news:title>
   <news:publication_date>2026-05-24T08:10:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693696</loc>
  <lastmod>2026-05-24T08:10:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動プログラミングによる深層学習の改良（Improving Deep Learning through Automatic Programming）</news:title>
   <news:publication_date>2026-05-24T08:10:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693694</loc>
  <lastmod>2026-05-24T08:09:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時空間インスタンス学習：クラス監視からのアクションチューブ（Spatio-Temporal Instance Learning: Action Tubes from Class Supervision）</news:title>
   <news:publication_date>2026-05-24T08:09:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693692</loc>
  <lastmod>2026-05-24T07:18:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>金融取引をゲームとして捉える―深層強化学習による自動売買の可能性（Financial Trading as a Game: A Deep Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-05-24T07:18:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693690</loc>
  <lastmod>2026-05-24T07:10:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>増分学習における蒸留と疑似リハーサルの偏り除去（Distillation Techniques for Pseudo-rehearsal Based Incremental Learning）</news:title>
   <news:publication_date>2026-05-24T07:10:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693688</loc>
  <lastmod>2026-05-24T07:10:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負のL1ノルム制約を持つベイズ最小二乗法の提案（BALSON: BAYESIAN LEAST SQUARES OPTIMIZATION WITH NONNEGATIVE L1-NORM CONSTRAINT）</news:title>
   <news:publication_date>2026-05-24T07:10:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693686</loc>
  <lastmod>2026-05-24T07:09:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モード視点が拓く統計の新時代（The Modal Age of Statistics）</news:title>
   <news:publication_date>2026-05-24T07:09:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693684</loc>
  <lastmod>2026-05-24T07:08:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フリンジパターン解析における深層学習（Fringe pattern analysis using deep learning）</news:title>
   <news:publication_date>2026-05-24T07:08:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693682</loc>
  <lastmod>2026-05-24T07:08:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非常に深い残差チャネル注意ネットワークによる画像超解像（Image Super-Resolution Using Very Deep Residual Channel Attention Networks）</news:title>
   <news:publication_date>2026-05-24T07:08:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693680</loc>
  <lastmod>2026-05-24T07:08:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>鳥の音を聞き分ける密結合CNNの実践（Densely Connected CNNs for Bird Audio Detection）</news:title>
   <news:publication_date>2026-05-24T07:08:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693678</loc>
  <lastmod>2026-05-24T06:17:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シナプスの位置と接続方向を同時に検出する手法の要諦（Detecting Synapse Location and Connectivity by Signed Proximity Estimation and Pruning with Deep Nets）</news:title>
   <news:publication_date>2026-05-24T06:17:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693676</loc>
  <lastmod>2026-05-24T06:16:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>母音フォルマント類型の深層生成モデル（A Deep Generative Model of Vowel Formant Typology）</news:title>
   <news:publication_date>2026-05-24T06:16:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693674</loc>
  <lastmod>2026-05-24T06:16:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群のデータ駆動アップサンプリング（Data-driven Upsampling of Point Clouds）</news:title>
   <news:publication_date>2026-05-24T06:16:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693672</loc>
  <lastmod>2026-05-24T06:16:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークのみで侵害するAndroidプライバシー（Nothing But Net: Invading Android User Privacy Using Only Network Access Patterns）</news:title>
   <news:publication_date>2026-05-24T06:16:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693670</loc>
  <lastmod>2026-05-24T06:16:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トリム推定量のロバスト学習とマニフォールドサンプリング（Robust Learning of Trimmed Estimators via Manifold Sampling）</news:title>
   <news:publication_date>2026-05-24T06:16:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693668</loc>
  <lastmod>2026-05-24T06:15:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼性の高いmmWave通信のための機械学習：遮へい予測と事前ハンドオフ（Machine Learning for Reliable mmWave Systems: Blockage Prediction and Proactive Handoff）</news:title>
   <news:publication_date>2026-05-24T06:15:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693666</loc>
  <lastmod>2026-05-24T06:15:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた地質パラメータ化とヒストリーマッチの革新（A Deep-Learning-Based Geological Parameterization for History Matching Complex Models）</news:title>
   <news:publication_date>2026-05-24T06:15:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693664</loc>
  <lastmod>2026-05-24T05:24:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相特徴を用いたDNNベース音楽音源分離の改良 (Improving DNN-based Music Source Separation using Phase Features)</news:title>
   <news:publication_date>2026-05-24T05:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693662</loc>
  <lastmod>2026-05-24T05:24:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSource: 深層学習による点状天体検出の実務的意義（DeepSource: Point Source Detection using Deep Learning）</news:title>
   <news:publication_date>2026-05-24T05:24:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693660</loc>
  <lastmod>2026-05-24T05:24:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速なパラメータ調整のための近似Leave-One-Out（Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions）</news:title>
   <news:publication_date>2026-05-24T05:24:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693658</loc>
  <lastmod>2026-05-24T05:23:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cellular Controlled Delay TCP（Cellular Controlled Delay TCP (C2TCP)）</news:title>
   <news:publication_date>2026-05-24T05:23:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693656</loc>
  <lastmod>2026-05-24T05:23:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合量子ラビモデル（The Mixed Quantum Rabi Model）</news:title>
   <news:publication_date>2026-05-24T05:23:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693654</loc>
  <lastmod>2026-05-24T05:23:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペクトル画像分類のための教師付き幾何認識写像アプローチ（A Supervised Geometry-Aware Mapping Approach for Classification of Hyperspectral Images）</news:title>
   <news:publication_date>2026-05-24T05:23:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693652</loc>
  <lastmod>2026-05-24T05:23:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>VFPredによる心室細動検出：信号処理と機械学習の融合（VFPred: A Fusion of Signal Processing and Machine Learning techniques in Detecting Ventricular Fibrillation from ECG Signals）</news:title>
   <news:publication_date>2026-05-24T05:23:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693650</loc>
  <lastmod>2026-05-24T04:32:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>堅牢でスケーラブルな微分可能ニューラルコンピュータ（Robust and Scalable Differentiable Neural Computer for Question Answering）</news:title>
   <news:publication_date>2026-05-24T04:32:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693648</loc>
  <lastmod>2026-05-24T04:32:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>白内障等級付けのためのトーナメント型ランキングCNN（Tournament Based Ranking CNN for the Cataract grading）</news:title>
   <news:publication_date>2026-05-24T04:32:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693646</loc>
  <lastmod>2026-05-24T04:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンショット質感セグメンテーション（One-shot Texture Segmentation）</news:title>
   <news:publication_date>2026-05-24T04:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693644</loc>
  <lastmod>2026-05-24T04:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲームの複雑性が合成エージェントのプレイ行動に与える影響（How game complexity affects the playing behavior of synthetic agents）</news:title>
   <news:publication_date>2026-05-24T04:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693642</loc>
  <lastmod>2026-05-24T04:30:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外観と動き条件によるビデオ予測 (Video Prediction with Appearance and Motion Conditions)</news:title>
   <news:publication_date>2026-05-24T04:30:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693640</loc>
  <lastmod>2026-05-24T04:30:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SQL学習のための推薦システムとヒント生成（Recommender system for learning SQL using hints）</news:title>
   <news:publication_date>2026-05-24T04:30:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693638</loc>
  <lastmod>2026-05-24T04:30:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>仕事が重要なとき：古典的ネットワーク構造をグラフCNNへ変換する手法 (When Work Matters: Transforming Classical Network Structures to Graph CNN)</news:title>
   <news:publication_date>2026-05-24T04:30:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693636</loc>
  <lastmod>2026-05-24T03:38:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>楽観的ミラーディセントによる鞍点問題の前進（OPTIMISTIC MIRROR DESCENT IN SADDLE-POINT PROBLEMS: GOING THE EXTRA (GRADIENT) MILE）</news:title>
   <news:publication_date>2026-05-24T03:38:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693634</loc>
  <lastmod>2026-05-24T03:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>滑空とパーチングのための深層強化学習（Deep-Reinforcement-Learning for Gliding and Perching Bodies）</news:title>
   <news:publication_date>2026-05-24T03:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693632</loc>
  <lastmod>2026-05-24T03:38:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中核保存に基づくネットワーク表現学習（Core2Vec: A core-preserving feature learning framework for networks）</news:title>
   <news:publication_date>2026-05-24T03:38:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693630</loc>
  <lastmod>2026-05-24T03:37:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的入力を持つリザバーコンピューティングの普遍性（Reservoir Computing Universality With Stochastic Inputs）</news:title>
   <news:publication_date>2026-05-24T03:37:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693628</loc>
  <lastmod>2026-05-24T03:37:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Anytime Neural Prediction via Slicing Networks Vertically（Anytime Neural Prediction via Slicing Networks Vertically）</news:title>
   <news:publication_date>2026-05-24T03:37:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693626</loc>
  <lastmod>2026-05-24T03:37:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳幼児の運動データから発達リスクを予測する（Predicting Infant Motor Development Status using Day Long Movement Data from Wearable Sensors）</news:title>
   <news:publication_date>2026-05-24T03:37:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693624</loc>
  <lastmod>2026-05-24T03:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配ハイパーアラインメント（Gradient Hyperalignment for multi-subject fMRI data alignment）</news:title>
   <news:publication_date>2026-05-24T03:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693622</loc>
  <lastmod>2026-05-24T02:45:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的確率的新奇検出と敵対的オートエンコーダ（Generative Probabilistic Novelty Detection with Adversarial Autoencoders）</news:title>
   <news:publication_date>2026-05-24T02:45:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693620</loc>
  <lastmod>2026-05-24T02:45:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Goldilocksゾーン：ニューラルネットワークの損失ランドスケープの理解に向けて（The Goldilocks zone: Towards better understanding of neural network loss landscapes）</news:title>
   <news:publication_date>2026-05-24T02:45:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693618</loc>
  <lastmod>2026-05-24T02:37:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス悪性度予測のための合成サンプリング（Synthetic Sampling for Multi-Class Malignancy Prediction）</news:title>
   <news:publication_date>2026-05-24T02:37:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693616</loc>
  <lastmod>2026-05-24T02:36:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療記録からトピックを抽出する非教師的グラフ分割法（From Text to Topics in Healthcare Records: An Unsupervised Graph Partitioning Methodology）</news:title>
   <news:publication_date>2026-05-24T02:36:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693614</loc>
  <lastmod>2026-05-24T02:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SmartSeedによる効率的なファジング向けシード生成（SmartSeed: Smart Seed Generation for Efficient Fuzzing）</news:title>
   <news:publication_date>2026-05-24T02:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693612</loc>
  <lastmod>2026-05-24T02:35:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程とカーネル法の関係と等価性（Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences）</news:title>
   <news:publication_date>2026-05-24T02:35:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693610</loc>
  <lastmod>2026-05-24T02:35:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多値ルールセットによる患者院内死亡予測の解釈可能モデル（Interpretable Patient Mortality Prediction with Multi-value Rule Sets）</news:title>
   <news:publication_date>2026-05-24T02:35:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693608</loc>
  <lastmod>2026-05-24T01:44:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化と解釈可能な患者心電図プロファイル（Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery）</news:title>
   <news:publication_date>2026-05-24T01:44:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693606</loc>
  <lastmod>2026-05-24T01:44:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Virtual Stereo Odometryを用いた単眼DSOの進化（Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry）</news:title>
   <news:publication_date>2026-05-24T01:44:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693604</loc>
  <lastmod>2026-05-24T01:43:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M-ADDAによる非監督ドメイン適応と深層距離学習の統合（M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning）</news:title>
   <news:publication_date>2026-05-24T01:43:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693602</loc>
  <lastmod>2026-05-24T01:43:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D回転に強い畳み込みネットワークの設計（3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data）</news:title>
   <news:publication_date>2026-05-24T01:43:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693600</loc>
  <lastmod>2026-05-24T01:43:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木幅に基づく計算可能性の新たな限界（New Limits of Treewidth-based Tractability in Optimization）</news:title>
   <news:publication_date>2026-05-24T01:43:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693598</loc>
  <lastmod>2026-05-24T01:43:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全にスケーラブルなガウス過程と部分空間誘導入力（Fully Scalable Gaussian Processes using Subspace Inducing Inputs）</news:title>
   <news:publication_date>2026-05-24T01:43:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693596</loc>
  <lastmod>2026-05-24T01:43:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載画像の境界線で位置推定をする技術の要点解説（VLASE: Vehicle Localization by Aggregating Semantic Edges）</news:title>
   <news:publication_date>2026-05-24T01:43:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693594</loc>
  <lastmod>2026-05-24T00:52:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙再電離末期に見つかった強力な電波明るいクエーサー（A POWERFUL RADIO-LOUD QUASAR AT THE END OF COSMIC REIONIZATION）</news:title>
   <news:publication_date>2026-05-24T00:52:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693592</loc>
  <lastmod>2026-05-24T00:52:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>荷電カレント深部非弾性散乱におけるジェット生成のNNLO QCD補正（NNLO QCD Corrections to Jet Production in Charged Current Deep Inelastic Scattering）</news:title>
   <news:publication_date>2026-05-24T00:52:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693590</loc>
  <lastmod>2026-05-24T00:51:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グループ作業におけるリーダーシップ属性と行動の記述と比較（Denoting and Comparing Leadership Attributes and Behaviors in Group Work）</news:title>
   <news:publication_date>2026-05-24T00:51:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693588</loc>
  <lastmod>2026-05-24T00:50:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的画像セグメンテーションのための全畳み込み二系統融合ネットワーク（A Fully Convolutional Two-Stream Fusion Network for Interactive Image Segmentation）</news:title>
   <news:publication_date>2026-05-24T00:50:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693586</loc>
  <lastmod>2026-05-24T00:50:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動するラベルの下で「意味のある」表現を学ぶ方法（Deep Multiple Instance Feature Learning via Variational Autoencoder）</news:title>
   <news:publication_date>2026-05-24T00:50:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693584</loc>
  <lastmod>2026-05-24T00:49:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>YouTubeを用いた患者教育：ユーザー生成動画から医療知識を抽出する深層学習の試み (YouTube for Patient Education: A Deep Learning Approach for Understanding Medical Knowledge from User-Generated Videos)</news:title>
   <news:publication_date>2026-05-24T00:49:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693582</loc>
  <lastmod>2026-05-24T00:49:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数選択チャネルと少ビットADCにおける共同チャネル推定・復号（Joint Channel-Estimation/Decoding with Frequency-Selective Channels and Few-Bit ADCs）</news:title>
   <news:publication_date>2026-05-24T00:49:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693580</loc>
  <lastmod>2026-05-23T23:57:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルツハイマー病の病状推移を深層学習で予測する（Forecasting Disease Trajectories in Alzheimer’s Disease Using Deep Learning）</news:title>
   <news:publication_date>2026-05-23T23:57:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693578</loc>
