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   <news:title>依存グラフを用いたスケーラブルな相互情報量推定（SCALABLE MUTUAL INFORMATION ESTIMATION USING DEPENDENCE GRAPHS）</news:title>
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   <news:title>メッシュの誤差を学習して補正する手法（Meshed Up: Learnt Error Correction in 3D Reconstructions）</news:title>
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   <news:title>高速な宇宙大網シミュレーションを生成するGANの応用（Fast Cosmic Web Simulations with Generative Adversarial Networks）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>IRSA伝送最適化をオンライン学習で行う（IRSA Transmission Optimization via Online Learning）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>直交符号化行列を用いた多クラス分類の確率推定（Solving for multi-class using orthogonal coding matrices）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>共分散に基づく非類似度測度による広義定常エルゴード過程のクラスタリング（Covariance-based Dissimilarity Measures Applied to Clustering Wide-sense Stationary Ergodic Processes）</news:title>
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   <news:title>重み付きラデマッハ複雑度による近似推論（Approximate Inference via Weighted Rademacher Complexity）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>静止画からシネマグラフを生成する手法（Image2GIF: Generating Cinemagraphs using Recurrent Deep Q-Networks）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:genres>Blog</news:genres>
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   <news:title>CHYの順列表現と散乱振幅の対応（Permutation in the CHY Formulation）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>GD-1 星流の詳細な解析：密度変動と波打ち（A deeper look at the GD1 stream: density variations and wiggles）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>勾配ベースのメタラーニングを階層ベイズとして読み解く（RECASTING GRADIENT-BASED META-LEARNING AS HIERARCHICAL BAYES）</news:title>
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   <news:title>L3ボリュメトリック攻撃検出のシミュレーション（Simulation for L3 Volumetric Attack Detection）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>電子カルテデータから薬理学的効果を検出する遅延回帰の方法論的検討 (Methodological variations in lagged regression for detecting physiologic drug effects in EHR data)</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>Correlated Components Analysisによる再現性の高い次元抽出（Correlated Components Analysis – Extracting Reliable Dimensions in Multivariate Data）</news:title>
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   <news:genres>Blog</news:genres>
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   <news:title>Windows PEマルウェア検出モデルからの回避を学ぶ（Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning）</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>単相液体アルゴン時間投影検出器のピクセル化チャージリードアウトの初デモンストレーション (First Demonstration of a Pixelated Charge Readout for Single-Phase Liquid Argon Time Projection Chambers)</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>HTMLドキュメントからのWeb API仕様自動抽出（Automatically Extracting Web API Specifications from HTML Documentation）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   <news:title>深層学習血管造影（Deep Learning Angiography: Three-dimensional C-arm Cone Beam CT Angiography Using Deep Learning）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>Flashゲーム向け強化学習プラットフォームの提案（FlashRL: A Reinforcement Learning Platform for Flash Games）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>連続作用空間における安全な探索（Safe Exploration in Continuous Action Spaces）</news:title>
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   <news:genres>Blog</news:genres>
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  <news:news>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>エッジ誘起せん断バンド化が示す実験解釈の転換（Edge-induced shear banding in entangled polymeric fluids）</news:title>
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    <news:language>ja</news:language>
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   <news:title>テンソル操作のための言語のモデル化 (Modeling of languages for tensor manipulation)</news:title>
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    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>異種モダリティ間の双方向生成を改善する手法（Improving Bi-directional Generation between Different Modalities with Variational Autoencoders）</news:title>
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   <news:genres>Blog</news:genres>
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    <news:name>AI Benchmark Research</news:name>
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   <news:title>文書二値化におけるPDNet：セマンティックセグメンテーションとプライマル・デュアルを統合する手法（PDNet: Semantic Segmentation integrated with a Primal-Dual Network for Document binarization）</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>
   </news:publication>
   <news:title>分類器のニューラル代数が拓く、見えない概念の認識（Neural Algebra of Classifiers）</news:title>
   <news:publication_date>2026-04-03T05:19:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675306</loc>
  <lastmod>2026-04-03T05:19:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>21.3百万件の手指衛生機会から読み解く遵守要因（21 Million Opportunities: A 19 Facility Investigation of Factors Affecting Hand Hygiene Compliance via Linear Predictive Models）</news:title>
   <news:publication_date>2026-04-03T05:19:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675304</loc>
  <lastmod>2026-04-03T05:19:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低資源言語のOOV語翻訳における文脈モデルの実践的示唆 (Context Models for OOV Word Translation in Low-Resource Languages)</news:title>
   <news:publication_date>2026-04-03T05:19:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675302</loc>
  <lastmod>2026-04-03T05:18:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>黒箱モデルの加法的説明を学ぶ際の考慮事項（Considerations When Learning Additive Explanations for Black-Box Models）</news:title>
   <news:publication_date>2026-04-03T05:18:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675300</loc>
  <lastmod>2026-04-03T05:18:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数関係射影による知識グラフ埋め込み（Knowledge Graph Embedding with Multiple Relation Projections）</news:title>
   <news:publication_date>2026-04-03T05:18:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675298</loc>
  <lastmod>2026-04-03T05:18:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HPC上でのストリーム処理を現実にするPilot-Streaming（Pilot-Streaming: A Stream Processing Framework for High-Performance Computing）</news:title>
   <news:publication_date>2026-04-03T05:18:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675296</loc>
  <lastmod>2026-04-03T05:17:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オントロジーに基づくFuzzy Markup Languageエージェントによる生徒とロボットの共学習（Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning）</news:title>
   <news:publication_date>2026-04-03T05:17:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675294</loc>
  <lastmod>2026-04-03T04:26:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>適応畳み込みを用いた生成的敵対ネットワークの革新（Generative Adversarial Networks Using Adaptive Convolution）</news:title>
   <news:publication_date>2026-04-03T04:26:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675292</loc>
  <lastmod>2026-04-03T04:26:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模オンラインサービスにおける不審アカウント活動の予測（Forecasting Suspicious Account Activity at Large-Scale Online Service Providers）</news:title>
   <news:publication_date>2026-04-03T04:26:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675290</loc>
  <lastmod>2026-04-03T04:25:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速二値埋め込みと構造化行列を用いた量子化圧縮センシング（Fast binary embeddings, and quantized compressed sensing with structured matrices）</news:title>
   <news:publication_date>2026-04-03T04:25:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675288</loc>
  <lastmod>2026-04-03T04:25:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動的精度スケーリングと量子化誤差指標（QUANTIZATION ERROR AS A METRIC FOR DYNAMIC PRECISION SCALING IN NEURAL NET TRAINING）</news:title>
   <news:publication_date>2026-04-03T04:25:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675286</loc>
  <lastmod>2026-04-03T04:24:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SPARQLをそのまま使ってプロパティグラフを問う（Killing Two Birds with One Stone – Querying Property Graphs using SPARQL via Gremlinator）</news:title>
   <news:publication_date>2026-04-03T04:24:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675284</loc>
  <lastmod>2026-04-03T04:24:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CycleGANによる手書き中国文字生成 (Generating Handwritten Chinese Characters using CycleGAN)</news:title>
   <news:publication_date>2026-04-03T04:24:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675282</loc>
  <lastmod>2026-04-03T04:24:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DeepLung：3Dデュアルパスネットによる肺結節自動検出と分類（DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification）</news:title>
   <news:publication_date>2026-04-03T04:24:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675280</loc>
  <lastmod>2026-04-03T03:32:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル端末とクラウドで分担するDNN処理の実用化（JointDNN: An Efficient Training and Inference Engine for Intelligent Mobile Cloud Computing Services）</news:title>
   <news:publication_date>2026-04-03T03:32:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675278</loc>
  <lastmod>2026-04-03T03:32:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>子宮頸部細胞分類のための深層畳み込みネットワーク（DeepPap: Deep Convolutional Networks for Cervical Cell Classification）</news:title>
   <news:publication_date>2026-04-03T03:32:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675276</loc>
  <lastmod>2026-04-03T03:32:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱教師あり自己段階的3D病変セグメンテーション（Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST）</news:title>
   <news:publication_date>2026-04-03T03:32:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675274</loc>
  <lastmod>2026-04-03T03:31:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>合成開口レーダー画像からのエンドツーエンド自動目標認識（Deep Learning for End-to-End Automatic Target Recognition from Synthetic Aperture Radar Imagery）</news:title>
   <news:publication_date>2026-04-03T03:31:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675272</loc>
  <lastmod>2026-04-03T03:30:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ICAとIVAのアルゴリズム開発と医用画像解析への応用（Development of ICA and IVA Algorithms with Application to Medical Image Analysis）</news:title>
   <news:publication_date>2026-04-03T03:30:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675270</loc>
  <lastmod>2026-04-03T02:39:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元における一般的スパース加法モデルの学習（Learning general sparse additive models from point queries in high dimensions）</news:title>
   <news:publication_date>2026-04-03T02:39:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675268</loc>
  <lastmod>2026-04-03T02:29:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>トポロジカル・マクスウェル格子の破壊挙動（Fracturing of topological Maxwell lattices）</news:title>
   <news:publication_date>2026-04-03T02:29:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675266</loc>
  <lastmod>2026-04-03T02:29:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マニュアル注釈なしで肺CT画像の嚢胞を自己学習で検出・分割する手法（Self-learning to detect and segment cysts in lung CT images without manual annotation）</news:title>
   <news:publication_date>2026-04-03T02:29:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675264</loc>
  <lastmod>2026-04-03T02:28:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>輸送写像構築の分散フレームワーク（A Distributed Framework for the Construction of Transport Maps）</news:title>
   <news:publication_date>2026-04-03T02:28:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675262</loc>
  <lastmod>2026-04-03T02:28:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SARと光学画像の対応パッチ同定を可能にする擬似シアム型CNN（Identifying Corresponding Patches in SAR and Optical Images with a Pseudo-Siamese CNN）</news:title>
   <news:publication_date>2026-04-03T02:28:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675260</loc>
  <lastmod>2026-04-03T02:28:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デジタル組織分解のための損失関数学習 (Loss-function learning for digital tissue deconvolution)</news:title>
   <news:publication_date>2026-04-03T02:28:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675258</loc>
  <lastmod>2026-04-03T02:27:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>腫瘍増大予測のための畳み込み侵入・拡張ネットワーク（Convolutional Invasion and Expansion Networks for Tumor Growth Prediction）</news:title>
   <news:publication_date>2026-04-03T02:27:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675256</loc>
  <lastmod>2026-04-03T01:36:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非偏極クォークの横運動量依存分布の初めての全体解析（A first determination of the unpolarized quark TMDs from a global analysis）</news:title>
   <news:publication_date>2026-04-03T01:36:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675254</loc>
  <lastmod>2026-04-03T01:36:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脆弱な集団向けのアジャイル開発（Agile Development for Vulnerable Populations）</news:title>
   <news:publication_date>2026-04-03T01:36:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675252</loc>
  <lastmod>2026-04-03T01:35:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複雑な赤道面塵構造の偏光と時間応答の解読（A near-infrared, optical and ultraviolet polarimetric and timing investigation of complex equatorial dusty structures）</news:title>
   <news:publication_date>2026-04-03T01:35:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675250</loc>
  <lastmod>2026-04-03T01:35:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>群衆中の人間行動理解：意思決定模倣による解析（Understanding Human Behaviors in Crowds by Imitating the Decision-Making Process）</news:title>
   <news:publication_date>2026-04-03T01:35:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675248</loc>
  <lastmod>2026-04-03T01:35:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型インパルス応答の正則化（Data-Driven Impulse Response Regularization via Deep Learning）</news:title>
   <news:publication_date>2026-04-03T01:35:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675246</loc>
  <lastmod>2026-04-03T01:35:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グローバルとローカルの整合性を保つ年齢生成敵対的ネットワーク（Global and Local Consistent Age Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-03T01:35:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675244</loc>
  <lastmod>2026-04-03T01:34:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デジタルインクを編集可能にする深層生成モデリング（DeepWriting: Making Digital Ink Editable via Deep Generative Modeling）</news:title>
   <news:publication_date>2026-04-03T01:34:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675242</loc>
  <lastmod>2026-04-03T00:43:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル選択と局所幾何学（Model selection and local geometry）</news:title>
   <news:publication_date>2026-04-03T00:43:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675240</loc>
  <lastmod>2026-04-03T00:43:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デュアル非対称ディープハッシング学習（Dual Asymmetric Deep Hashing Learning）</news:title>
   <news:publication_date>2026-04-03T00:43:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675238</loc>
  <lastmod>2026-04-03T00:42:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層オートエンコーダによる表情認識（Using Deep Autoencoders for Facial Expression Recognition）</news:title>
   <news:publication_date>2026-04-03T00:42:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675236</loc>
  <lastmod>2026-04-03T00:42:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>連続空間による並べ替えモデルがフレーズベース翻訳を変える（Continuous Space Reordering Models for Phrase-based MT）</news:title>
   <news:publication_date>2026-04-03T00:42:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675234</loc>
