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   <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>
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    <news:language>ja</news:language>
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   <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>
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   <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>
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    <news:language>ja</news:language>
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   <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>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <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>
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    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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  <lastmod>2026-05-23T06:27:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <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>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-05-23T05:34:00Z</lastmod>
  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>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>
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  <lastmod>2026-05-23T05:33:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Neural Processes（Neural Processes）</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>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>
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  <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>
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  <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>
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   <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>
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  <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>
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 <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>
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 <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>
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 <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>
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  <lastmod>2026-05-23T04:39:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <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>
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 <url>
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  <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>
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 <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>
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   <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>
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   <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>
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  <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>
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 </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>
   <news:title>HgCdTe APDアレイの天文応用（HgCdTe APD Arrays for Astronomy: Natural Guide Star Wavefront Sensing and Space Astronomy）</news:title>
   <news:publication_date>2026-05-22T08:59:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692986</loc>
  <lastmod>2026-05-22T08:57:36Z</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>2026-05-22T08:57:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692984</loc>
  <lastmod>2026-05-22T08:57:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低リソース環境での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>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692982</loc>
  <lastmod>2026-05-22T08:57:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>誤り訂正符号を用いたオンライントレーニングによるラベル回復（Online Label Recovery for Deep Learning-based Communication through Error Correcting Codes）</news:title>
   <news:publication_date>2026-05-22T08:57:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692980</loc>
  <lastmod>2026-05-22T08:57:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lipschitz連続性がGANにもたらす安定化効果（UNDERSTANDING THE EFFECTIVENESS OF LIPSCHITZ-CONTINUITY IN GENERATIVE ADVERSARIAL NETS）</news:title>
   <news:publication_date>2026-05-22T08:57:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692978</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アーチフィラメントの時間発展（Temporal evolution of arch filaments as seen in He i 10830 Å）</news:title>
   <news:publication_date>2026-05-22T08:04:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692976</loc>
  <lastmod>2026-05-22T08:04:34Z</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>2026-05-22T08:04:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692974</loc>
  <lastmod>2026-05-22T08:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相対的識別器：標準GANに欠けていた重要要素（The relativistic discriminator: a key element missing from standard GAN）</news:title>
   <news:publication_date>2026-05-22T08:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692972</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期的統計モデルによるマルチモーダル異常検知（CYCLOSTATIONARY STATISTICAL MODELS AND ALGORITHMS FOR ANOMALY DETECTION USING MULTI-MODAL DATA）</news:title>
   <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>
  <lastmod>2026-05-22T08:03:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Simulated Flying Shapes と Simulated Planar Manipulator データセットの紹介（Introducing the Simulated Flying Shapes and Simulated Planar Manipulator Datasets）</news:title>
   <news:publication_date>2026-05-22T08:03:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692968</loc>
  <lastmod>2026-05-22T08:03:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <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>
  <loc>https://aibr.jp/archives/692966</loc>
  <lastmod>2026-05-22T08:02:59Z</lastmod>
  <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>
  <loc>https://aibr.jp/archives/692964</loc>
  <lastmod>2026-05-22T07:11:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>普遍構造における有限大ラムジー次数（Finite big Ramsey degrees in universal structures）</news:title>
   <news:publication_date>2026-05-22T07:11:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692962</loc>
  <lastmod>2026-05-22T07:01:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>品詞タグ付けの改善：マルチタスク学習と文字レベル単語表現（IMPROVING PART-OF-SPEECH TAGGING VIA MULTI-TASK LEARNING AND CHARACTER-LEVEL WORD REPRESENTATIONS）</news:title>
   <news:publication_date>2026-05-22T07:01:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692960</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>乳房X線撮影の二面対応を学習するSiameseネットワーク（Mammography Dual View Mass Correspondence）</news:title>
   <news:publication_date>2026-05-22T07:00:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692958</loc>
  <lastmod>2026-05-22T07:00:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-05-22T07:00:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692956</loc>
  <lastmod>2026-05-22T06:59:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>限定的助言における容易なデータへの適応（Adaptation to Easy Data in Prediction with Limited Advice）</news:title>
   <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>
  <lastmod>2026-05-22T06:59:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Recurrent Spatial-Aware Networkによる群衆カウントの革新（Crowd Counting using Deep Recurrent Spatial-Aware Network）</news:title>
   <news:publication_date>2026-05-22T06:59:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692952</loc>
  <lastmod>2026-05-22T06:59:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダルな視点動画解析とMKLによる認識改善（Multi-modal Egocentric Activity Recognition using Audio-Visual Features）</news:title>
   <news:publication_date>2026-05-22T06:59:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692950</loc>
  <lastmod>2026-05-22T06:07:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル格子デコーダの基本と応用（NEURAL LATTICE DECODERS）</news:title>
   <news:publication_date>2026-05-22T06:07:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692948</loc>
  <lastmod>2026-05-22T06:07:26Z</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>2026-05-22T06:07:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692946</loc>
  <lastmod>2026-05-22T06:07:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロモルフィックデータを深層学習で分類する（Classifying neuromorphic data using a deep learning framework for image classification）</news:title>