  <lastmod>2026-05-23T23:56:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>典型的な携帯電話利用習慣：激しい使用は否定的な幸福感を予測しない（Typical Phone Use Habits: Intense Use Does Not Predict Negative Well-Being）</news:title>
   <news:publication_date>2026-05-23T23:56:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693576</loc>
  <lastmod>2026-05-23T23:56:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な機械学習による非平衡系の相境界推定（Interpretable machine learning for inferring the phase boundaries in a nonequilibrium system）</news:title>
   <news:publication_date>2026-05-23T23:56:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693574</loc>
  <lastmod>2026-05-23T23:56:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セキュリティ関連コミットの自動分類の実践的手法 (A Practical Approach to the Automatic Classification of Security-Relevant Commits)</news:title>
   <news:publication_date>2026-05-23T23:56:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693572</loc>
  <lastmod>2026-05-23T23:56:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠損データを考慮したマルチタスク学習（Multi-Task Learning with Incomplete Data for Healthcare）</news:title>
   <news:publication_date>2026-05-23T23:56:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693570</loc>
  <lastmod>2026-05-23T23:56:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ボリュメトリック医用スキャンにおける器官の深層逐次セグメンテーション（Deep Sequential Segmentation of Organs in Volumetric Medical Scans）</news:title>
   <news:publication_date>2026-05-23T23:56:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693568</loc>
  <lastmod>2026-05-23T23:55:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接線畳み込みによる3D密度予測の革新（Tangent Convolutions for Dense Prediction in 3D）</news:title>
   <news:publication_date>2026-05-23T23:55:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693566</loc>
  <lastmod>2026-05-23T23:03:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>病理画像分類における逆能動学習とAtrous DenseNetの統合（Reversed Active Learning and Atrous DenseNet for Pathological Image Classification）</news:title>
   <news:publication_date>2026-05-23T23:03:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693564</loc>
  <lastmod>2026-05-23T23:03:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球も少し扁平だと空気の流れがこう変わる（Simple geometric approximations for global atmospheres on moderately oblate planets）</news:title>
   <news:publication_date>2026-05-23T23:03:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693562</loc>
  <lastmod>2026-05-23T23:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソースコード上の一行差分を機械学習で予測する競技プラットフォーム（The CodRep Machine Learning on Source Code Competition）</news:title>
   <news:publication_date>2026-05-23T23:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693560</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-23T23:01:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-23T23:01:47Z</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>2026-05-23T23:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693556</loc>
  <lastmod>2026-05-23T23:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトウェア開発の成果物から授業効果を測る（Beyond Surveys: Analyzing Software Development Artifacts to Assess Teaching Efforts）</news:title>
   <news:publication_date>2026-05-23T23:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693554</loc>
  <lastmod>2026-05-23T23:01:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化予測によるラベルランキングのアプローチ（A Structured Prediction Approach for Label Ranking）</news:title>
   <news:publication_date>2026-05-23T23:01:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693552</loc>
  <lastmod>2026-05-23T22:09:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳構造グラフによるアルツハイマー病の早期検出（Graph of brain structures grading for early detection of Alzheimer’s disease）</news:title>
   <news:publication_date>2026-05-23T22:09:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693550</loc>
  <lastmod>2026-05-23T22:01:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパースビューCT再構成のためのDeep Back Projection（DEEP BACK PROJECTION FOR SPARSE-VIEW CT RECONSTRUCTION）</news:title>
   <news:publication_date>2026-05-23T22:01:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693548</loc>
  <lastmod>2026-05-23T22:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列変分特徴抽出による行動予測（A Variational Time Series Feature Extractor for Action Prediction）</news:title>
   <news:publication_date>2026-05-23T22:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693546</loc>
  <lastmod>2026-05-23T21:59:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>系列ラベリングにおけるサム・プロダクト・ネットワーク（Sum-Product Networks for Sequence Labeling）</news:title>
   <news:publication_date>2026-05-23T21:59:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693544</loc>
  <lastmod>2026-05-23T21:59:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メモリ拡張ポリシー最適化によるプログラム合成と意味解析の革新（Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing）</news:title>
   <news:publication_date>2026-05-23T21:59:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693542</loc>
  <lastmod>2026-05-23T21:59:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因果と情報圧縮で欠損に強くなる方法（Cause‑Effect Deep Information Bottleneck For Systematically Missing Covariates）</news:title>
   <news:publication_date>2026-05-23T21:59:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693540</loc>
  <lastmod>2026-05-23T21:58:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JUMPER：読みながら判断するテキスト分類（JUMPER: Learning When to Make Classification Decisions in Reading）</news:title>
   <news:publication_date>2026-05-23T21:58:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693538</loc>
  <lastmod>2026-05-23T21:07:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抽出型文書要約を一体学習で実現する手法（Neural Document Summarization by Jointly Learning to Score and Select Sentences）</news:title>
   <news:publication_date>2026-05-23T21:07:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693536</loc>
  <lastmod>2026-05-23T21:07:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化NFVオーケストレーションと監視の最適化（z-TORCH: An Automated NFV Orchestration and Monitoring Solution）</news:title>
   <news:publication_date>2026-05-23T21:07:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693534</loc>
  <lastmod>2026-05-23T21:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数試行で学習するロボット方策探索の概観 (A survey on policy search algorithms for learning robot controllers in a handful of trials)</news:title>
   <news:publication_date>2026-05-23T21:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693532</loc>
  <lastmod>2026-05-23T21:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次コピーネットワークの要点（Sequential Copying Networks）</news:title>
   <news:publication_date>2026-05-23T21:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693530</loc>
  <lastmod>2026-05-23T21:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>嗜好が変化するエージェントへのインセンティブ設計を扱う組合せバンディット（Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences）</news:title>
   <news:publication_date>2026-05-23T21:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693528</loc>
  <lastmod>2026-05-23T21:06:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシーを保ったオンライン部分集合最適化（Differentially Private Online Submodular Optimization）</news:title>
   <news:publication_date>2026-05-23T21:06:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693526</loc>
  <lastmod>2026-05-23T21:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列畳み込みネットワークによる特徴強化（Parallel Convolutional Networks for Image Recognition via a Discriminator）</news:title>
   <news:publication_date>2026-05-23T21:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693524</loc>
  <lastmod>2026-05-23T20:14:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌声スタイル転送におけるCycleBEGANの提案（Singing Style Transfer Using Cycle-Consistent Boundary Equilibrium Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-23T20:14:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693522</loc>
  <lastmod>2026-05-23T20:14:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力駆動環境における強化学習の分散削減（VARIANCE REDUCTION FOR REINFORCEMENT LEARNING IN INPUT-DRIVEN ENVIRONMENTS）</news:title>
   <news:publication_date>2026-05-23T20:14:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693520</loc>
  <lastmod>2026-05-23T20:12:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大学院教育における問題発見と創造性の向上（Towards Better Problem Finding and Creativity in Graduate School Education）</news:title>
   <news:publication_date>2026-05-23T20:12:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693518</loc>
  <lastmod>2026-05-23T20:12:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼性の異なる複数ソースからの転移学習の信頼性向上（Towards more Reliable Transfer Learning）</news:title>
   <news:publication_date>2026-05-23T20:12:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693516</loc>
  <lastmod>2026-05-23T20:12:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mask TextSpotter：任意形状の文字を同時検出・認識するエンドツーエンド手法（Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes）</news:title>
   <news:publication_date>2026-05-23T20:12:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693514</loc>
  <lastmod>2026-05-23T20:12:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度画像検索のための敵対的学習（Adversarial Learning for Fine-grained Image Search）</news:title>
   <news:publication_date>2026-05-23T20:12:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693512</loc>
  <lastmod>2026-05-23T20:11:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河面の三次元星間塵還元マップ（Three-dimensional interstellar dust reddening maps of the Galactic plane）</news:title>
   <news:publication_date>2026-05-23T20:11:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693510</loc>
  <lastmod>2026-05-23T19:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散自己段階学習の実装と意義（Distributed Self-Paced Learning in Alternating Direction Method of Multipliers）</news:title>
   <news:publication_date>2026-05-23T19:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693508</loc>
  <lastmod>2026-05-23T19:20:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習に基づく球面復号（Deep Learning Based Sphere Decoding）</news:title>
   <news:publication_date>2026-05-23T19:20:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693506</loc>
  <lastmod>2026-05-23T19:19:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>U-SLADSによる動的樹枝構造サンプリング（U-SLADS: Unsupervised Learning Approach for Dynamic Dendrite Sampling）</news:title>
   <news:publication_date>2026-05-23T19:19:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693504</loc>
  <lastmod>2026-05-23T19:19:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤差保証付き最適停止の多項式時間アルゴリズム（Polynomial time algorithm for optimal stopping with fixed accuracy）</news:title>
   <news:publication_date>2026-05-23T19:19:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693502</loc>
  <lastmod>2026-05-23T19:18:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>概念仕様と抽象化に基づく意味表現（A Concept Specification and Abstraction-based Semantic Representation）</news:title>
   <news:publication_date>2026-05-23T19:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693500</loc>
  <lastmod>2026-05-23T19:18:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進行型空間再帰ニューラルネットワークによるイントラ予測（Progressive Spatial Recurrent Neural Network for Intra Prediction）</news:title>
   <news:publication_date>2026-05-23T19:18:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693498</loc>
  <lastmod>2026-05-23T19:18:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界のコードを扱うプログラム合成データセットの意義（NAPS: Natural Program Synthesis Dataset）</news:title>
   <news:publication_date>2026-05-23T19:18:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693496</loc>
  <lastmod>2026-05-23T18:26:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転動作プリミティブの効率的な符号化（Encoding Motion Primitives for Autonomous Vehicles using Virtual Velocity Constraints and Neural Network Scheduling）</news:title>
   <news:publication_date>2026-05-23T18:26:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693494</loc>
  <lastmod>2026-05-23T18:18:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ拡張によるデジタルマンモグラフィーにおける構築異常検出（Data Augmentation for Detection of Architectural Distortion in Digital Mammography using Deep Learning Approach）</news:title>
   <news:publication_date>2026-05-23T18:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693492</loc>
  <lastmod>2026-05-23T18:18:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情誘発下のEEGを用いた個人識別と深層学習の実装知見（Affective EEG-Based Person Identification Using the Deep Learning Approach）</news:title>
   <news:publication_date>2026-05-23T18:18:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693490</loc>
  <lastmod>2026-05-23T18:17:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース深層ニューラルネットワークの厳密解法（Sparse Deep Neural Network Exact Solutions）</news:title>
   <news:publication_date>2026-05-23T18:17:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693488</loc>
  <lastmod>2026-05-23T18:17:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様なデータサイエンス学習への航海（Navigating Diverse Data Science Learning: Critical Reflections Towards Future Practice）</news:title>
   <news:publication_date>2026-05-23T18:17:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693486</loc>
  <lastmod>2026-05-23T18:17:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズを学習することで敵対的攻撃に強くなる（Implicit Generative Modeling of Random Noise during Training improves Adversarial Robustness）</news:title>
   <news:publication_date>2026-05-23T18:17:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693484</loc>
  <lastmod>2026-05-23T18:16:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サービスロボティクスにおける知識表現の総覧（A Survey of Knowledge Representation in Service Robotics）</news:title>
   <news:publication_date>2026-05-23T18:16:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693482</loc>
  <lastmod>2026-05-23T17:25:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サービスとしてのブロックチェーン：分散型かつ安全なコンピューティングパラダイム（Blockchain as a Service: A Decentralized and Secure Computing Paradigm）</news:title>
   <news:publication_date>2026-05-23T17:25:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693480</loc>
  <lastmod>2026-05-23T17:25:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的Levenberg–Marquardt法によるノイズ耐性最適化（A stochastic Levenberg–Marquardt method using random models with complexity results）</news:title>
   <news:publication_date>2026-05-23T17:25:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693478</loc>
  <lastmod>2026-05-23T17:25:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Protein-Protein Interaction抽出におけるShortest Dependency Pathを用いた双方向LSTMの効果（Feature Assisted bi-directional LSTM Model for Protein-Protein Interaction Identification from Biomedical Texts）</news:title>
   <news:publication_date>2026-05-23T17:25:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693476</loc>
  <lastmod>2026-05-23T17:24:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳房DCE-MRIの自動深層学習ベースの正規化（Automatic deep learning-based normalization of breast dynamic contrast-enhanced magnetic resonance images）</news:title>
   <news:publication_date>2026-05-23T17:24:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693474</loc>
  <lastmod>2026-05-23T17:24:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰的証拠連鎖によるスケーラブルなレコメンダー（Scalable Recommender Systems through Recursive Evidence Chains）</news:title>
   <news:publication_date>2026-05-23T17:24:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693472</loc>
  <lastmod>2026-05-23T17:24:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gridbot：脳の航法系を模倣するスパイキングニューラルネットワークで制御される自律ロボット (Gridbot: An autonomous robot controlled by a Spiking Neural Network mimicking the brain’s navigational system)</news:title>
   <news:publication_date>2026-05-23T17:24:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693470</loc>
  <lastmod>2026-05-23T17:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン多対象追跡のための時空間KSVD辞書学習（Spatiotemporal KSVD Dictionary Learning for Online Multi-target Tracking）</news:title>
   <news:publication_date>2026-05-23T17:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693468</loc>
  <lastmod>2026-05-23T16:33:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的経路積分オートエンコーダによる表現学習と計画（Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems）</news:title>
   <news:publication_date>2026-05-23T16:33:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693466</loc>
  <lastmod>2026-05-23T16:32:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Siamese-LSTMによる3Dヒューマンアクション認識（3D Human Action Recognition with Siamese-LSTM Based Deep Metric Learning）</news:title>
   <news:publication_date>2026-05-23T16:32:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693464</loc>
  <lastmod>2026-05-23T16:32:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LHCにおける作用素の特定を学ぶ：t¯tb¯b最終状態の解析（Learning to pinpoint effective operators at the LHC: a study of the t¯tb¯b signature）</news:title>
   <news:publication_date>2026-05-23T16:32:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693462</loc>
  <lastmod>2026-05-23T16:32:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的遅延フィードバックを伴う線形バンディット（Linear Bandits with Stochastic Delayed Feedback）</news:title>
   <news:publication_date>2026-05-23T16:32:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693460</loc>
  <lastmod>2026-05-23T16:31:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による弱レンズシアー測定の革新（Weak-lensing shear measurement with machine learning）</news:title>
   <news:publication_date>2026-05-23T16:31:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693458</loc>
  <lastmod>2026-05-23T16:31:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在的な3次元キーポイントの発見とエンドツーエンド幾何推論（Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning）</news:title>