  <lastmod>2026-04-03T00:42:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ローカル電力取引と請求のための安全かつプライバシー配慮されたプロトコル（Secure and Privacy-Friendly Local Electricity Trading and Billing）</news:title>
   <news:publication_date>2026-04-03T00:42:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675232</loc>
  <lastmod>2026-04-03T00:41:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オフィウクス星団における銀河の光学的性質（The optical properties of galaxies in the Ophiuchus cluster）</news:title>
   <news:publication_date>2026-04-03T00:41:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675230</loc>
  <lastmod>2026-04-02T23:50:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心音を読み取る深層学習――PCG信号の再帰型ニューラルネットワークによる異常心音検出（Phonocardiographic Sensing using Deep Learning for Abnormal Heartbeat Detection）</news:title>
   <news:publication_date>2026-04-02T23:50:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675228</loc>
  <lastmod>2026-04-02T23:50:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>格子ベースの前方安全なグループ署名（Forward-Secure Group Signatures from Lattices）</news:title>
   <news:publication_date>2026-04-02T23:50:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675226</loc>
  <lastmod>2026-04-02T23:50:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>情報利得比（gain ratio）の補正による決定木の改善（Information gain ratio correction: Improving prediction with more balanced decision tree splits）</news:title>
   <news:publication_date>2026-04-02T23:50:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675224</loc>
  <lastmod>2026-04-02T23:49:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラスラベルオートエンコーダによるゼロショット学習（Class label autoencoder for zero-shot learning）</news:title>
   <news:publication_date>2026-04-02T23:49:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675222</loc>
  <lastmod>2026-04-02T23:48:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NDDR-CNN：層ごとの特徴融合でマルチタスク学習を自動化する手法（NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs）</news:title>
   <news:publication_date>2026-04-02T23:48:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675220</loc>
  <lastmod>2026-04-02T23:48:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SocialML：ソーシャルメディア動画制作者のための機械学習（SocialML: machine learning for social media video creators）</news:title>
   <news:publication_date>2026-04-02T23:48:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675218</loc>
  <lastmod>2026-04-02T23:48:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>λリターンの分散を直接推定する方法（Directly Estimating the Variance of the λ-Return Using Temporal-Difference Methods）</news:title>
   <news:publication_date>2026-04-02T23:48:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675216</loc>
  <lastmod>2026-04-02T22:56:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的逐次凸近似による非凸確率最適化の解法（Stochastic Successive Convex Approximation for Non-Convex Constrained Stochastic Optimization）</news:title>
   <news:publication_date>2026-04-02T22:56:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675214</loc>
  <lastmod>2026-04-02T22:48:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュース推薦に知識を組み込む深層モデルの要点解説（DKN: Deep Knowledge-Aware Network for News Recommendation）</news:title>
   <news:publication_date>2026-04-02T22:48:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675212</loc>
  <lastmod>2026-04-02T22:48:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-02T22:48:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675210</loc>
  <lastmod>2026-04-02T22:48:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-02T22:48:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675208</loc>
  <lastmod>2026-04-02T22:46:57Z</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>2026-04-02T22:46:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675206</loc>
  <lastmod>2026-04-02T22:46:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-02T22:46:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675204</loc>
  <lastmod>2026-04-02T22:46:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>定常エルゴード過程のヒルベルト空間化（A Hilbert Space of Stationary Ergodic Processes）</news:title>
   <news:publication_date>2026-04-02T22:46:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675202</loc>
  <lastmod>2026-04-02T21:55:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-02T21:55:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675200</loc>
  <lastmod>2026-04-02T21:55:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層インタラクティブ進化（Deep Interactive Evolution）</news:title>
   <news:publication_date>2026-04-02T21:55:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675198</loc>
  <lastmod>2026-04-02T21:54:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>個人化された活動認識のための畳み込みニューラルネットワークによる転移学習（Personalized Human Activity Recognition Using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-02T21:54:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675196</loc>
  <lastmod>2026-04-02T21:53:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>能動的ニューラル位置推定（Active Neural Localization）</news:title>
   <news:publication_date>2026-04-02T21:53:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675194</loc>
  <lastmod>2026-04-02T21:53:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-02T21:53:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675192</loc>
  <lastmod>2026-04-02T21:53:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>金融におけるエージェントベースドモデルの明るい未来（A bright future for financial agent-based models）</news:title>
   <news:publication_date>2026-04-02T21:53:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675190</loc>
  <lastmod>2026-04-02T21:53:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-02T21:53:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675188</loc>
  <lastmod>2026-04-02T21:01:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MAttNetによる参照表現理解のモジュラー注意ネットワーク（MAttNet: Modular Attention Network for Referring Expression Comprehension）</news:title>
   <news:publication_date>2026-04-02T21:01:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675186</loc>
  <lastmod>2026-04-02T21:01:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学部生向けナノサイエンス教育プログラムの設計と成果（A Multidisciplinary Undergraduate Nanoscience and Nanotechnology Program at the University of North Dakota）</news:title>
   <news:publication_date>2026-04-02T21:01:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675184</loc>
  <lastmod>2026-04-02T21:00:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習支援によるM&amp;amp;V 2.0の開発と応用（Development and application of a machine learning supported methodology for measurement and verification (M&amp;amp;V) 2.0）</news:title>
   <news:publication_date>2026-04-02T21:00:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675182</loc>
  <lastmod>2026-04-02T20:59:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遠方ブレイザーのホスト銀河を解像する—LBT/LUCI 1 + ARGOSを用いた近赤外撮像（Resolving the Host Galaxy of a Distant Blazar with LBT/LUCI 1 + ARGOS）</news:title>
   <news:publication_date>2026-04-02T20:59:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675180</loc>
  <lastmod>2026-04-02T20:59:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>暗黒物質の探索（The Search for Dark Matter）</news:title>
   <news:publication_date>2026-04-02T20:59:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675178</loc>
  <lastmod>2026-04-02T20:59:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>木星の原始的な組成勾配を考慮した進化（Jupiter’s evolution with primordial composition gradients）</news:title>
   <news:publication_date>2026-04-02T20:59:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675176</loc>
  <lastmod>2026-04-02T20:58:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セクスタンズ矮小楕円銀河の星形成史──再電離前の“真の化石”という結論（The star formation history of the Sextans dwarf spheroidal galaxy: a true fossil of the pre-reionization era）</news:title>
   <news:publication_date>2026-04-02T20:58:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675174</loc>
  <lastmod>2026-04-02T20:07:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Psychlab: 深層強化学習エージェントのための心理実験室（Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents）</news:title>
   <news:publication_date>2026-04-02T20:07:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675172</loc>
  <lastmod>2026-04-02T20:06:50Z</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>2026-04-02T20:06:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675170</loc>
  <lastmod>2026-04-02T20:06:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Androidマルウェアにおけるライダー振る舞いの8年測定（Eight Years of Rider Measurement in the Android Malware Ecosystem）</news:title>
   <news:publication_date>2026-04-02T20:06:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675168</loc>
  <lastmod>2026-04-02T20:05:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形時相論理で制約された強化学習（Logically-Constrained Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-02T20:05:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675166</loc>
  <lastmod>2026-04-02T20:05:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時物体検出と姿勢推定の課題（The challenge of simultaneous object detection and pose estimation: a comparative study）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675164</loc>
  <lastmod>2026-04-02T20:05:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>未ラベル動画から学ぶ時系列一貫性に基づく表現学習（Unsupervised learning from videos using temporal coherency deep networks）</news:title>
   <news:publication_date>2026-04-02T20:05:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675162</loc>
  <lastmod>2026-04-02T20:05:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合層に基づく適応型再帰ニューラルネットワーク（Adaptive Recurrent Neural Network Based on Mixture Layer）</news:title>
   <news:publication_date>2026-04-02T20:05:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675160</loc>
  <lastmod>2026-04-02T19:13:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対称で低消費エネルギーな歩行の学習（Learning Symmetric and Low-Energy Locomotion）</news:title>
   <news:publication_date>2026-04-02T19:13:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675158</loc>
  <lastmod>2026-04-02T19:12:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ非依存で作る汎用敵対的摂動（Generalizable Data-free Objective for Crafting Universal Adversarial Perturbations）</news:title>
   <news:publication_date>2026-04-02T19:12:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675156</loc>
  <lastmod>2026-04-02T19:12:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Intel nGraph：フレームワークとハードウェアを橋渡しする中間表現とコンパイラ（Intel® nGraph™: An Intermediate Representation, Compiler, and Executor for Deep Learning）</news:title>
   <news:publication_date>2026-04-02T19:12:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675154</loc>
  <lastmod>2026-04-02T19:11:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケールアウト深層学習トレーニングの実践設計（On Scale-out Deep Learning Training for Cloud and HPC）</news:title>
   <news:publication_date>2026-04-02T19:11:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675152</loc>
  <lastmod>2026-04-02T19:11:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>幾何データ集合の内在次元（Intrinsic Dimension of Geometric Data Sets）</news:title>
   <news:publication_date>2026-04-02T19:11:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675150</loc>
  <lastmod>2026-04-02T19:11:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Training Set Debugging Using Trusted Items（Training Set Debugging Using Trusted Items）</news:title>
   <news:publication_date>2026-04-02T19:11:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675148</loc>
  <lastmod>2026-04-02T19:10:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>FMOの可視化結果をTensorFlowで識別（Application of TensorFlow to recognition of visualized results of fragment molecular orbital (FMO) calculations）</news:title>
   <news:publication_date>2026-04-02T19:10:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675146</loc>
  <lastmod>2026-04-02T18:18:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>構造化されたエネルギーに基づく画像インペインティング（Deep Structured Energy-Based Image Inpainting）</news:title>
   <news:publication_date>2026-04-02T18:18:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675144</loc>
  <lastmod>2026-04-02T18:18:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>対話的（インタラクティブ）機械学習システムの評価（Evaluation of Interactive Machine Learning Systems）</news:title>
   <news:publication_date>2026-04-02T18:18:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675142</loc>
  <lastmod>2026-04-02T18:18:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速道路における車両軌跡予測のためのLSTMネットワーク（An LSTM Network for Highway Trajectory Prediction）</news:title>
   <news:publication_date>2026-04-02T18:18:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675140</loc>
  <lastmod>2026-04-02T18:16:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>APOGEEデータにおける機械学習：K-meansによる教師なしスペクトル分類（Machine learning in APOGEE: Unsupervised spectral classification with K-means）</news:title>
   <news:publication_date>2026-04-02T18:16:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675138</loc>
  <lastmod>2026-04-02T18:16:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>セマンティック物体特徴のみを用いたUAVのVisual Teach and Repeat（UAV Visual Teach and Repeat Using Only Semantic Object Features）</news:title>
   <news:publication_date>2026-04-02T18:16:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675136</loc>
  <lastmod>2026-04-02T18:16:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波同期解析によるてんかん発作の予測（Anticipating epileptic seizures through the analysis of EEG synchronization as a data classification problem）</news:title>
   <news:publication_date>2026-04-02T18:16:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675134</loc>
  <lastmod>2026-04-02T18:16:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈注意による生成的画像インペインティング（Generative Image Inpainting with Contextual Attention）</news:title>
   <news:publication_date>2026-04-02T18:16:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675132</loc>
  <lastmod>2026-04-02T17:23:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ次数を教師なし正常性尺度として理論的に検証する（A Theoretical Investigation of Graph Degree as an Unsupervised Normality Measure）</news:title>
   <news:publication_date>2026-04-02T17:23:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675130</loc>
  <lastmod>2026-04-02T17:22:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情分析における深層学習の総覧 (Deep Learning for Sentiment Analysis: A Survey)</news:title>
   <news:publication_date>2026-04-02T17:22:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675128</loc>
  <lastmod>2026-04-02T17:22:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高次元状態空間モデルのガウス変分近似（Gaussian variational approximations for high-dimensional state space models）</news:title>
   <news:publication_date>2026-04-02T17:22:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675126</loc>
  <lastmod>2026-04-02T17:21:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>バッチサイズが能動学習の停止に与える影響（Impact of Batch Size on Stopping Active Learning for Text Classification）</news:title>
   <news:publication_date>2026-04-02T17:21:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675124</loc>
  <lastmod>2026-04-02T17:21:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サポートベクターマシンの能動学習と不均衡データへの対処（Support Vector Machine Active Learning Algorithms with Query-by-Committee versus Closest-to-Hyperplane Selection）</news:title>
   <news:publication_date>2026-04-02T17:21:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675122</loc>
  <lastmod>2026-04-02T17:20:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>説得されやすさの違いがもたらす意見ダイナミクス（Opinion Dynamics with Varying Susceptibility to Persuasion）</news:title>
   <news:publication_date>2026-04-02T17:20:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675120</loc>
