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   <news:title>大質量ブラックホールの重力波による観測視点（THE GRAVITATIONAL WAVE VIEW OF MASSIVE BLACK HOLES）</news:title>
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   <news:title>少数データから学ぶ植物根のMRI超解像3Dセグメンテーション（Learning Super-resolution 3D Segmentation of Plant Root MRI Images from Few Examples）</news:title>
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   <news:title>パズルを解くことで得られる「場面横断的な学習力」（Domain Generalization by Solving Jigsaw Puzzles）</news:title>
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   <news:title>六角格子の極値特性（AN EXTREMAL PROPERTY OF THE HEXAGONAL LATTICE）</news:title>
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   <news:title>ピクセル検出器データの超高速処理と機械学習フレームワーク（Ultrafast Processing of Pixel Detector Data with Machine Learning Frameworks）</news:title>
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   <news:title>GAN生成画像の検出に共起行列を用いる方法（Detecting GAN generated Fake Images using Co-occurrence Matrices）</news:title>
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   <news:title>見えない角度を生成する単一画像からの視点依存画像生成（Generate What You Can&amp;#039;t See - a View-dependent Image Generation）</news:title>
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   <news:title>天文学におけるアストロインフォマティクスとアストロスタティスティクスの次の10年（The Next Decade of Astroinformatics and Astrostatistics）</news:title>
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   <news:title>電極材料の電圧を機械学習で予測する（Machine Learning the Voltage of Electrode Materials in Metal-ion Batteries）</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>相関したパターン集合からの一般化（Generalization from correlated sets of patterns in the perceptron）</news:title>
   <news:publication_date>2026-08-18T17:36:06Z</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>宇宙黎明期のブラックホール放射と21 cm全体信号への影響（The Radio Scream from Black Holes at Cosmic Dawn）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>イソペリメトリック損失を用いたゼロショット学習（Zero Shot Learning with the Isoperimetric Loss）</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>ヘテロジニアスセルラーネットワークにおけるオンラインアンテナ調整と深層強化学習（Online Antenna Tuning in Heterogeneous Cellular Networks with Deep Reinforcement 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>壁越し姿勢推定のリアルタイム化──Many-to-Many Encoder/Decoderによる突破（Through-Wall Pose Imaging in Real-Time with a Many-to-Many Encoder/Decoder Paradigm）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>スマートな深層コピー＆ペースト（SMART, DEEP COPY-PASTE）</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>深層ニューラルネットワーク検証のアルゴリズム（Algorithms for Verifying Deep Neural Networks）</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>GitLabログを活用したソフトウェア工学教育の学習分析手法（A Methodology for Using GitLab for Software Engineering Learning Analytics）</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>Atari-HEAD：人間の視線と操作を同時に記録した大規模データセット（Atari Human Eye-Tracking and Demonstration Dataset）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>米国国内線の到着遅延予測を現場に活かす（A Data Mining Approach to Flight Arrival Delay Prediction for American Airlines）</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>ReLUの死亡現象と初期化（Dying ReLU and Initialization: Theory and Numerical Examples）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-18T15:49:35Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>キャンパス行動から見る大学生の成績予測（Predicting Academic Performance for College Students: A Campus Behavior Perspective）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>大規模状態空間における混合方策学習のサンプル効率（ON SAMPLE COMPLEXITY OF PROJECTION-FREE PRIMAL-DUAL METHODS FOR LEARNING MIXTURE POLICIES IN MARKOV DECISION PROCESSES）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>大規模電力網の多段階故障警報システム（MULTI-STAGE FAULT WARNING FOR LARGE ELECTRIC GRIDS USING ANOMALY DETECTION AND MACHINE LEARNING）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ニューラルネットワーク量子状態による二次元フラストレートJ1-J2モデルの研究（Study of the Two-Dimensional Frustrated J1-J2 Model with Neural Network Quantum States）</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>畳み込みニューラルネットワーク訓練の強スケーリング改善（Improving Strong-Scaling of CNN Training by Exploiting Finer-Grained Parallelism）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-08-18T14:56:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Dragonflyによるスケーラブルかつ頑健なベイズ最適化（Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly）</news:title>
   <news:publication_date>2026-08-18T14:56:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>GEE: VAEと勾配指紋で説明可能なネットワーク異常検知（GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection）</news:title>
   <news:publication_date>2026-08-18T14:55:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>カメラ姿勢回帰と改善のための敵対的ネットワーク（Adversarial Networks for Camera Pose Regression and Refinement）</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>高次元最適制御に挑む：DNNが次元の呪いを乗り越える（Rectified deep neural networks overcome the curse of dimensionality for nonsmooth value functions in zero-sum games of nonlinear stiff systems）</news:title>
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    <news:language>ja</news:language>
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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:publication_date>2026-08-18T14:54:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/724577</loc>
  <lastmod>2026-08-18T14:03:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異方的な堅牢性の証明：非一様境界の検証（On Certifying Non-uniform Bounds against Adversarial Attacks）</news:title>
   <news:publication_date>2026-08-18T14:03:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724575</loc>
  <lastmod>2026-08-18T14:03:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的畳み込みニューラルネットワークによる動画物体検出の高速化（SCNN: A General Distribution based Statistical Convolutional Neural Network with Application to Video Object Detection）</news:title>
   <news:publication_date>2026-08-18T14:03:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724573</loc>
  <lastmod>2026-08-18T14:02:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列分類における深層ニューラルネットワークのアンサンブル（Deep Neural Network Ensembles for Time Series Classification）</news:title>
   <news:publication_date>2026-08-18T14:02:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724571</loc>
  <lastmod>2026-08-18T14:01:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>政策蒸留と価値マッチングによるマルチエージェント強化学習の統合（Policy Distillation and Value Matching in Multiagent Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-18T14:01:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724569</loc>
  <lastmod>2026-08-18T14:01:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モンテカルロ・ウェーブレットによるフレーム離散化（Monte Carlo wavelets: a randomized approach to frame discretization）</news:title>
   <news:publication_date>2026-08-18T14:01:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724567</loc>
  <lastmod>2026-08-18T14:01:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般的M推定量の任意時点非漸近反復対数則（A nonasymptotic law of iterated logarithm for general M-estimators）</news:title>
   <news:publication_date>2026-08-18T14:01:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724565</loc>
  <lastmod>2026-08-18T14:01:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>選択的カーネルネットワーク（Selective Kernel Networks）</news:title>
   <news:publication_date>2026-08-18T14:01:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724563</loc>
  <lastmod>2026-08-18T13:09:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画への動画挿入手法（Inserting Videos into Videos）</news:title>
   <news:publication_date>2026-08-18T13:09:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724561</loc>
  <lastmod>2026-08-18T13:09:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>固有状態の局所測定から系のハミルトニアンを復元する（Determining system Hamiltonian from eigenstate measurements without correlation functions）</news:title>
   <news:publication_date>2026-08-18T13:09:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724559</loc>
  <lastmod>2026-08-18T13:08:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数ラベルによる雲画像分割（Multi-label Cloud Segmentation Using a Deep Network）</news:title>
   <news:publication_date>2026-08-18T13:08:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724557</loc>
  <lastmod>2026-08-18T13:08:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゴルフスイングの「映像イベント検出」が変える分析実務（GolfDB: A Video Database for Golf Swing Sequencing）</news:title>
   <news:publication_date>2026-08-18T13:08:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724555</loc>
  <lastmod>2026-08-18T13:08:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高スループットイメージング解析における表現型プロファイリング（Phenotypic Profiling of High Throughput Imaging Screens with Generic Deep Convolutional Features）</news:title>
   <news:publication_date>2026-08-18T13:08:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724553</loc>
  <lastmod>2026-08-18T13:07:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テニスランキングの新モデル：非負行列因子分解に動機づけられたランキングモデル（A Ranking Model Motivated by Nonnegative Matrix Factorization with Applications to Tennis Tournaments）</news:title>
   <news:publication_date>2026-08-18T13:07:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724551</loc>
  <lastmod>2026-08-18T13:07:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>攻撃的発言検出の最先端手法の探索（An Exploration of State-of-the-art Methods for Offensive Language Detection）</news:title>
   <news:publication_date>2026-08-18T13:07:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724549</loc>
  <lastmod>2026-08-18T12:16:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル融合の自動設計探索（MFAS: Multimodal Fusion Architecture Search）</news:title>
   <news:publication_date>2026-08-18T12:16:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724547</loc>
  <lastmod>2026-08-18T12:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューロモーフィックハードウェアにおける学習の学習（Neuromorphic Hardware learns to learn）</news:title>
   <news:publication_date>2026-08-18T12:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724545</loc>
  <lastmod>2026-08-18T12:15:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重バイオメトリクスによる双子識別（Twins Recognition with Multi Biometric System）</news:title>
   <news:publication_date>2026-08-18T12:15:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724543</loc>
  <lastmod>2026-08-18T12:14:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈対応型引用推薦モデルが変える参考文献探索（A Context-Aware Citation Recommendation Model with BERT and Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-18T12:14:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724541</loc>
  <lastmod>2026-08-18T12:14:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的プログラミングを用いた感情コンピューティングの実践（Applying Probabilistic Programming to Affective Computing）</news:title>
   <news:publication_date>2026-08-18T12:14:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724539</loc>
  <lastmod>2026-08-18T12:14:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単眼画像からの濃密セマンティック再構築（Monocular Dense Semantic Reconstruction using Learned Encoded Scene Representations）</news:title>
   <news:publication_date>2026-08-18T12:14:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724537</loc>
  <lastmod>2026-08-18T12:14:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>国際株式市場を同時に扱うマルチモーダル深層学習（Multimodal Deep Learning for Finance: Integrating and Forecasting International Stock Markets）</news:title>
   <news:publication_date>2026-08-18T12:14:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724535</loc>
  <lastmod>2026-08-18T11:22:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>睡眠における皮質覚醒の自動検出と日中の眠気への寄与（Automatic Detection of Cortical Arousals in Sleep and their Contribution to Daytime Sleepiness）</news:title>
   <news:publication_date>2026-08-18T11:22:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724533</loc>
  <lastmod>2026-08-18T11:22:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限体上の重要特徴列挙を高速化するアルゴリズム（A Faster Algorithm Enumerating Relevant Features over Finite Fields）</news:title>
   <news:publication_date>2026-08-18T11:22:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724531</loc>
  <lastmod>2026-08-18T11:21:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>児童の第二言語音声能力を自動評価する技術の実用性（AUTOMATIC ASSESSMENT OF SPOKEN LANGUAGE PROFICIENCY OF NON-NATIVE CHILDREN）</news:title>
   <news:publication_date>2026-08-18T11:21:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724529</loc>
  <lastmod>2026-08-18T11:20:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模ブラックボックス最適化ベンチマーク（COCO: The Large Scale Black-Box Optimization Benchmarking）</news:title>
   <news:publication_date>2026-08-18T11:20:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724527</loc>
  <lastmod>2026-08-18T11:20:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DFineNetによる深度補完と自己位置推定の統合（DFineNet: Ego-Motion Estimation and Depth Refinement from Sparse, Noisy Depth Input with RGB Guidance）</news:title>
   <news:publication_date>2026-08-18T11:20:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724525</loc>
  <lastmod>2026-08-18T11:20:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>品質を意識した非対応画像間翻訳（Quality-aware Unpaired Image-to-Image Translation）</news:title>
   <news:publication_date>2026-08-18T11:20:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724523</loc>
  <lastmod>2026-08-18T11:19:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次Dysthe方程式における変調波の数値シミュレーション（Numerical simulations of modulated waves in a higher-order Dysthe equation）</news:title>
   <news:publication_date>2026-08-18T11:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724521</loc>
  <lastmod>2026-08-18T10:26:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載レーダーの干渉除去に向けた深層学習アプローチ（A Deep Learning Approach for Automotive Radar Interference Mitigation）</news:title>
   <news:publication_date>2026-08-18T10:26:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724519</loc>
  <lastmod>2026-08-18T10:26:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイクベースの逆伝播による深層ニューラルネットワーク訓練の実現 (Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures)</news:title>
   <news:publication_date>2026-08-18T10:26:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724517</loc>
  <lastmod>2026-08-18T10:26:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FASTのドリフトスキャンにおけるパルサー候補選別のための集合ネットワーク（Pulsar Candidate Selection Using Ensemble Networks for FAST Drift-Scan Survey）</news:title>
   <news:publication_date>2026-08-18T10:26:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724515</loc>
  <lastmod>2026-08-18T10:24:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散強化学習におけるマルチエージェント・オフポリシー アクタークリティック（A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-18T10:24:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724513</loc>
  <lastmod>2026-08-18T10:24:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>軽量光学フローCNNの再設計（A Lightweight Optical Flow CNN — Revisiting Data Fidelity and Regularization）</news:title>
   <news:publication_date>2026-08-18T10:24:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724511</loc>
  <lastmod>2026-08-18T10:24:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数変調による異方性量子ラビモデルのシミュレーション（Simulating Anisotropic quantum Rabi model via frequency modulation）</news:title>
   <news:publication_date>2026-08-18T10:24:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724509</loc>