   <news:publication_date>2026-05-22T06:07:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692944</loc>
  <lastmod>2026-05-22T06:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neuro-Symbolic Execution（Neuro-Symbolic Execution: The Feasibility of an Inductive Approach to Symbolic Execution）</news:title>
   <news:publication_date>2026-05-22T06:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692942</loc>
  <lastmod>2026-05-22T06:05:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要性重みでのスパース学習によるキーワードスポッティングの効率化（WEIGHT-IMPORTANCE SPARSE TRAINING IN KEYWORD SPOTTING）</news:title>
   <news:publication_date>2026-05-22T06:05:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692940</loc>
  <lastmod>2026-05-22T06:05:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係情報を取り込むメトリック学習の制約設計（Relational Constraints for Metric Learning on Relational Data）</news:title>
   <news:publication_date>2026-05-22T06:05:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692938</loc>
  <lastmod>2026-05-22T06:05:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推論・学習・母集団サイズ：SRLモデルにおけるプロジェクティビティ（Inference, Learning, and Population Size: Projectivity for SRL Models）</news:title>
   <news:publication_date>2026-05-22T06:05:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692936</loc>
  <lastmod>2026-05-22T05:13:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HiPERCAMのファーストライトが切り拓いた高速光学天文学（First light with HiPERCAM on the GTC）</news:title>
   <news:publication_date>2026-05-22T05:13:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692934</loc>
  <lastmod>2026-05-22T05:13:07Z</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>2026-05-22T05:13:07Z</news:publication_date>
   <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>
   <news:title>Studio2Shop: スタジオ写真から商品認識へ（Studio2Shop: from studio photo shoots to fashion articles）</news:title>
   <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>
  <lastmod>2026-05-22T05:12:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間制約を考慮した人の移動データのクラスタリング（Clustering with Temporal Constraints on Spatio-Temporal Data of Human Mobility）</news:title>
   <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>
   <news:title>強力で可変な降着円盤風の新たな候補 — 銀河MCG-03-58-007の場合 (A new powerful and highly variable disk wind in an AGN-star forming galaxy, the case of MCG-03-58-007)</news:title>
   <news:publication_date>2026-05-22T05:11:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692926</loc>
  <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>
  <loc>https://aibr.jp/archives/692922</loc>
  <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>
  <loc>https://aibr.jp/archives/692920</loc>
  <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>
   <news:title>文脈化された場面モデリングと生成的推論（COSMO: Contextualized Scene Modeling with Boltzmann Machines）</news:title>
   <news:publication_date>2026-05-22T04:18:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692918</loc>
  <lastmod>2026-05-22T04:18:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分布適応における重み付き平衡手法（Balanced Distribution Adaptation）</news:title>
   <news:publication_date>2026-05-22T04:18:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </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>
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   <news:genres>Blog</news:genres>
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 </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>
  </news:news>
 </url>
 <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>
 </url>
 <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>
  </news:news>
 </url>
 <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>
  </news:news>
 </url>
 <url>
  <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>
  </news:news>
 </url>
 <url>
  <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>
  </news:news>
 </url>
 <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>
 </url>
 <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>
 </url>
 <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>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692711</loc>
  <lastmod>2026-05-21T14:31:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無人機画像における哺乳類検出の実践的手法（Detecting Mammals in UAV Images: Best Practices to address a substantially Imbalanced Dataset with Deep Learning）</news:title>
   <news:publication_date>2026-05-21T14:31:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692709</loc>
  <lastmod>2026-05-21T14:31:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競技会で使える合成データの質評価法（Measuring the quality of Synthetic data for use in competitions）</news:title>
   <news:publication_date>2026-05-21T14:31:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692707</loc>
  <lastmod>2026-05-21T14:30:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アミノ酸配列からタンパク質可溶性を予測する機械学習モデル（Develop machine learning based predictive models for engineering protein solubility）</news:title>
   <news:publication_date>2026-05-21T14:30:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692705</loc>
  <lastmod>2026-05-21T14:29:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複合モーダル衣服設計の共有潜在空間学習（Learning a Shared Shape Space for Multimodal Garment Design）</news:title>
   <news:publication_date>2026-05-21T14:29:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692703</loc>
  <lastmod>2026-05-21T14:29:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔軟な教師なし〜弱教師あり学習で行動検出を学ぶ（A flexible model for training action localization with varying levels of supervision）</news:title>
   <news:publication_date>2026-05-21T14:29:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692701</loc>
  <lastmod>2026-05-21T14:29:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元正式表現による概念空間の量子的性質（Quantum aspects of high dimensional formal representation of conceptual spaces）</news:title>
   <news:publication_date>2026-05-21T14:29:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692699</loc>
  <lastmod>2026-05-21T14:28:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランキングモデルの事後解釈可能性と二次学習データの活用（Posthoc Interpretability of Learning to Rank Models using Secondary Training Data）</news:title>
   <news:publication_date>2026-05-21T14:28:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692697</loc>
  <lastmod>2026-05-21T13:37:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在クラス文脈異常の無監督検出と説明（Unsupervised Detection and Explanation of Latent-class Contextual Anomalies）</news:title>
   <news:publication_date>2026-05-21T13:37:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692695</loc>
  <lastmod>2026-05-21T13:37:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Twitterにおけるフェイクニュース検出（Fake News Identification on Twitter with Hybrid CNN and RNN Models）</news:title>
   <news:publication_date>2026-05-21T13:37:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692693</loc>
  <lastmod>2026-05-21T13:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストから対応する画像を生成する改良GAN-CLS手法（Generate the corresponding Image from Text Description using Modified GAN-CLS Algorithm）</news:title>
   <news:publication_date>2026-05-21T13:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692691</loc>
  <lastmod>2026-05-21T13:36:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意味解釈と談話構造におけるバイアスのモデル化（Bias in Semantic and Discourse Interpretation）</news:title>
   <news:publication_date>2026-05-21T13:36:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692689</loc>
  <lastmod>2026-05-21T13:36:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一変量混合分布間のトータル・バリエーションに関する決定論的境界の保証（Guaranteed Deterministic Bounds on the Total Variation Distance between Univariate Mixtures）</news:title>
   <news:publication_date>2026-05-21T13:36:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692687</loc>
  <lastmod>2026-05-21T13:36:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数生体信号からの頑健な心拍検出（Robust Heartbeat Detection from Multimodal Data via CNN-based Generalizable Information Fusion）</news:title>
   <news:publication_date>2026-05-21T13:36:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692685</loc>
  <lastmod>2026-05-21T13:36:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件変化に不変な空間の発掘（Excavate Condition-invariant Space by Intrinsic Encoder）</news:title>
   <news:publication_date>2026-05-21T13:36:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692683</loc>
  <lastmod>2026-05-21T12:45:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速動的畳み込みニューラルネットワークによる視覚トラッキングの実務的意義（Fast Dynamic Convolutional Neural Networks for Visual Tracking）</news:title>