  <lastmod>2026-04-02T17:20:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ARQを利用した既存利用者との最適スペクトラム共有（Optimal Spectrum Sharing with ARQ based Legacy Users via Chain Decoding）</news:title>
   <news:publication_date>2026-04-02T17:20:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675118</loc>
  <lastmod>2026-04-02T16:28:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>電子カルテで実現するスケーラブルで高精度な深層学習（Scalable and accurate deep learning with electronic health records）</news:title>
   <news:publication_date>2026-04-02T16:28:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675116</loc>
  <lastmod>2026-04-02T16:19:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザー注意と製品注意でレビュー表現を改善する（Improving Review Representations with User Attention and Product Attention for Sentiment Classification）</news:title>
   <news:publication_date>2026-04-02T16:19:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675114</loc>
  <lastmod>2026-04-02T16:18:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>点群上の学習のための動的グラフCNN（Dynamic Graph CNN for Learning on Point Clouds）</news:title>
   <news:publication_date>2026-04-02T16:18:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675112</loc>
  <lastmod>2026-04-02T16:18:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>POSタグ誘導注意と構造化トリプレット学習によるVQA改善（Structured Triplet Learning with POS-tag Guided Attention for Visual Question Answering）</news:title>
   <news:publication_date>2026-04-02T16:18:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675110</loc>
  <lastmod>2026-04-02T16:17:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ウイルスの「種越え」を予測するアルゴリズム的バイオサーベイランス（Algorithmic Bio-surveillance For Precise Spatio-temporal Prediction of Zoonotic Emergence）</news:title>
   <news:publication_date>2026-04-02T16:17:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675108</loc>
  <lastmod>2026-04-02T16:16:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>サーバー支援型取り消し可能述語暗号（Server-Aided Revocable Predicate Encryption: Formalization and Lattice-Based Instantiation）</news:title>
   <news:publication_date>2026-04-02T16:16:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675106</loc>
  <lastmod>2026-04-02T16:16:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>統計的学習に基づくDC最適潮流の制御政策（Statistical Learning for DC Optimal Power Flow）</news:title>
   <news:publication_date>2026-04-02T16:16:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675103</loc>
  <lastmod>2026-04-02T15:24:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>PointCNN: X変換された点群に対する畳み込み（PointCNN: Convolution On X-Transformed Points）</news:title>
   <news:publication_date>2026-04-02T15:24:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675101</loc>
  <lastmod>2026-04-02T15:24:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラル機械翻訳における表現層の評価（Evaluating Layers of Representation in Neural Machine Translation on Part-of-Speech and Semantic Tagging Tasks）</news:title>
   <news:publication_date>2026-04-02T15:24:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675099</loc>
  <lastmod>2026-04-02T15:24:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実験室での「遅いすべり」断層の物理状態を地震波から推定する研究（Estimating the Physical State of a Laboratory Slow Slipping Fault from Seismic Signals）</news:title>
   <news:publication_date>2026-04-02T15:24:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675097</loc>
  <lastmod>2026-04-02T15:23:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>肺循環の数理モデルにおけるMCMCによるパラメータ推定（MCMC methods for inference in a mathematical model of pulmonary circulation）</news:title>
   <news:publication_date>2026-04-02T15:23:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675095</loc>
  <lastmod>2026-04-02T15:23:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズニューラルネットワークの実務的インパクト（A Study of Bayesian Neural Networks）</news:title>
   <news:publication_date>2026-04-02T15:23:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675093</loc>
  <lastmod>2026-04-02T15:22:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>47 Tucanaeの固有運動の精度向上（Improved measurements of the proper motion of the Galactic globular cluster 47 Tucanae）</news:title>
   <news:publication_date>2026-04-02T15:22:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675091</loc>
  <lastmod>2026-04-02T15:22:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散領域における最適輸送（Optimal Transport on Discrete Domains）</news:title>
   <news:publication_date>2026-04-02T15:22:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675089</loc>
  <lastmod>2026-04-02T14:30:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械の目に映る美術史の形 (The Shape of Art History in the Eyes of the Machine)</news:title>
   <news:publication_date>2026-04-02T14:30:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675087</loc>
  <lastmod>2026-04-02T14:30:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SCUBA-2宇宙論レガシー調査：EGS深宇宙領域の形態変化と多波長特性（The SCUBA-2 Cosmology Legacy Survey: The EGS deep field – II. Morphological transformation and multi-wavelength properties of faint submillimetre galaxies）</news:title>
   <news:publication_date>2026-04-02T14:30:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675085</loc>
  <lastmod>2026-04-02T14:29:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マスクで穴埋めすることで改善するテキスト生成（MASKGAN: Better Text Generation via Filling in the）</news:title>
   <news:publication_date>2026-04-02T14:29:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675083</loc>
  <lastmod>2026-04-02T14:28:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>角度マージンで識別力を高める手法の要点（ArcFace: Additive Angular Margin Loss for Deep Face Recognition）</news:title>
   <news:publication_date>2026-04-02T14:28:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675081</loc>
  <lastmod>2026-04-02T14:28:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模確率的ブールネットワークの効率的学習と推論（Tractable Learning and Inference for Large-Scale Probabilistic Boolean Networks）</news:title>
   <news:publication_date>2026-04-02T14:28:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675079</loc>
  <lastmod>2026-04-02T14:28:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Chrysalis Cipher Suite（Chrysalis Cipher Suite）</news:title>
   <news:publication_date>2026-04-02T14:28:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675077</loc>
  <lastmod>2026-04-02T14:28:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>薬剤選定のためのジョイントPushと学習-to-Rank（Drug Selection via Joint Push and Learning to Rank）</news:title>
   <news:publication_date>2026-04-02T14:28:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675075</loc>
  <lastmod>2026-04-02T13:36:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>浅い量子回路のベンチマークと訓練のための生成モデルアプローチ（A generative modeling approach for benchmarking and training shallow quantum circuits）</news:title>
   <news:publication_date>2026-04-02T13:36:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675073</loc>
  <lastmod>2026-04-02T13:36:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高赤方偏移における典型的な黒穴の初期成長（Early growth of typical high redshift black holes seeded by direct collapse）</news:title>
   <news:publication_date>2026-04-02T13:36:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675071</loc>
  <lastmod>2026-04-02T13:35:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>シグナルサブグラフの発見（Discovering the Signal Subgraph: An Iterative Screening Approach on Graphs）</news:title>
   <news:publication_date>2026-04-02T13:35:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675069</loc>
  <lastmod>2026-04-02T13:33:56Z</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・連続空間における逆強化学習（Inverse reinforcement learning in continuous time and space）</news:title>
   <news:publication_date>2026-04-02T13:33:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675067</loc>
  <lastmod>2026-04-02T13:33:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分類器出力を後工程で改善する戦略（A Classification Refinement Strategy for Semantic Segmentation）</news:title>
   <news:publication_date>2026-04-02T13:33:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675065</loc>
  <lastmod>2026-04-02T13:33:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>期待学習による適応的クロスモーダル刺激連合（Expectation Learning for Adaptive Crossmodal Stimuli Association）</news:title>
   <news:publication_date>2026-04-02T13:33:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675063</loc>
  <lastmod>2026-04-02T13:33:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>混合アンサンブルの遺伝的プログラミングモデルの剪定技術（Pruning Techniques for Mixed Ensembles of Genetic Programming Models）</news:title>
   <news:publication_date>2026-04-02T13:33:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675061</loc>
  <lastmod>2026-04-02T12:40:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率モデルを用いたニューラルネットワーク構造の動的最適化（Dynamic Optimization of Neural Network Structures Using Probabilistic Modeling）</news:title>
   <news:publication_date>2026-04-02T12:40:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675059</loc>
  <lastmod>2026-04-02T12:40:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CaosDBによる研究データ管理の現実解（CaosDB - Research Data Management for Complex, Changing, and Automated Research Workflows）</news:title>
   <news:publication_date>2026-04-02T12:40:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675057</loc>
  <lastmod>2026-04-02T12:39:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いたクラスタリングの分類と新手法（Clustering with Deep Learning: Taxonomy and New Methods）</news:title>
   <news:publication_date>2026-04-02T12:39:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675055</loc>
  <lastmod>2026-04-02T12:38:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリックなスパース付加自己回帰ネットワークモデル（Non-parametric sparse additive auto-regressive network models）</news:title>
   <news:publication_date>2026-04-02T12:38:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675053</loc>
  <lastmod>2026-04-02T12:38:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔画像で希少遺伝症を識別するDeepGestalt（DeepGestalt - Identifying Rare Genetic Syndromes Using Deep Learning）</news:title>
   <news:publication_date>2026-04-02T12:38:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675051</loc>
  <lastmod>2026-04-02T12:37:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高解像度顔補完と属性制御を同時に実現する進展的GAN（High Resolution Face Completion with Multiple Controllable Attributes via Fully End-to-End Progressive Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-02T12:37:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675049</loc>
  <lastmod>2026-04-02T11:45:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン講座における反応時間のモデル化と利活用（Modelling and Using Response Times in Online Courses）</news:title>
   <news:publication_date>2026-04-02T11:45:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675047</loc>
  <lastmod>2026-04-02T11:45:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高速度化された点広がり関数（PSF）モデルと深層学習による推定（Fast Point Spread Function Modeling with Deep Learning）</news:title>
   <news:publication_date>2026-04-02T11:45:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675045</loc>
  <lastmod>2026-04-02T11:44:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純な選択ハイパーヒューリスティックスが局所探索の近傍サイズを最適に制御する（Simple Hyper-heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes）</news:title>
   <news:publication_date>2026-04-02T11:44:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675043</loc>
  <lastmod>2026-04-02T11:44:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械同士の会話が教える問い直しの力（Analyzing Language Learned by an Active Question Answering Agent）</news:title>
   <news:publication_date>2026-04-02T11:44:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675041</loc>
  <lastmod>2026-04-02T11:44:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>「他者化（Othering）言語」を用いたヘイトスピーチ検出（’The Enemy Among Us’: Detecting Hate Speech with Threats Based Othering Language Embeddings）</news:title>
   <news:publication_date>2026-04-02T11:44:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675039</loc>
  <lastmod>2026-04-02T11:43:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SARpticalデータセットによるSARと光学画像の統合解析（The SARptical Dataset for Joint Analysis of SAR and Optical Image in Dense Urban Area）</news:title>
   <news:publication_date>2026-04-02T11:43:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675037</loc>
  <lastmod>2026-04-02T11:43:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ベイズ推論で実験的に検出する量子チェンジポイント（Experimentally Detecting a Quantum Change Point via Bayesian Inference）</news:title>
   <news:publication_date>2026-04-02T11:43:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675035</loc>
  <lastmod>2026-04-02T10:51:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ユーザ移動を考慮した強化学習による効率的な3D空中基地局配置（Efficient 3D Aerial Base Station Placement Considering Users Mobility by Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-02T10:51:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675033</loc>
  <lastmod>2026-04-02T10:51:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>感情を読み取る身体の動き：自動認識研究の総覧（Survey on Emotional Body Gesture Recognition）</news:title>
   <news:publication_date>2026-04-02T10:51:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675031</loc>
  <lastmod>2026-04-02T10:50:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハードウェア志向のCNN高速化を実現するSFSとCSF（STACKED FILTERS STATIONARY FLOW FOR HARDWARE-ORIENTED ACCELERATION OF DEEP CONVOLUTIONAL NEURAL NETWORKS）</news:title>
   <news:publication_date>2026-04-02T10:50:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675029</loc>
  <lastmod>2026-04-02T10:50:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スケルトン系列に基づく行動認識の新枠組み：Spatial-Temporal Graph Convolutional Networks（Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition）</news:title>
   <news:publication_date>2026-04-02T10:50:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675027</loc>
  <lastmod>2026-04-02T10:50:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>恒常性制御を組み込んだ好奇心駆動強化学習（Curiosity-driven reinforcement learning with homeostatic regulation）</news:title>
   <news:publication_date>2026-04-02T10:50:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675025</loc>
  <lastmod>2026-04-02T10:49:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>舌画像から漢方処方を自動構成する技術（Automatic Construction of Chinese Herbal Prescriptions From Tongue Images Using CNNs and Auxiliary Latent Therapy Topics）</news:title>
   <news:publication_date>2026-04-02T10:49:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675023</loc>
  <lastmod>2026-04-02T09:57:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画注目領域の再検討：大規模ベンチマークと新モデル（Revisiting Video Saliency: A Large-scale Benchmark and a New Model）</news:title>
   <news:publication_date>2026-04-02T09:57:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675021</loc>
  <lastmod>2026-04-02T09:57:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>一般化二次元線形判別分析と正則化による頑健化（Generalized two-dimensional linear discriminant analysis with regularization）</news:title>
   <news:publication_date>2026-04-02T09:57:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675019</loc>
  <lastmod>2026-04-02T09:56:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>開放量子系の次元切り詰めとテンソルネットワークによる可視化（Dimension truncation for open quantum systems in terms of tensor networks）</news:title>
   <news:publication_date>2026-04-02T09:56:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675017</loc>
  <lastmod>2026-04-02T09:55:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>凸近接慣性勾配降下法の非エルゴード的複雑性（Non-ergodic Complexity of Convex Proximal Inertial Gradient Descents）</news:title>