  <lastmod>2026-08-18T10:24:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人と物の相互作用認識と姿勢推定のターボ学習フレームワーク（Turbo Learning Framework for Human-Object Interactions Recognition and Human Pose Estimation）</news:title>
   <news:publication_date>2026-08-18T10:24:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724507</loc>
  <lastmod>2026-08-18T09:32:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像分類のための教師なし深層転移特徴学習（UNSUPERVISED DEEP TRANSFER FEATURE LEARNING FOR MEDICAL IMAGE CLASSIFICATION）</news:title>
   <news:publication_date>2026-08-18T09:32:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724505</loc>
  <lastmod>2026-08-18T09:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ターゲットシフトに配慮した敵対的ドメイン適応（On Target Shift in Adversarial Domain Adaptation）</news:title>
   <news:publication_date>2026-08-18T09:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724503</loc>
  <lastmod>2026-08-18T09:31:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習を用いたリスクモデルの実務的意義（Machine Learning Risk Models）</news:title>
   <news:publication_date>2026-08-18T09:31:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724501</loc>
  <lastmod>2026-08-18T09:30:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像の逐次改良を可能にするDeep Joint Source-Channel Coding（Successive Refinement of Images with Deep Joint Source-Channel Coding）</news:title>
   <news:publication_date>2026-08-18T09:30:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724499</loc>
  <lastmod>2026-08-18T09:30:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソフトマルチラベル学習による教師なし人物再識別（Unsupervised Person Re-identification by Soft Multilabel Learning）</news:title>
   <news:publication_date>2026-08-18T09:30:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724497</loc>
  <lastmod>2026-08-18T09:30:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期セントロイド問題に挑むDP-KMeans（Tackling Initial Centroid of K-Means with Distance Part (DP-KMeans)）</news:title>
   <news:publication_date>2026-08-18T09:30:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724495</loc>
  <lastmod>2026-08-18T09:30:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>太陽系の深時間サーベイ（Solar system Deep Time‑Surveys of atmospheres, surfaces, and rings）</news:title>
   <news:publication_date>2026-08-18T09:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724493</loc>
  <lastmod>2026-08-18T08:39:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウィンドウ化された姿勢グラフ最適化による教師なし単眼Visual Odometryの改善（Pose Graph Optimization for Unsupervised Monocular Visual Odometry）</news:title>
   <news:publication_date>2026-08-18T08:39:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724491</loc>
  <lastmod>2026-08-18T08:39:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>相互線形回帰に基づく離散ハッシュ（MUTUAL LINEAR REGRESSION-BASED DISCRETE HASHING）</news:title>
   <news:publication_date>2026-08-18T08:39:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724489</loc>
  <lastmod>2026-08-18T08:38:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>専門家の視線を模倣する試み（Toward Imitating Visual Attention of Experts in Software Development Tasks）</news:title>
   <news:publication_date>2026-08-18T08:38:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724487</loc>
  <lastmod>2026-08-18T08:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的モデルによる相関攻撃への防御研究アジェンダ（A Research Agenda: Dynamic Models to Defend Against Correlated Attacks）</news:title>
   <news:publication_date>2026-08-18T08:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724485</loc>
  <lastmod>2026-08-18T08:37:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散制約オンライン学習（Distributed Constrained Online Learning）</news:title>
   <news:publication_date>2026-08-18T08:37:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724483</loc>
  <lastmod>2026-08-18T08:37:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ROS2Learn：ROS 2向け強化学習フレームワーク（ROS2Learn: a reinforcement learning framework for ROS 2）</news:title>
   <news:publication_date>2026-08-18T08:37:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724481</loc>
  <lastmod>2026-08-18T08:37:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>gym-gazebo2を使ったROS 2とGazeboによる強化学習ツールキット（gym-gazebo2, a toolkit for reinforcement learning using ROS 2 and Gazebo）</news:title>
   <news:publication_date>2026-08-18T08:37:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724479</loc>
  <lastmod>2026-08-18T07:46:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像と言語を一つに学ぶ統合モデル（Show, Translate and Tell）</news:title>
   <news:publication_date>2026-08-18T07:46:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724477</loc>
  <lastmod>2026-08-18T07:45:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ジャマー抑圧のためのモデル駆動深層学習（Model-Driven Deep Learning Method for Jammer Suppression in Massive Connectivity Systems）</news:title>
   <news:publication_date>2026-08-18T07:45:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724475</loc>
  <lastmod>2026-08-18T07:45:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DysLexMLによるディスレクシアのスクリーニング（DysLexML: Screening Tool for Dyslexia Using Machine Learning）</news:title>
   <news:publication_date>2026-08-18T07:45:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724473</loc>
  <lastmod>2026-08-18T07:45:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模バッチ学習におけるK-FACの非効率性（Inefficiency of K-FAC for Large Batch Size Training）</news:title>
   <news:publication_date>2026-08-18T07:45:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724471</loc>
  <lastmod>2026-08-18T07:44:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調キャッシュ配置における学習オートマトン組み込みQ学習（Learning Automata Based Q-learning for Content Placement in Cooperative Caching）</news:title>
   <news:publication_date>2026-08-18T07:44:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724469</loc>
  <lastmod>2026-08-18T07:44:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Neural Architecture Searchの分類器改良をアンサンブル学習で実現（Improving Neural Architecture Search Image Classifiers via Ensemble Learning）</news:title>
   <news:publication_date>2026-08-18T07:44:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724467</loc>
  <lastmod>2026-08-18T07:44:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテデータでの機械学習予測を読み解く（Interpretation of machine learning predictions for patient outcomes in electronic health records）</news:title>
   <news:publication_date>2026-08-18T07:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724465</loc>
  <lastmod>2026-08-18T06:52:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コンテキスト付き強化学習における後悔ゼロ探索（No-regret Exploration in Contextual Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-18T06:52:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724463</loc>
  <lastmod>2026-08-18T06:52:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中性子星合体からの高エネルギー放射（High-energy emissions from neutron star mergers）</news:title>
   <news:publication_date>2026-08-18T06:52:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724461</loc>
  <lastmod>2026-08-18T06:51:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河進化を大規模構造の文脈で観測する意義（Observing Galaxy Evolution in the Context of Large-Scale Structure）</news:title>
   <news:publication_date>2026-08-18T06:51:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724459</loc>
  <lastmod>2026-08-18T06:51:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非極性二ループ重質量ピュアシングレットWilson係数の解析（The unpolarized two-loop massive pure singlet Wilson coefficients for deep-inelastic scattering）</news:title>
   <news:publication_date>2026-08-18T06:51:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724457</loc>
  <lastmod>2026-08-18T06:51:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>微細な差を見抜く注意機構：Trilinear Attention Sampling Networkによる微粒度画像認識（Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition）</news:title>
   <news:publication_date>2026-08-18T06:51:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724455</loc>
  <lastmod>2026-08-18T06:51:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の修正フィードバックに基づく探索を用いた深層強化学習（Deep Reinforcement Learning with Feedback-based Exploration）</news:title>
   <news:publication_date>2026-08-18T06:51:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724453</loc>
  <lastmod>2026-08-18T06:51:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WFIRSTで実現する超深場観測（An Ultra Deep Field Survey with WFIRST）</news:title>
   <news:publication_date>2026-08-18T06:51:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724451</loc>
  <lastmod>2026-08-18T05:59:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネスト化ポリヘドラルモデルによるテンソルコンパイル（Stripe: Tensor Compilation via the Nested Polyhedral Model）</news:title>
   <news:publication_date>2026-08-18T05:59:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724449</loc>
  <lastmod>2026-08-18T05:59:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結びついた超伝導フラックス量子ビットにおける非ストクァスティック・ハミルトニアンの実証（Demonstration of nonstoquastic Hamiltonian in coupled superconducting flux qubits）</news:title>
   <news:publication_date>2026-08-18T05:59:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724447</loc>
  <lastmod>2026-08-18T05:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スイッチ型ネットワークによる離散データ生成（Deep Switch Networks for Generating Discrete Data and Language）</news:title>
   <news:publication_date>2026-08-18T05:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724445</loc>
  <lastmod>2026-08-18T05:58:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>品質独立のJPEG復元のための深い残差オートエンコーダ（Deep Residual Autoencoder for quality independent JPEG restoration）</news:title>
   <news:publication_date>2026-08-18T05:58:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724443</loc>
  <lastmod>2026-08-18T05:58:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散化されたAttend-Infer-Repeatによる教師なしで解釈可能なシーン発見（Unsupervised and interpretable scene discovery with Discrete-Attend-Infer-Repeat）</news:title>
   <news:publication_date>2026-08-18T05:58:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724441</loc>
  <lastmod>2026-08-18T05:58:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀行顧客の潜在表現学習（Learning Latent Representations of Bank Customers With The Variational Autoencoder）</news:title>
   <news:publication_date>2026-08-18T05:58:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724439</loc>
  <lastmod>2026-08-18T05:58:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テンソルで圧縮し可視化するニューラルネット（Compression and Interpretability of Deep Neural Networks via Tucker Tensor Layer）</news:title>
   <news:publication_date>2026-08-18T05:58:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724437</loc>
  <lastmod>2026-08-18T05:06:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MSG-GANによるGANの安定化—マルチスケール勾配で高解像度生成を安定化する（MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-08-18T05:06:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724435</loc>
  <lastmod>2026-08-18T04:57:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>液体構造と核生成障壁をつなぐ過冷却の統計研究（Maximum Supercooling Studies in Ti39.5Zr39.5Ni21 and Zr80Pt20 – Connecting Liquid Structure and the Nucleation Barrier）</news:title>
   <news:publication_date>2026-08-18T04:57:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724433</loc>
  <lastmod>2026-08-18T04:57:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実行プロパティ（インバリアント）の妥当性を学習する手法（Are My Invariants Valid? A Learning Approach）</news:title>
   <news:publication_date>2026-08-18T04:57:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724431</loc>
  <lastmod>2026-08-18T04:57:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多項式時間で解ける線形ディオファントス問題（On Polynomial-Time Solvable Linear Diophantine Problems）</news:title>
   <news:publication_date>2026-08-18T04:57:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724429</loc>
  <lastmod>2026-08-18T04:56:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種デモンストレーションから学ぶ個別化ベイズ埋め込みの推定（Inferring Personalized Bayesian Embeddings for Learning from Heterogeneous Demonstration）</news:title>
   <news:publication_date>2026-08-18T04:56:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724427</loc>
  <lastmod>2026-08-18T04:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的ビーム探索とGumbel-Top-kトリック（Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement）</news:title>
   <news:publication_date>2026-08-18T04:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724425</loc>
  <lastmod>2026-08-18T04:55:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多波長空間コヒーレンス顕微鏡と深層学習によるマラリア赤血球分類（Deep learning enabled multi-wavelength spatial coherence microscope for the classification of malaria-infected stages with limited labelled data size）</news:title>
   <news:publication_date>2026-08-18T04:55:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724423</loc>
  <lastmod>2026-08-18T04:04:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ルチル型GeO2：両極性ドーピングが可能な超広帯域ギャップ半導体（Rutile GeO2: an ultrawide-band-gap semiconductor with ambipolar doping）</news:title>
   <news:publication_date>2026-08-18T04:04:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724421</loc>
  <lastmod>2026-08-18T04:03:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ストリーム重み付けによる視聴覚話者追跡（Audiovisual Speaker Tracking using Nonlinear Dynamical Systems with Dynamic Stream Weights）</news:title>
   <news:publication_date>2026-08-18T04:03:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724419</loc>
  <lastmod>2026-08-18T04:02:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療IoTの通信を優先するための機械学習と資源割当の統合設計（Using Machine Learning and Big Data Analytics to Prioritize Outpatients in HetNets）</news:title>
   <news:publication_date>2026-08-18T04:02:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724417</loc>
  <lastmod>2026-08-18T04:02:17Z</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Gaussian Process状態空間モデル：部分観測ダイナミクスの学習と計画（Online Gaussian Process State-Space Model: Learning and Planning for Partially Observable Dynamical Systems）</news:title>
   <news:publication_date>2026-08-18T04:02:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724415</loc>
  <lastmod>2026-08-18T04:02:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゴーストイメージングから学ぶイメージ不要の学習（On Learning from Ghost Imaging without Imaging）</news:title>
   <news:publication_date>2026-08-18T04:02:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724413</loc>
  <lastmod>2026-08-18T04:02:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミングデータからの質問応答に学習する記憶管理（Episodic Memory Reader: Learning What to Remember for Question Answering from Streaming Data）</news:title>
   <news:publication_date>2026-08-18T04:02:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724411</loc>
  <lastmod>2026-08-18T04:01:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き分布を直接推定する深層回帰（Deep Distribution Regression）</news:title>
   <news:publication_date>2026-08-18T04:01:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724409</loc>
  <lastmod>2026-08-18T03:10:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>事前学習モデルの適応戦略――調整するか否か（To Tune or Not to Tune? Adapting Pretrained Representations to Diverse Tasks）</news:title>
   <news:publication_date>2026-08-18T03:10:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724407</loc>
  <lastmod>2026-08-18T03:09:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈性と圧縮性を両立する補正決定木（Rectified Decision Trees: Towards Interpretability, Compression and Empirical Soundness）</news:title>