   <news:publication_date>2026-05-21T12:45:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692681</loc>
  <lastmod>2026-05-21T12:45:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>粗から細への再帰的改良による高精度セマンティックセグメンテーション（Gated Feedback Refinement Network for Coarse-to-Fine Dense Semantic Image Labeling）</news:title>
   <news:publication_date>2026-05-21T12:45:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692679</loc>
  <lastmod>2026-05-21T12:44:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深度映像におけるマルチビュー動的画像による行動認識（Action Recognition for Depth Video using Multi-view Dynamic Images）</news:title>
   <news:publication_date>2026-05-21T12:44:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692677</loc>
  <lastmod>2026-05-21T12:44:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観察からのワンショット学習による多段階タスク習得（One-Shot Learning of Multi-Step Tasks from Observation via Activity Localization in Auxiliary Video）</news:title>
   <news:publication_date>2026-05-21T12:44:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692675</loc>
  <lastmod>2026-05-21T12:44:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間行動認識と予測に関する総説（Human Action Recognition and Prediction: A Survey）</news:title>
   <news:publication_date>2026-05-21T12:44:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692673</loc>
  <lastmod>2026-05-21T12:44:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集合的判断に基づくオープンセット認識の枠組み（Collective Decision for Open Set Recognition）</news:title>
   <news:publication_date>2026-05-21T12:44:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692671</loc>
  <lastmod>2026-05-21T12:43:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>XGBoostのGPU並列化が切り拓いた大規模学習の時短（XGBoost: Scalable GPU Accelerated Learning）</news:title>
   <news:publication_date>2026-05-21T12:43:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692669</loc>
  <lastmod>2026-05-21T11:52:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模な品揃え生成のためのマルチモーダル推薦（A Multimodal Recommender System for Large-scale Assortment Generation in E-commerce）</news:title>
   <news:publication_date>2026-05-21T11:52:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692667</loc>
  <lastmod>2026-05-21T11:51:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測区間を狭める新しい損失関数：Expanded Interval Minimization（Tight Prediction Intervals Using Expanded Interval Minimization）</news:title>
   <news:publication_date>2026-05-21T11:51:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692665</loc>
  <lastmod>2026-05-21T11:51:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Subject2Vec: 画像パッチ集合から患者レベルの表現を作る手法（Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector）</news:title>
   <news:publication_date>2026-05-21T11:51:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692663</loc>
  <lastmod>2026-05-21T11:51:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮センシングMRI再構成の敵対的・知覚的洗練（Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction）</news:title>
   <news:publication_date>2026-05-21T11:51:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692661</loc>
  <lastmod>2026-05-21T11:51:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロキシによる公平性改善の実務的提案（Proxy Fairness）</news:title>
   <news:publication_date>2026-05-21T11:51:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692659</loc>
  <lastmod>2026-05-21T11:50:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多視点生成のための完全な表現学習（CR-GAN: Learning Complete Representations for Multi-view Generation）</news:title>
   <news:publication_date>2026-05-21T11:50:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692657</loc>
  <lastmod>2026-05-21T11:50:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>途中停止で速くするアンサンブル評価（Quit When You Can: Efficient Evaluation of Ensembles with Ordering Optimization）</news:title>
   <news:publication_date>2026-05-21T11:50:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692655</loc>
  <lastmod>2026-05-21T10:59:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号付き粒子とニューラルネットワークを組み合わせた量子系シミュレーション高速化（Combining neural networks and signed particles to simulate quantum systems more efficiently, Part III）</news:title>
   <news:publication_date>2026-05-21T10:59:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692653</loc>
  <lastmod>2026-05-21T10:59:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GenerationMania: 音楽からゲーム譜面を自動生成する手法の要点（GenerationMania: Learning to Semantically Choreograph）</news:title>
   <news:publication_date>2026-05-21T10:59:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692651</loc>
  <lastmod>2026-05-21T10:58:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>L2正則化の新たな視点（A New Angle on L2 Regularization）</news:title>
   <news:publication_date>2026-05-21T10:58:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692649</loc>
  <lastmod>2026-05-21T10:58:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットワークの敵対的再プログラミング（ADVERSARIAL REPROGRAMMING OF NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-05-21T10:58:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692647</loc>
  <lastmod>2026-05-21T10:58:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一指数潜在変数モデルによるネットワークトポロジー推定（Single Index Latent Variable Models for Network Topology Inference）</news:title>
   <news:publication_date>2026-05-21T10:58:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692645</loc>
  <lastmod>2026-05-21T10:58:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習管理システム（LMS）から教育用デジタルプラットフォームへ（Toward modern educational IT-ecosystems: from learning management systems to digital platforms）</news:title>
   <news:publication_date>2026-05-21T10:58:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692643</loc>
  <lastmod>2026-05-21T10:57:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱アノテーションで実現する3D医用画像のインスタンスセグメンテーション（Deep Learning Based Instance Segmentation in 3D Biomedical Images Using Weak Annotation）</news:title>
   <news:publication_date>2026-05-21T10:57:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692641</loc>
  <lastmod>2026-05-21T10:06:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移学習と画像カテゴリ発見のための確率的制約付きクラスタリング（A probabilistic constrained clustering for transfer learning and image category discovery）</news:title>
   <news:publication_date>2026-05-21T10:06:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692639</loc>
  <lastmod>2026-05-21T09:57:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習者英語のCEFRLレベル予測──メトリクスと全文から読み解く言語力の定量化（Predicting CEFRL levels in learner English on the basis of metrics and full texts）</news:title>
   <news:publication_date>2026-05-21T09:57:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692637</loc>
  <lastmod>2026-05-21T09:57:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然画像パッチの教師なし学習（Unsupervised Natural Image Patch Learning）</news:title>
   <news:publication_date>2026-05-21T09:57:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692635</loc>
  <lastmod>2026-05-21T09:57:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸クラスタリングで木構造を復元する（Recovering Trees with Convex Clustering）</news:title>
   <news:publication_date>2026-05-21T09:57:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692633</loc>
  <lastmod>2026-05-21T09:56:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習サービスにおけるメンバーシップ推測攻撃の解明（Demystifying Membership Inference Attacks in Machine Learning as a Service）</news:title>
   <news:publication_date>2026-05-21T09:56:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692631</loc>
  <lastmod>2026-05-21T09:56:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所相関分光の深層学習による高速化と定量化（Acceleration and Quantitation of Localized Correlated Spectroscopy using Deep Learning: A Pilot Simulation Study）</news:title>
   <news:publication_date>2026-05-21T09:56:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692629</loc>
  <lastmod>2026-05-21T09:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ファッション性（Style Quotient）で読み解く売上の本質（Understanding Fashionability: What drives sales of a style?）</news:title>
   <news:publication_date>2026-05-21T09:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692627</loc>
  <lastmod>2026-05-21T09:04:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュートリノ質量の順序問題—振動から宇宙観測まで（Neutrino Mass Ordering from Oscillations and Beyond: 2018 Status and Future Prospects）</news:title>
   <news:publication_date>2026-05-21T09:04:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692625</loc>
  <lastmod>2026-05-21T09:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ペルセウス銀河団の深いガンマ線観測による暗黒物質寿命制約（Constraining Dark Matter lifetime with a deep gamma-ray survey of the Perseus Galaxy Cluster with MAGIC）</news:title>