   <news:publication_date>2026-05-23T16:31:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693456</loc>
  <lastmod>2026-05-23T16:31:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子構造固有関数を用いたスケーラブルなガウス過程（Scalable Gaussian Processes with Grid-Structured Eigenfunctions）</news:title>
   <news:publication_date>2026-05-23T16:31:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693454</loc>
  <lastmod>2026-05-23T15:40:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる背景差分アルゴリズムを統合するCNNによる前景検出の改良（Combining Background Subtraction Algorithms with Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-23T15:40:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693452</loc>
  <lastmod>2026-05-23T15:39:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目標志向トラジェクトリによる効率的探索（Goal-oriented Trajectories for Efficient Exploration）</news:title>
   <news:publication_date>2026-05-23T15:39:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693450</loc>
  <lastmod>2026-05-23T15:39:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経路積分の曲率が引き起こす影響を解く—平均場Matsubara力学による回転振動スペクトル解析（Mean-field Matsubara dynamics: analysis of path-integral curvature effects in rovibrational spectra）</news:title>
   <news:publication_date>2026-05-23T15:39:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693448</loc>
  <lastmod>2026-05-23T15:38:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーボン富化岩石型系外惑星の鉱物学と居住可能性の実験的解明（Mineralogy, structure and habitability of carbon-enriched rocky exoplanets: A laboratory approach）</news:title>
   <news:publication_date>2026-05-23T15:38:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693446</loc>
  <lastmod>2026-05-23T15:38:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河平面を貫く球状星団の軌道と崩壊の兆候（THE ORBIT OF THE NEW MILKY WAY GLOBULAR CLUSTER FSR1716 = VVV-GC05）</news:title>
   <news:publication_date>2026-05-23T15:38:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693444</loc>
  <lastmod>2026-05-23T15:38:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銅と二酸化ケイ素のための高精度機械学習力場の構築（Construction of accurate machine learning force fields for copper and silicon dioxide）</news:title>
   <news:publication_date>2026-05-23T15:38:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693442</loc>
  <lastmod>2026-05-23T15:38:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットによる同時等化と復号の提案（Joint Neural Network Equalizer and Decoder）</news:title>
   <news:publication_date>2026-05-23T15:38:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693440</loc>
  <lastmod>2026-05-23T14:46:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TensorFlowにおける大規模モデル支援のグラフ書き換え（TFLMS: Large Model Support in TensorFlow by Graph Rewriting）</news:title>
   <news:publication_date>2026-05-23T14:46:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693438</loc>
  <lastmod>2026-05-23T14:46:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一貫した生成クエリネットワーク（Consistent Generative Query Networks）</news:title>
   <news:publication_date>2026-05-23T14:46:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693436</loc>
  <lastmod>2026-05-23T14:46:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変分オートエンコーダで学ぶ地図表現とSLAM（Learning Latent Maps for SLAM with Variational Autoencoders）</news:title>
   <news:publication_date>2026-05-23T14:46:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693434</loc>
  <lastmod>2026-05-23T14:45:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師なし欠陥分割を改善する構造類似度の適用（Improving Unsupervised Defect Segmentation by Applying Structural Similarity To Autoencoders）</news:title>
   <news:publication_date>2026-05-23T14:45:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693432</loc>
  <lastmod>2026-05-23T14:45:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高性能TensorFlowベースのOCRパッケージ Calamari（Calamari − A High-Performance Tensorflow-based Deep Learning Package for Optical Character Recognition）</news:title>
   <news:publication_date>2026-05-23T14:45:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693430</loc>
  <lastmod>2026-05-23T14:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非定常ベクトル自己回帰時系列からの動的ネットワーク同定（DYNAMIC NETWORK IDENTIFICATION FROM NON-STATIONARY VECTOR AUTOREGRESSIVE TIME SERIES）</news:title>
   <news:publication_date>2026-05-23T14:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693428</loc>
  <lastmod>2026-05-23T14:44:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンデマンド型複数空中基地局の配置法（On-Demand Deployment of Multiple Aerial Base Stations for Traffic Offloading and Network Recovery）</news:title>
   <news:publication_date>2026-05-23T14:44:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693426</loc>
  <lastmod>2026-05-23T13:53:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点情報を見直した効率的群衆カウント（Revisiting Perspective Information for Efficient Crowd Counting）</news:title>
   <news:publication_date>2026-05-23T13:53:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693424</loc>
  <lastmod>2026-05-23T13:53:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>商品陳列物の弱教師ありインスタンスセグメンテーション（Acquire, Augment, Segment &amp;amp; Enjoy: Weakly Supervised Instance Segmentation of Supermarket Products）</news:title>
   <news:publication_date>2026-05-23T13:53:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693422</loc>
  <lastmod>2026-05-23T13:52:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疎表現と非負値行列因子分解による画像ノイズ除去（Sparse Representation and Non-Negative Matrix Factorization for Image Denoising）</news:title>
   <news:publication_date>2026-05-23T13:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693420</loc>
  <lastmod>2026-05-23T13:52:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肉牛の個体分割を簡潔にする手法（Beef Cattle Instance Segmentation Using Fully Convolutional Neural Network）</news:title>
   <news:publication_date>2026-05-23T13:52:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693418</loc>
  <lastmod>2026-05-23T13:51:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Variational Bayesian dropoutの落とし穴と修正（Variational Bayesian dropout: pitfalls and ﬁxes）</news:title>
   <news:publication_date>2026-05-23T13:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693416</loc>
  <lastmod>2026-05-23T13:51:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>何が記憶に残るのか — プログラミングMOOCsにおける定着率の実証的知見 (What Stays in Mind? - Retention Rates in Programming MOOCs)</news:title>
   <news:publication_date>2026-05-23T13:51:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693414</loc>
  <lastmod>2026-05-23T13:51:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Arcades: 音声制御スマートホームのための適応型深層意思決定モデル（Arcades: A deep model for adaptive decision making in voice controlled smart-home）</news:title>
   <news:publication_date>2026-05-23T13:51:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693412</loc>
  <lastmod>2026-05-23T13:00:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド技術と拡張現実の展望（The Cloud Technologies and Augmented Reality: the Prospects of Use）</news:title>
   <news:publication_date>2026-05-23T13:00:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693410</loc>
  <lastmod>2026-05-23T12:59:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>開いた量子系における厳密マスター方程式と一般的な非マルコフ動力学（Exact Master Equation and General Non-Markovian Dynamics in Open Quantum Systems）</news:title>
   <news:publication_date>2026-05-23T12:59:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693408</loc>
  <lastmod>2026-05-23T12:59:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンロゴ検出チャレンジ（Open Logo Detection Challenge）</news:title>
   <news:publication_date>2026-05-23T12:59:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693406</loc>
  <lastmod>2026-05-23T12:58:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層スパース信号表現（Deeply-Sparse Signal rePresentations, DS2P）</news:title>
   <news:publication_date>2026-05-23T12:58:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693404</loc>
  <lastmod>2026-05-23T12:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アーキテクチャ性能評価のためのBoo(n)指標（A Boo(n) for Evaluating Architecture Performance）</news:title>
   <news:publication_date>2026-05-23T12:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693402</loc>
  <lastmod>2026-05-23T12:58:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジグソーパズル再構成における局所特徴共起の活用（JIGSAW PUZZLE SOLVING USING LOCAL FEATURE CO-OCCURRENCES IN DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-05-23T12:58:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693400</loc>
  <lastmod>2026-05-23T12:57:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Doomを題材にした補助目的を用いる深層強化学習（Deep Reinforcement Learning for Doom using Unsupervised Auxiliary Tasks）</news:title>
   <news:publication_date>2026-05-23T12:57:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693398</loc>
  <lastmod>2026-05-23T12:06:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小カメラ視点からのボリュメトリックパフォーマンスキャプチャ（Volumetric performance capture from minimal camera viewpoints）</news:title>
   <news:publication_date>2026-05-23T12:06:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693396</loc>
  <lastmod>2026-05-23T12:05:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ロボット運動の最適化と学習制御（Optimizing the Execution of Dynamic Robot Movements with Learning Control）</news:title>
   <news:publication_date>2026-05-23T12:05:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693394</loc>
  <lastmod>2026-05-23T12:04:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>区間尤度に基づくVAE学習──Kullback-Leibler及びR´enyi積分境界（Learning in Variational Autoencoders with Kullback-Leibler and Renyi Integral Bounds）</news:title>
   <news:publication_date>2026-05-23T12:04:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693392</loc>
  <lastmod>2026-05-23T12:04:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケール適応型アンカーによる単発テキスト検出器（A Single Shot Text Detector with Scale-adaptive Anchors）</news:title>
   <news:publication_date>2026-05-23T12:04:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693390</loc>
  <lastmod>2026-05-23T12:04:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層行列に基づく多重解像度ニューラルネットワーク（A multiscale neural network based on hierarchical matrices）</news:title>
   <news:publication_date>2026-05-23T12:04:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693388</loc>
  <lastmod>2026-05-23T12:03:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層Bi-GRU-CRFによる中国語語彙解析（Chinese Lexical Analysis with Deep Bi-GRU-CRF Network）</news:title>
   <news:publication_date>2026-05-23T12:03:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693386</loc>
  <lastmod>2026-05-23T12:03:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一鉄テトラフェニルポルフィリンダイアド上の電荷移動ダイナミクスの探索 (Probing Charge Transfer Dynamics in a Single Iron Tetraphenylporphyrin Dyad Adsorbed on an Insulating Surface)</news:title>
   <news:publication_date>2026-05-23T12:03:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693384</loc>
  <lastmod>2026-05-23T11:12:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>さまざまな単語埋め込みが感情分類に与える影響（A Review of Different Word Embeddings for Sentiment Classification using Deep Learning）</news:title>
   <news:publication_date>2026-05-23T11:12:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693382</loc>
  <lastmod>2026-05-23T11:11:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ難読化による学習データのプライバシー保護（Privacy-preserving Machine Learning through Data Obfuscation）</news:title>
   <news:publication_date>2026-05-23T11:11:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693380</loc>
  <lastmod>2026-05-23T11:11:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Ethereumスマートコントラクトの脆弱性検出を画像化で行う手法（Hunting the Ethereum Smart Contract: Color-inspired Inspection of Potential Attacks）</news:title>
   <news:publication_date>2026-05-23T11:11:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693378</loc>
  <lastmod>2026-05-23T11:10:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディコンボリューション型バックプロジェクトフィルタCT再構成法（Deconvolution-Based Backproject-Filter (BPF) Computed Tomography Image Reconstruction Method Using Deep Learning Technique）</news:title>
   <news:publication_date>2026-05-23T11:10:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693376</loc>
  <lastmod>2026-05-23T11:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディアから抽出する実行可能な知見――家庭内暴力（Domestic Violence）議論の活用（Extracting Actionable Knowledge from Domestic Violence Discourses on Social Media）</news:title>
   <news:publication_date>2026-05-23T11:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693374</loc>
  <lastmod>2026-05-23T11:10:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジスティック回帰とニューラルネットワークを再解釈する：Dempster–Shafer理論の視点（Logistic Regression, Neural Networks and Dempster-Shafer Theory: a New Perspective）</news:title>
   <news:publication_date>2026-05-23T11:10:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693372</loc>
  <lastmod>2026-05-23T11:10:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なオンライン量子状態推定とMEG法（Efficient online quantum state estimation using a matrix-exponentiated gradient method）</news:title>
   <news:publication_date>2026-05-23T11:10:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693370</loc>
  <lastmod>2026-05-23T10:19:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意思決定ごとの多段階時系列差分学習と制御変量（Per-decision Multi-step Temporal Difference Learning with Control Variates）</news:title>
   <news:publication_date>2026-05-23T10:19:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693368</loc>
  <lastmod>2026-05-23T10:19:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スポンサードサーチにおける収益管理の学習理論とアルゴリズム（Learning Theory and Algorithms for Revenue Management in Sponsored Search）</news:title>
   <news:publication_date>2026-05-23T10:19:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693366</loc>
  <lastmod>2026-05-23T10:18:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PortraitGANによる表情とモダリティの同時操作（PortraitGAN for Simultaneous Emotion and Modality Manipulation）</news:title>
   <news:publication_date>2026-05-23T10:18:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693364</loc>
  <lastmod>2026-05-23T10:18:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティクス保存型敵対学習による深層クロスモダリティ適応（Deep Cross-modality Adaptation via Semantics Preserving Adversarial Learning for Sketch-based 3D Shape Retrieval）</news:title>
   <news:publication_date>2026-05-23T10:18:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693362</loc>
  <lastmod>2026-05-23T10:18:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半勾配に基づく積み上げ分布による離散サンプリング（Discrete Sampling using Semigradient-based Product Mixtures）</news:title>
   <news:publication_date>2026-05-23T10:18:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693360</loc>
  <lastmod>2026-05-23T10:18:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートエンコーダーを用いた行列補完のデータ依存正則化（Regularizing Autoencoder-Based Matrix Completion Models via Manifold Learning）</news:title>
   <news:publication_date>2026-05-23T10:18:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693358</loc>
  <lastmod>2026-05-23T10:17:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TextTopicNetによる自己教師あり視覚特徴学習（TextTopicNet - Self-Supervised Learning of Visual Features Through Embedding Images on Semantic Text Spaces）</news:title>
   <news:publication_date>2026-05-23T10:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693356</loc>
  <lastmod>2026-05-23T09:26:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個別化表現学習による医用画像の逆問題への応用（Learning Personalized Representation for Inverse Problems in Medical Imaging Using Deep Neural Network）</news:title>
   <news:publication_date>2026-05-23T09:26:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693354</loc>
  <lastmod>2026-05-23T09:20:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文法駆動のツリー・トゥ・ツリーによるプログラム言語翻訳（Program Language Translation Using a Grammar-Driven Tree-to-Tree Model）</news:title>
   <news:publication_date>2026-05-23T09:20:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693352</loc>
  <lastmod>2026-05-23T09:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BOHBによる大規模ハイパーパラメータ最適化の実用化（BOHB: Robust and Efficient Hyperparameter Optimization at Scale）</news:title>
   <news:publication_date>2026-05-23T09:19:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693350</loc>
  <lastmod>2026-05-23T09:19:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>X線スペクトルから導く赤方偏移（XZ: Deriving redshifts from X-ray spectra of obscured AGN）</news:title>
   <news:publication_date>2026-05-23T09:19:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693348</loc>
  <lastmod>2026-05-23T09:17:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Seq2RDFによる自然文からのトリプル抽出（Seq2RDF: An end-to-end application for deriving Triples from Natural Language Text）</news:title>
   <news:publication_date>2026-05-23T09:17:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693346</loc>
  <lastmod>2026-05-23T09:17:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粒子ベースの変分推論の理解と加速（Understanding and Accelerating Particle-Based Variational Inference）</news:title>
   <news:publication_date>2026-05-23T09:17:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693344</loc>
  <lastmod>2026-05-23T09:17:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療セカンドオピニオンのための不確実性直接予測（Direct Uncertainty Prediction for Medical Second Opinions）</news:title>
   <news:publication_date>2026-05-23T09:17:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693342</loc>
  <lastmod>2026-05-23T08:25:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模統計モデリングとセンサー／アクチュエータ選択のための近接アルゴリズム（Proximal algorithms for large-scale statistical modeling and sensor/actuator selection）</news:title>