   <news:publication_date>2026-08-18T03:09:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724405</loc>
  <lastmod>2026-08-18T03:08:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰性が示す人間視覚の計算原理（Recurrence is required to capture the representational dynamics of the human visual system）</news:title>
   <news:publication_date>2026-08-18T03:08:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724403</loc>
  <lastmod>2026-08-18T03:08:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランクカーネル学習によるグラフベースクラスタリングの革新（Low-rank Kernel Learning for Graph-based Clustering）</news:title>
   <news:publication_date>2026-08-18T03:08:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724401</loc>
  <lastmod>2026-08-18T03:08:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANを用いた声帯波形生成による統計的パラメトリック音声合成の改善（Generative adversarial network-based glottal waveform model for statistical parametric speech synthesis）</news:title>
   <news:publication_date>2026-08-18T03:08:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724399</loc>
  <lastmod>2026-08-18T03:07:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続的な観測から離散的計画領域を増分学習する仕組み（Incremental Learning of Discrete Planning Domains from Continuous Perceptions）</news:title>
   <news:publication_date>2026-08-18T03:07:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724397</loc>
  <lastmod>2026-08-18T02:16:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散位相アレイ型MIMOにおけるチャネル推定とハイブリッドプレコーディング（Channel Estimation and Hybrid Precoding for Distributed Phased Arrays Based MIMO Wireless Communications）</news:title>
   <news:publication_date>2026-08-18T02:16:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724395</loc>
  <lastmod>2026-08-18T02:15:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的ボルツマン・ソフトマックスによる強化学習の価値推定改善（Reinforcement Learning with Dynamic Boltzmann Softmax Updates）</news:title>
   <news:publication_date>2026-08-18T02:15:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724393</loc>
  <lastmod>2026-08-18T02:15:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>攻撃的言語分類の比較研究（Absit invidia verbo: Comparing Deep Learning methods for offensive language）</news:title>
   <news:publication_date>2026-08-18T02:15:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724391</loc>
  <lastmod>2026-08-18T02:13:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一RGBカメラから服を着た人の3D復元を学習する（Learning to Reconstruct People in Clothing from a Single RGB Camera）</news:title>
   <news:publication_date>2026-08-18T02:13:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724389</loc>
  <lastmod>2026-08-18T02:13:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔画像のスケーラブル圧縮と深層特徴再構築（SCALABLE FACIAL IMAGE COMPRESSION WITH DEEP FEATURE RECONSTRUCTION）</news:title>
   <news:publication_date>2026-08-18T02:13:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724387</loc>
  <lastmod>2026-08-18T02:13:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Butterflyによる線形変換の高速アルゴリズム学習（Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations）</news:title>
   <news:publication_date>2026-08-18T02:13:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724385</loc>
  <lastmod>2026-08-18T02:13:24Z</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ARM big.LITTLEでの高スループットCNN推論（High-Throughput CNN Inference on Embedded ARM big.LITTLE Multi-Core Processors）</news:title>
   <news:publication_date>2026-08-18T02:13:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724383</loc>
  <lastmod>2026-08-18T01:21:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>通行人に不快感を与えずに注意を引くユーザー中心強化学習（Can User-Centered Reinforcement Learning Allow a Robot to Attract Passersby without Causing Discomfort?）</news:title>
   <news:publication_date>2026-08-18T01:21:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724381</loc>
  <lastmod>2026-08-18T01:21:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による方位推定を組み込んだCNNによる建物検出（Learning Orientation-Estimation Convolutional Neural Network for Building Detection in Optical Remote Sensing Image）</news:title>
   <news:publication_date>2026-08-18T01:21:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724379</loc>
  <lastmod>2026-08-18T01:20:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元スムーズ関数のより良い近似（Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units）</news:title>
   <news:publication_date>2026-08-18T01:20:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724377</loc>
  <lastmod>2026-08-18T01:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像集合認識のための制約付き相互凸錐法（Constrained Mutual Convex Cone Method for Image Set Based Recognition）</news:title>
   <news:publication_date>2026-08-18T01:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724375</loc>
  <lastmod>2026-08-18T01:20:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特許ランドスケーピング用ディープモデル（Deep Patent Landscaping Model）</news:title>
   <news:publication_date>2026-08-18T01:20:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724373</loc>
  <lastmod>2026-08-18T01:20:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱い監督の下でラベル依存構造を学ぶ（Learning Dependency Structures for Weak Supervision）</news:title>
   <news:publication_date>2026-08-18T01:20:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724371</loc>
  <lastmod>2026-08-18T01:19:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキストから画像を再記述で学習するMirrorGANの要点（MirrorGAN: Learning Text-to-image Generation by Redescription）</news:title>
   <news:publication_date>2026-08-18T01:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724369</loc>
  <lastmod>2026-08-18T00:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>帰属性に基づく因果分析による敵対的例の検出（Attribution-driven Causal Analysis for Detection of Adversarial Examples）</news:title>
   <news:publication_date>2026-08-18T00:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724367</loc>
  <lastmod>2026-08-18T00:28:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界画像を「浄化」するリアルタイムスタイル転送（Purifying Naturalistic Images through a Real-time Style Transfer Semantics Network）</news:title>
   <news:publication_date>2026-08-18T00:28:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724365</loc>
  <lastmod>2026-08-18T00:27:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>f-ダイバージェンスのべき乗カイ展開（Power chi expansions of f-divergences）</news:title>
   <news:publication_date>2026-08-18T00:27:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724363</loc>
  <lastmod>2026-08-18T00:27:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散学習によるチーム最適化の達成（Decentralized Learning for Optimality in Stochastic Dynamic Teams and Games with Local Control and Global State Information）</news:title>
   <news:publication_date>2026-08-18T00:27:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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  <lastmod>2026-08-18T00:26:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-18T00:26:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-18T00:26:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-18T00:25:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T23:34:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T23:32:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T23:32:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T23:32:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T22:40:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>自己教師あり特徴学習による一貫性のある対話生成（Consistent Dialogue Generation with Self-supervised Feature Learning）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T22:39:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既知でない拘束系の軌道最適化に対する強化学習アプローチ（Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-17T22:38:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724331</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T22:38:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T21:46:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T21:45:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-17T21:45:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>シーンに人を置く：3D屋内環境におけるアフォーダンス学習（Putting Humans in a Scene: Learning Affordance in 3D Indoor Environments）</news:title>
   <news:publication_date>2026-08-17T21:45:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数の文脈でのデモ学習における不確かさ認識（Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural Networks）</news:title>
   <news:publication_date>2026-08-17T21:45:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T21:44:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724311</loc>
  <lastmod>2026-08-17T20:53:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル・シーン分解によるマルチ人物モーションキャプチャ（Neural Scene Decomposition for Multi-Person Motion Capture）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T19:57:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-17T19:57:00Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RVOSによる動画物体分割の終端間リカレントネットワーク（RVOS: End-to-End Recurrent Network for Video Object Segmentation）</news:title>
   <news:publication_date>2026-08-17T19:57:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T19:05:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>LiDAR支援による大規模ストリートビューのプライバシー保護（LiDAR-assisted Large-scale Privacy Protection in Street-view Cycloramas）</news:title>
   <news:publication_date>2026-08-17T19:05:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>数学的センスメイキング──計算と概念の整合性を探る（Mathematical Sensemaking as Seeking Coherence between Calculations and Concepts: Instruction and Assessments for Introductory Physics）</news:title>
   <news:publication_date>2026-08-17T19:04:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応スケッチによるスケーラブルなガウス過程最適化（Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret）</news:title>
   <news:publication_date>2026-08-17T19:03:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-17T19:03:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパースペクトル画像のオンライン拡張手法（Online Augmentation for Hyperspectral Data）</news:title>
   <news:publication_date>2026-08-17T19:03:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-08-17T19:03:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スプートニク平原の再配向が示すもの（Reorientation of Sputnik Planitia implies a Subsurface Ocean on Pluto）</news:title>
   <news:publication_date>2026-08-17T19:03:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724273</loc>
  <lastmod>2026-08-17T19:02:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クォータニオン行列乗算の高性能実装と有効性（On the Efficacy and High-Performance Implementation of Quaternion Matrix Multiplication）</news:title>
   <news:publication_date>2026-08-17T19:02:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724271</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プルート表面での窒素氷対流が駆動する地質活動（Convection in a volatile nitrogen-ice-rich layer drives Pluto’s geological vigor）</news:title>
   <news:publication_date>2026-08-17T18:11:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>会話エージェント構築のためのNLUサービスベンチマーク（Benchmarking Natural Language Understanding Services for building Conversational Agents）</news:title>
   <news:publication_date>2026-08-17T18:09:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T18:09:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724265</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>網膜血管セグメンテーションの精度を変える接続感度注意U-Net（Connection Sensitive Attention U-NET for Accurate Retinal Vessel Segmentation）</news:title>
   <news:publication_date>2026-08-17T18:09:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724263</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>不均衡データ下の与信リスク予測手法（PREDICTING CLASS-IMBALANCED BUSINESS RISK USING RESAMPLING, REGULARIZATION, AND MODEL EMSEMBLING ALGORITHMS）</news:title>
   <news:publication_date>2026-08-17T18:09:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724261</loc>
  <lastmod>2026-08-17T18:08:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大k-プレックス問題に対する強化学習ベースの局所探索（Effective reinforcement learning based local search for the maximum k-plex problem）</news:title>
   <news:publication_date>2026-08-17T18:08:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724259</loc>
  <lastmod>2026-08-17T18:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T18:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724257</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>表面重力波伝播におけるBoussinesq成分と非Boussinesq成分の対立的役割（On the opposing roles of the Boussinesq and non-Boussinesq baroclinic torques in surface gravity wave propagation）</news:title>
   <news:publication_date>2026-08-17T17:16:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>難易度を意識した深層距離学習（Hardness-Aware Deep Metric Learning）</news:title>
   <news:publication_date>2026-08-17T17:15:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724253</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T17:14:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724251</loc>
  <lastmod>2026-08-17T17:14:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DEEPOBS: 深層学習の最適化器評価を標準化する試み（DEEPOBS: A Deep Learning Optimizer Benchmark Suite）</news:title>
   <news:publication_date>2026-08-17T17:14:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724249</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T17:13:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724247</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-17T17:13:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724245</loc>
  <lastmod>2026-08-17T17:13:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律3Dトーキングアバターのアニメーション化（Animating an Autonomous 3D Talking Avatar）</news:title>
   <news:publication_date>2026-08-17T17:13:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724243</loc>
  <lastmod>2026-08-17T16:21:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的意味情報追求の総覧（Visual Semantic Information Pursuit: A Survey）</news:title>
   <news:publication_date>2026-08-17T16:21:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724241</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>市場トレンド予測におけるセンチメント分析の実務的知見（Market Trend Prediction using Sentiment Analysis）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724239</loc>
  <lastmod>2026-08-17T16:20:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>資源抽象化による多エージェント渋滞問題の突破（Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems）</news:title>
   <news:publication_date>2026-08-17T16:20:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T16:20:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724235</loc>
  <lastmod>2026-08-17T16:20:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-17T16:20:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>オンライン予算制約下の学習──到着データで特徴を選ぶ現場のための枠組み（Online Budgeted Learning for Classifier Induction）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724219</loc>
  <lastmod>2026-08-17T15:25:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユークリッド空間に確実に埋め込める関係とは何か（What relations are reliably embeddable in Euclidean space?）</news:title>
   <news:publication_date>2026-08-17T15:25:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724217</loc>
  <lastmod>2026-08-17T15:24:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>核のインスタンス分割を頑健化するCIA-Net（CIA-Net: Robust Nuclei Instance Segmentation with Contour-aware Information Aggregation）</news:title>
   <news:publication_date>2026-08-17T15:24:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724215</loc>