   <news:publication_date>2026-05-21T09:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692623</loc>
  <lastmod>2026-05-21T09:03:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SAGAの直接加速とSampled Negative Momentum（Direct Acceleration of SAGA using Sampled Negative Momentum）</news:title>
   <news:publication_date>2026-05-21T09:03:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692621</loc>
  <lastmod>2026-05-21T09:03:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンドツーエンド深層模倣学習によるロボットサッカーの事例研究（End-to-End Deep Imitation Learning: Robot Soccer）</news:title>
   <news:publication_date>2026-05-21T09:03:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692619</loc>
  <lastmod>2026-05-21T09:02:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Network Cognitive Engineによる自律分散型アンダーレイ周波数共有の実現（Neural Network Cognitive Engine for Autonomous and Distributed Underlay Dynamic Spectrum Access）</news:title>
   <news:publication_date>2026-05-21T09:02:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692617</loc>
  <lastmod>2026-05-21T09:02:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>湿潤対流の機械学習パラメータ化の可能性（Using machine learning to parameterize moist convection）</news:title>
   <news:publication_date>2026-05-21T09:02:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692615</loc>
  <lastmod>2026-05-21T09:02:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Web検索における日常的学習の検出と支援（Detecting, Understanding and Supporting Everyday Learning in Web Search）</news:title>
   <news:publication_date>2026-05-21T09:02:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692613</loc>
  <lastmod>2026-05-21T08:10:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>αβ T細胞受容体の起源を定量化する研究（Genesis of the αβ T-cell receptor）</news:title>
   <news:publication_date>2026-05-21T08:10:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692611</loc>
  <lastmod>2026-05-21T08:10:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化されたPD-L1腫瘍細胞スコアリングの半教師あり生成学習（Deep Semi Supervised Generative Learning for Automated PD-L1 Tumor Cell Scoring on NSCLC Tissue Needle Biopsies）</news:title>
   <news:publication_date>2026-05-21T08:10:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692609</loc>
  <lastmod>2026-05-21T08:10:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速収束を実現する単純確率的分散削減アルゴリズム（A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates）</news:title>
   <news:publication_date>2026-05-21T08:10:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692607</loc>
  <lastmod>2026-05-21T08:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外観と形状の結合モデルによる頑健な姿勢追跡（Robust pose tracking with a joint model of appearance and shape）</news:title>
   <news:publication_date>2026-05-21T08:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692605</loc>
  <lastmod>2026-05-21T08:09:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習されたモーメント法による暗黙的生成モデル学習（Learning Implicit Generative Models with the Method of Learned Moments）</news:title>
   <news:publication_date>2026-05-21T08:09:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692603</loc>
  <lastmod>2026-05-21T08:09:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PCアルゴリズムのハイパーパラメータをベイズ最適化で自動化する（Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks）</news:title>
   <news:publication_date>2026-05-21T08:09:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692601</loc>
  <lastmod>2026-05-21T08:08:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LiDARとマルチスペクトル画像の統合による露出および地震脆弱性推定（Integration of LiDAR and multispectral images for exposure and earthquake vulnerability estimation）</news:title>
   <news:publication_date>2026-05-21T08:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692599</loc>
  <lastmod>2026-05-21T07:17:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固体中の核スピン集合体を制御する量子ダイナミクスによる機械学習（Machine learning with controllable quantum dynamics of a nuclear spin ensemble in a solid）</news:title>
   <news:publication_date>2026-05-21T07:17:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692597</loc>
  <lastmod>2026-05-21T07:17:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OpenML上での機械学習実験の自動探索（Automatic Exploration of Machine Learning Experiments on OpenML）</news:title>
   <news:publication_date>2026-05-21T07:17:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692595</loc>
  <lastmod>2026-05-21T07:16:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像のかすみ（ヘイズ）除去における深層学習の比較と解析（Deep learning for dehazing: Comparison and analysis）</news:title>
   <news:publication_date>2026-05-21T07:16:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692593</loc>
  <lastmod>2026-05-21T07:15:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスタからクエリへ：モジュラリティ景観の不確実性を活用する（From clusters to queries: exploiting uncertainty in the modularity landscape of complex networks）</news:title>
   <news:publication_date>2026-05-21T07:15:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692591</loc>
  <lastmod>2026-05-21T07:15:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超周辺（ultra-peripheral）p↑A衝突における単一スピン非対称性の新しい観察手段（Single spin asymmetries in ultra-peripheral p↑A collisions）</news:title>
   <news:publication_date>2026-05-21T07:15:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692589</loc>
  <lastmod>2026-05-21T07:15:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>極端に狭いResNetが持つ表現力の再評価（ResNet with one-neuron hidden layers is a Universal Approximator）</news:title>
   <news:publication_date>2026-05-21T07:15:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692587</loc>
  <lastmod>2026-05-21T07:15:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビジネス分析とオペレーションズリサーチにおける深層学習（Deep learning in business analytics and operations research: Models, applications and managerial implications）</news:title>
   <news:publication_date>2026-05-21T07:15:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692585</loc>
  <lastmod>2026-05-21T06:23:32Z</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>2026-05-21T06:23:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692583</loc>
  <lastmod>2026-05-21T06:23:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴選択による教師なしドメイン適応と最適輸送（Feature Selection for Unsupervised Domain Adaptation using Optimal Transport）</news:title>
   <news:publication_date>2026-05-21T06:23:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692581</loc>
  <lastmod>2026-05-21T06:22:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNベースのワードスポッティング向けアーキテクチャ探索（Exploring Architectures for CNN-Based Word Spotting）</news:title>
   <news:publication_date>2026-05-21T06:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692579</loc>
  <lastmod>2026-05-21T06:22:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepSDCS: Ki67染色スライドのがん増殖多様性解析（DeepSDCS: Dissecting cancer proliferation heterogeneity in Ki67 digital whole slide images）</news:title>
   <news:publication_date>2026-05-21T06:22:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692577</loc>
  <lastmod>2026-05-21T06:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Grassmannian Discriminant Maps による多様体次元削減と画像セット分類への応用（Grassmannian Discriminant Maps (GDM) for Manifold Dimensionality Reduction with Application to Image Set Classification）</news:title>
   <news:publication_date>2026-05-21T06:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692575</loc>
  <lastmod>2026-05-21T06:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模過負荷MIMO検出におけるデータ駆動型反復法の提案（Deep Learning-Aided Projected Gradient Detector for Massive Overloaded MIMO Channels）</news:title>
   <news:publication_date>2026-05-21T06:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692573</loc>
  <lastmod>2026-05-21T06:21:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成モデルを判定モデルで評価する手法（Training Discriminative Models to Evaluate Generative Ones）</news:title>
   <news:publication_date>2026-05-21T06:21:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692571</loc>
  <lastmod>2026-05-21T05:30:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>出力ラベルを低次元に埋めることで学習が速くなる（Beyond One-hot Encoding: lower dimensional target embedding）</news:title>
   <news:publication_date>2026-05-21T05:30:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692569</loc>
  <lastmod>2026-05-21T05:30:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層型強化学習と仮説的（アブダクティブ）計画の統合（Hierarchical Reinforcement Learning with Abductive Planning）</news:title>
   <news:publication_date>2026-05-21T05:30:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692567</loc>
