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   <news:title>乗法的ノイズによる特徴相関効果の除去（Removing the Feature Correlation Effect of Multiplicative Noise）</news:title>
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   <news:title>3D点群に対する敵対的生成の手法（Generating 3D Adversarial Point Clouds）</news:title>
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   <news:title>階層的自然言語生成における言語パターンの順序性の検討（Investigating Linguistic Pattern Ordering in Hierarchical Natural Language Generation）</news:title>
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   <news:title>混合変数データからの確率推定における固有中心性の応用（Using Eigencentrality to Estimate Joint, Conditional and Marginal Probabilities from Mixed-Variable Data: Method and Applications）</news:title>
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   <news:title>Positive-Unlabeled分類における事前確率シフトと非対称誤り（Positive-Unlabeled Classification under Class Prior Shift and Asymmetric Error）</news:title>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>接触力を活かした把持学習（Leveraging Contact Forces for Learning to Grasp）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>GwardarによるSDN保護の新視点（Gwardar: Towards Protecting a Software-Defined Network from Malicious Network Operating Systems）</news:title>
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    <news:language>ja</news:language>
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   <news:title>解釈可能な強化学習とアンサンブル手法（Interpretable Reinforcement Learning with Ensemble Methods）</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ノイズ下における二重振り子ダイナミクスのマニフォールド整合（Aligning Manifolds of Double Pendulum Dynamics Under the Influence of Noise）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>胎児先天性心疾患検出におけるディープラーニングの臨床的意義（Deep-learning models improve on community-level diagnosis for common congenital heart disease lesions）</news:title>
   <news:publication_date>2026-06-15T01:18:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-15T00:27:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ベガ周辺の内側15AUにおける深い惑星探索（A Deep Search for Planets in the Inner 15 AU Around Vega）</news:title>
   <news:publication_date>2026-06-15T00:27:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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    <news:language>ja</news:language>
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   <news:title>データ駆動型クラスタリングとパラメータ化されたLloyd族（Data-Driven Clustering via Parameterized Lloyd’s Families）</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>距離行列の部分線形時間低ランク近似（Sublinear Time Low-Rank Approximation of Distance Matrices）</news:title>
   <news:publication_date>2026-06-15T00:18:35Z</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>FastDeepIoTによるモバイル向けニューラルネット実行時間最適化（FastDeepIoT: Towards Understanding and Optimizing Neural Network Execution Time on Mobile and Embedded Devices）</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>グラフ依存の暗黙的正則化による分散SGD（Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-15T00:17:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>思春期の骨年齢評価に深層学習で挑む：エルボーX線とSauvegrain法の自動化（A Study on Deep Learning Based Sauvegrain Method for Measurement of Puberty Bone Age）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-15T00:16:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>サンプル再重み付けを用いたマルチタスク学習による機械読解の改善（Multi-task Learning with Sample Re-weighting for Machine Reading Comprehension）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-14T23:25:38Z</lastmod>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ポリマーナノピラーにおけるせん断帯形成の構造的指標の同定（Identifying structural signatures of shear banding in polymer nanopillars）</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>チーム編成における探索と活用のトレードオフ（Exploration vs. Exploitation in Team Formation for Collaborative Work）</news:title>
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   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-14T23:15:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Ba1−xNaxFe2As2における出現秩序の分光学的証拠（Spectral Evidence for Emergent Order in Ba1−xNaxFe2As2）</news:title>
   <news:publication_date>2026-06-14T23:15:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-14T23:15:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>予測的集合変数発見と深層ベイズモデル（Predictive Collective Variable Discovery with Deep Bayesian Models）</news:title>
   <news:publication_date>2026-06-14T23:15:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-14T23:14:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>粘塑性流のモデリングへの機械学習の応用（Application of machine learning to viscoplastic flow modeling）</news:title>
   <news:publication_date>2026-06-14T23:14:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-14T23:14:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>電力市場価格予測における深層学習（Power Market Price Forecasting via Deep Learning）</news:title>
   <news:publication_date>2026-06-14T23:14:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-14T23:14:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短発話に対する深層ボトルネック特徴を用いた言語識別（Language Identification with Deep Bottleneck Features）</news:title>
   <news:publication_date>2026-06-14T23:14:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/700753</loc>
  <lastmod>2026-06-14T22:23:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ダイバー追従アルゴリズムの効率と頑健性の両立（Towards a Generic Diver-Following Algorithm: Balancing Robustness and Efficiency in Deep Visual Detection）</news:title>
   <news:publication_date>2026-06-14T22:23:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/700751</loc>
  <lastmod>2026-06-14T22:22:48Z</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学習ダイナミクス（On the Learning Dynamics of Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-14T22:22:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/700749</loc>
  <lastmod>2026-06-14T22:22:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>k-NNとスライディングウィンドウによるMNIST分類（MNIST Dataset Classification Utilizing k-NN Classifier with Modified Sliding-window Metric）</news:title>
   <news:publication_date>2026-06-14T22:22:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/700747</loc>
  <lastmod>2026-06-14T22:21:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Labyrinth: 命令型制御フローを並列データフローへ編纂する技術（Labyrinth: Compiling Imperative Control Flow to Parallel Dataflows）</news:title>
   <news:publication_date>2026-06-14T22:21:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <loc>https://aibr.jp/archives/700745</loc>
  <lastmod>2026-06-14T22:21:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>スパイキングモーメントの伝搬を解析する線形ホークスネットワーク（Propagation of spiking moments in linear Hawkes networks）</news:title>
   <news:publication_date>2026-06-14T22:21:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-14T22:21:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>マルチアクセント音声認識を進化させる生徒–教師学習（ADVANCING MULTI-ACCENTED LSTM-CTC SPEECH RECOGNITION USING A DOMAIN SPECIFIC STUDENT-TEACHER LEARNING PARADIGM）</news:title>
   <news:publication_date>2026-06-14T22:21:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
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  <lastmod>2026-06-14T22:20:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Albumentations：高速で柔軟な画像拡張（Albumentations: fast and flexible image augmentations）</news:title>
   <news:publication_date>2026-06-14T22:20:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700739</loc>
  <lastmod>2026-06-14T21:29:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>拡張可能なNoCベースのニューロモルフィックハードウェアによる学習と推論（Scalable NoC-based Neuromorphic Hardware Learning and Inference）</news:title>
   <news:publication_date>2026-06-14T21:29:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700737</loc>
  <lastmod>2026-06-14T21:28:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所的因果構造を推定するベイズ手法（A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks）</news:title>
   <news:publication_date>2026-06-14T21:28:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700735</loc>
  <lastmod>2026-06-14T21:28:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>埋め込みで冗長性とモデル劣化に立ち向かう（Fighting Redundancy and Model Decay with Embeddings）</news:title>
   <news:publication_date>2026-06-14T21:28:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700733</loc>
  <lastmod>2026-06-14T21:27:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸な論理断片による学習と推論の設計（On a Convex Logic Fragment for Learning and Reasoning）</news:title>
   <news:publication_date>2026-06-14T21:27:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700731</loc>
  <lastmod>2026-06-14T21:27:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BOPからBOSSへ、そしてその先へ：辞書ベース時系列分類の再考（From BOP to BOSS and Beyond: Time Series Classification with Dictionary Based Classifiers）</news:title>
   <news:publication_date>2026-06-14T21:27:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700729</loc>
  <lastmod>2026-06-14T21:27:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TeV–PeV帯ニュートリノ–核子断面積の測定（TeV-PeV neutrino-nucleon cross section measurement with 5 years of IceCube data）</news:title>
   <news:publication_date>2026-06-14T21:27:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700727</loc>
  <lastmod>2026-06-14T21:26:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二乗項測定からの非凸デミキシング（Nonconvex Demixing from Bilinear Measurements）</news:title>
   <news:publication_date>2026-06-14T21:26:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700725</loc>
  <lastmod>2026-06-14T20:35:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>製造プロセスの再構成可能な適応最適制御のための多目的強化学習（Multiobjective Reinforcement Learning for Reconfigurable Adaptive Optimal Control of Manufacturing Processes）</news:title>
   <news:publication_date>2026-06-14T20:35:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700723</loc>
  <lastmod>2026-06-14T20:35:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>名詞–名詞複合語の解釈における転移学習とマルチタスク学習（Transfer and Multi-Task Learning for Noun–Noun Compound Interpretation）</news:title>
   <news:publication_date>2026-06-14T20:35:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700721</loc>
  <lastmod>2026-06-14T20:35:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>区間に連続的に到達するよう条件付けされた安定過程（STABLE PROCESSES CONDITIONED TO HIT AN INTERVAL CONTINUOUSLY FROM THE OUTSIDE）</news:title>
   <news:publication_date>2026-06-14T20:35:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700719</loc>
  <lastmod>2026-06-14T20:34:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>頻度非依存型単語表現（FRAGE: Frequency-Agnostic Word Representation）</news:title>
   <news:publication_date>2026-06-14T20:34:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700717</loc>
  <lastmod>2026-06-14T20:34:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ナノ光学における5つの全方位最適化手法の比較（Benchmarking five global optimization approaches for nano-optical shape optimization and parameter reconstruction）</news:title>
   <news:publication_date>2026-06-14T20:34:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700715</loc>
  <lastmod>2026-06-14T20:33:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二値転帰に対するベイズ最適治療規程の推定（Estimating Bayesian Optimal Treatment Regimes for Dichotomous Outcomes using Observational Data）</news:title>
   <news:publication_date>2026-06-14T20:33:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700713</loc>
  <lastmod>2026-06-14T20:33:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続特徴量に強い回転フォレストの有効性（Is rotation forest the best classifier for problems with continuous features?）</news:title>
   <news:publication_date>2026-06-14T20:33:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700711</loc>
  <lastmod>2026-06-14T19:41:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復視覚刺激を用いた多尺度相対固有ファジーエントロピーによる片頭痛前兆検出（SSVEP-based multi-scale relative inherent fuzzy entropy for migraine detection）</news:title>
   <news:publication_date>2026-06-14T19:41:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700709</loc>
  <lastmod>2026-06-14T19:41:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非構造3Dメッシュ上での内在的対応学習の単純な手法（A Simple Approach to Intrinsic Correspondence Learning on Unstructured 3D Meshes）</news:title>
   <news:publication_date>2026-06-14T19:41:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700707</loc>
  <lastmod>2026-06-14T19:41:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>属性認識を組み込んだ顔老化とWavelet GAN（Attribute-aware Face Aging with Wavelet-based Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-14T19:41:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700705</loc>
  <lastmod>2026-06-14T19:40:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エピソディック固定ホライズン製造プロセスのモデルフリー最適制御（Model-Free Adaptive Optimal Control of Episodic Fixed-Horizon Manufacturing Processes using Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-14T19:40:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700703</loc>
  <lastmod>2026-06-14T19:40:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Additive Bayesian Networksにおける適切な事前分布の比較（Comparison between Suitable Priors for Additive Bayesian Networks）</news:title>
   <news:publication_date>2026-06-14T19:40:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700701</loc>
  <lastmod>2026-06-14T19:39:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きな横方向運動量でのトップ生成の精度向上（Top production at large pt at NLO+NLL accuracy）</news:title>
   <news:publication_date>2026-06-14T19:39:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700699</loc>
  <lastmod>2026-06-14T19:39:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模2次元トーリック符号に対するニューラルネットワークデコーダ（Neural Network Decoders for Large-Distance 2D Toric Codes）</news:title>
   <news:publication_date>2026-06-14T19:39:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700697</loc>