   <news:publication_date>2026-04-02T09:55:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675015</loc>
  <lastmod>2026-04-02T09:55:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>貪欲法は依然有効：単調な部分加法＋超加法関数の最大化（Greed is Still Good: Maximizing Monotone Submodular+Supermodular Functions）</news:title>
   <news:publication_date>2026-04-02T09:55:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675013</loc>
  <lastmod>2026-04-02T09:55:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンライン動画から学ぶダンス動作解析（Let’s Dance: Learning From Online Dance Videos）</news:title>
   <news:publication_date>2026-04-02T09:55:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675011</loc>
  <lastmod>2026-04-02T09:54:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>主張（アサーション）に基づく質問応答とオープン情報抽出（Assertion-based QA with Question-Aware Open Information Extraction）</news:title>
   <news:publication_date>2026-04-02T09:54:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675009</loc>
  <lastmod>2026-04-02T09:02:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ランダムウォークに基づくノード類似性からのネットワーク学習（Learning Networks from Random Walk-Based Node Similarities）</news:title>
   <news:publication_date>2026-04-02T09:02:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675007</loc>
  <lastmod>2026-04-02T09:02:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>デルタ・シュア予想の探究（Exploring a Delta Schur Conjecture）</news:title>
   <news:publication_date>2026-04-02T09:02:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675005</loc>
  <lastmod>2026-04-02T09:00:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>空間分解されたSEDフィッティングが示す「見落とされた質量」問題の解法（Spatially-unresolved SED fitting can underestimate galaxy masses: a solution to the missing mass problem）</news:title>
   <news:publication_date>2026-04-02T09:00:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675003</loc>
  <lastmod>2026-04-02T09:00:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習による安全なモバイルクラウドセンシング（Secure Mobile Crowdsensing with Deep Learning）</news:title>
   <news:publication_date>2026-04-02T09:00:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/675001</loc>
  <lastmod>2026-04-02T09:00:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>数値座標回帰の新しい出力層：DSNTの提案（Numerical Coordinate Regression with Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-02T09:00:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674999</loc>
  <lastmod>2026-04-02T09:00:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハイブリッドなLSTMとGradient Boostingによる手術室データ予測（Hybrid Gradient Boosting Trees and Neural Networks for Forecasting Operating Room Data）</news:title>
   <news:publication_date>2026-04-02T09:00:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674997</loc>
  <lastmod>2026-04-02T08:59:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込みニューラルネットワークのフィルタ剪定を学習する（Learning to Prune Filters in Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-02T08:59:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674995</loc>
  <lastmod>2026-04-02T08:07:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CHALET: 3D家屋エージェント学習環境 (CHALET: Cornell House Agent Learning Environment)</news:title>
   <news:publication_date>2026-04-02T08:07:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674993</loc>
  <lastmod>2026-04-02T08:07:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>柔軟な深層ニューラルネットワーク処理（Flexible Deep Neural Network Processing）</news:title>
   <news:publication_date>2026-04-02T08:07:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674991</loc>
  <lastmod>2026-04-02T08:06:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>コミュニティの重要性：学習による影響力拡大（The Importance of Communities for Learning to Influence）</news:title>
   <news:publication_date>2026-04-02T08:06:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674989</loc>
  <lastmod>2026-04-02T08:06:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>有限要素法と機械学習による物理系モデリング（Machine Learning and Finite Element Method for Physical Systems Modeling）</news:title>
   <news:publication_date>2026-04-02T08:06:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674987</loc>
  <lastmod>2026-04-02T08:05:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空画像における車両検出の進展（Vehicle Detection in Aerial Images）</news:title>
   <news:publication_date>2026-04-02T08:05:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674985</loc>
  <lastmod>2026-04-02T08:05:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル位置データで読み解く個人ごとの飲食店選好と移動時間（Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data）</news:title>
   <news:publication_date>2026-04-02T08:05:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674983</loc>
  <lastmod>2026-04-02T08:04:55Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSSTアラートストリーム向け機械学習ブローカー（MACHINE LEARNING-BASED BROKERS FOR REAL-TIME CLASSIFICATION OF THE LSST ALERT STREAM）</news:title>
   <news:publication_date>2026-04-02T08:04:55Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674981</loc>
  <lastmod>2026-04-02T07:13:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>半教師あり畳み込みニューラルネットワークによる人間活動認識（Semi-Supervised Convolutional Neural Networks for Human Activity Recognition）</news:title>
   <news:publication_date>2026-04-02T07:13:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674979</loc>
  <lastmod>2026-04-02T07:12:42Z</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・ブートストラップ：Dropoutの代替としての実務的意義（The Hybrid Bootstrap: A Drop-in Replacement for Dropout）</news:title>
   <news:publication_date>2026-04-02T07:12:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674977</loc>
  <lastmod>2026-04-02T07:12:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Siamese GRUとRandom Forestを組み合わせた重複質問検出（Siamese Neural Networks with Random Forest for detecting duplicate question pairs）</news:title>
   <news:publication_date>2026-04-02T07:12:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674975</loc>
  <lastmod>2026-04-02T07:12:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー重視の近傍分類を実用化する一手（Secure k-ish Nearest Neighbors Classifier）</news:title>
   <news:publication_date>2026-04-02T07:12:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674973</loc>
  <lastmod>2026-04-02T07:11:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データセット自動収集による生物画像認識の省力化（Automating Dataset Creation for Image Recognition）</news:title>
   <news:publication_date>2026-04-02T07:11:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674971</loc>
  <lastmod>2026-04-02T06:20:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>無秩序格子ボースへの自己エネルギー汎関数理論と対称性破れ（Self-energy functional theory with symmetry breaking for disordered lattice bosons）</news:title>
   <news:publication_date>2026-04-02T06:20:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674969</loc>
  <lastmod>2026-04-02T06:19:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>射影空間のグロモフ–ウィッテン不変量に関するエネルギー境界と消滅結果（Energy Bounds and Vanishing Results for the Gromov-Witten Invariants of the Projective Space）</news:title>
   <news:publication_date>2026-04-02T06:19:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674967</loc>
  <lastmod>2026-04-02T06:18:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書き筆跡の軌跡復元（Handwriting Trajectory Recovery using End-to-End Deep Encoder-Decoder Network）</news:title>
   <news:publication_date>2026-04-02T06:18:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674965</loc>
  <lastmod>2026-04-02T06:18:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散学習における最適収束：SGMとSAの理論的保証（Optimal Convergence for Distributed Learning with SGM and SA）</news:title>
   <news:publication_date>2026-04-02T06:18:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674963</loc>
  <lastmod>2026-04-02T06:18:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Rover Descentによる最適化学習の再定義（Rover Descent: Learning to optimize by learning to navigate on prototypical loss surfaces）</news:title>
   <news:publication_date>2026-04-02T06:18:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674961</loc>
  <lastmod>2026-04-02T06:18:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>地震波全波形反演を深層学習ツールで実装する意義（Seismic Full-Waveform Inversion Using Deep Learning Tools and Techniques）</news:title>
   <news:publication_date>2026-04-02T06:18:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674959</loc>
  <lastmod>2026-04-02T05:26:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>三次元蛍光顕微鏡画像の合成とセグメンテーション（Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation）</news:title>
   <news:publication_date>2026-04-02T05:26:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674957</loc>
  <lastmod>2026-04-02T05:26:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニューラルネットの特徴抽出と縮重化の対応（Scale-invariant Feature Extraction of Neural Network and Renormalization Group Flow）</news:title>
   <news:publication_date>2026-04-02T05:26:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674955</loc>
  <lastmod>2026-04-02T05:25:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測区間の最適化：メタ検証によるRandom Forestのチューニング（Optimizing Prediction Intervals by Tuning Random Forest via Meta-Validation）</news:title>
   <news:publication_date>2026-04-02T05:25:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674953</loc>
  <lastmod>2026-04-02T05:24:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層学習を用いた計算タンパク質設計（Computational Protein Design with Deep Learning Neural Networks）</news:title>
   <news:publication_date>2026-04-02T05:24:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674951</loc>
  <lastmod>2026-04-02T05:24:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単語レベルのフォント変換を可能にする生成モデル（Word Level Font-to-Font Image Translation using Convolutional Recurrent Generative Adversarial Networks）</news:title>
   <news:publication_date>2026-04-02T05:24:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674949</loc>
  <lastmod>2026-04-02T05:24:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>E-swish: ネットワーク深度に応じた活性化の調整 (E-swish: Adjusting Activations to Different Network Depths)</news:title>
   <news:publication_date>2026-04-02T05:24:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674947</loc>
  <lastmod>2026-04-02T05:24:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ畳み込みネットワークの深い洞察（Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning）</news:title>
   <news:publication_date>2026-04-02T05:24:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674945</loc>
  <lastmod>2026-04-02T04:32:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>意思決定モデルにおける反省（Reflexion in mathematical models of decision-making）</news:title>
   <news:publication_date>2026-04-02T04:32:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674943</loc>
  <lastmod>2026-04-02T04:31:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オンラインニュースフィードのマルチソース・ソーシャルフィード（Multi-Source Social Feedback of Online News Feeds）</news:title>
   <news:publication_date>2026-04-02T04:31:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674941</loc>
  <lastmod>2026-04-02T04:30:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遅延チャネル情報と平均レイテンシ制約を考慮した一般化HARQプロトコル（Generalized HARQ Protocols with Delayed Channel State Information and Average Latency Constraints）</news:title>
   <news:publication_date>2026-04-02T04:30:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674939</loc>
  <lastmod>2026-04-02T04:30:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>分散適応学習における複数カーネルの拡張（Distributed Adaptive Learning with Multiple Kernels in Diffusion Networks）</news:title>
   <news:publication_date>2026-04-02T04:30:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674937</loc>
  <lastmod>2026-04-02T04:30:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュースに基づくマクロ経済指標の予測：解釈可能なセマンティック・パス・モデル（News-based forecasts of macroeconomic indicators: A semantic path model for interpretable predictions）</news:title>
   <news:publication_date>2026-04-02T04:30:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674935</loc>
  <lastmod>2026-04-02T04:29:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>結核自動検出に向けた深層学習の応用（Towards Automated Tuberculosis detection using Deep Learning）</news:title>
   <news:publication_date>2026-04-02T04:29:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674933</loc>
  <lastmod>2026-04-02T03:38:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Androidアプリにおけるフレームワーク特有例外の大規模解析（Large-Scale Analysis of Framework-Specific Exceptions in Android Apps）</news:title>
   <news:publication_date>2026-04-02T03:38:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674931</loc>
  <lastmod>2026-04-02T03:38:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多クラス分類問題に対するフィードフォワードニューラルネットの出力層設計（Binary output layer of feedforward neural networks for solving multi-class classification problems）</news:title>
   <news:publication_date>2026-04-02T03:38:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674929</loc>
  <lastmod>2026-04-02T03:37:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>局所接続を持つエクストリーム・ラーニング・マシン（Extreme Learning Machine with Local Connections）</news:title>
   <news:publication_date>2026-04-02T03:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674927</loc>
  <lastmod>2026-04-02T03:37:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>望ましくないバイアスの緩和を目的としたアドバーサリアル学習（Mitigating Unwanted Biases with Adversarial Learning）</news:title>
   <news:publication_date>2026-04-02T03:37:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674925</loc>
  <lastmod>2026-04-02T03:37:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>MRIのクロスモダリティ変換（MRI Cross-Modality NeuroImage-to-NeuroImage Translation）</news:title>
   <news:publication_date>2026-04-02T03:37:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674923</loc>
  <lastmod>2026-04-02T03:36:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>手書き漢字認識を変える「RADICAL」分解の発想（Trajectory-based Radical Analysis Network for Online Handwritten Chinese Character Recognition）</news:title>
   <news:publication_date>2026-04-02T03:36:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674921</loc>
  <lastmod>2026-04-02T03:36:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的プリミアル・デュアルハイブリッド勾配法の反復複雑度解析（On the Iteration Complexity Analysis of Stochastic Primal-Dual Hybrid Gradient Approach with High Probability）</news:title>
   <news:publication_date>2026-04-02T03:36:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674919</loc>
  <lastmod>2026-04-02T02:45:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クロスドメイン転移学習とターゲット・アプレンティス（Cross-Domain Transfer in Reinforcement Learning using Target Apprentice）</news:title>
   <news:publication_date>2026-04-02T02:45:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674917</loc>
  <lastmod>2026-04-02T02:45:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>基地局における共同キャッシュと推薦の学習的アプローチ（A Learning-based Approach to Joint Content Caching and Recommendation at Base Stations）</news:title>
   <news:publication_date>2026-04-02T02:45:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674915</loc>
  <lastmod>2026-04-02T02:44:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>最適なマルコフネットワーク位相の効率的学習（Efficient Learning of Optimal Markov Network Topology with k-Tree Modeling）</news:title>
   <news:publication_date>2026-04-02T02:44:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674913</loc>
  <lastmod>2026-04-02T02:43:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>HI過剰銀河の多波長調査：豊富な中性水素と驚くほど非効率な星形成（A multiwavelength survey of HI-excess galaxies with surprisingly inefficient star formation）</news:title>
   <news:publication_date>2026-04-02T02:43:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674911</loc>