  <lastmod>2026-05-21T05:30:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Switchable Normalization（Differentiable Learning-to-Normalize via Switchable Normalization）</news:title>
   <news:publication_date>2026-05-21T05:30:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692565</loc>
  <lastmod>2026-05-21T05:29:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAV通信ネットワークにおけるロバスト・ファジー学習による部分重畳チャネル割り当て（Robust Fuzzy-Learning For Partially Overlapping Channels Allocation In UAV Communication Networks）</news:title>
   <news:publication_date>2026-05-21T05:29:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692563</loc>
  <lastmod>2026-05-21T05:29:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次凸近似による非凸正則化を伴うスパース信号推定アルゴリズム（Successive Convex Approximation Algorithms for Sparse Signal Estimation with Nonconvex Regularizations）</news:title>
   <news:publication_date>2026-05-21T05:29:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692561</loc>
  <lastmod>2026-05-21T05:29:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態認識型アンチドリフト相関追跡（State-aware Anti-drift Robust Correlation Tracking）</news:title>
   <news:publication_date>2026-05-21T05:29:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692559</loc>
  <lastmod>2026-05-21T05:29:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能性手法のベンチマーク（A Benchmark for Interpretability Methods in Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-21T05:29:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692557</loc>
  <lastmod>2026-05-21T04:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内視鏡画像を使った登録アルゴリズムの自動初期化に向けて（Towards automatic initialization of registration algorithms using simulated endoscopy images）</news:title>
   <news:publication_date>2026-05-21T04:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692555</loc>
  <lastmod>2026-05-21T04:38:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈付きバンディットと代替損失による境界と効率的アルゴリズム（Contextual bandits with surrogate losses: Margin bounds and efficient algorithms）</news:title>
   <news:publication_date>2026-05-21T04:38:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692553</loc>
  <lastmod>2026-05-21T04:37:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生涯学習としての意味の計算理論（A Computational Theory for Life-Long Learning of Semantics）</news:title>
   <news:publication_date>2026-05-21T04:37:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692551</loc>
  <lastmod>2026-05-21T04:37:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手続き型レベル生成による深層強化学習の汎化の解明（Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation）</news:title>
   <news:publication_date>2026-05-21T04:37:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692549</loc>
  <lastmod>2026-05-21T04:36:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エミュレーションシーケンス学習による堅牢なニューラルマルウェア検出モデル（Robust Neural Malware Detection Models for Emulation Sequence Learning）</news:title>
   <news:publication_date>2026-05-21T04:36:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692547</loc>
  <lastmod>2026-05-21T04:36:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リスク回避的推定の公理的アプローチとWallace–Freeman推定の正当化（Risk-averse estimation, an axiomatic approach to inference, and Wallace-Freeman without MML）</news:title>
   <news:publication_date>2026-05-21T04:36:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692545</loc>
  <lastmod>2026-05-21T04:36:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不確実性を伴う深層エコー状態ネットワークによる時空間予測（Deep Echo State Networks with Uncertainty Quantification for Spatio-Temporal Forecasting）</news:title>
   <news:publication_date>2026-05-21T04:36:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692543</loc>
  <lastmod>2026-05-21T03:44:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep CNN Denoiserと多層Neighbor Component Embeddingによる顔ハリュシネーション（Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination）</news:title>
   <news:publication_date>2026-05-21T03:44:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692541</loc>
  <lastmod>2026-05-21T03:44:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類器の位相的正則化（A Topological Regularizer for Classiﬁers via Persistent Homology）</news:title>
   <news:publication_date>2026-05-21T03:44:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692539</loc>
  <lastmod>2026-05-21T03:44:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>獣医臨床ノートから診断を推定するDeepTagの考え方（DeepTag: inferring diagnoses from clinical notes in under-resourced medical domain）</news:title>
   <news:publication_date>2026-05-21T03:44:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692537</loc>
  <lastmod>2026-05-21T03:44:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造学習の分解法が示す経営的インパクト（Decomposition of structural learning about directed acyclic graphs）</news:title>
   <news:publication_date>2026-05-21T03:44:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692535</loc>
  <lastmod>2026-05-21T03:43:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関係データに対する経験的リスク最小化と確率的勾配降下法（Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data）</news:title>
   <news:publication_date>2026-05-21T03:43:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692533</loc>
  <lastmod>2026-05-21T03:43:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の補間スプラインがデータ解析を変える（Interpolating splines on graphs for data science applications）</news:title>
   <news:publication_date>2026-05-21T03:43:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692531</loc>
  <lastmod>2026-05-21T03:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Gradient Similarityによる敵対的攻撃検出（Gradient Similarity: An Explainable Approach to Detect Adversarial Attacks against Deep Learning）</news:title>
   <news:publication_date>2026-05-21T03:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692529</loc>
  <lastmod>2026-05-21T02:52:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非結合アイソトニック回帰と最小ワッサースタイン復元（Uncoupled Isotonic Regression via Minimum Wasserstein Deconvolution）</news:title>
   <news:publication_date>2026-05-21T02:52:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692527</loc>
  <lastmod>2026-05-21T02:52:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚情報と地図データで自転車経路を評価する手法（Bicycle Route Attractiveness from Street View and OpenStreetMap）</news:title>
   <news:publication_date>2026-05-21T02:52:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692525</loc>
  <lastmod>2026-05-21T02:52:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sivers関数の抽出とSIDISのTMD物理信号の評価 (Assessing signals of TMD physics in SIDIS azimuthal asymmetries and in the extraction of the Sivers function)</news:title>
   <news:publication_date>2026-05-21T02:52:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692523</loc>
  <lastmod>2026-05-21T02:51:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ効率の良いリソグラフィモデリング（Data Efficient Lithography Modeling with Transfer Learning and Active Data Selection）</news:title>
   <news:publication_date>2026-05-21T02:51:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692521</loc>
  <lastmod>2026-05-21T02:51:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習によるモデル予測制御則の効率的表現と近似（Efficient Representation and Approximation of Model Predictive Control Laws via Deep Learning）</news:title>
   <news:publication_date>2026-05-21T02:51:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692519</loc>
  <lastmod>2026-05-21T02:51:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークプリンター攻撃の行動分析と検出の枠組み（PIDS: A Behavioral Framework for Analysis and Detection of Network Printer Attacks）</news:title>
   <news:publication_date>2026-05-21T02:51:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692517</loc>
  <lastmod>2026-05-21T02:51:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二峰性を示すCa豊富ギャップ過渡現象 iPTF 16hgs の発見と示唆（Double-peaked Ca-rich gap transient iPTF 16hgs）</news:title>
   <news:publication_date>2026-05-21T02:51:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692515</loc>
  <lastmod>2026-05-21T02:00:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>識別器の近似能力がGANの多様性を保証する（Approximability of Discriminators Implies Diversity in GANs）</news:title>
   <news:publication_date>2026-05-21T02:00:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692513</loc>
  <lastmod>2026-05-21T01:59:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルライブ配信における成人向けコンテンツの実態（Adult content in Social Live Streaming Services: Characterizing deviant users and relationships）</news:title>
   <news:publication_date>2026-05-21T01:59:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692511</loc>