  <lastmod>2026-06-14T18:48:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実行時ニューロン活性パターンの監視（Runtime Monitoring Neuron Activation Patterns）</news:title>
   <news:publication_date>2026-06-14T18:48:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700695</loc>
  <lastmod>2026-06-14T18:43:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>改良型3DTV正則化とハイパースペクトル画像応用（Enhanced 3DTV Regularization and Its Applications on Hyper-spectral Image Denoising and Compressed Sensing）</news:title>
   <news:publication_date>2026-06-14T18:43:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700693</loc>
  <lastmod>2026-06-14T18:43:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>平均-最大注意オートエンコーダによる普遍的な文表現学習 (Learning Universal Sentence Representations with Mean-Max Attention Autoencoder)</news:title>
   <news:publication_date>2026-06-14T18:43:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700691</loc>
  <lastmod>2026-06-14T18:43:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SCC-rFMQによる連続行動協調学習（SCC-rFMQ Learning in Cooperative Markov Games with Continuous Actions）</news:title>
   <news:publication_date>2026-06-14T18:43:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700689</loc>
  <lastmod>2026-06-14T18:42:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータ空間ノイズによる等方性・方向性探索の切替（Switching Isotropic and Directional Exploration with Parameter Space Noise in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-14T18:42:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700687</loc>
  <lastmod>2026-06-14T18:41:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Macroblock ScalingによるCNNモデル圧縮の実務的インパクト（MBS: Macroblock Scaling for CNN Model Reduction）</news:title>
   <news:publication_date>2026-06-14T18:41:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700685</loc>
  <lastmod>2026-06-14T18:41:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAVによる水圧管検査のためのU-Net：多クラスセグメンテーションにおけるフォーカル損失の検討 (U-Net for MAV-based Penstock Inspection: an Investigation of Focal Loss in Multi-class Segmentation for Corrosion Identification)</news:title>
   <news:publication_date>2026-06-14T18:41:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700683</loc>
  <lastmod>2026-06-14T17:50:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像超解像の新アプローチ：決定論的–確率的合成と局所統計補正（Image Super-Resolution via Deterministic-Stochastic Synthesis and Local Statistical Rectification）</news:title>
   <news:publication_date>2026-06-14T17:50:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700681</loc>
  <lastmod>2026-06-14T17:49:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー情報を活用する意味フレーム解析の高速化と少データ化（User Information Augmented Semantic Frame Parsing using Coarse-to-Fine Neural Networks）</news:title>
   <news:publication_date>2026-06-14T17:49:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700679</loc>
  <lastmod>2026-06-14T17:48:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>不均衡な多相配電網のトポロジ推定とバス相同定（Unbalanced Multi-Phase Distribution Grid Topology Estimation and Bus Phase Identification）</news:title>
   <news:publication_date>2026-06-14T17:48:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700677</loc>
  <lastmod>2026-06-14T17:48:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人体のテクスチャ付き3D再構成（Deep Textured 3D Reconstruction of Human Bodies）</news:title>
   <news:publication_date>2026-06-14T17:48:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700675</loc>
  <lastmod>2026-06-14T17:48:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変動計量フォワード・バックワード分割アルゴリズムの収束解析（Convergence analysis of a variable metric forward-backward splitting algorithm with applications）</news:title>
   <news:publication_date>2026-06-14T17:48:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700673</loc>
  <lastmod>2026-06-14T17:48:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転のためのマルチモーダル軌道予測（Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks）</news:title>
   <news:publication_date>2026-06-14T17:48:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700671</loc>
  <lastmod>2026-06-14T17:47:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル保護型マルチタスク学習の要点（Model-Protected Multi-Task Learning）</news:title>
   <news:publication_date>2026-06-14T17:47:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700669</loc>
  <lastmod>2026-06-14T16:56:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形分類における実行可能な救済手段（Actionable Recourse in Linear Classification）</news:title>
   <news:publication_date>2026-06-14T16:56:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700667</loc>
  <lastmod>2026-06-14T16:56:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラメータレス確率的自然勾配法による離散最適化とニューラルネットワークのハイパーパラメータ最適化（Parameterless Stochastic Natural Gradient Method for Discrete Optimization）</news:title>
   <news:publication_date>2026-06-14T16:56:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700665</loc>
  <lastmod>2026-06-14T16:56:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大の光学応答を求めて：2次元材料の可能性（In Pursuit of 2D Materials for Maximum Optical Response）</news:title>
   <news:publication_date>2026-06-14T16:56:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700663</loc>
  <lastmod>2026-06-14T16:55:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HashTran‑DNNによるマルウェア検出の堅牢化（HashTran‑DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples）</news:title>
   <news:publication_date>2026-06-14T16:55:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700661</loc>
  <lastmod>2026-06-14T16:55:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-14T16:55:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700659</loc>
  <lastmod>2026-06-14T16:54:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セッション内での個人化による人材検索の最前線（In-Session Personalization for Talent Search）</news:title>
   <news:publication_date>2026-06-14T16:54:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700657</loc>
  <lastmod>2026-06-14T16:54:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層化乱流の“二つの原子”から学ぶ深層学習による混合効率予測（Deep learning of mixing by two ‘atoms’ of stratified turbulence）</news:title>
   <news:publication_date>2026-06-14T16:54:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700655</loc>
  <lastmod>2026-06-14T16:03:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LinkedInにおけるタレント検索と推薦の実務課題（Talent Search and Recommendation Systems at LinkedIn: Practical Challenges and Lessons Learned）</news:title>
   <news:publication_date>2026-06-14T16:03:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700653</loc>
  <lastmod>2026-06-14T16:02:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロ次元非凸確率的最適化の扱い（Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality and Saddle-Points）</news:title>
   <news:publication_date>2026-06-14T16:02:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700651</loc>
  <lastmod>2026-06-14T16:02:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンサンブルによる能動異常検知の実務的意義（Active Anomaly Detection via Ensembles）</news:title>
   <news:publication_date>2026-06-14T16:02:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700649</loc>
  <lastmod>2026-06-14T16:01:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タレントサーチにおける深層表現学習の実装と示唆（Towards Deep and Representation Learning for Talent Search at LinkedIn）</news:title>
   <news:publication_date>2026-06-14T16:01:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700647</loc>
  <lastmod>2026-06-14T16:01:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ推論とガウス過程の堅牢性保証（Robustness Guarantees for Bayesian Inference with Gaussian Processes）</news:title>
   <news:publication_date>2026-06-14T16:01:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700645</loc>
  <lastmod>2026-06-14T16:01:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己構成による機械学習の層別訓練法（Self-Configuration in Machine Learning）</news:title>
   <news:publication_date>2026-06-14T16:01:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700643</loc>
  <lastmod>2026-06-14T16:00:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mask Editor：不規則形状のための画像マスク編集ツール（Mask Editor : an Image Annotation Tool for Image Segmentation Tasks）</news:title>
   <news:publication_date>2026-06-14T16:00:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700641</loc>
  <lastmod>2026-06-14T15:08:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パラフレーズによる堅牢な音声言語理解（Robust Spoken Language Understanding via Paraphrasing）</news:title>
   <news:publication_date>2026-06-14T15:08:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700639</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>2026-06-14T14:49:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700637</loc>
  <lastmod>2026-06-14T14:48:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeClarEによる証拠対応型の信頼性評価（DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700635</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>遅延電圧回復のPMUによる監視と緩和（PMU-based Monitoring and Mitigation of Delayed Voltage Recovery using Admittances）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700633</loc>
  <lastmod>2026-06-14T14:47:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エンパワーメント正則化を用いた敵対的模倣学習（Adversarial Imitation via Variational Inverse Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-14T14:47:50Z</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>2026-06-14T14:47:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700629</loc>
  <lastmod>2026-06-14T14:47:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分観測マルコフ決定過程向けHMM推定に基づくQ学習（Hidden Markov Model Estimation-Based Q-learning for Partially Observable Markov Decision Process）</news:title>
   <news:publication_date>2026-06-14T14:47:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700627</loc>
  <lastmod>2026-06-14T13:56:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限次元での連続性だけで収束する射影分割（Projective Splitting with Forward Steps only Requires Continuity）</news:title>
   <news:publication_date>2026-06-14T13:56:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700625</loc>
  <lastmod>2026-06-14T13:56:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>運転データから動作プリミティブを学習し分割する手法（Learning to Segment and Represent Motion Primitives from Driving Data for Motion Planning Applications）</news:title>
   <news:publication_date>2026-06-14T13:56:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700623</loc>
  <lastmod>2026-06-14T13:55:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-14T13:55:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700621</loc>
  <lastmod>2026-06-14T13:54:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層マルチタスク学習による分子表現の転移可能性向上（Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks）</news:title>
   <news:publication_date>2026-06-14T13:54:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700619</loc>
  <lastmod>2026-06-14T13:53:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リンゴの花検出に深層畳み込みネットワークを使う意義（Apple Flower Detection using Deep Convolutional Networks）</news:title>
   <news:publication_date>2026-06-14T13:53:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700617</loc>
  <lastmod>2026-06-14T13:53:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多目的報酬関数にまたがる一般化を目指す深層強化学習（Generalizing Across Multi-Objective Reward Functions in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-14T13:53:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700615</loc>
  <lastmod>2026-06-14T13:53:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラベルフリー3次元光干渉顕微鏡画像の深層学習による支援診断（Computer-Aided Diagnosis of Label-Free 3-D Optical Coherence Microscopy Images）</news:title>
   <news:publication_date>2026-06-14T13:53:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700613</loc>
  <lastmod>2026-06-14T13:01:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オートマトンで導く示範付き強化学習（Automata Guided Reinforcement Learning With Demonstrations）</news:title>
   <news:publication_date>2026-06-14T13:01:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700611</loc>
  <lastmod>2026-06-14T13:01:40Z</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/700609</loc>
  <lastmod>2026-06-14T13:01:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非可分ペナルティを扱う近似メッセージパッシング（Approximate message-passing for convex optimization with non-separable penalties）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700607</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>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700605</loc>
  <lastmod>2026-06-14T13:00:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚ベースのシャドウ巧手のテレオペレーション（Vision-based Teleoperation of Shadow Dexterous Hand using End-to-End Deep Neural Network）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700603</loc>
  <lastmod>2026-06-14T13:00:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB-Dを用いたシーン認識のための有効表現学習（Learning Effective RGB-D Representations for Scene Recognition）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700601</loc>
  <lastmod>2026-06-14T13:00:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適行列モーメンタム確率近似とQ学習への適用（Optimal Matrix Momentum Stochastic Approximation and Applications to Q-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: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>有限フェルミオン鎖における端間相関の設計（Engineering large end-to-end correlations in finite fermionic chains）</news:title>
   <news:publication_date>2026-06-14T12:08:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700595</loc>
  <lastmod>2026-06-14T12:08:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチシナリオランキングの協調学習（Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-14T12:08:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700593</loc>