   <news:publication_date>2026-05-23T08:25:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693340</loc>
  <lastmod>2026-05-23T08:24:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推薦システムと自己動機付けユーザー（Recommendation Systems and Self Motivated Users）</news:title>
   <news:publication_date>2026-05-23T08:24:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693338</loc>
  <lastmod>2026-05-23T08:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AGNと星形成の関係をXMM-Newtonで解く（Disentangling the AGN and star formation connection using XMM-Newton）</news:title>
   <news:publication_date>2026-05-23T08:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693336</loc>
  <lastmod>2026-05-23T08:23:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Model Featuresによる強化学習の転移（Transfer with Model Features）</news:title>
   <news:publication_date>2026-05-23T08:23:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693334</loc>
  <lastmod>2026-05-23T08:23:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的な画像劣化と表面変化に対するニューラルネットワークの堅牢性評価（Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations）</news:title>
   <news:publication_date>2026-05-23T08:23:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693332</loc>
  <lastmod>2026-05-23T08:22:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LaneNet: 実時間車載レーン検出ネットワーク（LaneNet: Real-Time Lane Detection Networks for Autonomous Driving）</news:title>
   <news:publication_date>2026-05-23T08:22:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693330</loc>
  <lastmod>2026-05-23T08:22:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>レクスとヤックで学ぶコンパイラ教育の共同利用法（Methodic of joint using the tools of automation of lexical and parsing analysis）</news:title>
   <news:publication_date>2026-05-23T08:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693328</loc>
  <lastmod>2026-05-23T07:31:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動詞の意味タイプ自動識別に向けた取り組み（Towards Automation of Sense-type Identification of Verbs in OntoSenseNet(Telugu)）</news:title>
   <news:publication_date>2026-05-23T07:31:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693326</loc>
  <lastmod>2026-05-23T07:23:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPIDERによる非凸最適化の効率化（Spider: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator）</news:title>
   <news:publication_date>2026-05-23T07:23:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693324</loc>
  <lastmod>2026-05-23T07:22:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報学士に求められるプログラミング能力の構築（Bachelor of Informatics Competence in Programming）</news:title>
   <news:publication_date>2026-05-23T07:22:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693322</loc>
  <lastmod>2026-05-23T07:22:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MandarinとCantoneseのF0輪郭予測手法の比較とAdditive-BLSTMの提案（Generating Mandarin and Cantonese F0 Contours with Decision Trees and BLSTMs）</news:title>
   <news:publication_date>2026-05-23T07:22:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693320</loc>
  <lastmod>2026-05-23T07:21:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプル効率の高い強化学習とSTEVE（Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion）</news:title>
   <news:publication_date>2026-05-23T07:21:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693318</loc>
  <lastmod>2026-05-23T07:21:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テルグ語の語単位感情注釈によるベンチマークコーパスの構築（BCSAT: A Benchmark Corpus for Sentiment Analysis in Telugu Using Word-level Annotations）</news:title>
   <news:publication_date>2026-05-23T07:21:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693316</loc>
  <lastmod>2026-05-23T07:21:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランクド・リワードによる自己対戦強化学習の単一プレイヤー最適化への応用（Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial Optimization）</news:title>
   <news:publication_date>2026-05-23T07:21:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693314</loc>
  <lastmod>2026-05-23T06:29:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MIXGANによるドメイン概念の混合生成（MIXGAN: Learning Concepts from Different Domains for Mixture Generation）</news:title>
   <news:publication_date>2026-05-23T06:29:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693312</loc>
  <lastmod>2026-05-23T06:29:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散電力網の状態推定を学習で初期化する新手法（Data-Driven Learning-Based Optimization for Distribution System State Estimation）</news:title>
   <news:publication_date>2026-05-23T06:29:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693310</loc>
  <lastmod>2026-05-23T06:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語から空間関係を理解する（Encoding Spatial Relations from Natural Language）</news:title>
   <news:publication_date>2026-05-23T06:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693308</loc>
  <lastmod>2026-05-23T06:28:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブサンプリングによるプライバシー増幅（Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences）</news:title>
   <news:publication_date>2026-05-23T06:28:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693306</loc>
  <lastmod>2026-05-23T06:28:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間自己回帰による新規性検出（Latent Space Autoregression for Novelty Detection）</news:title>
   <news:publication_date>2026-05-23T06:28:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693304</loc>
  <lastmod>2026-05-23T06:27:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三次元受動スカラー混合における急峻な「崖」と飽和するスケーリング指数（Steep cliffs and saturated exponents in three dimensional scalar turbulence）</news:title>
   <news:publication_date>2026-05-23T06:27:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693302</loc>
  <lastmod>2026-05-23T06:27:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙地図による視覚的3D自己位置推定（Learning models for visual 3D localization with implicit mapping）</news:title>
   <news:publication_date>2026-05-23T06:27:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693300</loc>
  <lastmod>2026-05-23T05:35:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングによる多色ローカリゼーション顕微鏡の可能性（Multicolor localization microscopy by deep learning）</news:title>
   <news:publication_date>2026-05-23T05:35:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693298</loc>
  <lastmod>2026-05-23T05:34:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cimple: 命令並列性とメモリ並列性を引き出すDSL（Cimple: Instruction and Memory Level Parallelism）</news:title>
   <news:publication_date>2026-05-23T05:34:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693296</loc>
  <lastmod>2026-05-23T05:34:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>新生児の痛み表情認識における転移学習の実用性（Neonatal Pain Expression Recognition Using Transfer Learning）</news:title>
   <news:publication_date>2026-05-23T05:34:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693294</loc>
  <lastmod>2026-05-23T05:34:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Conformal PredictorsとEnsemble学習で信頼性を付与したMCIからアルツハイマーへの予後予測（Ensemble learning with Conformal Predictors: Targeting credible predictions of conversion from Mild Cognitive Impairment to Alzheimer’s Disease）</news:title>
   <news:publication_date>2026-05-23T05:34:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693292</loc>
  <lastmod>2026-05-23T05:33:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Processes（Neural Processes）</news:title>
   <news:publication_date>2026-05-23T05:33:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693290</loc>
  <lastmod>2026-05-23T05:33:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LHeCとFCC-heにおけるBSM物理学（BSM physics at the LHeC and the FCC-he）</news:title>
   <news:publication_date>2026-05-23T05:33:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693288</loc>
  <lastmod>2026-05-23T05:33:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サッカー試合結果予測の統計モデル比較と検証手法（Modeling outcomes of soccer matches）</news:title>
   <news:publication_date>2026-05-23T05:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693286</loc>
  <lastmod>2026-05-23T04:41:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QMCによる変分推論の高速化（Quasi-Monte Carlo Variational Inference）</news:title>
   <news:publication_date>2026-05-23T04:41:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693284</loc>
  <lastmod>2026-05-23T04:41:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Conditional Neural Processes（Conditional Neural Processes）</news:title>
   <news:publication_date>2026-05-23T04:41:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693282</loc>
  <lastmod>2026-05-23T04:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察者の脳波からエラー情報を読み解く際のロボット設計の影響（The role of robot design in decoding error-related information from EEG signals of a human observer）</news:title>
   <news:publication_date>2026-05-23T04:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693280</loc>
  <lastmod>2026-05-23T04:40:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BayesGradによるグラフCNN予測の説明（BayesGrad: Explaining Predictions of Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-05-23T04:40:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693278</loc>
  <lastmod>2026-05-23T04:40:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SEN1-2データセットによるSAR-光学データ融合の深層学習（THE SEN1-2 DATASET FOR DEEP LEARNING IN SAR-OPTICAL DATA FUSION）</news:title>
   <news:publication_date>2026-05-23T04:40:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693276</loc>
  <lastmod>2026-05-23T04:39:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二次（Quadratic）ニューラルネットワークとファジィ論理の接点（Quadratic Neural Networks and Fuzzy Logic）</news:title>
   <news:publication_date>2026-05-23T04:39:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693274</loc>
  <lastmod>2026-05-23T04:39:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OFDMベースの多段水中音響センサネットワークにおける秘匿率最大化（Maximizing Secrecy Rate of an OFDM-based Multi-hop Underwater Acoustic Sensor Network）</news:title>
   <news:publication_date>2026-05-23T04:39:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693272</loc>
  <lastmod>2026-05-23T03:48:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広帯域時刻領域デジタル逆変換のサブバンド処理と深層学習（Wideband Time-Domain Digital Backpropagation via Subband Processing and Deep Learning）</news:title>
   <news:publication_date>2026-05-23T03:48:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693270</loc>
  <lastmod>2026-05-23T03:48:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床時系列データ解析における転移学習の応用（Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-05-23T03:48:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693268</loc>
  <lastmod>2026-05-23T03:48:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TextSnakeによる任意形状テキスト検出の柔軟な表現（TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes）</news:title>
   <news:publication_date>2026-05-23T03:48:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693266</loc>
  <lastmod>2026-05-23T03:46:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療記録の合成データ生成法の実務的意義（Generating Synthetic but Plausible Healthcare Record Datasets）</news:title>
   <news:publication_date>2026-05-23T03:46:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693264</loc>
  <lastmod>2026-05-23T03:46:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復デコンボリューションによる量子制御パルスの較正（Learning to Calibrate Quantum Control Pulses by Iterative Deconvolution）</news:title>
   <news:publication_date>2026-05-23T03:46:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693262</loc>
  <lastmod>2026-05-23T03:46:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習された分離されたゴール空間の好奇心駆動探索（Curiosity Driven Exploration of Learned Disentangled Goal Spaces）</news:title>
   <news:publication_date>2026-05-23T03:46:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693260</loc>
  <lastmod>2026-05-23T03:46:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による部分形状のファジー集合表現（Learning Fuzzy Set Representations of Partial Shapes on Dual Embedding Spaces）</news:title>
   <news:publication_date>2026-05-23T03:46:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693258</loc>
  <lastmod>2026-05-23T02:54:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な画像スタイル転送のための非相関特徴符号化 (Uncorrelated Feature Encoding for Faster Image Style Transfer)</news:title>
   <news:publication_date>2026-05-23T02:54:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693256</loc>
  <lastmod>2026-05-23T02:45:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層オートエンコーダによる人体姿勢推定と体形アップスケーリング（Deep Autoencoder for Combined Human Pose Estimation and Body Model Upscaling）</news:title>
   <news:publication_date>2026-05-23T02:45:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693254</loc>
  <lastmod>2026-05-23T02:44:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分解可能バンディット（Factored Bandits）</news:title>
   <news:publication_date>2026-05-23T02:44:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693252</loc>
  <lastmod>2026-05-23T02:44:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験的固定点分岐解析の実務的示唆（Empirical Fixed Point Bifurcation Analysis）</news:title>
   <news:publication_date>2026-05-23T02:44:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693250</loc>
  <lastmod>2026-05-23T02:43:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型ニューラルネットワークを用いた教師あり強化学習による動的治療推薦（Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation）</news:title>
   <news:publication_date>2026-05-23T02:43:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693248</loc>
  <lastmod>2026-05-23T02:43:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習における多様性（Diversity in Machine Learning）</news:title>
   <news:publication_date>2026-05-23T02:43:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693246</loc>
  <lastmod>2026-05-23T02:43:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主成分分析を用いたテキスト分類の比較研究（A Comparative Study on using Principle Component Analysis with Different Text Classifiers）</news:title>
   <news:publication_date>2026-05-23T02:43:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693244</loc>
  <lastmod>2026-05-23T01:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細粒度検索のための深層サリエンシーハッシング（Deep Saliency Hashing for Fine-grained Retrieval）</news:title>
   <news:publication_date>2026-05-23T01:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693242</loc>
  <lastmod>2026-05-23T01:51:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情の二面性――極性（Polarity）と強度（Intensity）によるセンチメント解析の再定義 (Polarity and Intensity: the Two Aspects of Sentiment Analysis)</news:title>
   <news:publication_date>2026-05-23T01:51:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693240</loc>
  <lastmod>2026-05-23T01:51:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プラグ&amp;amp;プレイ型深層局所線形埋め込みによる映像フレーム補間（Video Frame Interpolation by Plug-and-Play Deep Locally Linear Embedding）</news:title>
   <news:publication_date>2026-05-23T01:51:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693238</loc>
  <lastmod>2026-05-23T01:50:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>前景注意に基づく識別的特徴学習による人物再識別（Discriminative Feature Learning with Foreground Attention for Person Re-identification）</news:title>
   <news:publication_date>2026-05-23T01:50:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693236</loc>
  <lastmod>2026-05-23T01:50:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成画像から実画像へ転移学習するVAEによる高精度位置検出（TRANSFER LEARNING FROM SYNTHETIC TO REAL IMAGES USING VARIATIONAL AUTOENCODERS FOR PRECISE POSITION DETECTION）</news:title>
   <news:publication_date>2026-05-23T01:50:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693234</loc>
  <lastmod>2026-05-23T01:50:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>広告画像の意味を読むための共注意による記号と物体の整合（Understanding Visual Ads by Aligning Symbols and Objects using Co-Attention）</news:title>
   <news:publication_date>2026-05-23T01:50:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693232</loc>
  <lastmod>2026-05-23T01:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二層ルテネートにおけるモット転移近傍の電子質量増強と磁気相分離（Electron mass enhancement and magnetic phase separation near the Mott transition in double layer ruthenates）</news:title>
   <news:publication_date>2026-05-23T01:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693230</loc>
  <lastmod>2026-05-23T00:58:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未教師ありのドメイン適応で人物識別を横断的に改善する手法（Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification）</news:title>
   <news:publication_date>2026-05-23T00:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693228</loc>
  <lastmod>2026-05-23T00:58:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルにスパースなずれを加えて圧縮センシングを拡張する（Modeling Sparse Deviations for Compressed Sensing using Generative Models）</news:title>
   <news:publication_date>2026-05-23T00:58:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693226</loc>
  <lastmod>2026-05-23T00:58:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QoSに基づくWebサービスの探索と選択（Qos-Based Web Service Discovery And Selection Using Machine Learning）</news:title>
   <news:publication_date>2026-05-23T00:58:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693224</loc>
  <lastmod>2026-05-23T00:57:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>入力ごとにブロックを落とす学習（SGAD: Soft-Guided Adaptively-Dropped Neural Network）</news:title>
   <news:publication_date>2026-05-23T00:57:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693222</loc>
  <lastmod>2026-05-23T00:57:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小スケール歩行者検出の新手法（Small-scale Pedestrian Detection Based on Somatic Topology Localization and Temporal Feature Aggregation）</news:title>
   <news:publication_date>2026-05-23T00:57:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693220</loc>