  <lastmod>2026-05-21T01:59:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>この画像はあの部分に似ている、と説明するAI（This Looks Like That: Deep Learning for Interpretable Image Recognition）</news:title>
   <news:publication_date>2026-05-21T01:59:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692509</loc>
  <lastmod>2026-05-21T01:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高スループット同定を加速する能動学習による原子間ポテンシャル取得手法（Accelerating high-throughput searches for new alloys with active learning of interatomic potentials）</news:title>
   <news:publication_date>2026-05-21T01:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692507</loc>
  <lastmod>2026-05-21T01:58:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>すべての画素を活かす：ホリスティック3D運動理解による教師なし形状学習（Every Pixel Counts: Unsupervised Geometry Learning with Holistic 3D Motion Understanding）</news:title>
   <news:publication_date>2026-05-21T01:58:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692505</loc>
  <lastmod>2026-05-21T01:58:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽におけるメジャー感の知覚モデル化（Modeling Majorness as a Perceptual Property in Music from Listener Ratings）</news:title>
   <news:publication_date>2026-05-21T01:58:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692503</loc>
  <lastmod>2026-05-21T01:57:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>V4046 Sgrを巡るサブアーク秒ALMA分子線イメージング調査（A Subarcsecond ALMA Molecular Line Imaging Survey of the Circumbinary, Protoplanetary Disk Orbiting V4046 Sgr）</news:title>
   <news:publication_date>2026-05-21T01:57:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692501</loc>
  <lastmod>2026-05-21T01:06:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>絡み合いとカオスを解きほぐす（Untangling entanglement and chaos）</news:title>
   <news:publication_date>2026-05-21T01:06:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692499</loc>
  <lastmod>2026-05-21T01:05:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>等方性Vlasov物質の低圧静的解の一意性（UNIQUENESS OF STATIC, ISOTROPIC LOW-PRESSURE SOLUTIONS OF THE EINSTEIN-VLASOV SYSTEM）</news:title>
   <news:publication_date>2026-05-21T01:05:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692497</loc>
  <lastmod>2026-05-21T01:05:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワンビット通知で最適なタスク割振りを学ぶ（ONLINE OPTIMAL TASK OFFLOADING WITH ONE-BIT FEEDBACK）</news:title>
   <news:publication_date>2026-05-21T01:05:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692495</loc>
  <lastmod>2026-05-21T01:04:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生波形を直接処理する音声デノイジングの革新（Speech Denoising with Deep Feature Losses）</news:title>
   <news:publication_date>2026-05-21T01:04:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692493</loc>
  <lastmod>2026-05-21T01:04:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無線メッシュネットワークにおける機械学習の概観（An Overview of Machine Learning Approaches in Wireless Mesh Networks）</news:title>
   <news:publication_date>2026-05-21T01:04:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692491</loc>
  <lastmod>2026-05-21T01:03:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイモンの量子アルゴリズムを学習する（Learning Simon’s quantum algorithm）</news:title>
   <news:publication_date>2026-05-21T01:03:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692489</loc>
  <lastmod>2026-05-21T01:03:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クエリ構築と合成のためのニューラル機械翻訳（Neural Machine Translation for Query Construction and Composition）</news:title>
   <news:publication_date>2026-05-21T01:03:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692487</loc>
  <lastmod>2026-05-21T00:11:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LPRNetによる自動ナンバープレート認識（LPRNet: License Plate Recognition via Deep Neural Networks）</news:title>
   <news:publication_date>2026-05-21T00:11:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692485</loc>
  <lastmod>2026-05-21T00:11:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ピクセルから学ぶ深層ステガノ解析（Deep Steganalysis: End-to-End Learning with Supervisory Information beyond Class Labels）</news:title>
   <news:publication_date>2026-05-21T00:11:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692483</loc>
  <lastmod>2026-05-21T00:11:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間圧縮による静的内部表象が示す認知上の時間圧縮（STATIC INTERNAL REPRESENTATION OF DYNAMIC SITUATIONS REVEALS TIME COMPACTION IN HUMAN COGNITION）</news:title>
   <news:publication_date>2026-05-21T00:11:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692481</loc>
  <lastmod>2026-05-21T00:10:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列スパイク列のオンライン学習と認識を可能にする神経模倣システム（A neuro-inspired system for online learning and recognition of parallel spike trains, based on spike latency and heterosynaptic STDP）</news:title>
   <news:publication_date>2026-05-21T00:10:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692479</loc>
  <lastmod>2026-05-21T00:10:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネステッドロジットモデル下の動的品揃え最適化（Dynamic Assortment Planning Under Nested Logit Models）</news:title>
   <news:publication_date>2026-05-21T00:10:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692477</loc>
  <lastmod>2026-05-21T00:10:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡散MRIに基づく軽度外傷性脳損傷の検出（MTBI Identification From Diffusion MR Images Using Bag of Adversarial Visual Features）</news:title>
   <news:publication_date>2026-05-21T00:10:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692475</loc>
  <lastmod>2026-05-21T00:10:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プレプリント分類と研究動向の整理（ArXiv Categories and Trends）</news:title>
   <news:publication_date>2026-05-21T00:10:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692473</loc>
  <lastmod>2026-05-20T23:19:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈可能な原子系ニューラルネットワークから得られる量子化学的知見（Quantum-chemical insights from interpretable atomistic neural networks）</news:title>
   <news:publication_date>2026-05-20T23:19:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692471</loc>
  <lastmod>2026-05-20T23:19:16Z</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3Dシーン探索のための視点有用性予測（Learn-to-Score: Efficient 3D Scene Exploration by Predicting View Utility）</news:title>
   <news:publication_date>2026-05-20T23:19:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692469</loc>
  <lastmod>2026-05-20T23:18:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚に基づく意味学習（Learning Visually-Grounded Semantics from Contrastive Adversarial Samples）</news:title>
   <news:publication_date>2026-05-20T23:18:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692467</loc>
  <lastmod>2026-05-20T23:18:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MONAS: マルチ目的ニューラルアーキテクチャ探索の実務的意義（MONAS: Multi-Objective Neural Architecture Search）</news:title>
   <news:publication_date>2026-05-20T23:18:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692465</loc>
  <lastmod>2026-05-20T23:17:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習ベース通信の一般化データ表現と訓練性能解析（A Generalized Data Representation and Training-Performance Analysis for Deep Learning-Based Communications Systems）</news:title>
   <news:publication_date>2026-05-20T23:17:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692463</loc>
  <lastmod>2026-05-20T23:17:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>食事画像から栄養評価を一気通貫で行う多目的学習（A Multi-Task Learning Approach for Meal Assessment）</news:title>
   <news:publication_date>2026-05-20T23:17:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692461</loc>
  <lastmod>2026-05-20T23:17:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D RoI対応U-Netによる高精度かつ高効率な結直腸腫瘍分割（3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation）</news:title>
   <news:publication_date>2026-05-20T23:17:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692459</loc>
  <lastmod>2026-05-20T22:25:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ニューラルネットワークの事後分布を圧縮する技術（Adversarial Posterior Distillation）</news:title>
   <news:publication_date>2026-05-20T22:25:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692457</loc>
  <lastmod>2026-05-20T22:25:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepObfuscationによるCNN構造保護（DeepObfuscation: Securing the Structure of Convolutional Neural Networks via Knowledge Distillation）</news:title>
   <news:publication_date>2026-05-20T22:25:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692455</loc>
  <lastmod>2026-05-20T22:25:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続自己位置推定を自己教師ありで高精度に学習する手法（CeMNet: Self-supervised learning for accurate continuous ego-motion estimation）</news:title>