  <lastmod>2026-06-14T12:08:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>少数データから指示を学ぶ高速で柔軟な訓練法（The Fast and the Flexible: training neural networks to learn to follow instructions from small data）</news:title>
   <news:publication_date>2026-06-14T12:08:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700591</loc>
  <lastmod>2026-06-14T12:08:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同じ写真由来の落とし穴：視覚的血縁判定データセットに潜む“チート”手法（FROM SAME PHOTO: CHEATING ON VISUAL KINSHIP CHALLENGES）</news:title>
   <news:publication_date>2026-06-14T12:08:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700589</loc>
  <lastmod>2026-06-14T12:07:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子統計に着想を得たニューラル注意（Quantum Statistics-Inspired Neural Attention）</news:title>
   <news:publication_date>2026-06-14T12:07:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700587</loc>
  <lastmod>2026-06-14T12:07:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>中間層深層特徴の圧縮—インテリジェントセンシングの次の戦場（Intermediate Deep Feature Compression: the Next Battlefield of Intelligent Sensing）</news:title>
   <news:publication_date>2026-06-14T12:07:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700585</loc>
  <lastmod>2026-06-14T11:16:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワークトポロジーによるボット分類 (A Network Topology Approach to Bot Classification)</news:title>
   <news:publication_date>2026-06-14T11:16:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700583</loc>
  <lastmod>2026-06-14T11:08:10Z</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CNNによる脳腫瘍セグメンテーション（Multi Modal Convolutional Neural Networks for Brain Tumor Segmentation）</news:title>
   <news:publication_date>2026-06-14T11:08:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700581</loc>
  <lastmod>2026-06-14T11:07:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>密度変化に強い適応型DBSCAN（ADBSCAN: Adaptive Density-Based Spatial Clustering of Applications with Noise for Identifying Clusters with Varying Densities）</news:title>
   <news:publication_date>2026-06-14T11:07:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700579</loc>
  <lastmod>2026-06-14T11:06:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ゼロ例ビデオ検索のための二重エンコーディング（Dual Encoding for Zero-Example Video Retrieval）</news:title>
   <news:publication_date>2026-06-14T11:06:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700577</loc>
  <lastmod>2026-06-14T11:06:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>KNN・SVM・LMNN・ENNの精度変動に関する観察研究（Study and Observation of the Variation of Accuracies of KNN, SVM, LMNN, ENN）</news:title>
   <news:publication_date>2026-06-14T11:06:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700575</loc>
  <lastmod>2026-06-14T11:06:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書き数字認識における隠れ層と学習回数の影響（Study and Observation of the Variations of Accuracies for Handwritten Digits Recognition with Various Hidden Layers and Epochs using Convolutional Neural Network）</news:title>
   <news:publication_date>2026-06-14T11:06:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700573</loc>
  <lastmod>2026-06-14T11:05:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書き数字認識における隠れ層とエポック数の精度変動の観察（Study and Observation of the Variations of Accuracies for Handwritten Digits Recognition with Various Hidden Layers and Epochs using Neural Network Algorithm）</news:title>
   <news:publication_date>2026-06-14T11:05:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700571</loc>
  <lastmod>2026-06-14T10:14:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自律型水中ロボットのマルチコンテキスト学習（Learning of Multi-Context Models for Autonomous Underwater Vehicles）</news:title>
   <news:publication_date>2026-06-14T10:14:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700569</loc>
  <lastmod>2026-06-14T10:13:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実世界電波信号における変調分類の実力（The Importance of Being Earnest: Performance of Modulation Classification for Real RF Signals）</news:title>
   <news:publication_date>2026-06-14T10:13:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700567</loc>
  <lastmod>2026-06-14T10:13:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>逆散乱を用いた幾何学的ボディ生成の機械学習的アプローチ（An Inverse Scattering Approach for Geometric Body Generation: A Machine Learning Perspective）</news:title>
   <news:publication_date>2026-06-14T10:13:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700565</loc>
  <lastmod>2026-06-14T10:11:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注ぎ動作の動的推定に関するRNNの応用（Dynamics Estimation Using Recurrent Neural Network）</news:title>
   <news:publication_date>2026-06-14T10:11:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700563</loc>
  <lastmod>2026-06-14T10:11:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造方程式モデルの正則化推定を凸化する手法（Convex Formulation for Regularized Estimation of Structural Equation Models）</news:title>
   <news:publication_date>2026-06-14T10:11:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700561</loc>
  <lastmod>2026-06-14T10:11:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Feature2Mass: 潜在空間での視覚特徴処理による現実的なラベル付き腫瘤生成（Feature2Mass: Visual Feature Processing in Latent Space for Realistic Labeled Mass Generation）</news:title>
   <news:publication_date>2026-06-14T10:11:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700559</loc>
  <lastmod>2026-06-14T10:10:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アイスキューブ信号分類のためのグラフニューラルネットワーク（Graph Neural Networks for IceCube Signal Classification）</news:title>
   <news:publication_date>2026-06-14T10:10:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700557</loc>
  <lastmod>2026-06-14T09:19:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カリキュラムによる目標マスキングで連続値強化学習を効率化する（Curriculum Goal Masking for Continuous Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-14T09:19:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700555</loc>
  <lastmod>2026-06-14T09:19:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OpenSubtitlesに基づく六言語パラフレーズコーパス（Open Subtitles Paraphrase Corpus for Six Languages）</news:title>
   <news:publication_date>2026-06-14T09:19:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700553</loc>
  <lastmod>2026-06-14T09:19:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>商業ビルにおける短期過去からの行動予測の学習（Learning short-term past as predictor of human behavior in commercial buildings）</news:title>
   <news:publication_date>2026-06-14T09:19:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700551</loc>
  <lastmod>2026-06-14T09:18:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重み付きSVMに対するスパン誤差境界と実務的ハイパーパラメータ選定（Span error bound for weighted SVM with applications in hyperparameter selection）</news:title>
   <news:publication_date>2026-06-14T09:18:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700549</loc>
  <lastmod>2026-06-14T09:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドラムリズム生成の条件付き適応ニューラルネットワーク（DeepDrum: An Adaptive Conditional Neural Network for generating drum rhythms）</news:title>
   <news:publication_date>2026-06-14T09:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700547</loc>
  <lastmod>2026-06-14T09:18:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>教師なし深層学習による画像レジストレーションの枠組み（A Deep Learning Framework for Unsupervised Affine and Deformable Image Registration）</news:title>
   <news:publication_date>2026-06-14T09:18:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700545</loc>
  <lastmod>2026-06-14T09:17:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチノミアルロジスティック回帰の初期化を見直す（Revisit Multinomial Logistic Regression in Deep Learning: Data Dependent Model Initialization for Image Recognition）</news:title>
   <news:publication_date>2026-06-14T09:17:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700543</loc>
  <lastmod>2026-06-14T08:27:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>cf2vec: Collaborative Filteringにおける分散表現を用いたアルゴリズム選択（cf2vec: Collaborative Filtering algorithm selection using graph distributed representations）</news:title>
   <news:publication_date>2026-06-14T08:27:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700541</loc>
  <lastmod>2026-06-14T08:26:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>筋活動推定に深層強化学習を使う意義（Muscle Excitation Estimation in Biomechanical Simulation Using NAF Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-14T08:26:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700539</loc>
  <lastmod>2026-06-14T08:26:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ドープした二層BiHにおけるキラルおよびヘリカルp波超伝導（Chiral and helical p-wave superconductivity in doped bilayer BiH）</news:title>
   <news:publication_date>2026-06-14T08:26:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700537</loc>
  <lastmod>2026-06-14T08:26:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オブジェクト感覚型深層強化学習（Object-sensitive Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-14T08:26:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700535</loc>
  <lastmod>2026-06-14T08:25:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>重要度サンプリングによる方策最適化（Policy Optimization via Importance Sampling）</news:title>
   <news:publication_date>2026-06-14T08:25:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700533</loc>
  <lastmod>2026-06-14T08:25:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理層通信におけるモデル駆動型深層学習（Model-Driven Deep Learning for Physical Layer Communications）</news:title>
   <news:publication_date>2026-06-14T08:25:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700531</loc>
  <lastmod>2026-06-14T08:25:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepEfficiencyによる高次元効率補正の新手法（DeepEfficiency - optimal efficiency inversion in higher dimensions at the LHC）</news:title>
   <news:publication_date>2026-06-14T08:25:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700529</loc>
  <lastmod>2026-06-14T07:34:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバー探索を活用した量子学習（A Grover-search Based Quantum Learning Scheme for Classification）</news:title>
   <news:publication_date>2026-06-14T07:34:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700527</loc>
  <lastmod>2026-06-14T07:33:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シリコンのドーピング限界を破る深い不純物（Breaking the doping limit in silicon by deep impurities）</news:title>
   <news:publication_date>2026-06-14T07:33:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700525</loc>
  <lastmod>2026-06-14T07:33:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>都市環境データを使ったマルコフ基盤の歩行者予測（Building Prior Knowledge: A Markov Based Pedestrian Prediction Model Using Urban Environmental Data）</news:title>
   <news:publication_date>2026-06-14T07:33:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700523</loc>
  <lastmod>2026-06-14T07:32:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳画像研究における認知表現の抽出が脳デコーディングを改善する（Extracting representations of cognition across neuroimaging studies improves brain decoding）</news:title>
   <news:publication_date>2026-06-14T07:32:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700521</loc>
  <lastmod>2026-06-14T07:32:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成的xベクトルによる話者認証の改良（GENERATIVE X-VECTORS FOR TEXT-INDEPENDENT SPEAKER VERIFICATION）</news:title>
   <news:publication_date>2026-06-14T07:32:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700519</loc>
  <lastmod>2026-06-14T07:32:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スキャッタリングネットワークによるハイブリッド表現学習（Scattering Networks for Hybrid Representation Learning）</news:title>
   <news:publication_date>2026-06-14T07:32:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700517</loc>
  <lastmod>2026-06-14T07:32:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多人数バンディット問題に対するトレッキング手法（Multi-Player Bandits: A Trekking Approach）</news:title>
   <news:publication_date>2026-06-14T07:32:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700515</loc>
  <lastmod>2026-06-14T06:41:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元スパースSIRの凸的定式化（A convex formulation for high-dimensional sparse sliced inverse regression）</news:title>
   <news:publication_date>2026-06-14T06:41:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700513</loc>
  <lastmod>2026-06-14T06:41:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最小限の注文板取引所シミュレータ（BSE: A Minimal Simulation of a Limit-Order-Book Stock Exchange）</news:title>
   <news:publication_date>2026-06-14T06:41:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700511</loc>
  <lastmod>2026-06-14T06:40:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習で導くスパースセンサー配置の貪欲アルゴリズム（Greedy Algorithms for Sparse Sensor Placement via Deep Learning）</news:title>
   <news:publication_date>2026-06-14T06:40:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700509</loc>
  <lastmod>2026-06-14T06:39:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サイバーフィジカルシステムにおける学習ベースの攻撃（Learning-based Attacks in Cyber-Physical Systems）</news:title>
   <news:publication_date>2026-06-14T06:39:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700507</loc>
  <lastmod>2026-06-14T06:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カーネルリッジ回帰の統計的・計算効率の高い分散推定法（Statistically and Computationally Efficient Variance Estimator for Kernel Ridge Regression）</news:title>
   <news:publication_date>2026-06-14T06:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700505</loc>
  <lastmod>2026-06-14T06:39:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>記録と脳画像の統合解析を行う記憶ベースのグラフ畳み込みネットワーク（Integrative Analysis of Patient Health Records and Neuroimages via Memory-based Graph Convolutional Network）</news:title>
   <news:publication_date>2026-06-14T06:39:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700503</loc>