  <lastmod>2026-05-23T00:56:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Batch Normalization の再構成による CNN 学習高速化（Restructuring Batch Normalization to Accelerate CNN Training）</news:title>
   <news:publication_date>2026-05-23T00:56:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693218</loc>
  <lastmod>2026-05-23T00:56:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データが乏しい実験でも機械学習は使える――合成データで覆い隠れた秩序を掘り起こす（Machine Learning in a data-limited regime: Augmenting experiments with synthetic data uncovers order in crumpled sheets）</news:title>
   <news:publication_date>2026-05-23T00:56:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693216</loc>
  <lastmod>2026-05-23T00:05:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きオートマトンと再帰型ニューラルネットワークの結びつき（Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning）</news:title>
   <news:publication_date>2026-05-23T00:05:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693214</loc>
  <lastmod>2026-05-22T23:56:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>到達領域を段階的に拡大するカリキュラム生成（Region Growing Curriculum Generation for Reinforcement Learning）</news:title>
   <news:publication_date>2026-05-22T23:56:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693212</loc>
  <lastmod>2026-05-22T23:56:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイアスを排した画像スタイル転送の回帰的制御（Unbiased Image Style Transfer）</news:title>
   <news:publication_date>2026-05-22T23:56:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693210</loc>
  <lastmod>2026-05-22T23:55:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データに対する特徴選択付き対角判別分析（Diagonal Discriminant Analysis with Feature Selection for High Dimensional Data）</news:title>
   <news:publication_date>2026-05-22T23:55:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693208</loc>
  <lastmod>2026-05-22T23:54:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Grassmannian上のエンドメンバー抽出（ENDMEMBER EXTRACTION ON THE GRASSMANNIAN）</news:title>
   <news:publication_date>2026-05-22T23:54:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693206</loc>
  <lastmod>2026-05-22T23:54:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>臨床ノートから学ぶ患者表現と可解性評価（Patient representation learning and interpretable evaluation using clinical notes）</news:title>
   <news:publication_date>2026-05-22T23:54:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693204</loc>
  <lastmod>2026-05-22T23:54:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線通信への深層学習を用いたジャミング攻撃と防御（Deep Learning for Launching and Mitigating Wireless Jamming Attacks）</news:title>
   <news:publication_date>2026-05-22T23:54:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693202</loc>
  <lastmod>2026-05-22T23:02:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層モデリングとフォトメトリック赤方偏移の統計的較正（Hierarchical modeling and statistical calibration for photometric redshifts）</news:title>
   <news:publication_date>2026-05-22T23:02:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693200</loc>
  <lastmod>2026-05-22T23:02:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡散による捕獲と拡散相互作用の概念（Diffusion to Capture and the Concept of Diffusive Interactions）</news:title>
   <news:publication_date>2026-05-22T23:02:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693198</loc>
  <lastmod>2026-05-22T23:02:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビッグデータの視覚的パターンドリブン探索（Visual Pattern-Driven Exploration of Big Data）</news:title>
   <news:publication_date>2026-05-22T23:02:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693196</loc>
  <lastmod>2026-05-22T23:01:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>皮膚疾患画像の異常検知におけるVariational Autoencoderの応用（Anomaly Detection for Skin Disease Images Using Variational Autoencoder）</news:title>
   <news:publication_date>2026-05-22T23:01:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693194</loc>
  <lastmod>2026-05-22T23:01:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習のためのクラウド技術の起源（THE CLOUD TECHNOLOGIES OF LEARNING: ORIGIN）</news:title>
   <news:publication_date>2026-05-22T23:01:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693192</loc>
  <lastmod>2026-05-22T23:00:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン圧縮型テンソル分解 OCTen（OCTen: Online Compression-based Tensor Decomposition）</news:title>
   <news:publication_date>2026-05-22T23:00:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693190</loc>
  <lastmod>2026-05-22T23:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アナログ配列向け高効率ConvNet設計（Efficient ConvNets for Analog Arrays）</news:title>
   <news:publication_date>2026-05-22T23:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693188</loc>
  <lastmod>2026-05-22T22:08:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型資源配分の効率設計——エージェント報酬最適化による正確なPrice of Anarchyの解析（Utility Design for Distributed Resource Allocation – Part I: Characterizing and Optimizing the Exact Price of Anarchy）</news:title>
   <news:publication_date>2026-05-22T22:08:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693186</loc>
  <lastmod>2026-05-22T21:59:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳がん診断における分類アルゴリズムの比較（Breast Cancer Diagnosis via Classification Algorithms）</news:title>
   <news:publication_date>2026-05-22T21:59:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693184</loc>
  <lastmod>2026-05-22T21:58:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顧客サポートを高速かつ高精度にするCOTA（COTA: Improving the Speed and Accuracy of Customer Support through Ranking and Deep Networks）</news:title>
   <news:publication_date>2026-05-22T21:58:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693182</loc>
  <lastmod>2026-05-22T21:57:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多モーダル生体認証のための一般化双線形深層畳み込みニューラルネットワーク（GENERALIZED BILINEAR DEEP CONVOLUTIONAL NEURAL NETWORKS FOR MULTIMODAL BIOMETRIC IDENTIFICATION）</news:title>
   <news:publication_date>2026-05-22T21:57:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693180</loc>
  <lastmod>2026-05-22T21:57:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期宇宙の星形成に関する制約（Constraints on Early Star Formation from the 21-cm Global Signal）</news:title>
   <news:publication_date>2026-05-22T21:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693178</loc>
  <lastmod>2026-05-22T21:57:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ポストスター ブラスト銀河の構造と消光経路の二分化（The structure of post-starburst galaxies at 0.5 &amp;lt; z &amp;lt; 2: evidence for two distinct quenching routes at different epochs）</news:title>
   <news:publication_date>2026-05-22T21:57:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693176</loc>
  <lastmod>2026-05-22T21:57:04Z</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からの多層特徴抽象化によるマルチモーダル生体認証（Multi-Level Feature Abstraction from Convolutional Neural Networks for Multimodal Biometric Identification）</news:title>
   <news:publication_date>2026-05-22T21:57:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693174</loc>
  <lastmod>2026-05-22T21:05:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dタンパク質構造に基づくエンドツーエンド学習によるインターフェース予測（End-to-End Learning on 3D Protein Structure for Interface Prediction）</news:title>
   <news:publication_date>2026-05-22T21:05:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693172</loc>
  <lastmod>2026-05-22T21:04:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似サーベイ伝播法による統計的推論（Approximate Survey Propagation for Statistical Inference）</news:title>
   <news:publication_date>2026-05-22T21:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693170</loc>
  <lastmod>2026-05-22T21:04:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1人称マルチプレイヤーゲームで人間レベルを達成した研究（Human-level performance in first-person multiplayer games with population-based deep reinforcement learning）</news:title>
   <news:publication_date>2026-05-22T21:04:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693168</loc>
  <lastmod>2026-05-22T21:04:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間レベルに迫る文法誤り訂正の新戦略（Reaching Human-Level Performance in Automatic Grammatical Error Correction: An Empirical Study）</news:title>
   <news:publication_date>2026-05-22T21:04:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693166</loc>
  <lastmod>2026-05-22T21:03:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然と対峙する意思決定：不確実性下の因果発見（Playing against Nature: causal discovery for decision making under uncertainty）</news:title>
   <news:publication_date>2026-05-22T21:03:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693164</loc>
  <lastmod>2026-05-22T21:03:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン勾配降下法の計算力について（On the Computational Power of Online Gradient Descent）</news:title>
   <news:publication_date>2026-05-22T21:03:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693162</loc>
  <lastmod>2026-05-22T21:03:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索と活用の動的制御（Dynamic Control of Explore/Exploit Trade-Off In Bayesian Optimization）</news:title>
   <news:publication_date>2026-05-22T21:03:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693160</loc>
  <lastmod>2026-05-22T20:12:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり適応DenseNetによる胸部疾患分類と異常箇所同定（A Weakly Supervised Adaptive DenseNet for Classifying Thoracic Diseases and Identifying Abnormalities）</news:title>
   <news:publication_date>2026-05-22T20:12:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693158</loc>
  <lastmod>2026-05-22T20:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遮蔽と限られたセンサー範囲に対処する集合ベースの安全検証（Tackling Occlusions &amp;amp; Limited Sensor Range with Set-based Safety Verification）</news:title>
   <news:publication_date>2026-05-22T20:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693156</loc>
  <lastmod>2026-05-22T20:11:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応学習ダイナミクスの安定性解析（On the stability of an adaptive learning dynamics in traffic games）</news:title>
   <news:publication_date>2026-05-22T20:11:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693154</loc>
  <lastmod>2026-05-22T20:10:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>細胞内シグナルネットワークにおける非連合学習の報告（Non-associative learning in intra-cellular signaling networks）</news:title>
   <news:publication_date>2026-05-22T20:10:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693152</loc>
  <lastmod>2026-05-22T20:10:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数領域における深層ニューラルネットワークの学習挙動（Training behavior of deep neural network in frequency domain）</news:title>
   <news:publication_date>2026-05-22T20:10:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693150</loc>
  <lastmod>2026-05-22T20:10:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SpaceNet: リモートセンシングデータセットとチャレンジ（SpaceNet: A Remote Sensing Dataset and Challenge）</news:title>
   <news:publication_date>2026-05-22T20:10:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693148</loc>
  <lastmod>2026-05-22T20:09:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子版GANによる離散分布生成の提案（Quantum generative adversarial network for generating discrete distribution）</news:title>
   <news:publication_date>2026-05-22T20:09:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693146</loc>
  <lastmod>2026-05-22T19:17:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非線形フォワードモデルに対する深層ニューラルネットワークによる超音波反射トモグラフィ再構成（DEEP NEURAL NETWORKS FOR NON-LINEAR MODEL-BASED ULTRASOUND RECONSTRUCTION）</news:title>
   <news:publication_date>2026-05-22T19:17:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693144</loc>
  <lastmod>2026-05-22T19:16:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所勾配平滑化による局所的敵対的攻撃の防御（Local Gradients Smoothing: Defense against localized adversarial attacks）</news:title>
   <news:publication_date>2026-05-22T19:16:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693142</loc>
  <lastmod>2026-05-22T19:16:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>整流を使った一本鎖DNAの配列決定（ssDNA sequencing by rectification）</news:title>
   <news:publication_date>2026-05-22T19:16:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693140</loc>
  <lastmod>2026-05-22T19:15:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マスターのプライバシーを守る符号化分散計算（Private Coded Computation for Machine Learning）</news:title>
   <news:publication_date>2026-05-22T19:15:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693138</loc>
  <lastmod>2026-05-22T19:15:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファッションのスタイルを学習してアイテムを補完する手法（Styling with Attention to Details）</news:title>
   <news:publication_date>2026-05-22T19:15:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693136</loc>
  <lastmod>2026-05-22T19:14:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>狭い深層ニューラルネットワークの判定領域について（On decision regions of narrow deep neural networks）</news:title>
   <news:publication_date>2026-05-22T19:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693134</loc>
  <lastmod>2026-05-22T19:14:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数カテゴリ変数を生成するGANの設計と評価（Generating Multi-Categorical Samples with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-22T19:14:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693132</loc>
  <lastmod>2026-05-22T18:22:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率ベースの独立サンプラーによるグラフィカル対数線形周辺モデルのベイズ定量学習（Probability Based Independence Sampler for Bayesian Quantitative Learning in Graphical Log-Linear Marginal Models）</news:title>
   <news:publication_date>2026-05-22T18:22:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693130</loc>
  <lastmod>2026-05-22T18:12:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>騒がしい学習データを扱う視覚検査のためのGANによる異常検知（Anomaly Detection Using GANs for Visual Inspection in Noisy Training Data）</news:title>
   <news:publication_date>2026-05-22T18:12:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693128</loc>
  <lastmod>2026-05-22T18:11:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公正分類の福祉と分配への影響（Welfare and Distributional Impacts of Fair Classification）</news:title>
   <news:publication_date>2026-05-22T18:11:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693126</loc>
  <lastmod>2026-05-22T18:11:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストなしで行間を読む：視覚・音響モダリティからのスケーラブルなマルチモーダル感情分類（Getting the subtext without the text: Scalable multimodal sentiment classification from visual and acoustic modalities）</news:title>
   <news:publication_date>2026-05-22T18:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693124</loc>
  <lastmod>2026-05-22T18:11:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり深層リカレントニューラルネットワークによる基本ダンスステップ生成（Weakly-Supervised Deep Recurrent Neural Networks for Basic Dance Step Generation）</news:title>
   <news:publication_date>2026-05-22T18:11:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693122</loc>
  <lastmod>2026-05-22T18:11:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SageMathCloudを用いた学生の協働支援の学習手法（The Learning Technique of the SageMathCloud Use for Students Collaboration Support）</news:title>
   <news:publication_date>2026-05-22T18:11:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693120</loc>
  <lastmod>2026-05-22T18:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SageMath Cloudを用いた高等学校数学教育の方法論（The Methodical Aspects of the Algebra and the Mathematical Analysis Study Using the SageMath Cloud）</news:title>
   <news:publication_date>2026-05-22T18:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693118</loc>
  <lastmod>2026-05-22T17:19:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教育機関のクラウド型コンピュータ数学システム（The Systems of Computer Mathematics in the Cloud-Based Learning Environment of Educational Institutions）</news:title>
   <news:publication_date>2026-05-22T17:19:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693116</loc>
  <lastmod>2026-05-22T17:18:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的チャネル非相関化ネットワーク（Stochastic Channel Decorrelation Network and Its Application to Visual Tracking）</news:title>
   <news:publication_date>2026-05-22T17:18:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693114</loc>
  <lastmod>2026-05-22T17:18:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウド上の計算数学システムを用いた学習コンポーネントの設計と評価（The Design and Evaluation of the Cloud-based Learning Components with the Use of the Systems of Computer Mathematics）</news:title>
   <news:publication_date>2026-05-22T17:18:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693112</loc>
  <lastmod>2026-05-22T17:18:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の平均場最適制御定式化（A Mean-Field Optimal Control Formulation of Deep Learning）</news:title>
   <news:publication_date>2026-05-22T17:18:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693110</loc>
  <lastmod>2026-05-22T17:17:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガンマ線ログ法における欠損値復元の実用的提案（Recovering Gaps in the Gamma-Ray Logging Method）</news:title>
   <news:publication_date>2026-05-22T17:17:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693108</loc>
  <lastmod>2026-05-22T17:17:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジでの階層的容量配備（HIERARCHICAL CAPACITY PROVISIONING FOR FOG COMPUTING）</news:title>
   <news:publication_date>2026-05-22T17:17:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693106</loc>
  <lastmod>2026-05-22T17:17:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワン・クラス・カーネル・スペクトル回帰の要点（One-Class Kernel Spectral Regression）</news:title>
   <news:publication_date>2026-05-22T17:17:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693104</loc>
  <lastmod>2026-05-22T16:25:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BIN-CT による都市ごみ収集の最適化（BIN-CT: Urban Waste Collection based on Predicting the Container Fill Level）</news:title>