  <lastmod>2026-04-02T02:43:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Bayesian畳み込みエンコーダ–デコーダによる代理モデルと不確実性定量化（Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification）</news:title>
   <news:publication_date>2026-04-02T02:43:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674909</loc>
  <lastmod>2026-04-02T02:43:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>衛星合成開口レーダー(InSAR)画像における火山地殻変動検出の自動化（Detecting Volcano Deformation in InSAR using Deep learning）</news:title>
   <news:publication_date>2026-04-02T02:43:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674907</loc>
  <lastmod>2026-04-02T02:43:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープラーニングにおける可視化解析の展望（Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers）</news:title>
   <news:publication_date>2026-04-02T02:43:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674905</loc>
  <lastmod>2026-04-02T01:51:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>メタヒューリスティック探索に基づくファジィクラスタリングの総覧（Review: Metaheuristic Search-Based Fuzzy Clustering Algorithms）</news:title>
   <news:publication_date>2026-04-02T01:51:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674903</loc>
  <lastmod>2026-04-02T01:50:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>低コスト単眼カメラによる自律追跡ドローンの実装（Monocular Imaging-based Autonomous Tracking for Low-cost Quad-rotor Design - TraQuad）</news:title>
   <news:publication_date>2026-04-02T01:50:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674901</loc>
  <lastmod>2026-04-02T01:50:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>心電図から発作性心房細動を予測する時系列カーネル類似度（Time Series Kernel Similarities for Predicting Paroxysmal Atrial Fibrillation from ECGs）</news:title>
   <news:publication_date>2026-04-02T01:50:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674899</loc>
  <lastmod>2026-04-02T01:49:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単純方程式の改良法と非線形シュレーディンガー方程式（On the modified method of simplest equation and the nonlinear Schrödinger equation）</news:title>
   <news:publication_date>2026-04-02T01:49:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674897</loc>
  <lastmod>2026-04-02T01:49:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多言語概念誘導による埋め込み学習（Embedding Learning Through Multilingual Concept Induction）</news:title>
   <news:publication_date>2026-04-02T01:49:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674895</loc>
  <lastmod>2026-04-02T01:49:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自動評価におけるニューラル・マルチタスク学習 (Neural Multi-task Learning in Automated Assessment)</news:title>
   <news:publication_date>2026-04-02T01:49:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674893</loc>
  <lastmod>2026-04-02T01:48:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>優先的付着グラフにおけるコミュニティ復元（Community Recovery in a Preferential Attachment Graph）</news:title>
   <news:publication_date>2026-04-02T01:48:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674891</loc>
  <lastmod>2026-04-02T00:56:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>因子化マーク付き時刻点過程のデカップリング学習 (Decoupled Learning for Factorial Marked Temporal Point Processes)</news:title>
   <news:publication_date>2026-04-02T00:56:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674889</loc>
  <lastmod>2026-04-02T00:56:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二つのニューラルネットワークの曲率に基づく比較 (Curvature-based Comparison of Two Neural Networks)</news:title>
   <news:publication_date>2026-04-02T00:56:01Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674887</loc>
  <lastmod>2026-04-02T00:55:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>RGB-Dデータに特化したDepth CNNの学び直し（Depth CNNs for RGB-D scene recognition: learning from scratch better than transferring from RGB-CNNs）</news:title>
   <news:publication_date>2026-04-02T00:55:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674885</loc>
  <lastmod>2026-04-02T00:55:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>条件付き敵対的ネットワークの分離学習（Decoupled Learning for Conditional Adversarial Networks）</news:title>
   <news:publication_date>2026-04-02T00:55:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674883</loc>
  <lastmod>2026-04-02T00:55:11Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一画像からの雨と霞の同時除去（Deep joint rain and haze removal from single images）</news:title>
   <news:publication_date>2026-04-02T00:55:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674881</loc>
  <lastmod>2026-04-02T00:54:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフデータベースの問い合わせ計画を高速化する学習（Learning to Speed Up Query Planning in Graph Databases）</news:title>
   <news:publication_date>2026-04-02T00:54:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674879</loc>
  <lastmod>2026-04-02T00:54:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>注意深い再帰テンソルモデルによるコミュニティ質問応答の改善 (Attentive Recurrent Tensor Model for Community Question Answering)</news:title>
   <news:publication_date>2026-04-02T00:54:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674877</loc>
  <lastmod>2026-04-02T00:02:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ノイズ除去事前分布を用いた画像復元の深層ニューラルネットワーク（Denoising Prior Driven Deep Neural Network for Image Restoration）</news:title>
   <news:publication_date>2026-04-02T00:02:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674875</loc>
  <lastmod>2026-04-02T00:01:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>確率的に汚れたデータベースの形式的枠組み（A Formal Framework for Probabilistic Unclean Databases）</news:title>
   <news:publication_date>2026-04-02T00:01:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674873</loc>
  <lastmod>2026-04-02T00:01:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>EnKCFによる高速単一ターゲット追跡のためのKCFアンサンブル（EnKCF: Ensemble of Kernelized Correlation Filters for High-Speed Object Tracking）</news:title>
   <news:publication_date>2026-04-02T00:01:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674871</loc>
  <lastmod>2026-04-02T00:00:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚入力によるエンドツーエンド多モーダル多タスク車両制御（End-to-end Multi-Modal Multi-Task Vehicle Control for Self-Driving Cars with Visual Perceptions）</news:title>
   <news:publication_date>2026-04-02T00:00:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674869</loc>
  <lastmod>2026-04-02T00:00:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>2次累積量スペクトルによる厳密定常性の検定（A Second Order Cumulant Spectrum Test That a Stochastic Process is Strictly Stationary and a Step Toward a Test for Graph Signal Strict Stationarity）</news:title>
   <news:publication_date>2026-04-02T00:00:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674867</loc>
  <lastmod>2026-04-01T23:09:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>カメラの画像処理を丸ごと学習する時代へ（DeepISP: Towards Learning an End-to-End Image Processing Pipeline）</news:title>
   <news:publication_date>2026-04-01T23:09:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674865</loc>
  <lastmod>2026-04-01T23:09:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒルベルト空間上の最小二乗分回帰に対するスペクトルアルゴリズムの最適収束率（Optimal Rates for Spectral Algorithms with Least-Squares Regression over Hilbert Spaces）</news:title>
   <news:publication_date>2026-04-01T23:09:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674863</loc>
  <lastmod>2026-04-01T23:09:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>タイトルのみを用いた深層学習による主題索引の高精度化（Using Deep Learning for Title-Based Semantic Subject Indexing to Reach Competitive Performance to Full-Text）</news:title>
   <news:publication_date>2026-04-01T23:09:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674861</loc>
  <lastmod>2026-04-01T23:07:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習による視覚データ拡張（Visual Data Augmentation through Learning）</news:title>
   <news:publication_date>2026-04-01T23:07:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674859</loc>
  <lastmod>2026-04-01T23:07:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的Qネットワークによるモデルベース戦略学習（Learning model-based strategies in simple environments with hierarchical q-networks）</news:title>
   <news:publication_date>2026-04-01T23:07:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674857</loc>
  <lastmod>2026-04-01T23:07:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リアルタイム光音響投影画像法に深層学習を組み合わせる意義（Real-time photoacoustic projection imaging using deep learning）</news:title>
   <news:publication_date>2026-04-01T23:07:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674855</loc>
  <lastmod>2026-04-01T23:07:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一符号化画像からのライトフィールド復元（Learning Light Field Reconstruction from a Single Coded Image）</news:title>
   <news:publication_date>2026-04-01T23:07:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674853</loc>
  <lastmod>2026-04-01T22:15:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オントロジー駆動の適応型電子教科書プラットフォーム（Ontology-based Adaptive e-Textbook Platform for Student and Machine Co-Learning）</news:title>
   <news:publication_date>2026-04-01T22:15:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674851</loc>
  <lastmod>2026-04-01T22:14:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自発核分裂するプルトニウム同位体の断片質量と全運動エネルギー分布（Fission Fragment Mass and Total Kinetic Energy Distributions of Spontaneously Fissioning Plutonium Isotopes）</news:title>
   <news:publication_date>2026-04-01T22:14:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674849</loc>
  <lastmod>2026-04-01T22:14:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高密度群衆カウントにおける不均一密度マップ学習（Structured Inhomogeneous Density Map Learning for Crowd Counting）</news:title>
   <news:publication_date>2026-04-01T22:14:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674847</loc>
  <lastmod>2026-04-01T22:13:47Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アップリンクRSSを用いたユーザ位置推定の機械学習手法（Machine Learning Methods for User Positioning With Uplink RSS in Distributed Massive MIMO）</news:title>
   <news:publication_date>2026-04-01T22:13:47Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674845</loc>
  <lastmod>2026-04-01T22:13:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>顔補完のためのサイド情報を用いたロバストPCA手法（Side Information for Face Completion: a Robust PCA Approach）</news:title>
   <news:publication_date>2026-04-01T22:13:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674843</loc>
  <lastmod>2026-04-01T22:13:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データ駆動型熱流体モデルの機械学習フレームワーク分類（Classification of Machine Learning Frameworks for Data-Driven Thermal Fluid Models）</news:title>
   <news:publication_date>2026-04-01T22:13:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674841</loc>
  <lastmod>2026-04-01T22:13:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層隠れ物理モデル（Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations）</news:title>
   <news:publication_date>2026-04-01T22:13:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674839</loc>
  <lastmod>2026-04-01T21:21:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多重記述畳み込みニューラルネットワークによる画像圧縮（Multiple Description Convolutional Neural Networks for Image Compression）</news:title>
   <news:publication_date>2026-04-01T21:21:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674837</loc>
  <lastmod>2026-04-01T21:19:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マルチビュー・ネットワーク埋め込みにおける保存と協調（MVN2VEC: Preservation and Collaboration in Multi-View Network Embedding）</news:title>
   <news:publication_date>2026-04-01T21:19:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674835</loc>
  <lastmod>2026-04-01T21:19:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モデル理論と機械学習の接点（Model Theory and Machine Learning）</news:title>
   <news:publication_date>2026-04-01T21:19:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674833</loc>
  <lastmod>2026-04-01T21:19:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多視点受容野を用いた映像監視の前景推論ネットワーク（A Foreground Inference Network for Video Surveillance Using Multi-View Receptive Field）</news:title>
   <news:publication_date>2026-04-01T21:19:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674831</loc>
  <lastmod>2026-04-01T21:18:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CMSIS-NNによる小型MCU向けニューラルネット最適化（CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs）</news:title>
   <news:publication_date>2026-04-01T21:18:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674829</loc>
  <lastmod>2026-04-01T20:27:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>声の時間伸縮を「正確」に行う仕組み（Epoch-Synchronous Overlap-Add for Time- and Pitch-Scale Modification of Speech Signals）</news:title>
   <news:publication_date>2026-04-01T20:27:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674827</loc>
  <lastmod>2026-04-01T20:20:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>既存ネットワークを「マスク」で拡張する手法の本質（Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights）</news:title>
   <news:publication_date>2026-04-01T20:20:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674825</loc>
  <lastmod>2026-04-01T20:20:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>小さな顔の検出と数え上げ（Detecting and counting tiny faces）</news:title>
   <news:publication_date>2026-04-01T20:20:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674823</loc>
  <lastmod>2026-04-01T20:19:49Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>図書館空間におけるIoT推薦の可視化と評価（The Bibliotelemetry of Information and Environment: an Evaluation of IoT-Powered Recommender Systems）</news:title>
   <news:publication_date>2026-04-01T20:19:49Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674821</loc>
  <lastmod>2026-04-01T20:18:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>模倣学習の総覧（Global overview of Imitation Learning）</news:title>
   <news:publication_date>2026-04-01T20:18:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674819</loc>
  <lastmod>2026-04-01T20:18:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ビッグデータ解析がネットワーク設計を自律化する道（Big Data Analytics for Network Design）</news:title>
   <news:publication_date>2026-04-01T20:18:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674817</loc>
  <lastmod>2026-04-01T19:26:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>厳密部分順序の能動学習が示す実務的示唆（Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations）</news:title>
   <news:publication_date>2026-04-01T19:26:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674815</loc>
  <lastmod>2026-04-01T19:26:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類における転移学習の実践ガイド（A Practitioners’ Guide to Transfer Learning for Text Classification using Convolutional Neural Networks）</news:title>
   <news:publication_date>2026-04-01T19:26:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674813</loc>
  <lastmod>2026-04-01T19:26:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>複数のソーシャルメディアに跨るサイバーブルイング検出を深層学習で行う意義（Deep Learning for Detecting Cyberbullying Across Multiple Social Media Platforms）</news:title>
   <news:publication_date>2026-04-01T19:26:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674811</loc>
  <lastmod>2026-04-01T19:24:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>共同研究のためのCollective Knowledgeワークフロー（A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques）</news:title>
   <news:publication_date>2026-04-01T19:24:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674809</loc>
  <lastmod>2026-04-01T19:24:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳MRIにおけるパッチベースFCNNの定量解析（Quantitative analysis of patch-based fully convolutional neural networks for tissue segmentation on brain magnetic resonance imaging）</news:title>