  <lastmod>2026-06-14T06:39:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DASNetによる画素注釈削減とセグメンテーション精度の両立（DASNet: Reducing Pixel-level Annotations for Instance and Semantic Segmentation）</news:title>
   <news:publication_date>2026-06-14T06:39:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700501</loc>
  <lastmod>2026-06-14T05:48:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サンプリングに基づく不確かさ推定におけるマージ戦略の評価（Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection）</news:title>
   <news:publication_date>2026-06-14T05:48:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700499</loc>
  <lastmod>2026-06-14T05:48:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層ニューラルネットワークにおける不確実性伝播を拡張カルマンフィルタで扱う（Uncertainty Propagation in Deep Neural Networks Using Extended Kalman Filtering）</news:title>
   <news:publication_date>2026-06-14T05:48:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700497</loc>
  <lastmod>2026-06-14T05:47:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オープンワールド学習と製品分類への応用（Open-world Learning and Application to Product Classification）</news:title>
   <news:publication_date>2026-06-14T05:47:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700495</loc>
  <lastmod>2026-06-14T05:47:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FermiNetsとGenerative Synthesisが切り拓くエッジAIの効率化（FermiNets: Learning generative machines to generate efficient neural networks via generative synthesis）</news:title>
   <news:publication_date>2026-06-14T05:47:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700493</loc>
  <lastmod>2026-06-14T05:47:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ正則化行列因子分解による不完全マルチビュークラスタリング（Incomplete Multi-view Clustering via Graph Regularized Matrix Factorization）</news:title>
   <news:publication_date>2026-06-14T05:47:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700491</loc>
  <lastmod>2026-06-14T05:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッド普遍的ブラインド量子計算（A Hybrid Universal Blind Quantum Computation）</news:title>
   <news:publication_date>2026-06-14T05:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700489</loc>
  <lastmod>2026-06-14T05:46:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模マルチビュー画像クラスタリングの高効率バイナリ圧縮（Highly-Economized Multi-View Binary Compression for Scalable Image Clustering）</news:title>
   <news:publication_date>2026-06-14T05:46:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700487</loc>
  <lastmod>2026-06-14T04:56:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>潜在空間における最適輸送を用いた生成モデル（Latent Space Optimal Transport for Generative Models）</news:title>
   <news:publication_date>2026-06-14T04:56:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700485</loc>
  <lastmod>2026-06-14T04:55:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話応答の情報量最大化による多様で有益な生成（Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization）</news:title>
   <news:publication_date>2026-06-14T04:55:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700483</loc>
  <lastmod>2026-06-14T04:55:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層提案ベースモデルに対する頑強な敵対的摂動（Robust Adversarial Perturbation on Deep Proposal-based Models）</news:title>
   <news:publication_date>2026-06-14T04:55:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700481</loc>
  <lastmod>2026-06-14T04:54:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一2D透視画像からの3D経路計画（3D Path Planning from a Single 2D Fluoroscopic Image for Robot Assisted Fenestrated Endovascular Aortic Repair）</news:title>
   <news:publication_date>2026-06-14T04:54:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700479</loc>
  <lastmod>2026-06-14T04:54:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>科学画像処理のための分散学習アーキテクチャ（A Distributed Learning Architecture for Scientific Imaging Problems）</news:title>
   <news:publication_date>2026-06-14T04:54:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700477</loc>
  <lastmod>2026-06-14T04:54:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>観測ラベルのノイズを扱う深層生成モデル（A Deep Generative Model for Semi-Supervised Classification with Noisy Labels）</news:title>
   <news:publication_date>2026-06-14T04:54:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700475</loc>
  <lastmod>2026-06-14T04:53:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Mrk 6の拡張放射フィラメント（A close look at the well-known Seyfert galaxy: extended emission filaments in Mrk 6）</news:title>
   <news:publication_date>2026-06-14T04:53:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700473</loc>
  <lastmod>2026-06-14T04:02:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変式道路標識（VMS）と利用者適応を組み込んだ日次動的交通配分モデル（Day-to-day dynamic traffic assignment model with variable message signs and endogenous user compliance）</news:title>
   <news:publication_date>2026-06-14T04:02:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700471</loc>
  <lastmod>2026-06-14T04:02:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最大エントロピーによる細分類学習の再考（Maximum Entropy Fine-Grained Classification）</news:title>
   <news:publication_date>2026-06-14T04:02:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700469</loc>
  <lastmod>2026-06-14T04:02:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さな深さのPTF回路に対する#SATアルゴリズム（A #SAT Algorithm for Small Constant-Depth Circuits with PTF gates）</news:title>
   <news:publication_date>2026-06-14T04:02:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700467</loc>
  <lastmod>2026-06-14T04:01:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カリキュラムに基づく近傍置換サンプリングによる系列予測の改善（Curriculum-Based Neighborhood Sampling For Sequence Prediction）</news:title>
   <news:publication_date>2026-06-14T04:01:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700465</loc>
  <lastmod>2026-06-14T04:01:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Hindsight学習の改良（Improvements on Hindsight Learning）</news:title>
   <news:publication_date>2026-06-14T04:01:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700463</loc>
  <lastmod>2026-06-14T04:01:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス分類を巡る総合的整理（Solving for multi-class: a survey and synthesis）</news:title>
   <news:publication_date>2026-06-14T04:01:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700461</loc>
  <lastmod>2026-06-14T04:01:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーミング学習におけるメモリ効率的なリハーサル（Memory Efficient Experience Replay for Streaming Learning）</news:title>
   <news:publication_date>2026-06-14T04:01:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700459</loc>
  <lastmod>2026-06-14T03:09:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メッシュCNN：エッジで捉える3Dメッシュ解析（MeshCNN: A Network with an Edge）</news:title>
   <news:publication_date>2026-06-14T03:09:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700457</loc>
  <lastmod>2026-06-14T03:09:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロセスインスタンス分類における再帰型ニューラルネットワークの応用（Classifying Process Instances Using Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-06-14T03:09:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700455</loc>
  <lastmod>2026-06-14T03:09:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>滑らかな多様体上の線形楕円偏微分方程式解の近似（Approximating solutions of linear elliptic PDE’s on a smooth manifold using local kernel）</news:title>
   <news:publication_date>2026-06-14T03:09:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700453</loc>
  <lastmod>2026-06-14T03:08:28Z</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と古典的機械学習のマルウェア検出比較（Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection）</news:title>
   <news:publication_date>2026-06-14T03:08:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700451</loc>
  <lastmod>2026-06-14T03:08:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり検出からの知識蒸留によるマルチラベル画像分類（Multi-Label Image Classification via Knowledge Distillation from Weakly-Supervised Detection）</news:title>
   <news:publication_date>2026-06-14T03:08:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700449</loc>
  <lastmod>2026-06-14T03:08:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタ埋め込みを補助タスクとして用いる正則化（Meta-Embedding as Auxiliary Task Regularization）</news:title>
   <news:publication_date>2026-06-14T03:08:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700447</loc>
  <lastmod>2026-06-14T03:07:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いたマルウェア検出の実証（An investigation of a deep learning based malware detection system）</news:title>
   <news:publication_date>2026-06-14T03:07:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700445</loc>
  <lastmod>2026-06-14T02:16:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動運転車における歩行者検出のためのFPGA高速化設計（An FPGA-Accelerated Design for Deep Learning Pedestrian Detection in Self-Driving Vehicles）</news:title>
   <news:publication_date>2026-06-14T02:16:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700443</loc>
  <lastmod>2026-06-14T02:16:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>集計データから個体推定するデータ分析基盤（A Data Analytics Framework for Aggregate Data Analysis）</news:title>
   <news:publication_date>2026-06-14T02:16:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700441</loc>
  <lastmod>2026-06-14T02:15:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>環境ノイズに強い道路検出のフィルタリング技術 (Road Detection Technique Using Filters for Autonomous Driving Systems)</news:title>
   <news:publication_date>2026-06-14T02:15:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700439</loc>
  <lastmod>2026-06-14T02:14:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Inspiration Learning through Preferences（Inspiration Learning through Preferences）</news:title>
   <news:publication_date>2026-06-14T02:14:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700437</loc>
  <lastmod>2026-06-14T02:14:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>短期認知ネットワークと非シナプス学習（Short-term Cognitive Networks, Flexible Reasoning and Nonsynaptic Learning）</news:title>
   <news:publication_date>2026-06-14T02:14:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700435</loc>
  <lastmod>2026-06-14T02:14:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン学習による線形動力学系の実用的示唆（On-Line Learning of Linear Dynamical Systems: Exponential Forgetting in Kalman Filters）</news:title>
   <news:publication_date>2026-06-14T02:14:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700433</loc>
  <lastmod>2026-06-14T02:14:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続時間ロバスト動的計画法（Continuous-Time Robust Dynamic Programming）</news:title>
   <news:publication_date>2026-06-14T02:14:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700431</loc>
  <lastmod>2026-06-14T01:22:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類損失による人物再識別の再評価（In Defense of the Classification Loss for Person Re-Identification）</news:title>
   <news:publication_date>2026-06-14T01:22:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700429</loc>
  <lastmod>2026-06-14T01:22:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>f-VAEsによるVAE改良（f-VAEs: Improve VAEs with Conditional Flows）</news:title>
   <news:publication_date>2026-06-14T01:22:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700427</loc>
  <lastmod>2026-06-14T01:21:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何学的一貫性を用いた片側教師なしドメインマッピング（Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping）</news:title>
   <news:publication_date>2026-06-14T01:21:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700425</loc>
  <lastmod>2026-06-14T01:21:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スループット最適化された非連続ワイドバンドスペクトラムセンシング（Throughput Optimized Non-Contiguous Wideband Spectrum Sensing via Online Learning and Sub-Nyquist Sampling）</news:title>
   <news:publication_date>2026-06-14T01:21:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700423</loc>
  <lastmod>2026-06-14T01:21:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音楽様式の統計的進化法則（Statistical Evolutionary Laws in Music Styles）</news:title>
   <news:publication_date>2026-06-14T01:21:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700421</loc>
  <lastmod>2026-06-14T01:21:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用マルチモーダル動的ジェスチャ認識システム（A Generic Multi-modal Dynamic Gesture Recognition System using Machine Learning）</news:title>
   <news:publication_date>2026-06-14T01:21:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700419</loc>
  <lastmod>2026-06-14T01:20:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フォグロボティクスによる動的ビジュアルサーボの実現（A Fog Robotic System for Dynamic Visual Servoing）</news:title>
   <news:publication_date>2026-06-14T01:20:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700417</loc>
  <lastmod>2026-06-14T00:30:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Unbiased LambdaMARTによる順位学習の脱バイアス（Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm）</news:title>
   <news:publication_date>2026-06-14T00:30:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700415</loc>
  <lastmod>2026-06-14T00:30:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限体上における線形独立成分分析（Linear Independent Component Analysis over Finite Fields: Algorithms and Bounds）</news:title>
   <news:publication_date>2026-06-14T00:30:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700413</loc>
  <lastmod>2026-06-14T00:23:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>見た目を学習して服を勧める ― 美的特徴を用いた衣服推薦（Aesthetic-based Clothing Recommendation）</news:title>
   <news:publication_date>2026-06-14T00:23:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700411</loc>
  <lastmod>2026-06-14T00:22:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメイン・ラベル付けLDAによる文書分類の実務的理解（Cross-Domain Labeled LDA for Cross-Domain Text Classification）</news:title>
   <news:publication_date>2026-06-14T00:22:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700409</loc>