   <news:publication_date>2026-05-22T16:25:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693102</loc>
  <lastmod>2026-05-22T16:25:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画セグメンテーションの新潮流：VideoGCRFがもたらす一貫性ある予測（Deep Spatio-Temporal Random Fields for Efficient Video Segmentation）</news:title>
   <news:publication_date>2026-05-22T16:25:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693100</loc>
  <lastmod>2026-05-22T16:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HAMLETによる脳白質トラクト学習の革新（HAMLET: Hierarchical Harmonic Filters for Learning Tracts from Diffusion MRI）</news:title>
   <news:publication_date>2026-05-22T16:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693098</loc>
  <lastmod>2026-05-22T16:24:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動ポリシー推定とオフポリシー評価における較正の重要性（Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters）</news:title>
   <news:publication_date>2026-05-22T16:24:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693096</loc>
  <lastmod>2026-05-22T16:24:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマノイドロボットによる対話的聴覚探索による深層物体解析（Deep Neural Object Analysis by Interactive Auditory Exploration with a Humanoid Robot）</news:title>
   <news:publication_date>2026-05-22T16:24:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693094</loc>
  <lastmod>2026-05-22T16:24:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模データ時代のガウス過程レビュー（When Gaussian Process Meets Big Data: A Review of Scalable GPs）</news:title>
   <news:publication_date>2026-05-22T16:24:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693092</loc>
  <lastmod>2026-05-22T16:23:44Z</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>2026-05-22T16:23:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693090</loc>
  <lastmod>2026-05-22T15:32:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>現場でのキッティングを可能にするオンラインドメイン適応（Kitting in the Wild through Online Domain Adaptation）</news:title>
   <news:publication_date>2026-05-22T15:32:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693088</loc>
  <lastmod>2026-05-22T15:32:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Semantic Video Classificationにおける深層構造とアンサンブルの有効性（Deep Architectures and Ensembles for Semantic Video Classification）</news:title>
   <news:publication_date>2026-05-22T15:32:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693086</loc>
  <lastmod>2026-05-22T15:31:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>屋内シーンにおける高速なバウンディングボックス注釈法（Faster Bounding Box Annotation for Object Detection in Indoor Scenes）</news:title>
   <news:publication_date>2026-05-22T15:31:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693084</loc>
  <lastmod>2026-05-22T15:30:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>距離尺度の線形結合によるサロゲートモデルの改良（Linear Combination of Distance Measures for Surrogate Models in Genetic Programming）</news:title>
   <news:publication_date>2026-05-22T15:30:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693082</loc>
  <lastmod>2026-05-22T15:30:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的探索空間におけるクリギング最適化のためのカーネルの初期解析（A First Analysis of Kernels for Kriging-based Optimization in Hierarchical Search Spaces）</news:title>
   <news:publication_date>2026-05-22T15:30:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693080</loc>
  <lastmod>2026-05-22T15:30:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる気象下でセマンティック情報を移転するモジュール型車両制御（Modular Vehicle Control for Transferring Semantic Information Between Weather Conditions Using GANs）</news:title>
   <news:publication_date>2026-05-22T15:30:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693078</loc>
  <lastmod>2026-05-22T15:29:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Coopetitive Soft Gating Ensemble（Coopetitive Soft Gating Ensemble）</news:title>
   <news:publication_date>2026-05-22T15:29:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693076</loc>
  <lastmod>2026-05-22T14:38:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回帰のための簡潔な表現学習：木構造ネットワークを進化させることで得られる解釈性（LEARNING CONCISE REPRESENTATIONS FOR REGRESSION BY EVOLVING NETWORKS OF TREES）</news:title>
   <news:publication_date>2026-05-22T14:38:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693074</loc>
  <lastmod>2026-05-22T14:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ノイズコントラスト推定によるニューラルTRF言語モデルの改善（IMPROVED TRAINING OF NEURAL TRANS-DIMENSIONAL RANDOM FIELD LANGUAGE MODELS WITH DYNAMIC NOISE-CONTRASTIVE ESTIMATION）</news:title>
   <news:publication_date>2026-05-22T14:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693072</loc>
  <lastmod>2026-05-22T14:38:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長時間活動ビデオ理解と機能的オブジェクト指向ネットワーク（Long Activity Video Understanding using Functional Object-Oriented Network）</news:title>
   <news:publication_date>2026-05-22T14:38:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693070</loc>
  <lastmod>2026-05-22T14:36:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模化可能なPSLの構造学習（Scalable Structure Learning for Probabilistic Soft Logic）</news:title>
   <news:publication_date>2026-05-22T14:36:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693068</loc>
  <lastmod>2026-05-22T14:36:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称畳み込みネットワークによる遮蔽検出（SymmNet: A Symmetric Convolutional Neural Network for Occlusion Detection）</news:title>
   <news:publication_date>2026-05-22T14:36:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693066</loc>
  <lastmod>2026-05-22T14:36:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MetaAnchorによるカスタマイズ可能なアンカー学習（Learning to Detect Objects with Customized Anchors）</news:title>
   <news:publication_date>2026-05-22T14:36:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693064</loc>
  <lastmod>2026-05-22T14:36:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元テンソル補完における低ランクテンソルリング分解（Higher-dimension Tensor Completion via Low-rank Tensor Ring Decomposition）</news:title>
   <news:publication_date>2026-05-22T14:36:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693062</loc>
  <lastmod>2026-05-22T13:43:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層ごとの確率的精度配分が示す効率化と正則化効果（Stochastic Layer-Wise Precision in Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-22T13:43:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693060</loc>
  <lastmod>2026-05-22T13:36:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>触覚探索経験を活かしたロボットによる新物体の物理特性学習（Leveraging Robotic Prior Tactile Exploratory Action Experiences For Learning New Objects’ Physical Properties）</news:title>
   <news:publication_date>2026-05-22T13:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/693058</loc>
  <lastmod>2026-05-22T13:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベッド上センサの心拍計測波形解析レビュー（Ballistocardiogram Signal Processing: A Literature Review）</news:title>
   <news:publication_date>2026-05-22T13:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693056</loc>
  <lastmod>2026-05-22T13:35:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線における反復的注意マイニングによる弱教師付き病変局在化（Iterative Attention Mining for Weakly Supervised Thoracic Disease Pattern Localization in Chest X-Rays）</news:title>
   <news:publication_date>2026-05-22T13:35:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693054</loc>
  <lastmod>2026-05-22T13:34:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ステレオタイプの賦活化を排すればバイアスは消えるのか（Does Removing Stereotype Priming Remove Bias? A Pilot Human-Robot Interaction Study）</news:title>
   <news:publication_date>2026-05-22T13:34:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693052</loc>
  <lastmod>2026-05-22T13:34:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二つの領域で類似属性を同時生成する技術（Resembled Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-22T13:34:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693050</loc>
  <lastmod>2026-05-22T13:33:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ化された確率集合における制約付き動的最適輸送（Constrained Dynamical Optimal Transport and Its Lagrangian Formulation）</news:title>
   <news:publication_date>2026-05-22T13:33:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693048</loc>
  <lastmod>2026-05-22T12:42:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動情報ボトルネックにおける不確実性（Uncertainty in the Variational Information Bottleneck）</news:title>
   <news:publication_date>2026-05-22T12:42:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693046</loc>
  <lastmod>2026-05-22T12:34:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不完全な情報からの巨視的予測の複雑性を情報幾何学で見る（An information geometric perspective on the complexity of macroscopic predictions arising from incomplete information）</news:title>
   <news:publication_date>2026-05-22T12:34:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693044</loc>
  <lastmod>2026-05-22T12:34:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル・ランダム射影による言語モデル（Neural Random Projections for Language Modelling）</news:title>
   <news:publication_date>2026-05-22T12:34:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693042</loc>
  <lastmod>2026-05-22T12:33:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Recurrent–OctoMapによる状態ベースの3Dマップ精緻化（Recurrent-OctoMap: Learning State-based Map Refinement for Long-Term Semantic Mapping with 3D-Lidar Data）</news:title>
   <news:publication_date>2026-05-22T12:33:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693040</loc>
  <lastmod>2026-05-22T12:32:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>言語変異と普遍性のモデリング（Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing）</news:title>
   <news:publication_date>2026-05-22T12:32:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693038</loc>
  <lastmod>2026-05-22T12:32:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限定データでのセマンティックセグメンテーション（Semantic Segmentation with Scarce Data）</news:title>
   <news:publication_date>2026-05-22T12:32:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693036</loc>
  <lastmod>2026-05-22T12:32:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択的ラベル下での学習と専門家の一貫性（Learning under selective labels in the presence of expert consistency）</news:title>
   <news:publication_date>2026-05-22T12:32:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693034</loc>
  <lastmod>2026-05-22T11:40:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Counterfactual Value Networksの解析と最適化（Analysis and Optimization of Deep Counterfactual Value Networks）</news:title>
   <news:publication_date>2026-05-22T11:40:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693032</loc>
  <lastmod>2026-05-22T11:39:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PCAの最適性と非最適性（OPTIMALITY AND SUB-OPTIMALITY OF PCA I: SPIKED RANDOM MATRIX MODELS）</news:title>
   <news:publication_date>2026-05-22T11:39:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693030</loc>
  <lastmod>2026-05-22T11:39:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化された手形状のためのモデルベース手指姿勢推定（Model-based Hand Pose Estimation for Generalized Hand Shape with Appearance Normalization）</news:title>
   <news:publication_date>2026-05-22T11:39:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693028</loc>
  <lastmod>2026-05-22T11:39:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非協調スペクトラムアクセスのマルチユーザ・マルチ腕バンディット（Multi-user Multi-armed Bandits for Uncoordinated Spectrum Access）</news:title>
   <news:publication_date>2026-05-22T11:39:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693026</loc>
  <lastmod>2026-05-22T11:39:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>戦術的運転行動検出のための半教師あり学習（Semi-supervised Learning: Fusion of Self-supervised, Supervised Learning, and Multimodal Cues for Tactical Driver Behavior Detection）</news:title>
   <news:publication_date>2026-05-22T11:39:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693024</loc>
  <lastmod>2026-05-22T11:39:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己濃縮によるグローバル・クラスターの極端なHe（ヘリウム）リッチ個体群（Self-enrichment in Globular Clusters: the extreme He-rich population of NGC 2808）</news:title>
   <news:publication_date>2026-05-22T11:39:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693022</loc>
  <lastmod>2026-05-22T11:39:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的多相流の不確かさ評価のための深層畳み込みエンコーダ・デコーダネットワーク（Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media）</news:title>
   <news:publication_date>2026-05-22T11:39:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693020</loc>
  <lastmod>2026-05-22T10:47:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クライアント固有情報を用いた顔プレゼンテーション攻撃検出の評価（On the Use of Client-Specific Information for Face Presentation Attack Detection Based on Anomaly Detection）</news:title>
   <news:publication_date>2026-05-22T10:47:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693018</loc>
  <lastmod>2026-05-22T10:47:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ほぼすべてのニューラルネットワークを改善する手法（Make (Nearly) Every Neural Network Better: Generating Neural Network Ensembles by Weight Parameter Resampling）</news:title>
   <news:publication_date>2026-05-22T10:47:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693016</loc>
  <lastmod>2026-05-22T10:46:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PRED18: DAVISイベントカメラを用いた捕食者・被食者ロボット追跡データセットと実験（PRED18: Dataset and Further Experiments with DAVIS Event Camera in Predator-Prey Robot Chasing）</news:title>
   <news:publication_date>2026-05-22T10:46:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693014</loc>
  <lastmod>2026-05-22T10:45:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユークリッド虫洞とベイビーユニバースが示す粒子物理と宇宙論への影響（Euclidean wormholes, baby universes, and their impact on particle physics and cosmology）</news:title>
   <news:publication_date>2026-05-22T10:45:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693012</loc>
  <lastmod>2026-05-22T10:45:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小惑星活動の大規模探索とSAFARIの示唆（SAFARI: Searching Asteroids For Activity Revealing Indicators）</news:title>
   <news:publication_date>2026-05-22T10:45:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693010</loc>
  <lastmod>2026-05-22T10:45:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近傍活動銀河核における銀河スケールの熱的アウトフローの不在（No evidence of galaxy-scale hot outflows in two nearby AGN）</news:title>
   <news:publication_date>2026-05-22T10:45:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693008</loc>
  <lastmod>2026-05-22T10:45:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プランク選定クラスターにおける銀河の星形成質量関数と衛星銀河のクワenching（The stellar mass function of galaxies in Planck-selected clusters at 0.5 &amp;lt; z &amp;lt; 0.7: new constraints on the timescale and location of satellite quenching）</news:title>
   <news:publication_date>2026-05-22T10:45:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693006</loc>
  <lastmod>2026-05-22T09:53:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なる天文サーベイ間の転移学習による銀河形態分類（Transfer learning for galaxy morphology from one survey to another）</news:title>
   <news:publication_date>2026-05-22T09:53:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693004</loc>
  <lastmod>2026-05-22T09:53:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所ハミルトニアンによるデータ分類（Classifying Data with Local Hamiltonians）</news:title>
   <news:publication_date>2026-05-22T09:53:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693002</loc>
  <lastmod>2026-05-22T09:52:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習で設計するフィードバック付き通信コード（Deepcode: Feedback Codes via Deep Learning）</news:title>
   <news:publication_date>2026-05-22T09:52:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/693000</loc>
  <lastmod>2026-05-22T09:52:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>表面電子の輸送測定と薄膜ヘリウムマイクロチャネルの可能性（Transport Measurements of Surface Electrons in 200 nm Deep Helium-Filled Microchannels Above Amorphous Metallic Electrodes）</news:title>
   <news:publication_date>2026-05-22T09:52:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692998</loc>
  <lastmod>2026-05-22T09:51:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルゴリズム的不公平を数値化する統一的アプローチ（A Unified Approach to Quantifying Algorithmic Unfairness）</news:title>
   <news:publication_date>2026-05-22T09:51:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692996</loc>
  <lastmod>2026-05-22T09:51:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成敵対ネットワークの潜在空間におけるアンビエント表現（Ambient Hidden Space of Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-22T09:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692994</loc>
  <lastmod>2026-05-22T09:50:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CoCalcを用いたニューラルネットワーク学習ツール（CoCalc as a Learning Tool for Neural Network Simulation）</news:title>
   <news:publication_date>2026-05-22T09:50:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692992</loc>
  <lastmod>2026-05-22T08:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>波形から単一正弦波への回帰で雑音下音声のF0等高線を推定する手法（Waveform to Single Sinusoid Regression to Estimate the F0 Contour from Noisy Speech Using Recurrent Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-22T08:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692990</loc>
  <lastmod>2026-05-22T08:59:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近似最適なアルゴリズム設定手法の実用化展望（LEAPSANDBOUNDS: A Method for Approximately Optimal Algorithm Configuration）</news:title>
   <news:publication_date>2026-05-22T08:59:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692988</loc>
  <lastmod>2026-05-22T08:59:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