   <news:publication_date>2026-04-01T19:24:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674807</loc>
  <lastmod>2026-04-01T19:24:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>画質分類に基づく画像解析による顔検出・認識の改善（Quality Classified Image Analysis with Application to Face Detection and Recognition）</news:title>
   <news:publication_date>2026-04-01T19:24:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674805</loc>
  <lastmod>2026-04-01T19:24:01Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>資源をほとんど使わないクロスリンガル意味テキスト類似度手法 (A Resource-Light Method for Cross-Lingual Semantic Textual Similarity)</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674803</loc>
  <lastmod>2026-04-01T18:32:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差分プライバシー下における近似最小全域木の公開（Private Approximated Minimum Spanning Tree）</news:title>
   <news:publication_date>2026-04-01T18:32:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>語彙埋め込みモデルの学習コーパスの規模と構造（Size vs. structure in training corpora for word embedding models）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </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>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-01T18:30:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>良い合成訓練データとは何か（What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>21cmマップを用いた再イオン化モデル分類（Reionization Models Classifier using 21cm Map Deep Learning）</news:title>
   <news:publication_date>2026-04-01T18:29:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674789</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>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
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   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>音声感情認識における転移学習の有効性（Transfer Learning for Improving Speech Emotion Classification Accuracy）</news:title>
   <news:publication_date>2026-04-01T17:37:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674783</loc>
  <lastmod>2026-04-01T17:37:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>剽窃検出の体系と機械学習アプローチ（Plagiarism: Taxonomy, Tools and Detection Techniques）</news:title>
   <news:publication_date>2026-04-01T17:37:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674781</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>量子化重みで学習するBinaryRelax（BinaryRelax: A Relaxation Approach For Training Deep Neural Networks With Quantized Weights）</news:title>
   <news:publication_date>2026-04-01T17:36:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-01T17:36:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>予測補正法による深層ニューラルネット訓練の高速化（A predictor-corrector method for the training of deep neural networks）</news:title>
   <news:publication_date>2026-04-01T17:36:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-01T17:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-01T16:44:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674773</loc>
  <lastmod>2026-04-01T16:43:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳活動から意味を言語化する手法の要点（Describing Semantic Representations of Brain Activity Evoked by Visual Stimuli）</news:title>
   <news:publication_date>2026-04-01T16:43:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674771</loc>
  <lastmod>2026-04-01T16:43:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散選択のためのディリクレ過程混合モデル（A Dirichlet Process Mixture Model of Discrete Choice）</news:title>
   <news:publication_date>2026-04-01T16:43:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674769</loc>
  <lastmod>2026-04-01T16:43:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超新星残骸1E0102の全領域分光観測が示す高速水素・硫黄豊富な噴出物（Integral Field Spectroscopy of Supernova Remnant 1E0102-7219 Reveals Fast-moving Hydrogen and Sulfur-rich Ejecta）</news:title>
   <news:publication_date>2026-04-01T16:43:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674767</loc>
  <lastmod>2026-04-01T16:42:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ソーシャルメディアからの多目的薬剤安全性モニタリング（Multi-Task Pharmacovigilance Mining from Social Media Posts）</news:title>
   <news:publication_date>2026-04-01T16:42:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-01T16:42:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>組織マイクロアレイ（TMA）に対するエンドツーエンド深層学習によるヒストケミカルスコア自動化（An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer Tissue Microarray）</news:title>
   <news:publication_date>2026-04-01T16:42:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674763</loc>
  <lastmod>2026-04-01T16:42:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>TextCNNが学ぶことの本質（What Does a TextCNN Learn?）</news:title>
   <news:publication_date>2026-04-01T16:42:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674761</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイル機械学習ハードウェアのSoC視点（Mobile Machine Learning Hardware at ARM: A Systems-on-Chip (SoC) Perspective）</news:title>
   <news:publication_date>2026-04-01T15:51:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674759</loc>
  <lastmod>2026-04-01T15:43:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マイクログリッドにおける強化学習ベースのエネルギー取引（Reinforcement Learning-based Energy Trading for Microgrids）</news:title>
   <news:publication_date>2026-04-01T15:43:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>IoTにおける機械学習を用いたセキュリティ技術（IoT Security Techniques Based on Machine Learning）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674753</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>動的クラウドストレージにおけるAPT防御のゲーム理論的アプローチ（Defense Against Advanced Persistent Threats in Dynamic Cloud Storage: A Colonel Blotto Game Approach）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674751</loc>
  <lastmod>2026-04-01T15:41:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>テキスト分類器の動作を探る（Investigating the Working of Text Classifiers）</news:title>
   <news:publication_date>2026-04-01T15:41:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674749</loc>
  <lastmod>2026-04-01T15:40:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大きな球が作る影の波動光学的扱い（Wave-optical treatment of the shadow cast by a large sphere）</news:title>
   <news:publication_date>2026-04-01T15:40:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674747</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モンテカルロ法を用いた一般化線形モデルの学習応用（The Application of Monte Carlo Methods for Learning Generalized Linear Model）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-01T14:49:18Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-01T14:49:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>遺伝子発現データにおけるネットワーク埋め込み深層全結合網の提案（A graph-embedded deep feedforward network for disease outcome classification and feature selection using gene expression data）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/674737</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>粒子形状からコロイド結晶を予測する逆設計と機械学習（Predicting colloidal crystals from shapes via inverse design and machine learning）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news: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>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674729</loc>
  <lastmod>2026-04-01T13:54:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-01T13:54:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-01T13:53:57Z</lastmod>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-01T13:53:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-01T13:53:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-01T13:53:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-01T13:53:18Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674721</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-01T13:52:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-01T13:01:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>ガウス過程からStudent’s-T過程への移行（Upgrading from Gaussian Processes to Student’s-T Processes）</news:title>
   <news:publication_date>2026-04-01T13:01:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/674715</loc>
  <lastmod>2026-04-01T13:01:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>汎用言語モデルのファインチューニングによるテキスト分類（Universal Language Model Fine-tuning for Text Classification）</news:title>
   <news:publication_date>2026-04-01T13:01:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/674713</loc>
  <lastmod>2026-04-01T13:00:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>非敵対的な教師なし単語翻訳の実務的要点（Non-Adversarial Unsupervised Word Translation）</news:title>
   <news:publication_date>2026-04-01T13:00:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/674711</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>自然言語マルチタスク学習による潜在表現の構造改善（Natural Language Multitasking: Analyzing and Improving Syntactic Saliency of Latent Representations）</news:title>
   <news:publication_date>2026-04-01T13:00:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-01T13:00:05Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-01T13:00:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:title>条件付きグラフ生成モデルによる多目的de novo創薬（Multi-Objective De Novo Drug Design with Conditional Graph Generative Model）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>大規模MIMOの自由度を活かした低次元デジタルプリディストーション（A Digital Predistortion Scheme Exploiting Degrees-of-Freedom for Massive MIMO Systems）</news:title>
   <news:publication_date>2026-04-01T12:08:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>単一温度熱プラズマのX線スペクトルパラメータ推定のためのニューラルネットワーク前処理（Neural network-based preprocessing to estimate the parameters of the X-ray emission of a single-temperature thermal plasma）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-01T12:06:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>3D CNNによるsMRIとMD-DTI画像を用いたアルツハイマー病研究の分類（3D CNN-based classification using sMRI and MD-DTI images for Alzheimer disease studies）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674697</loc>
  <lastmod>2026-04-01T12:05:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Near-lossless ℓ∞制約に基づく画像復号の深層ニューラルネットワーク（Near-lossless ℓ∞-constrained Image Decompression via Deep Neural Network）</news:title>
   <news:publication_date>2026-04-01T12:05:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674695</loc>
  <lastmod>2026-04-01T12:05:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-01T12:04:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Layered TPOTでパイプライン探索を高速化（Layered TPOT: Speeding up Tree-based Pipeline Optimization）</news:title>
   <news:publication_date>2026-04-01T12:04:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674691</loc>
  <lastmod>2026-04-01T11:13:29Z</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>2026-04-01T11:13:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674689</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>2026-04-01T11:13:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674687</loc>
  <lastmod>2026-04-01T11:12:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>データアクセス時間を減らすことで学習を速める手法（Faster Learning by Reduction of Data Access Time）</news:title>
   <news:publication_date>2026-04-01T11:12:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習分布の不確実性に対するロバストなプライバシー保証の効用コスト（The Utility Cost of Robust Privacy Guarantees）</news:title>
   <news:publication_date>2026-04-01T11:11:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/674683</loc>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
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   <news:publication_date>2026-04-01T11:11:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674681</loc>
  <lastmod>2026-04-01T11:11:31Z</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/674679</loc>
  <lastmod>2026-04-01T10:20:00Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>モバイルエッジキャッシングにおける強化学習を用いたセキュリティ（Security in Mobile Edge Caching with Reinforcement Learning）</news:title>
   <news:publication_date>2026-04-01T10:20:00Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-01T10:19:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Dice損失関数が腹部CTの多クラス臓器セグメンテーションに与える影響（On the influence of Dice loss function in multi-class organ segmentation of abdominal CT using 3D fully convolutional networks）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674673</loc>
  <lastmod>2026-04-01T10:18:22Z</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>2026-04-01T10:18:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/674671</loc>
  <lastmod>2026-04-01T10:18:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OGLEによるマゼラン橋と小マゼラン雲外縁の星団カタログ（OGLE Collection of Star Clusters）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
  <loc>https://aibr.jp/archives/674669</loc>
  <lastmod>2026-04-01T10:17:54Z</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>
    <news:language>ja</news:language>
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   <news:title>原子分解能STEM画像の深層学習による化学種同定と局所変換の追跡（Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <lastmod>2026-04-01T09:25:49Z</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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  <lastmod>2026-04-01T09:24:57Z</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>
    <news:language>ja</news:language>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-01T09:24:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674657</loc>
  <lastmod>2026-04-01T09:24:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-01T09:24:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674655</loc>
  <lastmod>2026-04-01T09:24:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-01T09:24:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674648</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>月極域の表層土が緩いという発見の意義（Experiments Indicate Regolith is Looser in the Lunar Polar Regions than at the Lunar Landing Sites）</news:title>
   <news:publication_date>2026-04-01T08:32:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674646</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>2026-04-01T08:32:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674644</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>中央座標学習による顔認識（Face Recognition via Centralized Coordinate Learning）</news:title>
   <news:publication_date>2026-04-01T08:31:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674642</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>QLBSのQ学習がNuQLearへ（The QLBS Q-Learner Goes NuQLear: Fitted Q Iteration, Inverse RL, and Option Portfolios）</news:title>
   <news:publication_date>2026-04-01T08:30:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674640</loc>
  <lastmod>2026-04-01T08:30:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ネットワーク内ニューラルネットワーク（In-network Neural Networks）</news:title>
   <news:publication_date>2026-04-01T08:30:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674638</loc>
  <lastmod>2026-04-01T07:38:56Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ヒューマノイドロボットにおける近接回避で対人インタラクションの安全性を高める手法（Compact Real-time avoidance on a Humanoid Robot for Human-robot Interaction）</news:title>
   <news:publication_date>2026-04-01T07:38:56Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674636</loc>
  <lastmod>2026-04-01T07:38:19Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-04-01T07:38:19Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674634</loc>
  <lastmod>2026-04-01T07:38:05Z</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>2026-04-01T07:38:05Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674632</loc>
  <lastmod>2026-04-01T07:36:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Query2Vecによるワークロード解析の一般化（Query2Vec: An Evaluation of NLP Techniques for Generalized Workload Analytics）</news:title>
   <news:publication_date>2026-04-01T07:36:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674630</loc>