  <lastmod>2026-06-14T00:22:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>経験ランク付け畳み込みニューラルネットワークを用いた深層学習（Deep Learning with Experience Ranking Convolutional Neural Network for Robot Manipulator）</news:title>
   <news:publication_date>2026-06-14T00:22:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700407</loc>
  <lastmod>2026-06-14T00:21:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重メモリネットワークによる偏りある製品レビューの感情分類（Dual Memory Network Model for Biased Product Review Classification）</news:title>
   <news:publication_date>2026-06-14T00:21:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700405</loc>
  <lastmod>2026-06-14T00:21:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>糖尿病に関する自由記述ノートを分類する深層学習の開発（Development of deep learning algorithms to categorize free-text notes pertaining to diabetes）</news:title>
   <news:publication_date>2026-06-14T00:21:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700403</loc>
  <lastmod>2026-06-13T23:29:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>接触を考慮したロボット制御のための価値関数区間からの学習（LVIS: Learning from Value Function Intervals for Contact-Aware Robot Controllers）</news:title>
   <news:publication_date>2026-06-13T23:29:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700401</loc>
  <lastmod>2026-06-13T23:28:51Z</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の直接訓練（Direct Training for Spiking Neural Networks: Faster, Larger, Better）</news:title>
   <news:publication_date>2026-06-13T23:28:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700399</loc>
  <lastmod>2026-06-13T23:28:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>状態ベースゲームにおける戦略的学習アルゴリズム（A Strategic Learning Algorithm for State-based Games）</news:title>
   <news:publication_date>2026-06-13T23:28:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700397</loc>
  <lastmod>2026-06-13T23:28:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BioASQ6におけるAUEBの文書・スニペット検索（AUEB at BioASQ 6: Document and Snippet Retrieval）</news:title>
   <news:publication_date>2026-06-13T23:28:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700395</loc>
  <lastmod>2026-06-13T23:27:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートフォンのWi‑Fi信号で移動手段を推定する研究（Mobility Mode Detection Using WiFi Signals）</news:title>
   <news:publication_date>2026-06-13T23:27:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700393</loc>
  <lastmod>2026-06-13T23:27:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GANVOによる単眼視からの自己教師なしカメラ位置推定と深度生成（GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-06-13T23:27:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700391</loc>
  <lastmod>2026-06-13T23:27:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生成機械学習で潜在的な移動行動特性を捉える（Modelling Latent Travel Behaviour Characteristics with Generative Machine Learning）</news:title>
   <news:publication_date>2026-06-13T23:27:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700389</loc>
  <lastmod>2026-06-13T22:36:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Agar.io攻略のためのサンプリング方策勾配（Sampled Policy Gradient for Learning to Play the Game Agar.io）</news:title>
   <news:publication_date>2026-06-13T22:36:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700387</loc>
  <lastmod>2026-06-13T22:35:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UAVとNOMAの組合せが拓く大規模接続の地平（UAV Communications Based on Non-Orthogonal Multiple Access）</news:title>
   <news:publication_date>2026-06-13T22:35:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700385</loc>
  <lastmod>2026-06-13T22:35:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超充電された光配列の設計（Supercharge optical arrays）</news:title>
   <news:publication_date>2026-06-13T22:35:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700383</loc>
  <lastmod>2026-06-13T22:35:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文字の細かな差分を学習する仕組み（Finding the way from ¨a to a: Sub-character morphological inflection for the SIGMORPHON 2018 Shared Task）</news:title>
   <news:publication_date>2026-06-13T22:35:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700381</loc>
  <lastmod>2026-06-13T22:34:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外部知識を用いたNLIの改善（Improving Natural Language Inference Using External Knowledge in the Science Questions Domain）</news:title>
   <news:publication_date>2026-06-13T22:34:57Z</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>
   </news:publication>
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   <news:publication_date>2026-06-13T22:34:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700377</loc>
  <lastmod>2026-06-13T22:34:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチスケール深層圧縮センシングネットワーク（Multi-Scale Deep Compressive Sensing Network）</news:title>
   <news:publication_date>2026-06-13T22:34:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700375</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>陽性データと未ラベルデータからの分類器とクラス事前確率の交互推定（Alternate Estimation of a Classifier and the Class-Prior from Positive and Unlabeled Data）</news:title>
   <news:publication_date>2026-06-13T21:43:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700373</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/700371</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>ガイド付き方策探索による生成的モータ反射で堅牢な操作スキルを学習する（Learning Robust Manipulation Skills with Guided Policy Search via Generative Motor Reflexes）</news:title>
   <news:publication_date>2026-06-13T21:43:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700369</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>観測器設計における敵対的強化学習の実用可能性（Adversarial Reinforcement Learning for Observer Design in Autonomous Systems under Cyber Attacks）</news:title>
   <news:publication_date>2026-06-13T21:42:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700367</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>CLUSEによるクロスリンガル語義埋め込みの提案（CLUSE: Cross-Lingual Unsupervised Sense Embeddings）</news:title>
   <news:publication_date>2026-06-13T21:42:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700365</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>ニューラルネットワークを人工仕様に用いる試み（Neural Networks as Artificial Specifications）</news:title>
   <news:publication_date>2026-06-13T21:42:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700363</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>2017トルコ国民投票におけるTwitter利用者の政治的志向推定（Inferring Political Alignments of Twitter Users）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700361</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>2026-06-13T20:50:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700359</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>再現性を担保する決定論的実装（Deterministic Implementations for Reproducibility in Deep Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-13T20:45:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700357</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>apk2vecによるAndroidアプリの半教師ありマルチビュー表現学習（apk2vec: Semi-supervised multi-view representation learning for profiling Android applications）</news:title>
   <news:publication_date>2026-06-13T20:40:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700355</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>テキスト分類のためのグラフ畳み込みネットワーク（Graph Convolutional Networks for Text Classification）</news:title>
   <news:publication_date>2026-06-13T20:39:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700353</loc>
  <lastmod>2026-06-13T20:39:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OffsetNet：レンダリング画像を用いた肺内位置推定の深層学習（OffsetNet: Deep Learning for Localization in the Lung using Rendered Images）</news:title>
   <news:publication_date>2026-06-13T20:39:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700351</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>2026-06-13T20:38:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700349</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/700347</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>正則化二次スコアで学ぶ高次元グラフィカルモデル（Learning high-dimensional graphical models with regularized quadratic scoring）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700345</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/700343</loc>
  <lastmod>2026-06-13T19:47:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メール検索ランキングのためのマルチタスク学習と補助クエリクラスタリング（Multi-Task Learning for Email Search Ranking with Auxiliary Query Clustering）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700341</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700339</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700337</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>全結合層の非反復再計算によるDCNN学習高速化と性能向上（Non-iterative recomputation of dense layers for performance improvement of DCNN）</news:title>
   <news:publication_date>2026-06-13T19:46:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700335</loc>
  <lastmod>2026-06-13T19:46:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用ホールドアウト（The Generic Holdout: Preventing False-Discoveries in Adaptive Data Science）</news:title>
   <news:publication_date>2026-06-13T19:46:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700333</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>エントロピック最適輸送と最尤デコンボリューション（Entropic optimal transport is maximum-likelihood deconvolution）</news:title>
   <news:publication_date>2026-06-13T18:55:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700331</loc>
  <lastmod>2026-06-13T18:47:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700329</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:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700327</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:publication_date>2026-06-13T18:46:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700325</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>視覚を伴う強化学習の挙動可視化（Visual Diagnostics for Deep Reinforcement Learning Policy Development）</news:title>
   <news:publication_date>2026-06-13T18:45:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700323</loc>
  <lastmod>2026-06-13T18:44:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機能的MRIからの脳状態復元におけるLSTM再帰型ニューラルネットワークの活用（Brain decoding from functional MRI using long short-term memory recurrent neural networks）</news:title>
   <news:publication_date>2026-06-13T18:44:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700321</loc>
  <lastmod>2026-06-13T18:44:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-13T18:44:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700319</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:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/700317</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>メムリスタに基づく深層畳み込みニューラルネットワークの事例研究（Memristor-based Deep Convolution Neural Network: A Case Study）</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>
  <loc>https://aibr.jp/archives/700313</loc>
  <lastmod>2026-06-13T17:52:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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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>
   <news:title>適応型量子強化位相推定の堅牢性（Robustness of Adaptive Quantum-Enhanced Phase Estimation）</news:title>
   <news:publication_date>2026-06-13T17:52:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700307</loc>
  <lastmod>2026-06-13T17:52:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な構造化予測における代理損失と正則化の工夫（Efficient Structured Surrogate Loss and Regularization in Structured Prediction）</news:title>
   <news:publication_date>2026-06-13T17:52:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700305</loc>
  <lastmod>2026-06-13T17:00:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模神経記録における活動電位圧縮のための深層圧縮オートエンコーダ（Deep Compressive Autoencoder for Action Potential Compression in Large-Scale Neural Recording）</news:title>
   <news:publication_date>2026-06-13T17:00:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700303</loc>
  <lastmod>2026-06-13T17:00:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一ショット画像からの量子相転移検出（Identifying Quantum Phase Transitions using Artificial Neural Networks on Experimental Data）</news:title>
   <news:publication_date>2026-06-13T17:00:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700301</loc>
  <lastmod>2026-06-13T17:00:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計学習に基づく超高信頼低遅延通信の設計（A Statistical Learning Approach to Ultra-Reliable Low Latency Communication）</news:title>
   <news:publication_date>2026-06-13T17:00:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700299</loc>
  <lastmod>2026-06-13T16:59:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチカメラ車載視覚による位置推定と3D認識（Project AutoVision: Localization and 3D Scene Perception for an Autonomous Vehicle with a Multi-Camera System）</news:title>
   <news:publication_date>2026-06-13T16:59:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700297</loc>
  <lastmod>2026-06-13T16:59:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データから意思決定へつなぐ学習法（Melding the Data‑Decisions Pipeline: Decision‑Focused Learning for Combinatorial Optimization）</news:title>
   <news:publication_date>2026-06-13T16:59:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700295</loc>
  <lastmod>2026-06-13T16:59:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音響物理モデルの複数段階パラメータ推定アルゴリズム（A Multi-Stage Algorithm for Acoustic Physical Model Parameters Estimation）</news:title>
   <news:publication_date>2026-06-13T16:59:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700293</loc>
  <lastmod>2026-06-13T16:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ストリーム処理の自動チューニングを強化学習で実現する（Auto-tuning Distributed Stream Processing Systems using Reinforcement Learning）</news:title>