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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:title>低リソース環境でのノイズ付き自動注釈データを用いたニューラルネットワークの学習（Training a Neural Network in a Low-Resource Setting on Automatically Annotated Noisy Data）</news:title>
   <news:publication_date>2026-05-22T08:57:27Z</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:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-22T08:57:02Z</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:publication_date>2026-05-22T08:04:42Z</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>
  <loc>https://aibr.jp/archives/692974</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692972</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-22T08:03:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692970</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>2026-05-22T08:03:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-22T08:03:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>外観ベース視線追跡における個人最適化学習（Learning to Personalize in Appearance-Based Gaze Tracking）</news:title>
   <news:publication_date>2026-05-22T08:03:13Z</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>信用デフォルト検出における機械学習とヒューリスティックの組合せによる実務的アプローチ（Credit Default Mining Using Combined Machine Learning and Heuristic Approach）</news:title>
   <news:publication_date>2026-05-22T08:02:59Z</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>2026-05-22T07:11:45Z</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>
  </news:news>
 </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>
   </news:publication>
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   <news:publication_date>2026-05-22T07:00:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-22T06:59:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692954</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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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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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-22T06:07:57Z</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>
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   <news:publication_date>2026-05-22T06:07:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-05-22T06:07:12Z</lastmod>
  <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:publication_date>2026-05-22T06:06:02Z</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>
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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>
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   <news:publication_date>2026-05-22T06:05:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-22T06:05:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-05-22T06:05:12Z</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>
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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>
  <loc>https://aibr.jp/archives/692932</loc>
  <lastmod>2026-05-22T05:12:54Z</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>2026-05-22T05:12:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692930</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>2026-05-22T05:12:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692928</loc>
  <lastmod>2026-05-22T05:11:54Z</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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  <lastmod>2026-05-22T05:11:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SphereReID: 深層ハイパースフィア埋め込みによる人物再識別（SphereReID: Deep Hypersphere Manifold Embedding for Person Re-Identification）</news:title>
   <news:publication_date>2026-05-22T05:11:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692924</loc>
  <lastmod>2026-05-22T05:10:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話音声の句読点予測がもたらす実務変化（Punctuation Prediction Model for Conversational Speech）</news:title>
   <news:publication_date>2026-05-22T05:10:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-22T04:19:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像キャプション生成におけるジェンダーバイアス是正（Women also Snowboard: Overcoming Bias in Captioning Models）</news:title>
   <news:publication_date>2026-05-22T04:19:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-22T04:18:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-22T04:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-05-22T04:18:37Z</lastmod>
  <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>
  <loc>https://aibr.jp/archives/692916</loc>
  <lastmod>2026-05-22T04:18:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>膠芽腫の個別放射線治療設計（Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans and Bayesian Inference）</news:title>
   <news:publication_date>2026-05-22T04:18:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692914</loc>
  <lastmod>2026-05-22T04:17:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セグメンテーション品質予測に不確実性推定を活用する（Leveraging Uncertainty Estimates for Predicting Segmentation Quality）</news:title>
   <news:publication_date>2026-05-22T04:17:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692912</loc>
  <lastmod>2026-05-22T04:17:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微細粒度画像認識のための知識埋め込み表現学習（Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition）</news:title>
   <news:publication_date>2026-05-22T04:17:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692910</loc>
  <lastmod>2026-05-22T04:17:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会関係理解のための知識グラフによる深層推論（Deep Reasoning with Knowledge Graph for Social Relationship Understanding）</news:title>
   <news:publication_date>2026-05-22T04:17:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692908</loc>
  <lastmod>2026-05-22T03:26:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Active Testingによる精度推定の効率化と頑健性（Active Testing: An Efficient and Robust Framework for Estimating Accuracy）</news:title>
   <news:publication_date>2026-05-22T03:26:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692906</loc>
  <lastmod>2026-05-22T03:25:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動誘導による公平性テスト（Automated Directed Fairness Testing）</news:title>
   <news:publication_date>2026-05-22T03:25:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692904</loc>
  <lastmod>2026-05-22T03:25:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低質量比かつ深接触連星の観測と赤色新星への進化可能性（TY Pup: a low-mass-ratio and deep contact binary as a progenitor candidate of luminous red novae）</news:title>
   <news:publication_date>2026-05-22T03:25:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692902</loc>
  <lastmod>2026-05-22T03:25:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTネットワークにおけるマルチアームドバンディット学習の有効性（Multi-Armed Bandit Learning in IoT Networks: Learning helps even in non-stationary settings）</news:title>
   <news:publication_date>2026-05-22T03:25:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692900</loc>
  <lastmod>2026-05-22T03:25:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文法誤り訂正のための単純だが有効な分類モデル（A Simple but Effective Classification Model for Grammatical Error Correction）</news:title>
   <news:publication_date>2026-05-22T03:25:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692898</loc>
  <lastmod>2026-05-22T03:24:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートウォッチのタップ認証（Tap-based User Authentication for Smartwatches）</news:title>
   <news:publication_date>2026-05-22T03:24:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692896</loc>
  <lastmod>2026-05-22T03:24:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FATE：低消費電力DNNアクセラレータ設計のための高速かつ高精度なタイミング誤差予測フレームワーク (FATE: Fast and Accurate Timing Error Prediction Framework for Low Power DNN Accelerator Design)</news:title>
   <news:publication_date>2026-05-22T03:24:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692894</loc>
  <lastmod>2026-05-22T02:33:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線をセンサーとして活用する車両分類の実装と意義（Leveraging the Channel as a Sensor: Real-time Vehicle Classification Using Multidimensional Radio-fingerprinting）</news:title>
   <news:publication_date>2026-05-22T02:33:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692892</loc>
  <lastmod>2026-05-22T02:33:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ColdRouteによるコールドクエスチョンの効果的ルーティング（ColdRoute: Effective Routing of Cold Questions in Stack Exchange Sites）</news:title>
   <news:publication_date>2026-05-22T02:33:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692890</loc>
  <lastmod>2026-05-22T02:33:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>保護属性に起因する望ましくない変動を取り除くことで表現をデバイアスする方法（Debiasing representations by removing unwanted variation due to protected attributes）</news:title>
   <news:publication_date>2026-05-22T02:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692888</loc>
  <lastmod>2026-05-22T02:32:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム映像分類に対する敵対的摂動の脆弱性（Adversarial Perturbations Against Real-Time Video Classification Systems）</news:title>
   <news:publication_date>2026-05-22T02:32:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692886</loc>
  <lastmod>2026-05-22T02:32:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>均等カスケード畳み込みネットワーク（Evenly Cascaded Convolutional Networks）</news:title>
   <news:publication_date>2026-05-22T02:32:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692884</loc>
  <lastmod>2026-05-22T02:31:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不正な内部者取引の発掘と予測（Mining Illegal Insider Trading of Stocks: A Proactive Approach）</news:title>
   <news:publication_date>2026-05-22T02:31:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692882</loc>
  <lastmod>2026-05-22T02:31:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連合学習に対するバックドア攻撃の実装と影響（How To Backdoor Federated Learning）</news:title>
   <news:publication_date>2026-05-22T02:31:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692880</loc>
  <lastmod>2026-05-22T01:40:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディピオン光生成と金核のQ2による形状変化の解析（Dipion photoproduction and the Q2 evolution of the shape of the gold nucleus）</news:title>
   <news:publication_date>2026-05-22T01:40:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692878</loc>
  <lastmod>2026-05-22T01:40:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Elastic Neural Networks: 組み込み向け画像認識のためのスケーラブルフレームワーク（Elastic Neural Networks: A Scalable Framework for Embedded Computer Vision）</news:title>
   <news:publication_date>2026-05-22T01:40:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692876</loc>
  <lastmod>2026-05-22T01:40:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行列データを直接扱う分類器の新展開 — マルチディスタンスサポートマトリックスマシン（Multi-distance Support Matrix Machines）</news:title>
   <news:publication_date>2026-05-22T01:40:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692874</loc>
  <lastmod>2026-05-22T01:40:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>チャンネル非依存なエンドツーエンド通信学習（Channel Agnostic End-to-End Learning based Communication Systems with Conditional GAN）</news:title>
   <news:publication_date>2026-05-22T01:40:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692872</loc>
  <lastmod>2026-05-22T01:39:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な生成的判別モデルが切り開く神経画像解析の新地平（Generative discriminative models for multivariate inference and statistical mapping in medical imaging）</news:title>
   <news:publication_date>2026-05-22T01:39:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692870</loc>
  <lastmod>2026-05-22T01:39:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点確率距離による方策最適化（Policy Optimization With Penalized Point Probability Distance）</news:title>
   <news:publication_date>2026-05-22T01:39:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692868</loc>
  <lastmod>2026-05-22T01:39:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Eコマースの「代謝」を加速する強化学習型メカニズム設計（Speeding up the Metabolism in E-commerce by Reinforcement Mechanism Design）</news:title>
   <news:publication_date>2026-05-22T01:39:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692865</loc>
  <lastmod>2026-05-22T00:48:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱ラベル多相CTボリュームからの肝病変検出（Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector）</news:title>
   <news:publication_date>2026-05-22T00:48:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692863</loc>
  <lastmod>2026-05-22T00:48:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線画像の深層学習における交絡変数と汎化性の低下（Confounding variables can degrade generalization performance of radiological deep learning models）</news:title>
   <news:publication_date>2026-05-22T00:48:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692861</loc>
  <lastmod>2026-05-22T00:47:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列の動的予測長を学習するSeq2Seqモデル（Dynamic Prediction Length for Time Series with Sequence to Sequence Networks）</news:title>
   <news:publication_date>2026-05-22T00:47:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692859</loc>
  <lastmod>2026-05-22T00:47:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限値の量子ゆらぎによるニューラルネット最適化（Optimization of neural networks via finite-value quantum fluctuations）</news:title>
   <news:publication_date>2026-05-22T00:47:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692857</loc>
  <lastmod>2026-05-22T00:47:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子密度表現が開く材料機械学習の地平（Atom-Density Representations for Machine Learning）</news:title>
   <news:publication_date>2026-05-22T00:47:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692855</loc>
  <lastmod>2026-05-22T00:47:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>1日で車を走らせる学習法（Learning to Drive in a Day）</news:title>
   <news:publication_date>2026-05-22T00:47:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692853</loc>
  <lastmod>2026-05-22T00:46:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RECISTの2Dマーカーから全容を復元する弱教師付きスライス伝搬学習（Accurate Weakly-Supervised Deep Lesion Segmentation using Large-Scale Clinical Annotations: Slice-Propagated 3D Mask Generation from 2D RECIST）</news:title>
   <news:publication_date>2026-05-22T00:46:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692851</loc>
  <lastmod>2026-05-21T23:55:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラム合成を用いた強化学習の混合最適化（Towards Mixed Optimization for Reinforcement Learning with Program Synthesis）</news:title>
   <news:publication_date>2026-05-21T23:55:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692849</loc>
  <lastmod>2026-05-21T23:54:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分ランキングに対する反対変数とモンテカルロによるカーネル推定（Antithetic and Monte Carlo kernel estimators for partial rankings）</news:title>
   <news:publication_date>2026-05-21T23:54:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692847</loc>
  <lastmod>2026-05-21T23:54:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オブジェクト関係データのモデルベース例外抽出（Model-based Exception Mining for Object-Relational Data）</news:title>
   <news:publication_date>2026-05-21T23:54:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692845</loc>
  <lastmod>2026-05-21T23:54:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース領域適応のための拡張サイクル敵対学習（AUGMENTED CYCLIC ADVERSARIAL LEARNING FOR LOW RESOURCE DOMAIN ADAPTATION）</news:title>
   <news:publication_date>2026-05-21T23:54:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692843</loc>
  <lastmod>2026-05-21T23:54:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差別への勾配反転でつくる公正なニューラルネット（Gradient Reversal Against Discrimination）</news:title>
   <news:publication_date>2026-05-21T23:54:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692841</loc>
  <lastmod>2026-05-21T23:54:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実験物理に関する学生の見解とプロジェクト所有感の相関（Correlating students’ views about experimental physics with their sense of project ownership）</news:title>
   <news:publication_date>2026-05-21T23:54:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692839</loc>
  <lastmod>2026-05-21T23:53:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列・スケーラブルなベイズ最適化の新しいヒューリスティクス (New Heuristics for Parallel and Scalable Bayesian Optimization)</news:title>
   <news:publication_date>2026-05-21T23:53:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692837</loc>
  <lastmod>2026-05-21T23:02:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勝ち負けを超えて：逆強化学習による人間の動機と行動のモデリング (Beyond Winning and Losing: Modeling Human Motivations and Behaviors Using Inverse Reinforcement Learning)</news:title>
   <news:publication_date>2026-05-21T23:02:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692835</loc>
  <lastmod>2026-05-21T23:02:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様体仮説のマルチスケール検定のためのヒューリスティック枠組み（Heuristic Framework for Multi-Scale Testing of the Multi-Manifold Hypothesis）</news:title>
   <news:publication_date>2026-05-21T23:02:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692833</loc>
  <lastmod>2026-05-21T23:01:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SRAM内演算でBNNを高速化するXcel‑RAM（Xcel‑RAM: Accelerating Binary Neural Networks in High‑Throughput SRAM Compute Arrays）</news:title>
   <news:publication_date>2026-05-21T23:01:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692831</loc>
  <lastmod>2026-05-21T23:00:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動のサティスファイング尺度によるリスク評価と順位付け（Data-driven satisficing measure and ranking）</news:title>
   <news:publication_date>2026-05-21T23:00:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692829</loc>
  <lastmod>2026-05-21T23:00:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械工学教育におけるクラウド・モバイル利用の訓練（Mechanical Engineers’ Training in Using Cloud and Mobile Services in Professional Activity）</news:title>