  <lastmod>2026-08-17T14:33:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>探索ベースの効率的な重み付きモデル積分（Efficient Search-Based Weighted Model Integration）</news:title>
   <news:publication_date>2026-08-17T14:33:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724213</loc>
  <lastmod>2026-08-17T14:33:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>WiFiで群衆を数えるDeepCount（DeepCount: Crowd Counting with WiFi via Deep Learning）</news:title>
   <news:publication_date>2026-08-17T14:33:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724211</loc>
  <lastmod>2026-08-17T14:32:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチモーダル感情分類（Multimodal Emotion Classification）</news:title>
   <news:publication_date>2026-08-17T14:32:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724209</loc>
  <lastmod>2026-08-17T14:30:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>JWSTによる再電離時代の探索とワイドフィールド時間領域サーベイ（JWST: Probing the Epoch of Reionization with a Wide Field Time-Domain Survey）</news:title>
   <news:publication_date>2026-08-17T14:30:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724207</loc>
  <lastmod>2026-08-17T14:30:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチジオメトリ空間音響モデリングによる遠隔音声認識の堅牢化（MULTI-GEOMETRY SPATIAL ACOUSTIC MODELING FOR DISTANT SPEECH RECOGNITION）</news:title>
   <news:publication_date>2026-08-17T14:30:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724205</loc>
  <lastmod>2026-08-17T14:30:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性情報に基づくゼロショットドメイン適応（Zero-shot Domain Adaptation Based on Attribute Information）</news:title>
   <news:publication_date>2026-08-17T14:30:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724203</loc>
  <lastmod>2026-08-17T14:30:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元における最尤推定の最適性と有界凸回帰の検証（Optimality of Maximum Likelihood for Log-Concave Density Estimation and Bounded Convex Regression）</news:title>
   <news:publication_date>2026-08-17T14:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724201</loc>
  <lastmod>2026-08-17T13:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河中心研究の次の10年を描く（Envisioning the next decade of Galactic Center science）</news:title>
   <news:publication_date>2026-08-17T13:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724199</loc>
  <lastmod>2026-08-17T13:37:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>銀河ハローの中間年齢集団の欠如（The intermediate age population of the Galactic halo）</news:title>
   <news:publication_date>2026-08-17T13:37:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724197</loc>
  <lastmod>2026-08-17T13:37:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数のシフトだけで十分である：効率的な畳み込みニューラルネットワーク設計（All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification）</news:title>
   <news:publication_date>2026-08-17T13:37:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724195</loc>
  <lastmod>2026-08-17T13:36:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値確率方策に対するAugment‑Reinforce‑Merge方策勾配（Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy）</news:title>
   <news:publication_date>2026-08-17T13:36:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724193</loc>
  <lastmod>2026-08-17T13:35:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再生可能エネルギーの時空間シナリオ予測（Forecasting Spatio-Temporal Renewable Scenarios: a Deep Generative Approach）</news:title>
   <news:publication_date>2026-08-17T13:35:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724191</loc>
  <lastmod>2026-08-17T13:35:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stokes流懸濁液のシミュレーション高速化（Machine learning acceleration of simulations of Stokesian suspensions）</news:title>
   <news:publication_date>2026-08-17T13:35:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724189</loc>
  <lastmod>2026-08-17T13:34:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タスク志向の設計を深層強化学習で実現する手法（Task-oriented Design through Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-17T13:34:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724187</loc>
  <lastmod>2026-08-17T12:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測に直結する特徴量ランキングの柔軟な枠組み（A flexible model-free prediction-based framework for feature ranking）</news:title>
   <news:publication_date>2026-08-17T12:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724185</loc>
  <lastmod>2026-08-17T12:42:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文を取り込む新しいSRL手法：SupertagsによるSyntax-aware Neural Semantic Role Labeling with Supertags (Syntax-aware Neural Semantic Role Labeling with Supertags)</news:title>
   <news:publication_date>2026-08-17T12:42:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724183</loc>
  <lastmod>2026-08-17T12:42:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>AutoMLコンペの設計と成果（AutoML @ NeurIPS 2018 challenge: Design and Results）</news:title>
   <news:publication_date>2026-08-17T12:42:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724181</loc>
  <lastmod>2026-08-17T12:41:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組織画像から予後を予測する無教師学習の試み（TOWARDS UNSUPERVISED CANCER SUBTYPING: PREDICTING PROGNOSIS USING A HISTOLOGIC VISUAL DICTIONARY）</news:title>
   <news:publication_date>2026-08-17T12:41:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724179</loc>
  <lastmod>2026-08-17T12:41:28Z</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の解像度パラメータを学習する方法（Learning Resolution Parameters for Graph Clustering）</news:title>
   <news:publication_date>2026-08-17T12:41:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724177</loc>
  <lastmod>2026-08-17T12:41:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間領域における特徴集約を学習する手法（Learning Feature Aggregation in Temporal Domain for Re-Identification）</news:title>
   <news:publication_date>2026-08-17T12:41:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724175</loc>
  <lastmod>2026-08-17T12:41:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションから実環境へゼロショットで移行する自動運転制御（Zero-Shot Autonomous Vehicle Policy Transfer: From Simulation to Real-World via Adversarial Learning）</news:title>
   <news:publication_date>2026-08-17T12:41:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724173</loc>
  <lastmod>2026-08-17T11:48:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負ローカルスパースコーディングによるサブスペースクラスタリング（Non-Negative Local Sparse Coding for Subspace Clustering）</news:title>
   <news:publication_date>2026-08-17T11:48:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724171</loc>
  <lastmod>2026-08-17T11:46:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>“Hang in there”：共感的応答を要する投稿の自動検出（“Hang in there”: Lexical and visual analysis to identify posts warranting empathetic responses）</news:title>
   <news:publication_date>2026-08-17T11:46:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724169</loc>
  <lastmod>2026-08-17T11:39:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的にもっと自然なVRの把持（A Visually Plausible Grasping System for Object Manipulation and Interaction in Virtual Reality Environments）</news:title>
   <news:publication_date>2026-08-17T11:39:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724167</loc>
  <lastmod>2026-08-17T11:38:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原始星系の組み立てにおける変動性（Variability in the Assembly of Protostellar Systems）</news:title>
   <news:publication_date>2026-08-17T11:38:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724165</loc>
  <lastmod>2026-08-17T11:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>修正的な人間フィードバックからガウス方策を学ぶ（Learning Gaussian Policies from Corrective Human Feedback）</news:title>
   <news:publication_date>2026-08-17T11:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724163</loc>
  <lastmod>2026-08-17T11:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>信頼性を重視したカーネルスパースコーディングと辞書学習（Conﬁdent Kernel Sparse Coding and Dictionary Learning）</news:title>
   <news:publication_date>2026-08-17T11:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724161</loc>
  <lastmod>2026-08-17T11:37:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Alfvén波のチャーピングと高速イオン損失の機械学習解析（Machine learning characterisation of Alfvénic and sub-Alfvénic chirping and correlation with fast ion loss at NSTX）</news:title>
   <news:publication_date>2026-08-17T11:37:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724159</loc>
  <lastmod>2026-08-17T10:46:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープフィードフォワードを用いた流体の縮約モデル構築（Construction of Reduced Order Models for Fluid Flows Using Deep Feedforward Neural Networks）</news:title>
   <news:publication_date>2026-08-17T10:46:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724157</loc>
  <lastmod>2026-08-17T10:46:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゲーム開発で学ぶプログラミング概念（Teaching Programming Concepts by Developing Games）</news:title>
   <news:publication_date>2026-08-17T10:46:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724155</loc>
  <lastmod>2026-08-17T10:45:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形化されたベンジャミン方程式の可制御性と安定化（On the Controllability and Stabilization of the Linearized Benjamin Equation on a Periodic Domain）</news:title>
   <news:publication_date>2026-08-17T10:45:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724153</loc>
  <lastmod>2026-08-17T10:44:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙天気における機械学習の挑戦（The Challenge of Machine Learning in Space Weather）</news:title>
   <news:publication_date>2026-08-17T10:44:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724151</loc>
  <lastmod>2026-08-17T10:44:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>継続的に学習するシステムの参照アーキテクチャ（Continual Learning in Practice）</news:title>
   <news:publication_date>2026-08-17T10:44:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724149</loc>
  <lastmod>2026-08-17T10:44:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>建物エネルギー管理における強化学習の総覧（A Review of Reinforcement Learning for Autonomous Building Energy Management）</news:title>
   <news:publication_date>2026-08-17T10:44:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724147</loc>
  <lastmod>2026-08-17T10:44:20Z</lastmod>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/724075</loc>
  <lastmod>2026-08-17T05:11:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブミリ波で切り拓く銀河団研究の新展望（SZ spectroscopy in the coming decade: Galaxy cluster cosmology and astrophysics in the submillimeter）</news:title>
   <news:publication_date>2026-08-17T05:11:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724073</loc>
  <lastmod>2026-08-17T05:11:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>認証済みユーザーの特徴と予測手法（What sets Verified Users apart? Insights, Analysis and Prediction of Verified Users on Twitter）</news:title>
   <news:publication_date>2026-08-17T05:11:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724071</loc>
  <lastmod>2026-08-17T05:11:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>目的指向行動と変分予測符号化による視覚注意とワーキングメモリの動的統合（Goal-Directed Behavior under Variational Predictive Coding）</news:title>
   <news:publication_date>2026-08-17T05:11:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724069</loc>
  <lastmod>2026-08-17T05:10:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴を凝縮して整列させる教師なしドメイン適応（Learning Condensed and Aligned Features for Unsupervised Domain Adaptation Using Label Propagation）</news:title>
   <news:publication_date>2026-08-17T05:10:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724067</loc>
  <lastmod>2026-08-17T05:10:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RFループ内での深層学習を組み込む無線機器のリアルタイム化（Big Data Goes Small: Real-Time Spectrum-Driven Embedded Wireless Networking Through Deep Learning in the RF Loop）</news:title>
   <news:publication_date>2026-08-17T05:10:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724065</loc>
  <lastmod>2026-08-17T05:10:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>並列医用画像解析による知能的医用画像分析（Parallel Medical Imaging for Intelligent Medical Image Analysis: Concepts, Methods, and Applications）</news:title>
   <news:publication_date>2026-08-17T05:10:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724063</loc>
  <lastmod>2026-08-17T05:09:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歴史文書の正規化における少数例学習とゼロショット学習の実証（Few-Shot and Zero-Shot Learning for Historical Text Normalization）</news:title>
   <news:publication_date>2026-08-17T05:09:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724061</loc>
  <lastmod>2026-08-17T04:18:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ガウス過程とベイズ最適化の金融応用（Financial Applications of Gaussian Processes and Bayesian Optimization）</news:title>
   <news:publication_date>2026-08-17T04:18:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724059</loc>
  <lastmod>2026-08-17T04:18:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散データにおける条件付き独立性検定（Testing Conditional Independence on Discrete Data using Stochastic Complexity）</news:title>
   <news:publication_date>2026-08-17T04:18:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724057</loc>
  <lastmod>2026-08-17T04:16:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地中鉱山における発破作業による岩盤挙動の数値モデリング (NUMERICAL MODELING OF ROCKMASS BEHAVIOUR DUE TO BLASTING OPERATIONS IN UNDERGROUND MINES)</news:title>
   <news:publication_date>2026-08-17T04:16:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724055</loc>
  <lastmod>2026-08-17T04:16:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン人間行動認識に階層化隠れマルコフモデルを用いる（Online Human Activity Recognition Employing Hierarchical Hidden Markov Models）</news:title>
   <news:publication_date>2026-08-17T04:16:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724053</loc>
  <lastmod>2026-08-17T04:16:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習アーキテクチャによる攻撃的言語分析（Offensive Language Analysis using Deep Learning Architecture）</news:title>
   <news:publication_date>2026-08-17T04:16:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724051</loc>
  <lastmod>2026-08-17T04:16:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逐次モンテカルロの要素（Elements of Sequential Monte Carlo）</news:title>
   <news:publication_date>2026-08-17T04:16:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724049</loc>
  <lastmod>2026-08-17T04:15:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主成分分析に基づくマルチビュー深層表現による画像分類（Image Classification base on PCA of Multi-view Deep Representation）</news:title>
   <news:publication_date>2026-08-17T04:15:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724047</loc>
  <lastmod>2026-08-17T03:23:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エネルギー効率の高い物体検出を実現するSpiking‑YOLO（Spiking‑YOLO: Spiking Neural Network for Energy‑Efficient Object Detection）</news:title>
   <news:publication_date>2026-08-17T03:23:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724045</loc>
  <lastmod>2026-08-17T03:23:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師ありセルフトaught深層学習による指骨セグメンテーション（Semi-Supervised Self-Taught Deep Learning for Finger Bones Segmentation）</news:title>
   <news:publication_date>2026-08-17T03:23:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724043</loc>
  <lastmod>2026-08-17T03:23:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サブミリ波で作る宇宙の3次元地図（The case for a ‘sub-millimeter SDSS’: a 3D map of galaxy evolution to z ≈10）</news:title>
   <news:publication_date>2026-08-17T03:23:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724041</loc>