   <news:publication_date>2026-06-13T16:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700291</loc>
  <lastmod>2026-06-13T16:07:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特徴選択におけるスクリーニング手法の有用性（Are screening methods useful in feature selection? An empirical study）</news:title>
   <news:publication_date>2026-06-13T16:07:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700289</loc>
  <lastmod>2026-06-13T16:07:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェアを意識した機械学習がもたらす変化（Hardware-Aware Machine Learning: Modeling and Optimization）</news:title>
   <news:publication_date>2026-06-13T16:07:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700287</loc>
  <lastmod>2026-06-13T16:07:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー嗜好を取り込むベイズ多目的最適化：期待重み付きハイパーボリューム改善基準（User preferences in Bayesian multi-objective optimization: the expected weighted hypervolume improvement criterion）</news:title>
   <news:publication_date>2026-06-13T16:07:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700285</loc>
  <lastmod>2026-06-13T16:06:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フェムト秒レーザーで駆動するテラヘルツ級スピン—電荷変換の制御（Femtosecond control of terahertz spin-charge conversion in ferromagnetic heterostructures）</news:title>
   <news:publication_date>2026-06-13T16:06:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700283</loc>
  <lastmod>2026-06-13T16:06:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自由分数（Free Fractions: An Invitation to (applied) Free Fields）</news:title>
   <news:publication_date>2026-06-13T16:06:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700281</loc>
  <lastmod>2026-06-13T16:05:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多段ホップ同質性によるネットワーク分類（Multi-hop assortativities for network classification）</news:title>
   <news:publication_date>2026-06-13T16:05:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700279</loc>
  <lastmod>2026-06-13T16:05:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SCORESによる3D形状合成の再考（SCORES: Shape Composition with Recursive Substructure Priors）</news:title>
   <news:publication_date>2026-06-13T16:05:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700277</loc>
  <lastmod>2026-06-13T15:14:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群に基づくグラフ学習のためのマルチカーネル拡散CNN（Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds）</news:title>
   <news:publication_date>2026-06-13T15:14:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700275</loc>
  <lastmod>2026-06-13T15:13:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カテゴリ単位で学ぶ把持技能の転移（Transferring Category-based Functional Grasping Skills by Latent Space Non-Rigid Registration）</news:title>
   <news:publication_date>2026-06-13T15:13:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700273</loc>
  <lastmod>2026-06-13T15:13:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シミュレーションと実機実験を組み合わせた二足歩行のベイズ最適化（Combining Simulations and Real-robot Experiments for Bayesian Optimization of Bipedal Gait Stabilization）</news:title>
   <news:publication_date>2026-06-13T15:13:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700271</loc>
  <lastmod>2026-06-13T15:12:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子密度の転移可能な機械学習モデル（A Transferable Machine-Learning Model of the Electron Density）</news:title>
   <news:publication_date>2026-06-13T15:12:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700269</loc>
  <lastmod>2026-06-13T15:12:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ的学習を使った高速反復型組合せオークション（Fast Iterative Combinatorial Auctions via Bayesian Learning）</news:title>
   <news:publication_date>2026-06-13T15:12:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700267</loc>
  <lastmod>2026-06-13T15:12:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚音声言語モデル（Visual Speech Language Models）</news:title>
   <news:publication_date>2026-06-13T15:12:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700265</loc>
  <lastmod>2026-06-13T15:12:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Adaptive Samplingで高速化するグラフ表現学習（Towards Fast Graph Representation Learning）</news:title>
   <news:publication_date>2026-06-13T15:12:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700263</loc>
  <lastmod>2026-06-13T14:20:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高精度な分極率予測を機械学習で実現する道（Accurate molecular polarizabilities with coupled-cluster theory and machine learning）</news:title>
   <news:publication_date>2026-06-13T14:20:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700261</loc>
  <lastmod>2026-06-13T14:20:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復収縮閾値付けによる非凸罰則での効率的なランク最小化（Efficient Rank Minimization via Solving Non-convex Penalties by Iterative Shrinkage-Thresholding Algorithm）</news:title>
   <news:publication_date>2026-06-13T14:20:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700259</loc>
  <lastmod>2026-06-13T14:20:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自然言語処理から学んだ教訓による深層CNNフレーム補間（Deep CNN Frame Interpolation with Lessons Learned from Natural Language Processing）</news:title>
   <news:publication_date>2026-06-13T14:20:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700257</loc>
  <lastmod>2026-06-13T14:18:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>質問の「言い回し」を指紋化する手法（Learning to Fingerprint the Latent Structure in Question Articulation）</news:title>
   <news:publication_date>2026-06-13T14:18:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700255</loc>
  <lastmod>2026-06-13T14:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黙的最適事前分布を持つ変分オートエンコーダ（Variational Autoencoder with Implicit Optimal Priors）</news:title>
   <news:publication_date>2026-06-13T14:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700253</loc>
  <lastmod>2026-06-13T14:18:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>キーポイントベースの弱教師ありヒューマンパーシング（Keypoint Based Weakly Supervised Human Parsing）</news:title>
   <news:publication_date>2026-06-13T14:18:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700251</loc>
  <lastmod>2026-06-13T14:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Macquarie UniversityによるBioASQ 6bへの挑戦：深層学習と深層強化学習によるクエリ指向多文書要約 (Deep learning and deep reinforcement learning for query-based multi-document summarisation)</news:title>
   <news:publication_date>2026-06-13T14:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700249</loc>
  <lastmod>2026-06-13T13:26:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定性的対戦バンディット問題（Dueling Bandits with Qualitative Feedback）</news:title>
   <news:publication_date>2026-06-13T13:26:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700247</loc>
  <lastmod>2026-06-13T13:26:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バイオメディカルデータのクエリベース抽出型要約のための教師あり機械学習（Supervised Machine Learning for Extractive Query Based Summarisation of Biomedical Data）</news:title>
   <news:publication_date>2026-06-13T13:26:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700245</loc>
  <lastmod>2026-06-13T13:26:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心臓MRIにおける左心室のセグメンテーションと容積推定（Left Ventricle Segmentation and Volume Estimation on Cardiac MRI using Deep Learning）</news:title>
   <news:publication_date>2026-06-13T13:26:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700243</loc>
  <lastmod>2026-06-13T13:25:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スマートグリッドにおけるオンラインサイバー攻撃検知（Online Cyber-Attack Detection in Smart Grid: A Reinforcement Learning Approach）</news:title>
   <news:publication_date>2026-06-13T13:25:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700241</loc>
  <lastmod>2026-06-13T13:25:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク再構築（Network Recasting: A Universal Method for Network Architecture Transformation）</news:title>
   <news:publication_date>2026-06-13T13:25:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700239</loc>
  <lastmod>2026-06-13T13:24:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SQLクエリを自然文で説明する仕組み（SQL-to-Text Generation with Graph-to-Sequence Model）</news:title>
   <news:publication_date>2026-06-13T13:24:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700237</loc>
  <lastmod>2026-06-13T13:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Random Warping Series: 時系列埋め込みのためのランダム特徴法（Random Warping Series: A Random Features Method for Time-Series Embedding）</news:title>
   <news:publication_date>2026-06-13T13:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700235</loc>
  <lastmod>2026-06-13T12:33:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>変形医療画像登録の学習フレームワーク（VoxelMorph: A Learning Framework for Deformable Medical Image Registration）</news:title>
   <news:publication_date>2026-06-13T12:33:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700233</loc>
  <lastmod>2026-06-13T12:32:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザ定義の部分グラフ関係によるパターンマイニングと学習（Graph Pattern Mining and Learning through User-defined Relations）</news:title>
   <news:publication_date>2026-06-13T12:32:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700231</loc>
  <lastmod>2026-06-13T12:24:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>抑制性ヘッブ学習による時間的連想記憶の拡張（Extended temporal association memory by inhibitory Hebbian learning）</news:title>
   <news:publication_date>2026-06-13T12:24:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700229</loc>
  <lastmod>2026-06-13T12:23:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムビニング特徴量の再訪：高速収束と強い並列化性（Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability）</news:title>
   <news:publication_date>2026-06-13T12:23:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700227</loc>
  <lastmod>2026-06-13T12:23:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元データのリアルタイム非パラメトリック異常検知（Real-Time Nonparametric Anomaly Detection in High-Dimensional Settings）</news:title>
   <news:publication_date>2026-06-13T12:23:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700225</loc>
  <lastmod>2026-06-13T12:22:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長さ制御付き変分オートエンコーダによる教師なし抽象的文要約（Unsupervised Abstractive Sentence Summarization using Length Controlled Variational Autoencoder）</news:title>
   <news:publication_date>2026-06-13T12:22:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700223</loc>
  <lastmod>2026-06-13T12:22:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース訓練のためのニューラルネットワーク位相（Neural Network Topologies for Sparse Training）</news:title>
   <news:publication_date>2026-06-13T12:22:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700221</loc>
  <lastmod>2026-06-13T11:31:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>眼底画像からの緑内障スクリーニングと視神経乳頭・盲点分割の改良（Enhanced Optic Disk and Cup Segmentation with Glaucoma Screening from Fundus Images using Position encoded CNNs）</news:title>
   <news:publication_date>2026-06-13T11:31:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700219</loc>
  <lastmod>2026-06-13T11:31:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>法的文書からの自動キャッチフレーズ抽出（Automatic Catchphrase Extraction from Legal Case Documents via Scoring using Deep Neural Networks）</news:title>
   <news:publication_date>2026-06-13T11:31:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700217</loc>
  <lastmod>2026-06-13T11:30:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動デバイアス機械学習による因果・構造効果推定（AUTOMATIC DEBIASED MACHINE LEARNING OF CAUSAL AND STRUCTURAL EFFECTS）</news:title>
   <news:publication_date>2026-06-13T11:30:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700215</loc>
  <lastmod>2026-06-13T11:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>協調型マルチゴール・多段階マルチエージェント強化学習（CM3: COOPERATIVE MULTI-GOAL MULTI-STAGE MULTI-AGENT REINFORCEMENT LEARNING）</news:title>
   <news:publication_date>2026-06-13T11:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700213</loc>
  <lastmod>2026-06-13T11:29:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データを用いた肝臓腫瘍のグラフカット画像分割法（A Time Series Graph Cut Image Segmentation Scheme for Liver Tumors）</news:title>
   <news:publication_date>2026-06-13T11:29:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700211</loc>
  <lastmod>2026-06-13T11:29:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデルベース強化学習をメタ最適化で強化する手法（Model-Based Reinforcement Learning via Meta-Policy Optimization）</news:title>
   <news:publication_date>2026-06-13T11:29:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700209</loc>
  <lastmod>2026-06-13T11:29:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療画像解析におけるGANの応用（GANs for Medical Image Analysis）</news:title>
   <news:publication_date>2026-06-13T11:29:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700207</loc>
  <lastmod>2026-06-13T10:37:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プレイ・バイ・プレイデータから選手の役割を識別する手法（Distinguishing between roles of football players in play-by-play match event data）</news:title>
   <news:publication_date>2026-06-13T10:37:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700205</loc>
  <lastmod>2026-06-13T10:37:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データの説明可能な改変手法（Explainable time series tweaking via irreversible and reversible temporal transformations）</news:title>
   <news:publication_date>2026-06-13T10:37:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700203</loc>
  <lastmod>2026-06-13T10:36:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>パスに基づくサッカー選手の「オン・ザ・ボール」貢献の定量化（Measuring football players’ on-the-ball contributions from passes during games）</news:title>
   <news:publication_date>2026-06-13T10:36:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700201</loc>
  <lastmod>2026-06-13T10:36:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スムーズなM推定量の決定的不等式（Deterministic Inequalities for Smooth M-estimators）</news:title>