   <news:publication_date>2026-05-20T22:25:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692453</loc>
  <lastmod>2026-05-20T22:24:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的価格市場における電解槽の最適スケジューリング（Optimal Scheduling of Electrolyzer in Power Market with Dynamic Prices）</news:title>
   <news:publication_date>2026-05-20T22:24:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692451</loc>
  <lastmod>2026-05-20T22:24:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>QT-Optによる視覚基盤ロボット把持の大規模強化学習（QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation）</news:title>
   <news:publication_date>2026-05-20T22:24:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692449</loc>
  <lastmod>2026-05-20T22:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>独立深層学習行列解析による多チャンネル音源分離（Independent Deeply Learned Matrix Analysis for Multichannel Audio Source Separation）</news:title>
   <news:publication_date>2026-05-20T22:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692447</loc>
  <lastmod>2026-05-20T22:23:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非均一サンプリングからの行列補完（Matrix Completion from Non-Uniformly Sampled Entries）</news:title>
   <news:publication_date>2026-05-20T22:23:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692445</loc>
  <lastmod>2026-05-20T21:32:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限データで平均と分散の保証を与えるスケーラブルなガウス過程推論（Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees）</news:title>
   <news:publication_date>2026-05-20T21:32:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692443</loc>
  <lastmod>2026-05-20T21:24:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Auto-Kerasによる効率的なニューラルアーキテクチャ探索（Auto-Keras: An Efficient Neural Architecture Search System）</news:title>
   <news:publication_date>2026-05-20T21:24:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692441</loc>
  <lastmod>2026-05-20T21:24:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空映像における主要物体の階層的深層共分割（Hierarchical Deep Co-segmentation of Primary Objects in Aerial Videos）</news:title>
   <news:publication_date>2026-05-20T21:24:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692439</loc>
  <lastmod>2026-05-20T21:24:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分的局所線形近似によるブラックボックス解釈（Optimal Piecewise Local-Linear Approximations）</news:title>
   <news:publication_date>2026-05-20T21:24:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692437</loc>
  <lastmod>2026-05-20T21:23:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ランダム自己改変計算（Quantum Random Self-Modifiable Computation）</news:title>
   <news:publication_date>2026-05-20T21:23:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692435</loc>
  <lastmod>2026-05-20T21:22:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人の目に合うサリエンシー評価を学習する（Learning a Saliency Evaluation Metric Using Crowdsourced Perceptual Judgments）</news:title>
   <news:publication_date>2026-05-20T21:22:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692433</loc>
  <lastmod>2026-05-20T21:22:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Guided evolutionary strategiesの実務的解説（Guided evolutionary strategies: Augmenting random search with surrogate gradients）</news:title>
   <news:publication_date>2026-05-20T21:22:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692431</loc>
  <lastmod>2026-05-20T20:31:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付きスパースℓp回帰の実務的含意（Conditional Sparse ℓp-norm Regression With Optimal Probability）</news:title>
   <news:publication_date>2026-05-20T20:31:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692429</loc>
  <lastmod>2026-05-20T20:30:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核の短距離相関のエネルギー・運動量依存性（Energy and momentum dependence of nuclear short-range correlations - Spectral function, exclusive scattering experiments and the contact formalism）</news:title>
   <news:publication_date>2026-05-20T20:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692427</loc>
  <lastmod>2026-05-20T20:30:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幼児向けウェブ学習プラットフォームの採用意図要因（The Determinants For User Intention To Adopt Web Based Early Childhood Supplementary Educational Platform）</news:title>
   <news:publication_date>2026-05-20T20:30:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692425</loc>
  <lastmod>2026-05-20T20:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予算制約付きデュアルSVM訓練（Dual SVM Training on a Budget）</news:title>
   <news:publication_date>2026-05-20T20:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692423</loc>
  <lastmod>2026-05-20T20:29:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延付き確率的勾配降下法の収束解析（A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates）</news:title>
   <news:publication_date>2026-05-20T20:29:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692421</loc>
  <lastmod>2026-05-20T20:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Feature Factorizationによる概念発見（Deep Feature Factorization For Concept Discovery）</news:title>
   <news:publication_date>2026-05-20T20:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692419</loc>
  <lastmod>2026-05-20T20:29:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>競合する隠れユニットによる教師なし学習（Unsupervised Learning by Competing Hidden Units）</news:title>
   <news:publication_date>2026-05-20T20:29:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692417</loc>
  <lastmod>2026-05-20T19:37:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>名前一致（Record Linkage）に基づく確率的手法による顧客名照合（Record Linkage to Match Customer Names: A Probabilistic Approach）</news:title>
   <news:publication_date>2026-05-20T19:37:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692415</loc>
  <lastmod>2026-05-20T19:37:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前計算された黄金分割探索によるBudgeted SGD-SVMの高速化（Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section Search）</news:title>
   <news:publication_date>2026-05-20T19:37:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692413</loc>
  <lastmod>2026-05-20T19:37:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチマージによる予算付きSGD-SVMの高速化（Multi-Merge Budget Maintenance for Stochastic Gradient Descent SVM Training）</news:title>
   <news:publication_date>2026-05-20T19:37:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692411</loc>
  <lastmod>2026-05-20T19:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生化学回路における確率的推論の具現化（Embodying probabilistic inference in biochemical circuits）</news:title>
   <news:publication_date>2026-05-20T19:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692409</loc>
  <lastmod>2026-05-20T19:36:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セプシス患者のICU死亡リスク検出を高精度化する意味的強化動的ベイジアンネットワーク（Semantically Enhanced Dynamic Bayesian Network for Detecting Sepsis Mortality Risk in ICU Patients with Infection）</news:title>
   <news:publication_date>2026-05-20T19:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692407</loc>
  <lastmod>2026-05-20T19:36:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ適応型圧縮センシングの学習—勾配アンローリングによる測定行列の最適化（Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling）</news:title>
   <news:publication_date>2026-05-20T19:36:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692405</loc>
  <lastmod>2026-05-20T19:36:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モジュール化メタラーニングの原理と実践（Modular meta-learning）</news:title>
   <news:publication_date>2026-05-20T19:36:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692403</loc>
  <lastmod>2026-05-20T18:44:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stripe 82 1–2 GHz VLAスナップショット調査の多波長カウンターパート解析（The Stripe 82 1–2 GHz Very Large Array Snapshot Survey: Multiwavelength Counterparts）</news:title>
   <news:publication_date>2026-05-20T18:44:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692401</loc>
  <lastmod>2026-05-20T18:44:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>疾患進行学習を活用した医療画像認識の刷新（Leveraging Disease Progression Learning for Medical Image Recognition）</news:title>
   <news:publication_date>2026-05-20T18:44:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692399</loc>
  <lastmod>2026-05-20T18:43:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生波形で挑む音楽生成の課題（The challenge of realistic music generation: modelling raw audio at scale）</news:title>
   <news:publication_date>2026-05-20T18:43:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692397</loc>
  <lastmod>2026-05-20T18:43:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存の社会的慣習を観察データで学習する（Learning Existing Social Conventions via Observationally Augmented Self-Play）</news:title>