  <lastmod>2026-04-01T07:36:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>効率的なテストコレクション構築の能動学習アプローチ（Efficient Test Collection Construction via Active Learning）</news:title>
   <news:publication_date>2026-04-01T07:36:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674628</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>2026-04-01T07:36:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674626</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>2026-04-01T07:36:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674624</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>顔認証のための加法マージンソフトマックス（Additive Margin Softmax for Face Verification）</news:title>
   <news:publication_date>2026-04-01T06:26:11Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674622</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>2026-04-01T06:25:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674620</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>2026-04-01T06:25:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674618</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>交互慣性を持つ近接勾配法の特性（On the Proximal Gradient Algorithm with Alternated Inertia）</news:title>
   <news:publication_date>2026-04-01T06:24:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674616</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>2026-04-01T06:24:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674614</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>2026-04-01T05:32:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674612</loc>
  <lastmod>2026-04-01T05:21:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Proximal Policy OptimizationとK-FACを組み合わせた実証的解析（An Empirical Analysis of Proximal Policy Optimization with Kronecker-factored Natural Gradients）</news:title>
   <news:publication_date>2026-04-01T05:21:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674610</loc>
  <lastmod>2026-04-01T05:21:31Z</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>2026-04-01T05:21:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674608</loc>
  <lastmod>2026-04-01T05:20:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>超臨界流体におけるWidomデルタの微視的共存（Widom delta of supercritical gas-liquid coexistence）</news:title>
   <news:publication_date>2026-04-01T05:20:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674606</loc>
  <lastmod>2026-04-01T05:19:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Semi-supervised FusedGANで条件付き画像生成を高精度に制御する（Semi-supervised FusedGAN for Conditional Image Generation）</news:title>
   <news:publication_date>2026-04-01T05:19:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674604</loc>
  <lastmod>2026-04-01T05:19:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>学習層ごとの計量と部分空間を学習する勾配ベースのメタ学習（Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace）</news:title>
   <news:publication_date>2026-04-01T05:19:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674602</loc>
  <lastmod>2026-04-01T05:19:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>動画ベースの顔ランドマーク検出を高速化する再帰型エンコーダ・デコーダ（RED-Net: A Recurrent Encoder-Decoder Network for Video-based Face Alignment）</news:title>
   <news:publication_date>2026-04-01T05:19:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674600</loc>
  <lastmod>2026-04-01T04:27:38Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>NELS―音を学び続ける仕組みが変える現場（NELS - Never-Ending Learner of Sounds）</news:title>
   <news:publication_date>2026-04-01T04:27:38Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674598</loc>
  <lastmod>2026-04-01T04:27:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Additive Latent Effect (ALE) による成績予測の実務的示唆（ALE: Additive Latent Effect Models for Grade Prediction）</news:title>
   <news:publication_date>2026-04-01T04:27:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674596</loc>
  <lastmod>2026-04-01T04:26:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>匿名化解除（Blind De-anonymization Attacks using Social Networks）</news:title>
   <news:publication_date>2026-04-01T04:26:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674594</loc>
  <lastmod>2026-04-01T04:25:58Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>二重クラスタリングで行う強化学習ベースレコメンダ（Reinforcement Learning based Recommender System using Biclustering Technique）</news:title>
   <news:publication_date>2026-04-01T04:25:58Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674592</loc>
  <lastmod>2026-04-01T04:25:45Z</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>2026-04-01T04:25:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674590</loc>
  <lastmod>2026-04-01T03:33:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Cellular-Connected UAVs over 5G: Deep Reinforcement Learning for Interference Management（Cellular-Connected UAVs over 5G: Deep Reinforcement Learning for Interference Management）</news:title>
   <news:publication_date>2026-04-01T03:33:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674588</loc>
  <lastmod>2026-04-01T03:33:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ハッブルで見つけた磁気異常天体の赤外対応体の同定（IDENTIFICATION OF THE INFRARED COUNTERPART OF SGR 1935+2154 WITH THE HUBBLE SPACE TELESCOPE）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-01T03:33:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Masked Conditional Neural Networksを用いた音楽ジャンル自動分類（Automatic Classification of Music Genre using Masked Conditional Neural Networks）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-04-01T03:32:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚環境における畳み込みネットワーク（Convolutional Networks in Visual Environments）</news:title>
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   <news:genres>Blog</news:genres>
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 </url>
 <url>
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  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>同時分解と分類のための深層ネットワーク（Deep Network for Simultaneous Decomposition and Classification in UWB-SAR Imagery）</news:title>
   <news:publication_date>2026-04-01T03:32:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674580</loc>
  <lastmod>2026-04-01T03:32:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>量子ウォークに基づくグラフニューラルネットワーク（Quantum Walk Neural Networks for Graph-Structured Data）</news:title>
   <news:publication_date>2026-04-01T03:32:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674578</loc>
  <lastmod>2026-04-01T03:31:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>弱結合グラフ上の相互作用に対する信念制御戦略 (Belief Control Strategies for Interactions over Weakly-Connected Graphs)</news:title>
   <news:publication_date>2026-04-01T03:31:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674576</loc>
  <lastmod>2026-04-01T02:40:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>LSTMの解釈を一歩進める文脈分解（Contextual Decomposition）</news:title>
   <news:publication_date>2026-04-01T02:40:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674574</loc>
  <lastmod>2026-04-01T02:39:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ニュース報道の「同情（Sympathy）」はTwitterでどう伝わるか（Measuring, Understanding, and Classifying News Media Sympathy on Twitter after Crisis Events）</news:title>
   <news:publication_date>2026-04-01T02:39:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674572</loc>
  <lastmod>2026-04-01T02:39:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層直交相関LSTM（Deep Canonically Correlated LSTMs）</news:title>
   <news:publication_date>2026-04-01T02:39:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674570</loc>
  <lastmod>2026-04-01T02:39:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>グラフ上の近接アルゴリズムの組合せ的プリコンディショナ（Combinatorial Preconditioners for Proximal Algorithms on Graphs）</news:title>
   <news:publication_date>2026-04-01T02:39:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674568</loc>
  <lastmod>2026-04-01T02:38:22Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波（EEG）を用いた自動てんかん検出システム（An Automated System for Epilepsy Detection using EEG Brain Signals based on Deep Learning Approach）</news:title>
   <news:publication_date>2026-04-01T02:38:22Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674566</loc>
  <lastmod>2026-04-01T02:38:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Expectation Propagationと自由確率が切り開く近似推論の実用化（Expectation Propagation for Approximate Inference: Free Probability Framework）</news:title>
   <news:publication_date>2026-04-01T02:38:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674564</loc>
  <lastmod>2026-04-01T01:47:03Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>発展途上国における救急搬送最適化の実務的示唆（Ambulance Emergency Response Optimization in Developing Countries）</news:title>
   <news:publication_date>2026-04-01T01:47:03Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674562</loc>
  <lastmod>2026-04-01T01:46:48Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>想像で学ぶ低ショット学習（Low-Shot Learning from Imaginary Data）</news:title>
   <news:publication_date>2026-04-01T01:46:48Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674560</loc>
  <lastmod>2026-04-01T01:46:33Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>差別の方向性に関する情報理論的分析（On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning）</news:title>
   <news:publication_date>2026-04-01T01:46:33Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674558</loc>
  <lastmod>2026-04-01T01:45:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>時系列データの自動セグメンテーションが変える現場の知見抽出（Time Series Segmentation through Automatic Feature Learning）</news:title>
   <news:publication_date>2026-04-01T01:45:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674556</loc>
  <lastmod>2026-04-01T01:45:14Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>リレーショナルデータベースからの特徴学習（Feature Learning From Relational Databases）</news:title>
   <news:publication_date>2026-04-01T01:45:14Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674554</loc>
  <lastmod>2026-04-01T01:45:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>StressedNetsによる効率的特徴表現の合成（StressedNets: Efficient Feature Representations via Stress-induced Evolutionary Synthesis of Deep Neural Networks）</news:title>
   <news:publication_date>2026-04-01T01:45:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674552</loc>
  <lastmod>2026-04-01T01:44:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>実験数学入門としての能動学習の試み（A Random Walk through Experimental Maths）</news:title>
   <news:publication_date>2026-04-01T01:44:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674541</loc>
  <lastmod>2026-04-01T00:53:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再識別を正しく行うための実践（Re‑ID done right: towards good practices for person re-identification）</news:title>
   <news:publication_date>2026-04-01T00:53:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674539</loc>
  <lastmod>2026-04-01T00:52:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Evidential Occupancy Grid Map Augmentation using Deep Learning（Evidential Occupancy Grid Map Augmentation using Deep Learning）</news:title>
   <news:publication_date>2026-04-01T00:52:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674537</loc>
  <lastmod>2026-04-01T00:52:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深層一クラス分類が変える異常検知の常識（Deep One-Class Classification）</news:title>
   <news:publication_date>2026-04-01T00:52:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674535</loc>
  <lastmod>2026-04-01T00:51:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ラプラシアンピラミッド自己符号化器による教師なし表現学習（Unsupervised Representation Learning with Laplacian Pyramid Auto-encoders）</news:title>
   <news:publication_date>2026-04-01T00:51:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674533</loc>
  <lastmod>2026-04-01T00:51:27Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>行動時間スケールにおけるエリジビリティトレースと可塑性（Eligibility Traces and Plasticity on Behavioral Time Scales）</news:title>
   <news:publication_date>2026-04-01T00:51:27Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674531</loc>
  <lastmod>2026-04-01T00:51:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>畳み込み層のCP分解におけるランク選択とVBMF（Rank Selection of CP-decomposed Convolutional Layers with Variational Bayesian Matrix Factorization）</news:title>
   <news:publication_date>2026-04-01T00:51:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674529</loc>
  <lastmod>2026-04-01T00:51:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プライバシー制約下のMOOCデータによる予測と再現性のための枠組み（MORF: A Framework for Predictive Modeling and Replication At Scale With Privacy-Restricted MOOC Data）</news:title>
   <news:publication_date>2026-04-01T00:51:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674527</loc>
  <lastmod>2026-03-31T23:59:13Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>離散化された活性化関数を持つネットワークの実験的探究（Empirical Explorations in Training Networks with Discrete Activations）</news:title>
   <news:publication_date>2026-03-31T23:59:13Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674525</loc>
  <lastmod>2026-03-31T23:51:30Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>開放量子系における非可逆性の幾何学的境界（Geometrical bounds on irreversibility in open quantum systems）</news:title>
   <news:publication_date>2026-03-31T23:51:30Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674523</loc>
  <lastmod>2026-03-31T23:50:04Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>異スペクトル画像の高精度整列を可能にする深層不変記述子学習（Deep Multi-Spectral Registration Using Invariant Descriptor Learning）</news:title>
   <news:publication_date>2026-03-31T23:50:04Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674521</loc>
  <lastmod>2026-03-31T23:49:50Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>クラウドアノテーションを活かす敵対的学習による中国語固有表現抽出（Adversarial Learning for Chinese NER from Crowd Annotations）</news:title>
   <news:publication_date>2026-03-31T23:49:50Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674519</loc>
  <lastmod>2026-03-31T23:49:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>OneNetによるドメイン・インテント・スロットの同時予測（OneNet: Joint Domain, Intent, Slot Prediction for Spoken Language Understanding）</news:title>
   <news:publication_date>2026-03-31T23:49:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674517</loc>
  <lastmod>2026-03-31T23:49:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>GitGraph によるニューラル探索空間の設計（GitGraph - Architecture Search Space Creation through Frequent Computational Subgraph Mining）</news:title>
   <news:publication_date>2026-03-31T23:49:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674515</loc>
  <lastmod>2026-03-31T22:58:12Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>CNN-LSTMによる画像ノイズ除去と復元（Image denoising and restoration with CNN-LSTM Encoder Decoder with Direct Attention）</news:title>
   <news:publication_date>2026-03-31T22:58:12Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674513</loc>
  <lastmod>2026-03-31T22:57:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>航空写真を用いた断線ガラス絶縁物の高速・高精度位置検出（An Accurate and Real-time Self-blast Glass Insulator Location Method Based On Faster R-CNN and U-net with Aerial Images）</news:title>
   <news:publication_date>2026-03-31T22:57:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674511</loc>
  <lastmod>2026-03-31T22:57:29Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>DropoutとBatch Normalizationの不協和（Understanding the Disharmony between Dropout and Batch Normalization by Variance Shift）</news:title>
   <news:publication_date>2026-03-31T22:57:29Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674509</loc>
  <lastmod>2026-03-31T22:56:59Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Localization-Aware Active Learning for Object Detection（Localization-Aware Active Learning for Object Detection）</news:title>