   <news:publication_date>2026-06-13T10:36:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700199</loc>
  <lastmod>2026-06-13T10:36:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>敵対的攻撃に対する深層ニューラルネットワーク強化のための防御的ドロップアウト（Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks）</news:title>
   <news:publication_date>2026-06-13T10:36:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700197</loc>
  <lastmod>2026-06-13T10:35:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ワイヤレスセンサーのスケジューリングを強化学習で最適化する（Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber-Physical Systems）</news:title>
   <news:publication_date>2026-06-13T10:35:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700195</loc>
  <lastmod>2026-06-13T10:35:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>イベント駆動制御のための深層強化学習 (Deep Reinforcement Learning for Event-Triggered Control)</news:title>
   <news:publication_date>2026-06-13T10:35:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700193</loc>
  <lastmod>2026-06-13T09:44:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全球球体再構築(GSR)の独立実装（The Global sphere reconstruction (GSR): Demonstrating an independent implementation of the astrometric core solution for Gaia）</news:title>
   <news:publication_date>2026-06-13T09:44:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700191</loc>
  <lastmod>2026-06-13T09:44:31Z</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とゲーミフィケーションによるエネルギー削減の実証（A Deep Learning and Gamification Approach to Energy Conservation at Nanyang Technological University）</news:title>
   <news:publication_date>2026-06-13T09:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700189</loc>
  <lastmod>2026-06-13T09:44:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>可変精度データに対するガウス過程分類（Gaussian Process Classification for Variable Fidelity Data）</news:title>
   <news:publication_date>2026-06-13T09:44:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700187</loc>
  <lastmod>2026-06-13T09:43:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランキングを選ぶ──選択から作るランキングモデル（Choosing to Rank）</news:title>
   <news:publication_date>2026-06-13T09:43:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700185</loc>
  <lastmod>2026-06-13T09:43:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FliPerによる星の表面重力推定（FliPer: Flicker in Power）</news:title>
   <news:publication_date>2026-06-13T09:43:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700183</loc>
  <lastmod>2026-06-13T09:43:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>エッジラベルを活用したネットワーク埋め込み強化（Enhanced Network Embeddings via Exploiting Edge Labels）</news:title>
   <news:publication_date>2026-06-13T09:43:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700181</loc>
  <lastmod>2026-06-13T09:43:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IL-Netによる分岐型ニューラルネットワーク設計の教科書化（IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural Networks）</news:title>
   <news:publication_date>2026-06-13T09:43:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700179</loc>
  <lastmod>2026-06-13T08:52:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ケンタウルスA衛星銀河の微光端における光度関数（The faint end of the Centaurus A satellite luminosity function）</news:title>
   <news:publication_date>2026-06-13T08:52:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700177</loc>
  <lastmod>2026-06-13T08:52:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行方向排他ビクラスタリングによる遺伝子発現解析（Exclusive Row Biclustering for Gene Expression Using a Combinatorial Auction Approach）</news:title>
   <news:publication_date>2026-06-13T08:52:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700175</loc>
  <lastmod>2026-06-13T08:51:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>社会的ジレンマにおける同調と報酬模倣の競合と協調（Competition and partnership between conformity and payoff-based imitations in social dilemmas）</news:title>
   <news:publication_date>2026-06-13T08:51:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700173</loc>
  <lastmod>2026-06-13T08:51:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>周波数ビン量子ビットに対する制御NOTゲートの実装（A controlled-NOT gate for frequency-bin qubits）</news:title>
   <news:publication_date>2026-06-13T08:51:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700171</loc>
  <lastmod>2026-06-13T08:51:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイドンとモーツァルトの境界を探る — 弦楽四重奏における作曲家分類（Where Does Haydn End and Mozart Begin? Composer Classification of String Quartets）</news:title>
   <news:publication_date>2026-06-13T08:51:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700169</loc>
  <lastmod>2026-06-13T08:51:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>導関数を使わないオンライン学習による逆動力学モデルの実用性（Derivative-free online learning of inverse dynamics models）</news:title>
   <news:publication_date>2026-06-13T08:51:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700167</loc>
  <lastmod>2026-06-13T08:51:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>物理プリミティブ分解による物体理解（Physical Primitive Decomposition）</news:title>
   <news:publication_date>2026-06-13T08:51:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700165</loc>
  <lastmod>2026-06-13T07:59:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-13T07:59:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/700163</loc>
  <lastmod>2026-06-13T07:59:40Z</lastmod>
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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>
  <loc>https://aibr.jp/archives/700161</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>2026-06-13T07:59:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700159</loc>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>INCSQLによるインクリメンタルText-to-SQL学習と非決定的オラクルの提案 (INCSQL: TRAINING INCREMENTAL TEXT-TO-SQL PARSERS WITH NON-DETERMINISTIC ORACLES)</news:title>
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   <news:genres>Blog</news:genres>
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 <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>2026-06-13T07:58:20Z</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:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-13T07:57:54Z</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:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハミルトニアン降下法（Hamiltonian Descent Methods）</news:title>
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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: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>
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   <news:publication_date>2026-06-13T07:05:45Z</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>
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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>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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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>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-13T06:13:30Z</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>
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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>
   </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>
   </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>
  <loc>https://aibr.jp/archives/700113</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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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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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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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定量的品質と知覚的品質を同時に考慮する深層学習ベースの画像超解像（Deep Learning-based Image Super-Resolution Considering Quantitative and Perceptual Quality）</news:title>
   <news:publication_date>2026-06-13T03:35:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
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 <url>
  <loc>https://aibr.jp/archives/700091</loc>
  <lastmod>2026-06-13T03:35:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子線で誘導したSi原子移動中の原子構造追跡を深層機械学習で解く（Tracking atomic structure evolution during directed electron beam induced Si-atom motion in graphene via deep machine learning）</news:title>
   <news:publication_date>2026-06-13T03:35:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700089</loc>
  <lastmod>2026-06-13T03:35:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非局所対流の数値解析（Numerical Analysis of Nonlocal Convection — Comparison with Three-Dimensional Numerical Simulations of Efficient Turbulent Convection）</news:title>
   <news:publication_date>2026-06-13T03:35:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700087</loc>
  <lastmod>2026-06-13T03:34:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知覚重視のGANによる超解像──周波数領域の損失で視覚品質を高める（Generative Adversarial Network-based Image Super-Resolution using Perceptual Content Losses）</news:title>
   <news:publication_date>2026-06-13T03:34:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700085</loc>
  <lastmod>2026-06-13T03:34:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム同時意味分割と深度推定の実用化（Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations）</news:title>
   <news:publication_date>2026-06-13T03:34:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700083</loc>
  <lastmod>2026-06-13T03:34:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一受信機で波形を同時推定して画像化する深層学習（Deep Learning for Waveform Estimation and Imaging in Passive Radar）</news:title>
   <news:publication_date>2026-06-13T03:34:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700081</loc>
  <lastmod>2026-06-13T02:43:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>希土類遷移金属二元合金のキュリー温度を導く重要記述子（Important Descriptors and Descriptor Groups of Curie Temperatures of Rare-earth Transition-metal Binary Alloys）</news:title>
   <news:publication_date>2026-06-13T02:43:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700079</loc>
  <lastmod>2026-06-13T02:43:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量時系列に対する生成的敵対ネットワークを用いた異常検知（Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series）</news:title>
   <news:publication_date>2026-06-13T02:43:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700077</loc>
  <lastmod>2026-06-13T02:43:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>測地線クラスタリングと深層生成モデル（Geodesic Clustering in Deep Generative Models）</news:title>
   <news:publication_date>2026-06-13T02:43:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700075</loc>
  <lastmod>2026-06-13T02:42:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平性を考慮した分類の基準・凸性・境界（Fairness-aware Classification: Criterion, Convexity, and Bounds）</news:title>
   <news:publication_date>2026-06-13T02:42:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700073</loc>
  <lastmod>2026-06-13T02:42:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>照明と視点変化に適応するセマンティックセグメンテーション（Adapting Semantic Segmentation Models for Changes in Illumination and Camera Perspective）</news:title>
   <news:publication_date>2026-06-13T02:42:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700071</loc>
  <lastmod>2026-06-13T02:41:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DispSegNet：意味情報を活用したステレオ画像からの視差推定のEnd-to-End学習（DispSegNet: Leveraging Semantics for End-to-End Learning of Disparity Estimation from Stereo Imagery）</news:title>
   <news:publication_date>2026-06-13T02:41:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700069</loc>
  <lastmod>2026-06-13T02:41:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的な視覚トラッキングのための敵対的特徴サンプリング学習（Adversarial Feature Sampling Learning for Efficient Visual Tracking）</news:title>
   <news:publication_date>2026-06-13T02:41:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700067</loc>
  <lastmod>2026-06-13T01:50:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>外れ値（Out-of-distribution）検出評価の偏りを減らす手法（A Less Biased Evaluation of Out-of-distribution Sample Detectors）</news:title>
   <news:publication_date>2026-06-13T01:50:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700065</loc>
  <lastmod>2026-06-13T01:40:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑な動力学を伴うロボット課題におけるシムトゥリアルトランスファ学習（Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics）</news:title>
   <news:publication_date>2026-06-13T01:40:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700063</loc>
  <lastmod>2026-06-13T01:40:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>公平性を組み込んだハイブリッド推薦システム（A Fairness-aware Hybrid Recommender System）</news:title>
   <news:publication_date>2026-06-13T01:40:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700061</loc>
  <lastmod>2026-06-13T01:39:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何情報を活かした画像合成（Geometric Image Synthesis）</news:title>
   <news:publication_date>2026-06-13T01:39:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700059</loc>
  <lastmod>2026-06-13T01:39:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-06-13T01:39:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-13T01:39:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>放射線所見の要約自動化の学習（Learning to Summarize Radiology Findings）</news:title>
   <news:publication_date>2026-06-13T01:39:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700055</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>蒸留型ワッサースタイン学習による単語埋め込みとトピックモデル（Distilled Wasserstein Learning for Word Embedding and Topic Modeling）</news:title>
   <news:publication_date>2026-06-13T01:39:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700053</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>2026-06-13T00:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700051</loc>