  <lastmod>2026-08-17T03:22:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス内分割によるオープンセット認識（Open-Set Recognition Using Intra-Class Splitting）</news:title>
   <news:publication_date>2026-08-17T03:22:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724039</loc>
  <lastmod>2026-08-17T03:22:22Z</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パラドックス：類似でありながら異なり、異なりながら類似である（Paradox in Deep Neural Networks: Similar yet Different while Different yet Similar）</news:title>
   <news:publication_date>2026-08-17T03:22:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724037</loc>
  <lastmod>2026-08-17T03:22:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SmartEDA: 自動化された探索的データ解析が変える現場（SmartEDA: An R Package for Automated Exploratory Data Analysis）</news:title>
   <news:publication_date>2026-08-17T03:22:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724035</loc>
  <lastmod>2026-08-17T03:21:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔認識における閉塞指向コンパクトテンプレート学習（Occlusion-guided compact template learning for ensemble deep network-based pose-invariant face recognition）</news:title>
   <news:publication_date>2026-08-17T03:21:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724033</loc>
  <lastmod>2026-08-17T02:30:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフにおける予測と説明のための相互作用埋め込み（Interaction Embeddings for Prediction and Explanation in Knowledge Graphs）</news:title>
   <news:publication_date>2026-08-17T02:30:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724031</loc>
  <lastmod>2026-08-17T02:29:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ミャンマー語の音節ベースニューラル固有表現抽出（Syllable-Based Neural Named Entity Recognition for Myanmar Language）</news:title>
   <news:publication_date>2026-08-17T02:29:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724029</loc>
  <lastmod>2026-08-17T02:29:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超大型望遠鏡を用いたダークマターの性質検証（Testing the Nature of Dark Matter with Extremely Large Telescopes）</news:title>
   <news:publication_date>2026-08-17T02:29:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724027</loc>
  <lastmod>2026-08-17T02:28:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再プログラマブルな電気光学的非線形活性化関数（Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks）</news:title>
   <news:publication_date>2026-08-17T02:28:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724025</loc>
  <lastmod>2026-08-17T02:28:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>進化的に学習するGANによる楽曲生成の実践と意義（Progressive Generative Adversarial Binary Networks for Music Generation）</news:title>
   <news:publication_date>2026-08-17T02:28:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724023</loc>
  <lastmod>2026-08-17T02:28:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低ランクテンソルグリッドによる画像補完（Low-rank Tensor Grid for Image Completion）</news:title>
   <news:publication_date>2026-08-17T02:28:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724021</loc>
  <lastmod>2026-08-17T02:28:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平方井戸ポテンシャルによる核天体物理学的融合反応の解釈（Potential model for nuclear astrophysical fusion reactions with a square-well potential）</news:title>
   <news:publication_date>2026-08-17T02:28:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724019</loc>
  <lastmod>2026-08-17T01:35:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高エネルギー物理における機械学習の適用（Machine Learning Solutions for High Energy Physics）</news:title>
   <news:publication_date>2026-08-17T01:35:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724017</loc>
  <lastmod>2026-08-17T01:32:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈対応学習によるニューラル機械翻訳（Context-Aware Learning for Neural Machine Translation）</news:title>
   <news:publication_date>2026-08-17T01:32:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724015</loc>
  <lastmod>2026-08-17T01:32:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイト単位深層ニューラルネットワークの活性解析（Activation Analysis of a Byte-Based Deep Neural Network for Malware Classification）</news:title>
   <news:publication_date>2026-08-17T01:32:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724013</loc>
  <lastmod>2026-08-17T01:32:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動化医用画像解析の深層学習革新（Deep Learning for Automated Medical Image Analysis）</news:title>
   <news:publication_date>2026-08-17T01:32:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724011</loc>
  <lastmod>2026-08-17T01:31:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lq安定性のための指数的エフロン–スタイン不等式（An Exponential Efron-Stein Inequality for Lq Stable Learning Rules）</news:title>
   <news:publication_date>2026-08-17T01:31:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724009</loc>
  <lastmod>2026-08-17T01:31:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実践的な多忠実度ベイズ最適化によるハイパーパラメータ探索（Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning）</news:title>
   <news:publication_date>2026-08-17T01:31:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724007</loc>
  <lastmod>2026-08-17T01:31:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一RGB画像から複雑トポロジーのメッシュを生成する骨格ブリッジ学習（A Skeleton-bridged Deep Learning Approach for Generating Meshes of Complex Topologies from Single RGB Images）</news:title>
   <news:publication_date>2026-08-17T01:31:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724005</loc>
  <lastmod>2026-08-17T00:39:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>転移適応学習の10年サーベイ（Transfer Adaptation Learning: A Decade Survey）</news:title>
   <news:publication_date>2026-08-17T00:39:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/724003</loc>
  <lastmod>2026-08-17T00:39:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なセマンティックセグメンテーションのための知識適応（Knowledge Adaptation for Efficient Semantic Segmentation）</news:title>
   <news:publication_date>2026-08-17T00:39:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/724001</loc>
  <lastmod>2026-08-17T00:39:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層強化学習によるアイス状態の生成（Generation of ice states through deep reinforcement learning）</news:title>
   <news:publication_date>2026-08-17T00:39:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723999</loc>
  <lastmod>2026-08-17T00:38:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リングオシレーターネットワークを用いたハードウェアトロイ検出と教師あり学習の比較（Supervised Machine Learning Techniques for Trojan Detection with Ring Oscillator Network）</news:title>
   <news:publication_date>2026-08-17T00:38:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723997</loc>
  <lastmod>2026-08-17T00:38:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチクラス動的OD需要の推定（Estimating multi-class dynamic origin-destination demand through a forward-backward algorithm on computational graphs）</news:title>
   <news:publication_date>2026-08-17T00:38:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723995</loc>
  <lastmod>2026-08-17T00:37:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時間変動する特徴量を扱う可証明学習アルゴリズム（Provably Correct Learning Algorithms in the Presence of Time-Varying Features Using a Variational Perspective）</news:title>
   <news:publication_date>2026-08-17T00:37:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723993</loc>
  <lastmod>2026-08-17T00:37:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低消費電力識別型深層信念ネットワークのための近似計算フレームワーク（AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks）</news:title>
   <news:publication_date>2026-08-17T00:37:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723991</loc>
  <lastmod>2026-08-16T23:45:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Log-Likelihood Ratio Quantization（Deep Log-Likelihood Ratio Quantization）</news:title>
   <news:publication_date>2026-08-16T23:45:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723989</loc>
  <lastmod>2026-08-16T23:45:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎化されたスパース加法モデル（Generalized Sparse Additive Models）</news:title>
   <news:publication_date>2026-08-16T23:45:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723987</loc>
  <lastmod>2026-08-16T23:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不規則間隔データに対するウェーブレット回帰と加法モデル（Wavelet regression and additive models for irregularly spaced data）</news:title>
   <news:publication_date>2026-08-16T23:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723985</loc>
  <lastmod>2026-08-16T22:51:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>株価バー画像を使ったCNNによるアルゴリズム取引モデル（Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-16T22:51:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723983</loc>
  <lastmod>2026-08-16T22:40:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LEAPによる辺性質の学習（Learning Edge Properties in Graphs from Path Aggregations）</news:title>
   <news:publication_date>2026-08-16T22:40:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723981</loc>
  <lastmod>2026-08-16T22:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ彩色問題とDeep Learningの邂逅（Graph Colouring Meets Deep Learning: Effective Graph Neural Network Models for Combinatorial Problems）</news:title>
   <news:publication_date>2026-08-16T22:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723979</loc>
  <lastmod>2026-08-16T22:39:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>圧縮ビデオ品質向上のための品質ゲート付きConvLSTM（Quality-Gated Convolutional LSTM for Enhancing Compressed Video）</news:title>
   <news:publication_date>2026-08-16T22:39:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723977</loc>
  <lastmod>2026-08-16T22:39:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地球近傍の超新星爆発が示す証拠と示唆（Near-Earth Supernova Explosions: Evidence, Implications, and Opportunities）</news:title>
   <news:publication_date>2026-08-16T22:39:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723975</loc>
  <lastmod>2026-08-16T22:38:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波リズムの出現：EEGデータのモデル解釈（Emergence of Brain Rhythms: Model Interpretation of EEG Data）</news:title>
   <news:publication_date>2026-08-16T22:38:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723973</loc>
  <lastmod>2026-08-16T21:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既知の相互作用だけで薬物相互作用を予測する手法の提案（Detecting drug-drug interactions using artificial neural networks and classic graph similarity measures）</news:title>
   <news:publication_date>2026-08-16T21:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723971</loc>
  <lastmod>2026-08-16T21:46:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モノラル音声改善と認識のギャップを埋める（Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling）</news:title>
   <news:publication_date>2026-08-16T21:46:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723969</loc>
  <lastmod>2026-08-16T21:46:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補助的学習による壊滅的忘却の克服（Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay）</news:title>
   <news:publication_date>2026-08-16T21:46:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723967</loc>
  <lastmod>2026-08-16T21:45:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深い可逆変換で分散MCMCを速く正確にする手法（Embarrassingly parallel MCMC using deep invertible transformations）</news:title>
   <news:publication_date>2026-08-16T21:45:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723965</loc>
  <lastmod>2026-08-16T21:44:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類における意図しないバイアスを多面的に測る指標群（Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification）</news:title>
   <news:publication_date>2026-08-16T21:44:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723963</loc>
  <lastmod>2026-08-16T21:44:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GOGGLESによる自動画像ラベリング（GOGGLES: Automatic Image Labeling with Affinity Coding）</news:title>
   <news:publication_date>2026-08-16T21:44:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723961</loc>
  <lastmod>2026-08-16T21:44:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EDGES低周波スペクトルにおける赤方偏移した21cm信号（THE REDSHIFTED 21-CM SIGNAL IN THE EDGES LOW-BAND SPECTRUM）</news:title>
   <news:publication_date>2026-08-16T21:44:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723959</loc>
  <lastmod>2026-08-16T20:52:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層Seq2Seqを用いた高速Text-to-Speech（Deep Text-to-Speech System with Seq2Seq Model）</news:title>
   <news:publication_date>2026-08-16T20:52:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723957</loc>
  <lastmod>2026-08-16T20:52:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模交通信号制御のためのマルチエージェント深層強化学習（Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control）</news:title>
   <news:publication_date>2026-08-16T20:52:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723955</loc>
  <lastmod>2026-08-16T20:52:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NASAのSDOミッションから作られた機械学習用データセットの意義（A Machine Learning Dataset Prepared From the NASA Solar Dynamics Observatory Mission）</news:title>
   <news:publication_date>2026-08-16T20:52:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723953</loc>
  <lastmod>2026-08-16T20:51:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>巨大衝突の現場で使える機械学習モデル（Realistic On-The-Fly Outcomes of Planetary Collisions: Machine Learning Applied to Simulations of Giant Impacts）</news:title>
   <news:publication_date>2026-08-16T20:51:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723951</loc>
  <lastmod>2026-08-16T20:51:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>会話と転移学習による実用的意味解析（Practical Semantic Parsing for Spoken Language Understanding）</news:title>
   <news:publication_date>2026-08-16T20:51:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723949</loc>
  <lastmod>2026-08-16T20:51:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再電離期の宇宙の相転移をLyαで解き明かす（Unveiling the Phase Transition of the Universe During the Reionization Epoch with Lyα）</news:title>
   <news:publication_date>2026-08-16T20:51:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723947</loc>
  <lastmod>2026-08-16T20:51:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>普遍的な変分量子計算の実現可能性（Universal Variational Quantum Computation）</news:title>
   <news:publication_date>2026-08-16T20:51:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723945</loc>
  <lastmod>2026-08-16T19:59:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小マゼラン雲の個別恒星を用いたTP-AGB段階の制約（Constraining the thermally-pulsing asymptotic giant branch phase with resolved stellar populations in the Small Magellanic Cloud）</news:title>
   <news:publication_date>2026-08-16T19:59:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723943</loc>
  <lastmod>2026-08-16T19:49:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マニフォールド上の行列因子分解としてのクラスタリングの再考（Revisiting clustering as matrix factorisation on the Stiefel manifold）</news:title>
   <news:publication_date>2026-08-16T19:49:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723941</loc>
  <lastmod>2026-08-16T19:49:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ割当モデル：非負テンソル分解とトピックモデルのための逐次モンテカルロ推論（Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Pólya Urns）</news:title>
   <news:publication_date>2026-08-16T19:49:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723939</loc>
  <lastmod>2026-08-16T19:48:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>神経剪定による継続学習（Continual Learning via Neural Pruning）</news:title>