   <news:publication_date>2026-03-31T22:56:59Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674507</loc>
  <lastmod>2026-03-31T22:56:45Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視覚ベースのナビゲーションにおける深層学習を活用したサンプルベース計画の強化（Learning to Navigate: Exploiting Deep Networks to Inform Sample-Based Planning During Vision-Based Navigation）</news:title>
   <news:publication_date>2026-03-31T22:56:45Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674505</loc>
  <lastmod>2026-03-31T22:56:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非同期双方向デコーディングによる機械翻訳の改良（Asynchronous Bidirectional Decoding for Neural Machine Translation）</news:title>
   <news:publication_date>2026-03-31T22:56:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674503</loc>
  <lastmod>2026-03-31T22:05:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>自己教師ありで動画の手ブレを戻す方法（Reblur2Deblur: Deblurring Videos via Self-Supervised Learning）</news:title>
   <news:publication_date>2026-03-31T22:05:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
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  <lastmod>2026-03-31T22:04:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>階層的テキスト→画像生成のための意味的レイアウト推定（Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis）</news:title>
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   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674499</loc>
  <lastmod>2026-03-31T22:04:43Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>再帰型ニューラルネットワークからのルール抽出比較（A Comparative Study of Rule Extraction for Recurrent Neural Networks）</news:title>
   <news:publication_date>2026-03-31T22:04:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674497</loc>
  <lastmod>2026-03-31T22:03:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習による自律UAV航行（Autonomous UAV Navigation Using Reinforcement Learning）</news:title>
   <news:publication_date>2026-03-31T22:03:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674495</loc>
  <lastmod>2026-03-31T22:03:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>視点と環境変化に強い場所認識の作法（Don&amp;#039;t Look Back: Robustifying Place Categorization for Viewpoint- and Condition-Invariant Place Recognition）</news:title>
   <news:publication_date>2026-03-31T22:03:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674493</loc>
  <lastmod>2026-03-31T22:03:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>医療の自由文から複数診断を予測する畳み込み残差モデル（Multi-Label Learning from Medical Plain Text with Convolutional Residual Models）</news:title>
   <news:publication_date>2026-03-31T22:03:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674491</loc>
  <lastmod>2026-03-31T22:03:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習説明の定量評価：人間注視ベンチマークの意義（Quantitative Evaluation of Machine Learning Explanations: A Human-Grounded Benchmark）</news:title>
   <news:publication_date>2026-03-31T22:03:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674489</loc>
  <lastmod>2026-03-31T21:11:28Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>生徒は教師を超えた：ノイズラベルで学ぶ脳室セグメンテーション（Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR）</news:title>
   <news:publication_date>2026-03-31T21:11:28Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674487</loc>
  <lastmod>2026-03-31T21:11:15Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>線形二次レギュレータに対する方策勾配法の全域収束（Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator）</news:title>
   <news:publication_date>2026-03-31T21:11:15Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674485</loc>
  <lastmod>2026-03-31T21:11:07Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Predictive Systems Toxicology（Predictive Systems Toxicology）</news:title>
   <news:publication_date>2026-03-31T21:11:07Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674483</loc>
  <lastmod>2026-03-31T21:09:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>オクツリーセル占有に基づく局所幾何次元記述子（AN OCTREE CELLS OCCUPANCY GEOMETRIC DIMENSIONALITY DESCRIPTOR FOR MASSIVE ON-SERVER POINT CLOUD VISUALISATION AND CLASSIFICATION）</news:title>
   <news:publication_date>2026-03-31T21:09:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674481</loc>
  <lastmod>2026-03-31T20:16:44Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械型通信における高速アップリンク割当の課題と機会（Fast Uplink Grant for Machine Type Communications: Challenges and Opportunities）</news:title>
   <news:publication_date>2026-03-31T20:16:44Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674479</loc>
  <lastmod>2026-03-31T20:16:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SVMの一般化・解釈・最適化の一貫的枠組み（Generalizing, Decoding, and Optimizing Support Vector Machine Classification）</news:title>
   <news:publication_date>2026-03-31T20:16:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674477</loc>
  <lastmod>2026-03-31T20:15:46Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習でエネルギー材料の性質を予測する手法（Applying machine learning techniques to predict the properties of energetic materials）</news:title>
   <news:publication_date>2026-03-31T20:15:46Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674475</loc>
  <lastmod>2026-03-31T19:24:31Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>監視衛星の軌道予測を機械学習で高精度化する手法（Improving Orbit Prediction Accuracy through Supervised Machine Learning）</news:title>
   <news:publication_date>2026-03-31T19:24:31Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674473</loc>
  <lastmod>2026-03-31T19:24:17Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Radio Galaxy Zoo: 深層学習による電波銀河のコンパクト/拡張分類（Radio Galaxy Zoo: Compact and extended radio source classification with deep learning）</news:title>
   <news:publication_date>2026-03-31T19:24:17Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674471</loc>
  <lastmod>2026-03-31T19:23:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>陽子スピンと将来の電子イオンコライダー（The Proton Spin, Semi-Inclusive processes, and a future Electron Ion Collider）</news:title>
   <news:publication_date>2026-03-31T19:23:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674469</loc>
  <lastmod>2026-03-31T19:23:32Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>BIERによる埋め込み強化：独立性を高めるディープ距離学習の実践（Deep Metric Learning with BIER: Boosting Independent Embeddings Robustly）</news:title>
   <news:publication_date>2026-03-31T19:23:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674467</loc>
  <lastmod>2026-03-31T19:23:23Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>機械学習による非パラメトリック n 体 力場の効率化（Eﬃcient nonparametric n-body force fields from machine learning）</news:title>
   <news:publication_date>2026-03-31T19:23:23Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674465</loc>
  <lastmod>2026-03-31T19:23:08Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>プロット要約から映画ジャンルを予測する（Predicting Movie Genres Based on Plot Summaries）</news:title>
   <news:publication_date>2026-03-31T19:23:08Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674463</loc>
  <lastmod>2026-03-31T19:22:39Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ロボットが解き明かす身体性を基点とした認知の研究（Robots as powerful allies for the study of embodied cognition from the bottom up）</news:title>
   <news:publication_date>2026-03-31T19:22:39Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674461</loc>
  <lastmod>2026-03-31T18:31:57Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>深いパイプラインを持つ通信隠蔽共役勾配法（The Communication-Hiding Conjugate Gradient Method with Deep Pipelines）</news:title>
   <news:publication_date>2026-03-31T18:31:57Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674459</loc>
  <lastmod>2026-03-31T18:31:42Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>τ-FPL: 線形時間での許容率制約学習（τ-FPL: Tolerance-Constrained Learning in Linear Time）</news:title>
   <news:publication_date>2026-03-31T18:31:42Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674457</loc>
  <lastmod>2026-03-31T18:31:21Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文脈を拡大しコストを抑える: トリムド畳み込みによる効率的算術符号化（Enlarging Context with Low Cost: Efficient Arithmetic Coding with Trimmed Convolution）</news:title>
   <news:publication_date>2026-03-31T18:31:21Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674455</loc>
  <lastmod>2026-03-31T18:31:06Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>人間の目に見えず物理世界で効く敵対的攻撃の作り方（Towards Imperceptible and Robust Adversarial Example Attacks against Neural Networks）</news:title>
   <news:publication_date>2026-03-31T18:31:06Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674453</loc>
  <lastmod>2026-03-31T18:30:51Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スパース性を用いた線形分類器への敵対的攻撃防御（Sparsity-based Defense against Adversarial Attacks on Linear Classifiers）</news:title>
   <news:publication_date>2026-03-31T18:30:51Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674451</loc>
  <lastmod>2026-03-31T18:30:37Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ライダのみの自己位置推定に対するバイアス補正の学習（Learning a Bias Correction for Lidar-only Motion Estimation）</news:title>
   <news:publication_date>2026-03-31T18:30:37Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674449</loc>
  <lastmod>2026-03-31T17:39:34Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>ディープニューラルネットワークの並列化手法「Leapfrogging」（Leapfrogging for parallelism in deep neural networks）</news:title>
   <news:publication_date>2026-03-31T17:39:34Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674447</loc>
  <lastmod>2026-03-31T17:39:24Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>層ごとの重要度を見極めるための構造的圧縮（Deep Net Triage: Analyzing the Importance of Network Layers via Structural Compression）</news:title>
   <news:publication_date>2026-03-31T17:39:24Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674445</loc>
  <lastmod>2026-03-31T17:39:09Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>高ダイナミックレンジ検出器による2D材料の深いサブオングストロームイメージング（Deep sub-Ångstrom imaging of 2D materials with a high dynamic range detector）</news:title>
   <news:publication_date>2026-03-31T17:39:09Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674443</loc>
  <lastmod>2026-03-31T17:38:35Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>アルゴリズム的多項式とその意義（Algorithmic Polynomials）</news:title>
   <news:publication_date>2026-03-31T17:38:35Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674441</loc>
  <lastmod>2026-03-31T17:38:25Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>マクロスケールの分子通信としての疫学モデル化（Molecular Communications at the Macroscale: A Novel Framework for Modeling Epidemic Spreading and Mitigation）</news:title>
   <news:publication_date>2026-03-31T17:38:25Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674439</loc>
  <lastmod>2026-03-31T17:38:10Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>フレーム再帰型ビデオ超解像の要点解説（Frame-Recurrent Video Super-Resolution）</news:title>
   <news:publication_date>2026-03-31T17:38:10Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674437</loc>
  <lastmod>2026-03-31T17:38:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>胚発生における細胞運動を深層強化学習で解く（Deep Reinforcement Learning of Cell Movement in the Early Stage of C. elegans Embryogenesis）</news:title>
   <news:publication_date>2026-03-31T17:38:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674435</loc>
  <lastmod>2026-03-31T16:46:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>強化学習によるファジングの定式化（Deep Reinforcement Fuzzing）</news:title>
   <news:publication_date>2026-03-31T16:46:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674433</loc>
  <lastmod>2026-03-31T16:36:41Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>文書とクラスの距離で特徴を絞る手法（DCDistance: A Supervised Text Document Feature extraction based on class labels）</news:title>
   <news:publication_date>2026-03-31T16:36:41Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674431</loc>
  <lastmod>2026-03-31T16:36:20Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>Finis Terrae II における機械学習フレームワークの評価（Evaluation of Machine Learning Frameworks on Finis Terrae II）</news:title>
   <news:publication_date>2026-03-31T16:36:20Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674429</loc>
  <lastmod>2026-03-31T16:35:53Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>勾配法を次元で加速する「永続ランダムウォーカー」手法（A dimensional acceleration of gradient descent-like methods, using persistent random walkers）</news:title>
   <news:publication_date>2026-03-31T16:35:53Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/674427</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>低レベル無線通信における協調型マルチエージェント強化学習（Cooperative Multi-Agent Reinforcement Learning for Low-Level Wireless Communication）</news:title>
   <news:publication_date>2026-03-31T16:35:43Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/674425</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>層をまたいだ残差の蓄積による改善（Using accumulation to optimize deep residual neural nets）</news:title>
   <news:publication_date>2026-03-31T16:35:32Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/674423</loc>
  <lastmod>2026-03-31T16:35:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
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   <news:publication_date>2026-03-31T16:35:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/674421</loc>
  <lastmod>2026-03-31T15:44:02Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>非パラメトリック変換ネットワーク（Non-Parametric Transformation Networks）</news:title>
   <news:publication_date>2026-03-31T15:44:02Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/674419</loc>
  <lastmod>2026-03-31T15:43:52Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>脳波（EEG）時系列選択の新しいグラフベース手法（Brain EEG Time Series Selection: A Novel Graph-Based Approach for Classification）</news:title>
   <news:publication_date>2026-03-31T15:43:52Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674417</loc>
  <lastmod>2026-03-31T15:43:36Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>多変量時系列分類のためのMLSTM-FCN（Multivariate LSTM‑FCN）</news:title>
   <news:publication_date>2026-03-31T15:43:36Z</news:publication_date>
   <news:genres>Blog</news:genres>
  </news:news>
 </url>
 <url>
  <loc>https://aibr.jp/archives/674415</loc>
  <lastmod>2026-03-31T15:42:54Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>SDPから導くネステロフ法の明示的収束率（An Explicit Convergence Rate for Nesterov’s Method from SDP）</news:title>
   <news:publication_date>2026-03-31T15:42:54Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/674413</loc>
  <lastmod>2026-03-31T15:42:40Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>反復計算を不要にする深層学習によるトポロジー最適設計の近似（Deep learning for determining a near-optimal topological design without any iteration）</news:title>
   <news:publication_date>2026-03-31T15:42:40Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/674411</loc>
  <lastmod>2026-03-31T15:42:26Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>繁殖における配偶選択の確率論的モデル（On a statistical approach to mate choices in reproduction）</news:title>
   <news:publication_date>2026-03-31T15:42:26Z</news:publication_date>
   <news:genres>Blog</news:genres>
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 <url>
  <loc>https://aibr.jp/archives/674409</loc>
  <lastmod>2026-03-31T15:42:16Z</lastmod>
  <news:news>
   <news:publication>
    <news:name>AI Benchmark Research</news:name>
    <news:language>ja</news:language>
   </news:publication>
   <news:title>スピン依存パートン分布関数のNNLO解析手法（Analytical approaches to the determination of spin-dependent parton distribution functions at NNLO approximation）</news:title>
   <news:publication_date>2026-03-31T15:42:16Z</news:publication_date>
   <news:genres>Blog</news:genres>
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