  <lastmod>2026-06-13T00:48:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習で強化された光子学的ユニバーサル量子ゲートの生成（Production of photonic universal quantum gates enhanced by machine learning）</news:title>
   <news:publication_date>2026-06-13T00:48:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700049</loc>
  <lastmod>2026-06-13T00:48:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長いプログラムの自動合成と学習型ガベージコレクタ（Automatic Program Synthesis of Long Programs with a Learned Garbage Collector）</news:title>
   <news:publication_date>2026-06-13T00:48:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700047</loc>
  <lastmod>2026-06-13T00:46:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散・非同期ベイズ最適化を現場で使うためのPARyOpt（PARyOpt: A software for Parallel Asynchronous Remote Bayesian Optimization）</news:title>
   <news:publication_date>2026-06-13T00:46:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700045</loc>
  <lastmod>2026-06-13T00:46:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>光散乱によるスピークル障害下の超冷却原子のエネルギー予測（Supervised machine learning of ultracold atoms with speckle disorder）</news:title>
   <news:publication_date>2026-06-13T00:46:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700043</loc>
  <lastmod>2026-06-13T00:46:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クリック予測のための統一バッチオンライン学習フレームワーク（A Unified Batch Online Learning Framework for Click Prediction）</news:title>
   <news:publication_date>2026-06-13T00:46:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700041</loc>
  <lastmod>2026-06-13T00:46:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基本ブロック再配置の改良—実行ファイル性能を左右するコード配置の最適化（Improved Basic Block Reordering）</news:title>
   <news:publication_date>2026-06-13T00:46:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700039</loc>
  <lastmod>2026-06-12T23:54:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アテローム性心血管疾患リスク予測における公平性の構築（CREATING FAIR MODELS OF ATHEROSCLEROTIC CARDIOVASCULAR DISEASE）</news:title>
   <news:publication_date>2026-06-12T23:54:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700037</loc>
  <lastmod>2026-06-12T23:54:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>推薦システムと意見形成の閉ループ（The closed loop between opinion formation and personalised recommendations）</news:title>
   <news:publication_date>2026-06-12T23:54:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700035</loc>
  <lastmod>2026-06-12T23:54:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アンドロメダIIの運動性は大規模合併が起源（The major merger origin of the Andromeda II kinematics）</news:title>
   <news:publication_date>2026-06-12T23:54:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700033</loc>
  <lastmod>2026-06-12T23:53:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚品質駆動型学習による水中画像の視覚改善 (VISUAL-QUALITY-DRIVEN LEARNING FOR UNDERWATER VISION ENHANCEMENT)</news:title>
   <news:publication_date>2026-06-12T23:53:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700031</loc>
  <lastmod>2026-06-12T23:53:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的勾配ハミルトニアンモンテカルロの有限時間収束と加速性（Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Stochastic Optimization: Non-Asymptotic Performance Bounds and Momentum-Based Acceleration）</news:title>
   <news:publication_date>2026-06-12T23:53:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700029</loc>
  <lastmod>2026-06-12T23:53:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異種画像ペアのマッチングを可能にする深層スペクトル対応（Deep Spectral Correspondence for Matching Disparate Image Pairs）</news:title>
   <news:publication_date>2026-06-12T23:53:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700027</loc>
  <lastmod>2026-06-12T23:52:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なるドメインの顔に対するランドマーク検出の二段階学習法（A Two-Step Learning Method for Detecting Landmarks on Faces from Different Domains）</news:title>
   <news:publication_date>2026-06-12T23:52:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/700025</loc>
  <lastmod>2026-06-12T23:01:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散チェルノフ検定によるネットワーク上の最適意思決定（Distributed Chernoff Test: Optimal Decision Systems over Networks）</news:title>
   <news:publication_date>2026-06-12T23:01:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-06-12T23:01:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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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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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 <url>
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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>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:genres>Blog</news:genres>
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 <url>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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 </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>
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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>2026-06-12T20:21:20Z</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>
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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>
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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>
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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>
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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>
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    <news:name>AI Benchmark Research</news:name>
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 <url>
  <loc>https://aibr.jp/archives/699951</loc>
  <lastmod>2026-06-12T18:25:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>初期引用データから論文の将来の影響力を予測する（Predicting citation counts based on deep neural network learning techniques）</news:title>
   <news:publication_date>2026-06-12T18:25:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699949</loc>
  <lastmod>2026-06-12T18:25:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タンパク質のB因子（柔軟性）を盲検的に予測する手法（Blind prediction of protein B-factor and flexibility）</news:title>
   <news:publication_date>2026-06-12T18:25:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699947</loc>
  <lastmod>2026-06-12T18:25:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データ分類における深層学習の総覧（Deep learning for time series classification: a review）</news:title>
   <news:publication_date>2026-06-12T18:25:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699945</loc>
  <lastmod>2026-06-12T18:24:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心拍変動に基づく睡眠段階判定のためのLSTMと知識転移（LSTM knowledge transfer for HRV-based sleep staging）</news:title>
   <news:publication_date>2026-06-12T18:24:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699943</loc>
  <lastmod>2026-06-12T18:24:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異なるデータセットで深層ニューラルネットワークを訓練する手法（Training Deep Neural Networks with Different Datasets In-the-wild: The Emotion Recognition Paradigm）</news:title>
   <news:publication_date>2026-06-12T18:24:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699941</loc>
  <lastmod>2026-06-12T17:33:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>全身アーム操作を用いた人体移動のための位相基盤表現における強化学習（Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation）</news:title>
   <news:publication_date>2026-06-12T17:33:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699939</loc>
  <lastmod>2026-06-12T17:24:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報セキュリティ分野における深層学習の実務的意義（DEEP LEARNING IN INFORMATION SECURITY）</news:title>
   <news:publication_date>2026-06-12T17:24:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699937</loc>
  <lastmod>2026-06-12T17:23:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>UGC 1922 の内部動力学と星形成（A Malin 1 “cousin” with counter-rotation: internal dynamics and stellar content of the giant low surface brightness galaxy UGC 1922）</news:title>
   <news:publication_date>2026-06-12T17:23:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699935</loc>
  <lastmod>2026-06-12T17:22:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>作業記憶モデルによる中国詩生成（Chinese Poetry Generation with a Working Memory Model）</news:title>
   <news:publication_date>2026-06-12T17:22:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699933</loc>
  <lastmod>2026-06-12T17:22:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>歌詞から自動作曲するニューラル手法（Neural Melody Composition from Lyrics）</news:title>
   <news:publication_date>2026-06-12T17:22:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699931</loc>
  <lastmod>2026-06-12T17:22:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>長期視覚追跡における回帰と検証ネットワークの統合（Learning regression and verification networks for long-term visual tracking）</news:title>
   <news:publication_date>2026-06-12T17:22:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699929</loc>
  <lastmod>2026-06-12T17:22:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>特異結合を持つクラモトモデルにおけるFilippov軌道とクラスタリング（FILIPPOV TRAJECTORIES AND CLUSTERING IN THE KURAMOTO MODEL WITH SINGULAR COUPLINGS）</news:title>
   <news:publication_date>2026-06-12T17:22:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699927</loc>
  <lastmod>2026-06-12T16:30:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚場面における発話を用いたマルチモーダルな呼びかけ先認識（Deep Learning Based Multi-modal Addressee Recognition in Visual Scenes with Utterances）</news:title>
   <news:publication_date>2026-06-12T16:30:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699925</loc>
  <lastmod>2026-06-12T16:30:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構文と意味情報を埋め込みに取り込む方法（Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks）</news:title>
   <news:publication_date>2026-06-12T16:30:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699923</loc>
  <lastmod>2026-06-12T16:30:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>欠測データからの連続時間ベイジアンネットワーク構造学習におけるクラスタ変分近似（Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data）</news:title>
   <news:publication_date>2026-06-12T16:30:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699921</loc>
  <lastmod>2026-06-12T16:29:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>知識を取り入れた会話型テーブル意味解析 (Knowledge-Aware Conversational Semantic Parsing Over Web Tables)</news:title>
   <news:publication_date>2026-06-12T16:29:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699919</loc>
  <lastmod>2026-06-12T16:29:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続変数を離散的に緩和して実用的な変分推論を可能にする方法（Discretely Relaxing Continuous Variables for tractable Variational Inference）</news:title>
   <news:publication_date>2026-06-12T16:29:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699917</loc>
  <lastmod>2026-06-12T16:29:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>網膜OCT画像における層分割と不確実性可視化：ベイズ深層学習による信頼度の導入（Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images using Bayesian Deep Learning）</news:title>
   <news:publication_date>2026-06-12T16:29:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699915</loc>
  <lastmod>2026-06-12T16:29:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Music Transformerによる長期構造を持つ音楽生成（MUSIC TRANSFORMER: GENERATING MUSIC WITH LONG-TERM STRUCTURE）</news:title>
   <news:publication_date>2026-06-12T16:29:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699913</loc>
  <lastmod>2026-06-12T15:37:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MotherNets による迅速なディープアンサンブル学習（MOTHERNETS: RAPID DEEP ENSEMBLE LEARNING）</news:title>
   <news:publication_date>2026-06-12T15:37:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699911</loc>
  <lastmod>2026-06-12T15:37:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Wasserstein重心を高速に求めるアルゴリズム（A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters）</news:title>
   <news:publication_date>2026-06-12T15:37:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699909</loc>
  <lastmod>2026-06-12T15:37:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>部分文字列で単語埋め込みを一般化する（Generalizing Word Embeddings using Bag of Subwords）</news:title>
   <news:publication_date>2026-06-12T15:37:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699907</loc>
  <lastmod>2026-06-12T15:36:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波(EEG)を用いた視聴映像認識とグラフ畳み込みニューラルネットワーク（EEG-BASED VIDEO IDENTIFICATION USING GRAPH SIGNAL MODELING AND GRAPH CONVOLUTIONAL NEURAL NETWORK）</news:title>
   <news:publication_date>2026-06-12T15:36:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699905</loc>
  <lastmod>2026-06-12T15:36:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>糖尿病性網膜症と黄斑浮腫の自動診断に向けたCNNアンサンブル手法（ENSEMBLE OF CONVOLUTIONAL NEURAL NETWORKS FOR AUTOMATIC GRADING OF DIABETIC RETINOPATHY AND MACULAR EDEMA）</news:title>
   <news:publication_date>2026-06-12T15:36:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699903</loc>
  <lastmod>2026-06-12T15:36:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時変安全性を考慮した安全探索：ST-SAFEMDP（Safe Exploration in Markov Decision Processes with Time-Variant Safety using Spatio-Temporal Gaussian Process）</news:title>
   <news:publication_date>2026-06-12T15:36:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/699901</loc>
  <lastmod>2026-06-12T15:36:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>洗練された対戦相手に対する効率的検出と最適応答（Towards Efficient Detection and Optimal Response against Sophisticated Opponents）</news:title>
   <news:publication_date>2026-06-12T15:36:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
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