   <news:publication_date>2026-08-16T19:48:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723937</loc>
  <lastmod>2026-08-16T19:47:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>conLSH：文脈を使ってノイズの多い長リードをマッピングする新しいハッシュ法（conLSH: Context based Locality Sensitive Hashing for Mapping of noisy SMRT Reads）</news:title>
   <news:publication_date>2026-08-16T19:47:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723935</loc>
  <lastmod>2026-08-16T19:47:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチメッセンジャー天文学の展望（Opportunities for Multimessenger Astronomy in the 2020s）</news:title>
   <news:publication_date>2026-08-16T19:47:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723933</loc>
  <lastmod>2026-08-16T19:47:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NGC 1533、IC 2038、IC 2039：ドラード群の相互作用する三重銀河（VEGAS: NGC 1533, IC 2038 and IC 2039: an interacting triplet in the Dorado group）</news:title>
   <news:publication_date>2026-08-16T19:47:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723931</loc>
  <lastmod>2026-08-16T18:55:18Z</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スケーリング—キャパシティ配分の視点（Scaling up deep neural networks: a capacity allocation perspective）</news:title>
   <news:publication_date>2026-08-16T18:55:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723929</loc>
  <lastmod>2026-08-16T18:55:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚的コミュニケーションにおける語用論的推論と視覚的抽象化（Pragmatic inference and visual abstraction enable contextual flexibility during visual communication）</news:title>
   <news:publication_date>2026-08-16T18:55:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723927</loc>
  <lastmod>2026-08-16T18:55:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で送信アンテナを賢く選ぶ：Massive MIMO-GSMにおける実証的改善（Transmit Antenna Selection for Massive MIMO-GSM with Machine Learning）</news:title>
   <news:publication_date>2026-08-16T18:55:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723925</loc>
  <lastmod>2026-08-16T18:53:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多層ニューラルネットワークの平均場解析（Mean Field Analysis of Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-16T18:53:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723923</loc>
  <lastmod>2026-08-16T18:53:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M33に対する新規深部JVLA電波サーベイ（A NEW, DEEP JVLA RADIO SURVEY OF M33）</news:title>
   <news:publication_date>2026-08-16T18:53:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723921</loc>
  <lastmod>2026-08-16T18:53:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反応学習戦略が変える反復ゲームの設計（REACTIVE LEARNING STRATEGIES FOR ITERATED GAMES）</news:title>
   <news:publication_date>2026-08-16T18:53:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723919</loc>
  <lastmod>2026-08-16T18:53:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理知識とAIを賢く組み合わせる（Physics Enhanced Artificial Intelligence）</news:title>
   <news:publication_date>2026-08-16T18:53:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723917</loc>
  <lastmod>2026-08-16T18:01:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>インタラクティブ知覚によるアフォーダンス地図の構築（Building an Affordances Map with Interactive Perception）</news:title>
   <news:publication_date>2026-08-16T18:01:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723915</loc>
  <lastmod>2026-08-16T17:53:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Lγ-PageRankによる半教師あり学習（Lγ-PageRank for Semi-Supervised Learning）</news:title>
   <news:publication_date>2026-08-16T17:53:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723913</loc>
  <lastmod>2026-08-16T17:53:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子エンタングルメントスイッチの確率解析（On the Stochastic Analysis of a Quantum Entanglement Switch）</news:title>
   <news:publication_date>2026-08-16T17:53:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723911</loc>
  <lastmod>2026-08-16T17:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡散K平均法による多様体クラスタリング（Diffusion K-means clustering on manifolds: provable exact recovery via semidefinite relaxations）</news:title>
   <news:publication_date>2026-08-16T17:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723909</loc>
  <lastmod>2026-08-16T17:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース深層強化学習による機械の「描画学習」(Learning to Paint With Model-based Deep Reinforcement Learning)</news:title>
   <news:publication_date>2026-08-16T17:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723907</loc>
  <lastmod>2026-08-16T17:52:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分子設計のための深層学習レビュー（Deep learning for molecular design – a review of the state of the art）</news:title>
   <news:publication_date>2026-08-16T17:52:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723905</loc>
  <lastmod>2026-08-16T17:51:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Accuracy BoosterによるCNN性能向上（Accuracy Booster: Performance Boosting using Feature Map Re-calibration）</news:title>
   <news:publication_date>2026-08-16T17:51:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723903</loc>
  <lastmod>2026-08-16T17:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TensorFlowによるHPC評価と実運用への含意（An Evaluation of TensorFlow Performance in HPC Applications）</news:title>
   <news:publication_date>2026-08-16T17:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723901</loc>
  <lastmod>2026-08-16T17:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>原子エネルギー写像によるニューラルネットワークポテンシャルの検証（Atomic energy mapping of neural network potential）</news:title>
   <news:publication_date>2026-08-16T17:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723899</loc>
  <lastmod>2026-08-16T17:00:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SleepNetによる自動睡眠解析（SleepNet: Automated sleep analysis via dense convolutional neural network using physiological time series）</news:title>
   <news:publication_date>2026-08-16T17:00:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723897</loc>
  <lastmod>2026-08-16T16:58:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパイキングニューラルネットワークによる関係推論とニューロモーフィック逆伝播学習（A Spiking Network for Inference of Relations Trained with Neuromorphic Backpropagation）</news:title>
   <news:publication_date>2026-08-16T16:58:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723895</loc>
  <lastmod>2026-08-16T16:58:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベラー・ホット表現による脳波（EEG）てんかん性短時間活動の検出（Labeler-hot Detection of EEG Epileptic Transients）</news:title>
   <news:publication_date>2026-08-16T16:58:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723893</loc>
  <lastmod>2026-08-16T16:58:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>源を差し引いた宇宙赤外背景の背後にある集団（Populations behind the source-subtracted cosmic infrared background anisotropies）</news:title>
   <news:publication_date>2026-08-16T16:58:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723891</loc>
  <lastmod>2026-08-16T16:58:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>所定性能制御を用いた方策改良で時相論理タスクを満たす（Prescribed Performance Control Guided Policy Improvement for Satisfying Signal Temporal Logic Tasks）</news:title>
   <news:publication_date>2026-08-16T16:58:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723889</loc>
  <lastmod>2026-08-16T16:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフライン署名検証における多表現学習とマルチロス・スナップショットアンサンブル（Multi-Representational Learning for Offline Signature Verification using Multi-Loss Snapshot Ensemble of CNNs）</news:title>
   <news:publication_date>2026-08-16T16:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723887</loc>
  <lastmod>2026-08-16T16:05:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPMF: 信頼と嗜好の分割に基づく行列分解型推薦アルゴリズム（SPMF: A Social Trust and Preference Segmentation–based Matrix Factorization Recommendation Algorithm）</news:title>
   <news:publication_date>2026-08-16T16:05:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723885</loc>
  <lastmod>2026-08-16T16:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Recurrent Q-LearningとDeep Q-Learningの比較（Deep Recurrent Q-Learning vs Deep Q-Learning on a simple Partially Observable Markov Decision Process with Minecraft）</news:title>
   <news:publication_date>2026-08-16T16:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723883</loc>
  <lastmod>2026-08-16T16:04:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベクトル流解析を超音波とCNNで実現する可能性（Demonstration of Vector Flow Imaging using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-16T16:04:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723881</loc>
  <lastmod>2026-08-16T16:04:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネル保存埋め込みによる類似度学習（Similarity Learning via Kernel Preserving Embedding）</news:title>
   <news:publication_date>2026-08-16T16:04:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723879</loc>
  <lastmod>2026-08-16T16:04:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習のための勾配降下ベース最適化アルゴリズム（Gradient Descent based Optimization Algorithms for Deep Learning Models Training）</news:title>
   <news:publication_date>2026-08-16T16:04:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723877</loc>
  <lastmod>2026-08-16T16:04:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Manifold Mixupによる文字認識の改善（Manifold Mixup improves text recognition with CTC loss）</news:title>
   <news:publication_date>2026-08-16T16:04:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723875</loc>
  <lastmod>2026-08-16T15:13:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>InceptionGCNによる疾病予測の新地平（InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction）</news:title>
   <news:publication_date>2026-08-16T15:13:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723873</loc>
  <lastmod>2026-08-16T15:13:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>宇宙マイクロ波背景放射のスペクトル歪みが切り拓く新たな観測窓（Spectral Distortions of the CMB as a Probe of Inflation, Recombination, Structure Formation and Particle Physics）</news:title>
   <news:publication_date>2026-08-16T15:13:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723871</loc>
  <lastmod>2026-08-16T15:12:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多様な画像補完（Pluralistic Image Completion）</news:title>
   <news:publication_date>2026-08-16T15:12:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723869</loc>
  <lastmod>2026-08-16T15:12:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散深層学習によるマルチサイトCT血腫セグメンテーションの実務的示唆（Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury）</news:title>
   <news:publication_date>2026-08-16T15:12:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723867</loc>
  <lastmod>2026-08-16T15:11:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周期的不整合と知識蒸留による単眼深度推定の改良（Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation）</news:title>
   <news:publication_date>2026-08-16T15:11:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723865</loc>
  <lastmod>2026-08-16T15:11:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>解釈性から推論へ――汎用近似器の推定フレームワーク（From interpretability to inference: an estimation framework for universal approximators）</news:title>
   <news:publication_date>2026-08-16T15:11:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723863</loc>
  <lastmod>2026-08-16T15:11:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二人の大統領を分ける確率的決闘（A probabilistic duel to distinguish two presidents）</news:title>
   <news:publication_date>2026-08-16T15:11:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723861</loc>
  <lastmod>2026-08-16T14:20:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:publication_date>2026-08-16T14:20:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T14:19:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T14:18:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチ基準学習による高速かつ高精度なニューラル中国語分かち書きの実装（Towards Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning）</news:title>
   <news:publication_date>2026-08-16T14:18:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アップリンク大規模MIMOにおける半ブラインドなチャネル・信号推定（Semi-Blind Channel-and-Signal Estimation for Uplink Massive MIMO With Channel Sparsity）</news:title>
   <news:publication_date>2026-08-16T13:26:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラジオとX線で探る宇宙の衝撃波─宇宙間ガスの可視化に向けた観測戦略（Detecting shocked intergalactic gas with X-ray and radio observations）</news:title>
   <news:publication_date>2026-08-16T13:25:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Fisher-Bures型敵対的グラフ畳み込みネットワーク（Fisher-Bures Adversary Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-08-16T13:25:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T13:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T13:24:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T13:24:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T12:32:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T12:31:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/723829</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T12:30:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T12:30:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723825</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T12:29:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723823</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T12:29:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723821</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T12:28:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723819</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T11:37:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723817</loc>
  <lastmod>2026-08-16T11:37:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T11:37:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723815</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T11:36:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>資産価格付けにおける深層学習の実用革命（Deep Learning in Asset Pricing）</news:title>
   <news:publication_date>2026-08-16T11:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723811</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T11:36:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723809</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T11:35:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723807</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-16T11:35:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-16T10:44:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未知の重力波検出器グリッチを迅速に見つけ出す手法（Classifying the unknown: discovering novel gravitational-wave detector glitches using similarity learning）</news:title>
   <news:publication_date>2026-08-16T10:44:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチバンド観測が開くブラックホール連星研究の新局面（What We Can Learn From Multi-Band Observations of Black Hole Binaries）</news:title>
   <news:publication_date>2026-08-16T10:44:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T10:44:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間データにおける興味ある高密度領域の探索（Exploration of Interesting Dense Regions in Spatial Data）</news:title>
   <news:publication_date>2026-08-16T10:43:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>尤度なしMCMCを可能にする近似比推定器の実装と意義（Likelihood-free Markov chain Monte Carlo with Amortized Approximate Ratio Estimators）</news:title>
   <news:publication_date>2026-08-16T10:43:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一巡で高次元データを圧縮して学ぶ手法の要点と応用（One-Pass Sparsified Gaussian Mixtures）</news:title>