   <news:publication_date>2026-05-20T18:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692395</loc>
  <lastmod>2026-05-20T18:42:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率データベースにおける任意時点近似の一般枠組み（A General Framework for Anytime Approximation in Probabilistic Databases）</news:title>
   <news:publication_date>2026-05-20T18:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692393</loc>
  <lastmod>2026-05-20T18:42:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムシャッフルは有限エポックでSGDを上回る（Random Shuffling Beats SGD after Finite Epochs）</news:title>
   <news:publication_date>2026-05-20T18:42:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692391</loc>
  <lastmod>2026-05-20T18:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>作物収量予測のための効率的データウェアハウス（An Efficient Data Warehouse for Crop Yield Prediction）</news:title>
   <news:publication_date>2026-05-20T18:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692389</loc>
  <lastmod>2026-05-20T17:51:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep k-Meansによる表現学習とクラスタリングの同時最適化（Deep k-Means: Jointly clustering with k-Means and learning representations）</news:title>
   <news:publication_date>2026-05-20T17:51:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692387</loc>
  <lastmod>2026-05-20T17:50:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的シェーピングにおけるブラインド復号指標推定（Blind Decoding-Metric Estimation for Probabilistic Shaping via Expectation Maximization）</news:title>
   <news:publication_date>2026-05-20T17:50:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692385</loc>
  <lastmod>2026-05-20T17:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adaptive Blending Units（ADAPTIVE BLENDING UNITS: TRAINABLE ACTIVATION FUNCTIONS FOR DEEP NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-05-20T17:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692383</loc>
  <lastmod>2026-05-20T17:49:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆カウントの密度適応ネットワーク（Crowd Counting with Density Adaption Networks）</news:title>
   <news:publication_date>2026-05-20T17:49:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692381</loc>
  <lastmod>2026-05-20T17:49:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デイアクティック・イメージ・マッピングによる姿勢不変な操作学習（Deictic Image Mapping）</news:title>
   <news:publication_date>2026-05-20T17:49:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692379</loc>
  <lastmod>2026-05-20T17:49:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ℓ∞,1混合ノルム球への効率的な射影：ニュートン根探索法による高速化（Efficient Projection onto the ℓ∞,1 Mixed-Norm Ball using a Newton Root Search Method）</news:title>
   <news:publication_date>2026-05-20T17:49:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692377</loc>
  <lastmod>2026-05-20T17:49:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>関数は低次元か？（Is your function low-dimensional?）</news:title>
   <news:publication_date>2026-05-20T17:49:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692375</loc>
  <lastmod>2026-05-20T16:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>符号なしラプラシアンスペクトルで決定されるグラフの意義（Graphs determined by signless Laplacian Spectra）</news:title>
   <news:publication_date>2026-05-20T16:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692373</loc>
  <lastmod>2026-05-20T16:57:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆問題モデル学習のための敵対的能動探索（Adversarial Active Exploration for Inverse Dynamics Model Learning）</news:title>
   <news:publication_date>2026-05-20T16:57:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692371</loc>
  <lastmod>2026-05-20T16:56:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件性の原理が高次元回帰に与える示唆（The conditionality principle in high-dimensional regression）</news:title>
   <news:publication_date>2026-05-20T16:56:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692369</loc>
  <lastmod>2026-05-20T16:56:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習によるモチーフとニューロン集団検出（LEMONADE: Learned Motif and Neuronal Assembly Detection in Calcium Imaging Videos）</news:title>
   <news:publication_date>2026-05-20T16:56:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692367</loc>
  <lastmod>2026-05-20T16:56:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的指数型ファミリー因子分解モデルのための分離拡張カルマンフィルタ (The Decoupled Extended Kalman Filter for Dynamic Exponential-Family Factorization Models)</news:title>
   <news:publication_date>2026-05-20T16:56:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692365</loc>
  <lastmod>2026-05-20T16:56:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>市民社会ラボ：市民サイエンス枠組みにおける人間行動実験のデジタルプラットフォーム（Citizen Social Lab: A digital platform for human behaviour experimentation within a citizen science framework）</news:title>
   <news:publication_date>2026-05-20T16:56:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692363</loc>
  <lastmod>2026-05-20T16:56:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>界面活性剤で覆われた変形滴の電気流体移動（Electrohydrodynamic migration of a surfactant-coated deformable drop in Poiseuielle flow）</news:title>
   <news:publication_date>2026-05-20T16:56:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692361</loc>
  <lastmod>2026-05-20T16:04:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数コントラストMRIのための連結辞書学習（Coupled Dictionary Learning for Multi-Contrast MRI Reconstruction）</news:title>
   <news:publication_date>2026-05-20T16:04:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692359</loc>
  <lastmod>2026-05-20T16:03:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト非依存の話者認証で嵐を呼んだ組合せ手法（Text-Independent Speaker Verification Based on Deep Neural Networks and Segmental Dynamic Time Warping）</news:title>
   <news:publication_date>2026-05-20T16:03:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692357</loc>
  <lastmod>2026-05-20T16:03:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ブラックボックスを開く — データ駆動型の説明手法の要点（Open the Black Box: Data-Driven Explanation of Black Box Decision Systems）</news:title>
   <news:publication_date>2026-05-20T16:03:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692355</loc>
  <lastmod>2026-05-20T16:02:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Autograd Image Registration Laboratory（AIRLab: Autograd Image Registration Laboratory）</news:title>
   <news:publication_date>2026-05-20T16:02:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692353</loc>
  <lastmod>2026-05-20T16:02:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的VampPriorを用いた変分公平オートエンコーダ（Hierarchical VampPrior Variational Fair Auto-Encoder）</news:title>
   <news:publication_date>2026-05-20T16:02:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692351</loc>
  <lastmod>2026-05-20T16:02:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接線空間正則化による動的システムのニューラルネットワークモデル改善（Tangent-Space Regularization for Neural-Network Models of Dynamical Systems）</news:title>
   <news:publication_date>2026-05-20T16:02:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692349</loc>
  <lastmod>2026-05-20T16:02:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様体上の構造化予測（Manifold Structured Prediction）</news:title>
   <news:publication_date>2026-05-20T16:02:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692347</loc>
  <lastmod>2026-05-20T15:10:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化された自動音楽生成のための生波形生成モデルの条件付け（Conditioning Deep Generative Raw Audio Models for Structured Automatic Music）</news:title>
   <news:publication_date>2026-05-20T15:10:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692345</loc>
  <lastmod>2026-05-20T15:10:25Z</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を用いた金属結合タンパク質設計と新規フォールド創出（Design of metalloproteins and novel protein folds using variational autoencoders）</news:title>
   <news:publication_date>2026-05-20T15:10:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692343</loc>
  <lastmod>2026-05-20T15:09:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>回帰問題におけるドロップアウトに基づく能動学習（Dropout-based Active Learning for Regression）</news:title>
   <news:publication_date>2026-05-20T15:09:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692341</loc>
  <lastmod>2026-05-20T15:09:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結合辞書学習に基づくマルチモーダル画像ノイズ除去（MULTIMODAL IMAGE DENOISING BASED ON COUPLED DICTIONARY LEARNING）</news:title>
   <news:publication_date>2026-05-20T15:09:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/692339</loc>
  <lastmod>2026-05-20T15:09:00Z</lastmod>
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