   <news:publication_date>2026-05-21T23:00:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692827</loc>
  <lastmod>2026-05-21T23:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズに強くクリーンデータでも精度を落とさない敵対的学習の試み（Towards Adversarial Training with Moderate Performance Improvement for Neural Network Classification）</news:title>
   <news:publication_date>2026-05-21T23:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692825</loc>
  <lastmod>2026-05-21T22:59:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分離型データ駆動制御による確率的最適制御の実践（A Decoupled Data Based Control Approach to Stochastic Optimal Control Problems）</news:title>
   <news:publication_date>2026-05-21T22:59:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692823</loc>
  <lastmod>2026-05-21T22:08:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LiDARと単眼カメラからの自己教師付きSparse-to-Dense深度補完（Self-Supervised Sparse-to-Dense: Self-Supervised Depth Completion from LiDAR and Monocular Camera）</news:title>
   <news:publication_date>2026-05-21T22:08:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692821</loc>
  <lastmod>2026-05-21T22:00:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多フィールドカテゴリデータに対するProduct-based Neural Networksの要点解説（Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data）</news:title>
   <news:publication_date>2026-05-21T22:00:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692819</loc>
  <lastmod>2026-05-21T21:59:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称量子化による低ビットニューラルネットワークの効率化（SYQ: Learning Symmetric Quantization For Efficient Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-21T21:59:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692817</loc>
  <lastmod>2026-05-21T21:59:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチタスク生成的敵対ネットワークと共有メモリによるクロスドメイン協調制御（Multi-Task Generative Adversarial Nets with Shared Memory for Cross-Domain Coordination Control）</news:title>
   <news:publication_date>2026-05-21T21:59:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692815</loc>
  <lastmod>2026-05-21T21:58:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Blipparを用いた機械工学実習へのAR導入の実践（Using Blippar Augmented Reality Browser in the Practical Training of Mechanical Engineers）</news:title>
   <news:publication_date>2026-05-21T21:58:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692813</loc>
  <lastmod>2026-05-21T21:58:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解析関数に対する深層ニューラルネットワークの指数収束（Exponential Convergence of the Deep Neural Network Approximation for Analytic Functions）</news:title>
   <news:publication_date>2026-05-21T21:58:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692811</loc>
  <lastmod>2026-05-21T21:57:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律的ディープラーニング：画像分類のための遺伝的DCNN設計器（Autonomous Deep Learning: A Genetic DCNN Designer for Image Classification）</news:title>
   <news:publication_date>2026-05-21T21:57:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692809</loc>
  <lastmod>2026-05-21T21:06:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限記憶SR1を使ったトラストリージョン法による機械学習最適化の提案（Trust-Region Algorithms for Machine Learning Using Indefinite Hessian Approximations）</news:title>
   <news:publication_date>2026-05-21T21:06:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692807</loc>
  <lastmod>2026-05-21T20:59:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォトリアリスティックな映像のスタイル転送（Photorealistic Video Style Transfer）</news:title>
   <news:publication_date>2026-05-21T20:59:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692805</loc>
  <lastmod>2026-05-21T20:58:50Z</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、GAN、超解像を用いた画像圧縮の性能比較（Performance Comparison of Convolutional AutoEncoders, Generative Adversarial Networks and Super-Resolution for Image Compression）</news:title>
   <news:publication_date>2026-05-21T20:58:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692803</loc>
  <lastmod>2026-05-21T20:58:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジ向けニューロメモリスティブ回路のレビュー（Neuro-memristive Circuits for Edge Computing: A Review）</news:title>
   <news:publication_date>2026-05-21T20:58:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692801</loc>
  <lastmod>2026-05-21T20:57:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習の不確かさを正確にする較正回帰（Accurate Uncertainties for Deep Learning Using Calibrated Regression）</news:title>
   <news:publication_date>2026-05-21T20:57:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692799</loc>
  <lastmod>2026-05-21T20:57:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形システムにおける合成モデル下の学習理論（A Learning Theory in Linear Systems under Compositional Models）</news:title>
   <news:publication_date>2026-05-21T20:57:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692797</loc>
  <lastmod>2026-05-21T20:56:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的モデルに基づく最適化の実践と示唆（Stochastic model-based minimization under high-order growth）</news:title>
   <news:publication_date>2026-05-21T20:56:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692795</loc>
  <lastmod>2026-05-21T20:04:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トップロジー分類によるLHCリアルタイム選別の改善（Topology classification with deep learning to improve real-time event selection at the LHC）</news:title>
   <news:publication_date>2026-05-21T20:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692793</loc>
  <lastmod>2026-05-21T20:02:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プログラマーのアマニュエンシス（Amanuensis: The Programmer’s Apprentice）</news:title>
   <news:publication_date>2026-05-21T20:02:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692791</loc>
  <lastmod>2026-05-21T20:02:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散型データシャッフリングの基礎限界（Fundamental Limits of Decentralized Data Shuffling）</news:title>
   <news:publication_date>2026-05-21T20:02:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692789</loc>
  <lastmod>2026-05-21T20:02:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発話系対話システムにおけるドメイン分類とOOD検出の同時学習（Joint Learning of Domain Classification and Out-of-Domain Detection with Dynamic Class Weighting for Satisﬁcing False Acceptance Rates）</news:title>
   <news:publication_date>2026-05-21T20:02:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692787</loc>
  <lastmod>2026-05-21T20:02:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>完全非パラメトリックなベイズ加法回帰木（Fully Nonparametric Bayesian Additive Regression Trees）</news:title>
   <news:publication_date>2026-05-21T20:02:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692785</loc>
  <lastmod>2026-05-21T20:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と機械の学びを同時に改善する視座（Training Humans and Machines）</news:title>
   <news:publication_date>2026-05-21T20:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692783</loc>
  <lastmod>2026-05-21T20:01:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スラッグ星雲からの銀河間Hα検出（The Detection of Intergalactic Hα Emission from the Slug Nebula）</news:title>
   <news:publication_date>2026-05-21T20:01:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692781</loc>
  <lastmod>2026-05-21T19:09:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組み込み機での顔感情認識は何がネックか（It All Matters: Reporting Accuracy, Inference Time and Power Consumption for Face Emotion Recognition on Embedded Systems）</news:title>
   <news:publication_date>2026-05-21T19:09:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692779</loc>
  <lastmod>2026-05-21T18:59:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインSNSにおける友人関係強度の推定（Determination of friendship intensity between online social network users based on their interaction）</news:title>
   <news:publication_date>2026-05-21T18:59:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692777</loc>
  <lastmod>2026-05-21T18:58:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習における敵対的事例の特徴付けと分岐（Adversarial Examples in Deep Learning: Characterization and Divergence）</news:title>
   <news:publication_date>2026-05-21T18:58:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692775</loc>
  <lastmod>2026-05-21T18:58:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平性制約などの一般化を高める二データセット最適化（Training Well-Generalizing Classiﬁers for Fairness Metrics and Other Data-Dependent Constraints）</news:title>
   <news:publication_date>2026-05-21T18:58:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692773</loc>
  <lastmod>2026-05-21T18:57:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>塵と惑星の出会い：PDS 70系における惑星の軌道と大気の解明（Orbital and atmospheric characterization of the planet within the gap of the PDS 70 transition disk）</news:title>
   <news:publication_date>2026-05-21T18:57:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/692771</loc>
  <lastmod>2026-05-21T18:57:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>偏微分方程式を解くニューラルネットワークの層一般性の発見（Neural Networks Trained to Solve Differential Equations Learn General Representations）</news:title>
   <news:publication_date>2026-05-21T18:57:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/692769</loc>
  <lastmod>2026-05-21T18:57:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マゼラン系におけるType II セファイドのOGLEコレクション（The OGLE Collection of Variable Stars. Type II Cepheids in the Magellanic System）</news:title>
   <news:publication_date>2026-05-21T18:57:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/692767</loc>
  <lastmod>2026-05-21T18:06:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>形状事前知識を組み込んだ深層ネットワークによる核検出（DEEP NETWORKS WITH SHAPE PRIORS FOR NUCLEUS DETECTION）</news:title>
   <news:publication_date>2026-05-21T18:06:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/692765</loc>
  <lastmod>2026-05-21T18:05:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エントロピー経路に沿った結晶核形成の新しい見方（Crystal nucleation along an entropic pathway: Teaching liquids how to transition）</news:title>
   <news:publication_date>2026-05-21T18:05:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/692763</loc>
  <lastmod>2026-05-21T18:05:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダム化目的関数によるベイズ非パラメトリック学習（Nonparametric learning from Bayesian models with randomized objective functions）</news:title>
   <news:publication_date>2026-05-21T18:05:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/692761</loc>
  <lastmod>2026-05-21T18:04:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーグリッド上の高次元離散積分（High Dimensional Discrete Integration over the Hypergrid）</news:title>
   <news:publication_date>2026-05-21T18:04:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/692759</loc>
  <lastmod>2026-05-21T18:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TextWorld：テキストベースゲームの学習環境（TextWorld: A Learning Environment for Text-based Games）</news:title>
   <news:publication_date>2026-05-21T18:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692757</loc>
  <lastmod>2026-05-21T18:03:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子化された分散勾配降下法が示す通信効率の新基準（An Exact Quantized Decentralized Gradient Descent Algorithm）</news:title>
   <news:publication_date>2026-05-21T18:03:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692755</loc>
  <lastmod>2026-05-21T18:03:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチセンサーによる3D追跡のエンドツーエンド学習（End-to-end Learning of Multi-sensor 3D Tracking by Detection）</news:title>
   <news:publication_date>2026-05-21T18:03:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692753</loc>
  <lastmod>2026-05-21T17:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース三パラメータ制限付きインディアンビュッフェ過程による国際貿易データ解析（SPARSE THREE-PARAMETER RESTRICTED INDIAN BUFFET PROCESS FOR UNDERSTANDING INTERNATIONAL TRADE）</news:title>
   <news:publication_date>2026-05-21T17:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/692751</loc>
  <lastmod>2026-05-21T17:11:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小限情報で学ぶ連続ゲームの学習（Learning with Minimal Information in Continuous Games）</news:title>
   <news:publication_date>2026-05-21T17:11:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692749</loc>
  <lastmod>2026-05-21T17:11:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストベースのゲームで学ぶ探索と汎化の勘所（Counting to Explore and Generalize in Text-based Games）</news:title>
   <news:publication_date>2026-05-21T17:11:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692747</loc>
  <lastmod>2026-05-21T17:10:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ的反事実リスク最小化（Bayesian Counterfactual Risk Minimization）</news:title>
   <news:publication_date>2026-05-21T17:10:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692745</loc>
  <lastmod>2026-05-21T17:10:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep LearningとLHC物理解析の応用（Deep Learning and Its Application to LHC Physics）</news:title>
   <news:publication_date>2026-05-21T17:10:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692743</loc>
  <lastmod>2026-05-21T17:10:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフクラスタリング評価の新視点（Comparing Graph Clusterings: Set partition measures vs. Graph-aware measures）</news:title>
   <news:publication_date>2026-05-21T17:10:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692741</loc>
  <lastmod>2026-05-21T17:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再生時間に基づく音声対話システムのユーザー–エンティティ親和性モデル（Play Duration based User-Entity Affinity Modeling in Spoken Dialog System）</news:title>
   <news:publication_date>2026-05-21T17:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692739</loc>
  <lastmod>2026-05-21T16:18:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造を保つ完全畳み込みネットワークによる医用画像合成（SynNet: Structure-Preserving Fully Convolutional Networks for Medical Image Synthesis）</news:title>
   <news:publication_date>2026-05-21T16:18:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692737</loc>
  <lastmod>2026-05-21T16:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子コンピュータ上のベイジアン深層学習 (Bayesian Deep Learning on a Quantum Computer)</news:title>
   <news:publication_date>2026-05-21T16:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692735</loc>
  <lastmod>2026-05-21T16:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRFusionによるPANとMS画像融合による土地被覆マッピング（MRFusion: A Deep Learning architecture to fuse PAN and MS imagery for land cover mapping）</news:title>
   <news:publication_date>2026-05-21T16:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692733</loc>
  <lastmod>2026-05-21T16:17:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スペクトラルクラスタリングのグラフカット最適性保証（Certifying Global Optimality of Graph Cuts via Semidefinite Relaxation）</news:title>
   <news:publication_date>2026-05-21T16:17:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692731</loc>
  <lastmod>2026-05-21T16:17:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Grapevine: マルチ次元クラスタリングによるワイン推薦アルゴリズム（Grapevine: A Wine Prediction Algorithm Using Multi-dimensional Clustering Methods）</news:title>
   <news:publication_date>2026-05-21T16:17:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692729</loc>
  <lastmod>2026-05-21T16:16:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話の深層構造を発見するDiscourse-Wizard（Discourse-Wizard: Discovering Deep Discourse Structure in your Conversation with RNNs）</news:title>
   <news:publication_date>2026-05-21T16:16:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692727</loc>
  <lastmod>2026-05-21T16:16:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CPUでリアルタイムに近い単眼深度推定を可能にする軽量モデル（Towards real-time unsupervised monocular depth estimation on CPU）</news:title>
   <news:publication_date>2026-05-21T16:16:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692725</loc>
  <lastmod>2026-05-21T15:24:51Z</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の近似能力に関する理論的限界（Bounds on the Approximation Power of Feedforward Neural Networks）</news:title>
   <news:publication_date>2026-05-21T15:24:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692723</loc>
  <lastmod>2026-05-21T15:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一回の見本で学ぶジェスチャ認識の確率的手法（A Probabilistic Modeling Approach to One-Shot Gesture Recognition）</news:title>
   <news:publication_date>2026-05-21T15:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692721</loc>
  <lastmod>2026-05-21T15:23:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散表現（Distributional）と記号的（Symbolic）手法の比較研究（A Comparative Study of Distributional and Symbolic Paradigms for Relational Learning）</news:title>
   <news:publication_date>2026-05-21T15:23:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692719</loc>
  <lastmod>2026-05-21T15:23:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周辺分割可能な時空間モデルと逐次最尤推定の実務的意義（Marginally Parametrized Spatio-Temporal Models and Stepwise Maximum Likelihood Estimation）</news:title>
   <news:publication_date>2026-05-21T15:23:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692717</loc>
  <lastmod>2026-05-21T15:23:24Z</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一般化理論（Theory IIIb: Generalization in Deep Networks）</news:title>
   <news:publication_date>2026-05-21T15:23:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692715</loc>
  <lastmod>2026-05-21T15:23:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造変異を含むグラフからの学習 (Learning from graphs with structural variation)</news:title>
   <news:publication_date>2026-05-21T15:23:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692713</loc>
  <lastmod>2026-05-21T15:22:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANの収束問題の理論的整理（Convergence Problems with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-05-21T15:22:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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