   <news:publication_date>2026-08-16T10:43:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>視覚情報からロボット操作を学ぶ「Affordance」表現の実用化（Affordance Learning for End-to-End Visuomotor Robot Control）</news:title>
   <news:publication_date>2026-08-16T10:42:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T09:51:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T09:50:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-16T09:50:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>最適な共謀フリー教授法（Optimal Collusion-Free Teaching）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-16T09:50:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>車載通信における深層学習ベースの資源割当方式 (A Deep Learning Based Resource Allocation Scheme in Vehicular Communication Systems)</news:title>
   <news:publication_date>2026-08-16T09:50:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-16T09:50:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多項分布ランダムフォレスト：一貫性とプライバシー保存への一歩（Multinomial Random Forest: Toward Consistency and Privacy-Preservation）</news:title>
   <news:publication_date>2026-08-16T09:50:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723779</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>学習ベースの法線フィルタリングによるメッシュノイズ除去（NormalNet: Learning-based Normal Filtering for Mesh Denoising）</news:title>
   <news:publication_date>2026-08-16T09:49:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T08:58:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723775</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-16T08:58:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子診療録における固有表現認識：ルールベースと機械学習アプローチの比較（Named Entity Recognition for Electronic Health Records: A Comparison of Rule-based and Machine Learning Approaches）</news:title>
   <news:publication_date>2026-08-16T08:57:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>限定角度CTのシノグラム補完手法（A Sinogram Inpainting Method based on Generative Adversarial Network for Limited-angle Computed Tomography）</news:title>
   <news:publication_date>2026-08-16T08:57:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723769</loc>
  <lastmod>2026-08-16T08:57:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>位相再構成を深めるDeep Griffin–Lim Iteration（DEEP GRIFFIN–LIM ITERATION）</news:title>
   <news:publication_date>2026-08-16T08:57:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723767</loc>
  <lastmod>2026-08-16T08:57:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングを使った位相制御とOAMビーム生成（Deep learning-based phase control method for coherent beam combining and its application in generating orbital angular momentum beams）</news:title>
   <news:publication_date>2026-08-16T08:57:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723765</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>主観的視覚属性の深層ロバスト予測（Deep Robust Subjective Visual Property Prediction in Crowdsourcing）</news:title>
   <news:publication_date>2026-08-16T08:56:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Haar特徴に基づくカスケード分類器を用いた対象認識と追跡（Object recognition and tracking using Haar-like Features Cascade Classifiers: Application to a quad-rotor UAV）</news:title>
   <news:publication_date>2026-08-16T08:05:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>内積操作による分散SGDの破壊（Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation）</news:title>
   <news:publication_date>2026-08-16T08:05:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723759</loc>
  <lastmod>2026-08-16T08:05:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepTagRec：コンテンツとユーザ関係を統合したタグ推薦フレームワーク（DeepTagRec: A Content-cum-User based Tag Recommendation Framework for Stack Overflow）</news:title>
   <news:publication_date>2026-08-16T08:05:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律ロボットにおける自己適応を可能にする機械学習と定量的プランニング（Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots）</news:title>
   <news:publication_date>2026-08-16T08:04:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習に基づく3D/4D膝MRI領域分割の新手法（Learning-Based Cost Functions for 3D and 4D Multi-Surface Multi-Object Segmentation of Knee MRI）</news:title>
   <news:publication_date>2026-08-16T08:04:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期フェデレーテッド最適化の実践的意義（ASYNCHRONOUS FEDERATED OPTIMIZATION）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723749</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長方形バウンディング過程による効率的な空間分割（Rectangular Bounding Process）</news:title>
   <news:publication_date>2026-08-16T07:13:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723747</loc>
  <lastmod>2026-08-16T07:13:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Shape2Motionによる単一3D形状からの可動部解析（Shape2Motion: Joint Analysis of Motion Parts and Attributes from 3D Shapes）</news:title>
   <news:publication_date>2026-08-16T07:13:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723745</loc>
  <lastmod>2026-08-16T07:13:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロバストな対数損失分類における公平性の統合（Fairness for Robust Log Loss Classification）</news:title>
   <news:publication_date>2026-08-16T07:13:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723743</loc>
  <lastmod>2026-08-16T07:12:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電磁過渡事象の原因同定のための時空間特徴学習（Cause Identification of Electromagnetic Transient Events using Spatiotemporal Feature Learning）</news:title>
   <news:publication_date>2026-08-16T07:12:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723741</loc>
  <lastmod>2026-08-16T07:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー2D/3D剛体位置合わせの実務的意義（Multiview 2D/3D Rigid Registration via a Point-Of-Interest Network for Tracking and Triangulation）</news:title>
   <news:publication_date>2026-08-16T07:12:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723739</loc>
  <lastmod>2026-08-16T07:12:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティクスを保つ敵対的攻撃（Semantics Preserving Adversarial Attacks）</news:title>
   <news:publication_date>2026-08-16T07:12:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723737</loc>
  <lastmod>2026-08-16T07:12:14Z</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>2026-08-16T07:12:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723735</loc>
  <lastmod>2026-08-16T06:20:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GNNExplainerによるグラフニューラルネットワークの説明生成（GNNExplainer: Generating Explanations for Graph Neural Networks）</news:title>
   <news:publication_date>2026-08-16T06:20:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723733</loc>
  <lastmod>2026-08-16T06:19:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNNの構造とショートカットを同時に進化させるハイブリッドGA-PSO（A Hybrid GA-PSO Method for Evolving Architecture and Short Connections of Deep Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-08-16T06:19:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723731</loc>
  <lastmod>2026-08-16T06:19:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非負カーネルスパースコーディングによる動作データ分類（Non-Negative Kernel Sparse Coding for the Classification of Motion Data）</news:title>
   <news:publication_date>2026-08-16T06:19:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723729</loc>
  <lastmod>2026-08-16T06:18:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人は教えるか、ただ動くか――目的学習における人モデルの誤指定を問う（Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective Learning）</news:title>
   <news:publication_date>2026-08-16T06:18:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723727</loc>
  <lastmod>2026-08-16T06:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シーンメモリトランスフォーマーによる長期タスクへの応用（Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks）</news:title>
   <news:publication_date>2026-08-16T06:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723725</loc>
  <lastmod>2026-08-16T06:17:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepPoolによるライドシェア最適化（DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-16T06:17:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723723</loc>
  <lastmod>2026-08-16T06:17:52Z</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>2026-08-16T06:17:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723721</loc>
  <lastmod>2026-08-16T05:25:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多流（マルチストリーム）時系列データの先読みを可能にするFPCAベースの非パラメトリック手法（Functional Principal Component Analysis for Extrapolating Multi-stream Longitudinal Data）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-16T05:25:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/723717</loc>
  <lastmod>2026-08-16T05:25:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>日次電力取引におけるスプレッド密度推定と蓄電運用の最適化（Estimating Dynamic Conditional Spread Densities to Optimise Daily Storage Trading of Electricity）</news:title>
   <news:publication_date>2026-08-16T05:25:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723715</loc>
  <lastmod>2026-08-16T05:24:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BayesODによる物体検出の不確実性推定（BayesOD: A Bayesian Approach for Uncertainty Estimation in Deep Object Detectors）</news:title>
   <news:publication_date>2026-08-16T05:24:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723713</loc>
  <lastmod>2026-08-16T05:24:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラス基盤の最適輸送に関する回復境界とSON正則化枠組み（Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework）</news:title>
   <news:publication_date>2026-08-16T05:24:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723711</loc>
  <lastmod>2026-08-16T05:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>補間一貫性訓練による半教師あり学習の実務的示唆（Interpolation Consistency Training for Semi-Supervised Learning）</news:title>
   <news:publication_date>2026-08-16T05:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723709</loc>
  <lastmod>2026-08-16T05:24:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接触リッチ作業に対するデータ駆動Model Predictive Control（Data-Driven Model Predictive Control for the Contact-Rich Task of Food Cutting）</news:title>
   <news:publication_date>2026-08-16T05:24:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723707</loc>
  <lastmod>2026-08-16T04:33:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッドベイズ軌道最適化による移動計画 (Locomotion Planning through a Hybrid Bayesian Trajectory Optimization)</news:title>
   <news:publication_date>2026-08-16T04:33:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723705</loc>
  <lastmod>2026-08-16T04:32:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>漸進的過剰緩和Q学習（Successive Over-Relaxation Q-Learning）</news:title>
   <news:publication_date>2026-08-16T04:32:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723703</loc>
  <lastmod>2026-08-16T04:32:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>導入物理における「負の性質」枠組みの提示（A framework for the natures of negativity in introductory physics）</news:title>
   <news:publication_date>2026-08-16T04:32:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723701</loc>
  <lastmod>2026-08-16T04:31:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインプログラミングサービス向けゲーティッドグラフ注意ニューラルネットワークによるプログラム分類（Program Classification Using Gated Graph Attention Neural Network for Online Programming Services）</news:title>
   <news:publication_date>2026-08-16T04:31:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723699</loc>
  <lastmod>2026-08-16T04:31:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>直交結合によるワッサースタイン距離推定の改良（Orthogonal Estimation of Wasserstein Distances）</news:title>
   <news:publication_date>2026-08-16T04:31:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723697</loc>
  <lastmod>2026-08-16T04:30:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報理論的手法による汎化誤差の確率的上界の強化（Strengthened Information-theoretic Bounds on the Generalization Error）</news:title>
   <news:publication_date>2026-08-16T04:30:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723695</loc>
  <lastmod>2026-08-16T04:30:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Sparse Switchable Normalization（SSN: Learning Sparse Switchable Normalization via SparsestMax）</news:title>
   <news:publication_date>2026-08-16T04:30:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723693</loc>
  <lastmod>2026-08-16T03:38:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みニューラルネットワークの解釈と理解（Interpreting and Understanding Graph Convolutional Neural Network using Gradient-based Attribution Method）</news:title>
   <news:publication_date>2026-08-16T03:38:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723691</loc>
  <lastmod>2026-08-16T03:38:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分順序プルーニング：速度と精度の最適トレードオフを探すニューラルアーキテクチャ探索（Partial Order Pruning: for Best Speed/Accuracy Trade-off in Neural Architecture Search）</news:title>
   <news:publication_date>2026-08-16T03:38:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723689</loc>
  <lastmod>2026-08-16T03:38:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロジックルール強化による知識グラフ埋め込み（Logic Rules Powered Knowledge Graph Embedding）</news:title>
   <news:publication_date>2026-08-16T03:38:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723687</loc>
  <lastmod>2026-08-16T03:36:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>計算ジョブの予測と分類によるデータセンター運用最適化（Machine Learning Based Prediction and Classification of Computational Jobs in Cloud Computing Centers）</news:title>
   <news:publication_date>2026-08-16T03:36:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723685</loc>
  <lastmod>2026-08-16T03:36:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二段階の歩行が示すPageRank順序（Two-Hop Walks Indicate PageRank Order）</news:title>
   <news:publication_date>2026-08-16T03:36:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723683</loc>
  <lastmod>2026-08-16T03:36:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>M81銀河群の深いHIサーベイ（A 5°×5° deep Hi survey of the M81 group）</news:title>
   <news:publication_date>2026-08-16T03:36:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723681</loc>
  <lastmod>2026-08-16T03:35:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電圧制御問題に対する扱いやすい楕円体近似 (A tractable ellipsoidal approximation for voltage regulation problems)</news:title>
   <news:publication_date>2026-08-16T03:35:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723679</loc>
  <lastmod>2026-08-16T02:43:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>COSMOS領域におけるX線系の分光学的サーベイ（A Spectroscopic Census of X-Ray Systems in the COSMOS Field）</news:title>
   <news:publication_date>2026-08-16T02:43:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723677</loc>
  <lastmod>2026-08-16T02:43:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的シーンにおける疎表現による物体・自己運動推定（Sparse Representations for Object and Ego-motion Estimation in Dynamic Scenes）</news:title>
   <news:publication_date>2026-08-16T02:43:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723675</loc>
  <lastmod>2026-08-16T02:43:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイパーパラメトリックモデルによるロバスト影響力最大化（Robust Influence Maximization for Hyperparametric Models）</news:title>
   <news:publication_date>2026-08-16T02:43:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723673</loc>
  <lastmod>2026-08-16T02:42:28Z</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最適化1ビットプリコーディング（Neural-Network Optimized 1-bit Precoding for Massive MU-MIMO）</news:title>
   <news:publication_date>2026-08-16T02:42:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723671</loc>
  <lastmod>2026-08-16T02:42:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識グラフからルールを導く解釈可能な推薦（Jointly Learning Explainable Rules for Recommendation with Knowledge Graph）</news:title>
   <news:publication_date>2026-08-16T02:42:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723669</loc>
  <lastmod>2026-08-16T02:42:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Stiefel上の制約付き勾配降下による量子グラフィカルモデルの学習 (Learning Quantum Graphical Models using Constrained Gradient Descent on the Stiefel Manifold)</news:title>
   <news:publication_date>2026-08-16T02:42:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723667</loc>
  <lastmod>2026-08-16T02:41:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空を制御する―階層型空中基地局における生存性・カバレッジ・移動則（Control over Skies: Survivability, Coverage, and Mobility Laws for Hierarchical Aerial Base Stations）</news:title>
   <news:publication_date>2026-08-16T02:41:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723665</loc>
  <lastmod>2026-08-16T01:50:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Skew-Fit：状態を網羅する自己監督型強化学習（Skew-Fit: State-Covering Self-Supervised Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-16T01:50:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723663</loc>
  <lastmod>2026-08-16T01:42:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応的電力系統緊急制御における深層強化学習（Adaptive Power System Emergency Control using Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-16T01:42:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723661</loc>
  <lastmod>2026-08-16T01:41:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非コヒーレントMIMOの変調学習（Learning to Modulate for Non-coherent MIMO）</news:title>
   <news:publication_date>2026-08-16T01:41:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723659</loc>
  <lastmod>2026-08-16T01:41:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Deep Learningを用いた2ウェイリレーネットワークの星座最適化（Deep Learning-Based Constellation Optimization for Physical Network Coding in Two-Way Relay Networks）</news:title>
   <news:publication_date>2026-08-16T01:41:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723657</loc>
  <lastmod>2026-08-16T01:40:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胸部X線からの年齢推定（Age prediction using a large chest X-ray dataset）</news:title>
   <news:publication_date>2026-08-16T01:40:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723655</loc>
  <lastmod>2026-08-16T01:40:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NeuTra HMCによる悪いジオメトリの是正（NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport）</news:title>
   <news:publication_date>2026-08-16T01:40:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723653</loc>
  <lastmod>2026-08-16T01:40:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴フィードバックを持つ線形バンディット（Linear Bandits with Feature Feedback）</news:title>
   <news:publication_date>2026-08-16T01:40:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723651</loc>
  <lastmod>2026-08-16T00:49:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画像のプライバシー予測を深層ニューラルネットワークで行う（Image Privacy Prediction Using Deep Neural Networks）</news:title>
   <news:publication_date>2026-08-16T00:49:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723649</loc>
  <lastmod>2026-08-16T00:48:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存知識を効率的に移す視点──マルチビューとしてのLUPIと蒸留の統一的理解（Everything old is new again: A multi-view learning approach to learning using privileged information and distillation）</news:title>
   <news:publication_date>2026-08-16T00:48:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723647</loc>
  <lastmod>2026-08-16T00:48:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低次元における凸体の能動学習（Active-Learning a Convex Body in Low Dimensions）</news:title>
   <news:publication_date>2026-08-16T00:48:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723645</loc>
  <lastmod>2026-08-16T00:47:46Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パーセレイテッド多重解像度ニューラルネットワークによる定量的磁化率逆問題の解法（Quantitative Susceptibility Inversion through Parcellated Multiresolution Neural Networks and K-Space Substitution）</news:title>
   <news:publication_date>2026-08-16T00:47:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-16T00:47:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723639</loc>
  <lastmod>2026-08-16T00:47:03Z</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>2026-08-16T00:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/723637</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>大規模エネルギー収穫ネットワークのオンライン送信電力制御を深層学習で実現する（DEEP LEARNING BASED ONLINE POWER CONTROL FOR LARGE ENERGY HARVESTING NETWORKS）</news:title>
   <news:publication_date>2026-08-15T23:54:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>星形成初期質量関数の変動が示す銀河進化への意味（Variations of the stellar Initial Mass Function in Semi-Analytic Models）</news:title>
   <news:publication_date>2026-08-15T23:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/723633</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>自己対戦で学習する組合せ最適化エージェントの可能性（Learning Self-Game-Play Agents for Combinatorial Optimization Problems）</news:title>
   <news:publication_date>2026-08-15T23:54:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/723631</loc>
  <lastmod>2026-08-15T23:53:37Z</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JLによる特徴ハッシュの理解（Understanding Sparse JL for Feature Hashing）</news:title>
   <news:publication_date>2026-08-15T23:53:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/723629</loc>
  <lastmod>2026-08-15T23:53:30Z</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>2026-08-15T23:53:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723627</loc>
  <lastmod>2026-08-15T23:53:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転の頑健性と安全性を高める敵対的強化学習（Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-15T23:53:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723625</loc>
  <lastmod>2026-08-15T23:53:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RF給電バックスキャッタ通信における干渉回避ゲームの強化学習（Reinforcement Learning for Interference Avoidance Game in RF-Powered Backscatter Communications）</news:title>
   <news:publication_date>2026-08-15T23:53:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723623</loc>
  <lastmod>2026-08-15T23:01:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース変分ガウス過程回帰の収束速度に関する考察（Rates of Convergence for Sparse Variational Gaussian Process Regression）</news:title>
   <news:publication_date>2026-08-15T23:01:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的微分同相（位相保存）登録の教師なし学習（Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces）</news:title>
   <news:publication_date>2026-08-15T22:51:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>触覚で物体を識別する学習（Learning to Identify Object Instances by Touch: Tactile Recognition via Multimodal Matching）</news:title>
   <news:publication_date>2026-08-15T22:51:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2Dアイジンモデルの臨界温度推定を深層学習オートエンコーダで探る（The critical temperature of the 2D-Ising model through Deep Learning Autoencoders）</news:title>
   <news:publication_date>2026-08-15T22:50:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速な深度推定のための2D畳み込みによるコストシグネチャ処理（Fast Deep Stereo with 2D Convolutional Processing of Cost Signatures）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>視覚情報と強化学習を組み合わせた皮膚診断支援の革新（Improving Skin Condition Classification with a Visual Symptom Checker Trained using Reinforcement Learning）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>三者対戦型GANによる難易度の高いサンプル生成と分類器強化（A Three-Player GAN: Generating Hard Samples To Improve Classification Networks）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>GF-2高解像度衛星画像を用いたピクセルベースとオブジェクト指向分類の比較（Research on the pixel-based and object-oriented methods of urban feature extraction with GF-2 remote-sensing images）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T21:57:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>3D複数物体生成の進化：Auto-Encoding Progressive GANs（Auto-Encoding Progressive Generative Adversarial Networks For 3D Multi Object Scenes）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ランダム行列を用いたワッサースタイン距離推定の改良（Random Matrix-Improved Estimation of the Wasserstein Distance between two Centered Gaussian Distributions）</news:title>
   <news:publication_date>2026-08-15T21:05:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>実測データで学ぶ信号復調の深層学習（Deep Learning for Signal Demodulation in Physical Layer Wireless Communications: Prototype Platform, Open Dataset, and Analytics）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学イメージング装置の不確実性対応型性能評価（Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MLWeavingによるGLM高速化（Accelerating Generalized Linear Models with MLWeaving）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>高次元イメージングバイオマーカーを用いた事象ベースモデルによる認知症の空間的進行推定（Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>中性子星データから状態方程式を推定する深層ニューラルネットワーク（Mapping neutron star data to the equation of state using the deep neural network）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T20:11:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723573</loc>
  <lastmod>2026-08-15T20:11:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T20:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>近接最適化問題に深層学習を当てる—駐車違反巡回の近似手法（Approximating Optimisation Solutions for Travelling Officer Problem with Customised Deep Learning Network）</news:title>
   <news:publication_date>2026-08-15T20:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T20:11:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大余裕マージン多重カーネル学習による識別的特徴選択と表現学習 (Large-Margin Multiple Kernel Learning for Discriminative Features Selection and Representation Learning)</news:title>
   <news:publication_date>2026-08-15T20:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723567</loc>
  <lastmod>2026-08-15T19:19:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複素値ゲーテッドオートエンコーダによる映像予測（Complex Valued Gated Auto-encoder for Video Frame Prediction）</news:title>
   <news:publication_date>2026-08-15T19:19:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723565</loc>
  <lastmod>2026-08-15T19:09:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光学・赤外測光データに基づくクエーサー候補選択の効率化（Efficient Selection of Quasar Candidates Based on Optical and Infrared Photometric Data Using Machine Learning）</news:title>
   <news:publication_date>2026-08-15T19:09:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手持ち物の姿勢と形状をRGB画像から推定する研究（Learning to Estimate Pose and Shape of Hand-Held Objects from RGB Images）</news:title>
   <news:publication_date>2026-08-15T19:09:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723561</loc>
  <lastmod>2026-08-15T19:08:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模グラフ上でのヒューリスティクス学習（Learning Heuristics over Large Graphs via Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-08-15T19:08:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723559</loc>
  <lastmod>2026-08-15T19:08:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識を埋め込むルーティングでシーングラフ生成を強化する手法（Knowledge-Embedded Routing Network for Scene Graph Generation）</news:title>
   <news:publication_date>2026-08-15T19:08:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723557</loc>
  <lastmod>2026-08-15T19:08:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3Dメッシュ変形ネットワークの実務的意義（3DN: 3D Deformation Network）</news:title>
   <news:publication_date>2026-08-15T19:08:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T19:07:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Small Data時代におけるファジィ分類器は不要か（Do we still need fuzzy classifiers for Small Data in the Era of Big Data?）</news:title>
   <news:publication_date>2026-08-15T19:07:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723553</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T18:16:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723551</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>証明可能なテンソルリング補完（Provable Tensor Ring Completion）</news:title>
   <news:publication_date>2026-08-15T18:15:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T18:15:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T18:15:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成データから学ぶ群衆計数の実務応用（Learning from Synthetic Data for Crowd Counting in the Wild）</news:title>
   <news:publication_date>2026-08-15T18:14:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723543</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>骨格軌跡に学習される規則性による映像異常検知（Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos）</news:title>
   <news:publication_date>2026-08-15T18:13:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T18:13:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列分類の性能評価を見直すべきか（Should we Reload Time Series Classification Performance Evaluation ?）</news:title>
   <news:publication_date>2026-08-15T18:13:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習者の「混乱」を言語で特定する手法（An Identification of Learners’ Confusion through Language and Discourse Analysis）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T17:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>階層クラス表現学習に基づく属性獲得（Attribute Acquisition in Ontology based on Representation Learning of Hierarchical Classes and Attributes）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723533</loc>
  <lastmod>2026-08-15T17:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>外科トレーニングにおける視覚・触覚シミュレーション概説 (A Survey of Visuo-Haptic Simulation in Surgical Training)</news:title>
   <news:publication_date>2026-08-15T17:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>地平線下の航空機検出に深層学習を適用する意義（Below Horizon Aircraft Detection Using Deep Learning for Vision-Based Sense and Avoid）</news:title>
   <news:publication_date>2026-08-15T17:20:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723529</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723527</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T17:20:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T16:28:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>触覚ユーザインタフェースと実践学習による低侵襲手術トレーニング（Haptic User Interfaces and Practice-based Learning for Minimally Invasive Surgical Training）</news:title>
   <news:publication_date>2026-08-15T16:28:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-08-15T16:27:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T16:27:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T16:26:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-08-15T16:26:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723515</loc>
  <lastmod>2026-08-15T16:26:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超深宇宙ミリ波サーベイが開く新しい宇宙観（Science from an Ultra-Deep, High-Resolution Millimeter-Wave Survey）</news:title>
   <news:publication_date>2026-08-15T16:26:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/723513</loc>
  <lastmod>2026-08-15T16:25:48Z</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>2026-08-15T16:25:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-08-15T15:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要領域を学習して効率的な経路計画を実現する（Learn and Link: Learning Critical Regions for Efficient Planning）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/723501</loc>
  <lastmod>2026-08-15T15:32:18Z</lastmod>
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   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/723499</loc>
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